2021 Research Portfolio : simplebooklet.com

Engineered Systems35Correlated Sensing of Health and Exposure for Personalized Asthma MonitoringHealth and Exposure Tracker (HET): Integration and Demonstration of a Modular WearableMonitoring System Self-Powered Platform for Cardiovascular and Asthma MonitoringSenSE: AI-Driven, Resilient and Adaptive Monitoring of Sleep (AI-DReAMS)Bio-Electro-Photonic Microsystem Interfaces for Small AnimalsCough Detection Using Wearables and Embedded Machine Learning3637 38394041TABLE OF CONTENTSLow Power SensingEnergy Harvesting & StorageFlexible Thermoelectric Generators for Body Heat HarvestingModeling of Thermoelectric Generators for Body Heat HarvestingSelf-Powered Smart Insoles for Balance and Gait DetectionNew Mode of Mechanical-to-Electrical Energy HarvestingPrinting of Stretchable Conductors Enabled by Highly Tunable Multiphase Liquid Metal PastesDevelopment of Sweat BioCapacitor for Self-Powered Multimodal Metabolite SensorsUltrasonic Energy/Data Transfer for ImplantablesHigh Energy Density Lithium-Ion Capacitor for Wearable TechnologiesHigh-Performance Three-Dimensional Thin-Film Thermoelectric Generators51525Introduction267891011121314Ultra-Low Power Metal Oxide Electronic Nose Arrays for Environmental and Breath MonitoringCapacitive Micromachined Ultrasonic Transducer based Gas and Breath SensingMultimodal Biosensing System for Electrochemical and Photonic Monitoring of HealthNovel Biomaterials and Bioelectronics for Implantable Cardiovascular TherapiesUltra-Low Power PhotoPlethysmoGraphy (PPG) for Wearable ApplicationsPotentiometric Detection of Neuropeptides for Non-Invasive Monitoring of StressImproving the Performance and Design of Potentiometric Biosensors for the Detection of Extracellular Histones in Blood with Deep LearningUse Case: Long-Term Wound Monitoring with Multimodal PatchesZero-Power Wearable Sweat Assays and Long-term Sensing Device Interfaces Using Osmotic Pumpingand Paper Microfluidics16171819202122 2324Low Power Systems-on-ChipUltra-Low Power System on Chip (SoC) Wireless Wakeup for Energy Reduction in Plugged-In MELs (Miscellaneous Electric Loads)Novel, Flexible, High Efficiency and Multifunctional Wearable AntennasBody Worn Flexible Antenna for Applications in Communication and RF Energy Harvesting2627282931E-TextilesTransformative Textiles Designs for Self-Powered, Multi-Modal Sensing GarmentsMethod of Automated Handling of Textiles for Improved Efficiency and Accuracy to Enable E-TextileManufacturingNovel Textile-Based Sensors for Inner Prosthetic Socket Environment Monitoring3233 34

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Since 2012, the NSF-funded Center for Advanced Self-PoweredSystems of Integrated Sensors and Technologies (ASSIST) hascontinued to lead the way in developing flexible, self-poweredwearable devices that enable continuous monitoring of bothpersonal health and personal environment. These devices aremonitoring a variety of chronic health diseases, and the dataare being generated to support physicians and patients.Recently, we also added implantable devices to provideadditional continuous monitoring capabilities. The ASSIST Center is led by NC State and includes FloridaInternational University, Penn State University, and the Universitiesof Michigan, North Carolina, Notre Dame, Virginia, and Utah aspartners. We maintain our technical leadership in five themeareas, i.e., energy harvesting and storage, low power sensors,low power electronics, electronic textiles, and engineeredsystems and data analysis. This inaugural issue of the annualresearch brochure highlights key accomplishments in 31 projectsspread among the five themes. Together, these researchprojects successfully drive the demonstration of multiple self-powered wearable systems with multimodal sensing capability.We are very proud of our recent accomplishments in systemsintegration as well as in many cutting edge technologies. Ourhealth and environment monitoring systems for monitoringasthma and metabolism, and our self-powered cardiac systemsfor vigilant ECG monitoring, provide unique capabilities. Wehave built ultra light and flexible wound monitoring patches.Several of our wearable systems are in clinical validation studies.This past year, even with COVID restrictions, we made significantaccomplishments in developing novel flexible materialsproperties for thermoelectric generators (TEGs), which are nowmore flexible than ever with record-high power levels. With tworecent NSF Partnerships for Innovation grants, ASSIST is nowfocusing on manufacturing TEGs and capacitivemicromachined ultrasonic transducers (CMUTs). The CMUTs arebeing used for sensing and ultrasound energy transfer inimplantables. Our biochemical sensing portfolio includes severalbiomarkers as well as the ability to collect sweat and other fluidspassively and at zero power.FROM OURCENTERDIRECTOR:Our research team is multidisciplinary, multi-university, andclinically engaged, with partnerships in the medical fieldhelping us to validate our systems. For example, we arepartnering with the University of Miami for monitoring woundsand with East Carolina University Medical School for kidneytransplant monitoring. Our research is highly entrepreneurial,with spinouts representing our most successful technologytransfer and commercialization avenue to date. ASSISTlaunched two more companies last year, bringing its total to 10startups. Alongside our research mission, we are also training apipeline of students, from K-12 to doctoral levels, for nextgeneration leadership in health and technology. As we enter our tenth year, we look forward to graduating fromNSF and moving towards self-sufficiency. We have addedseveral new research projects through new funding, and weare expanding our industry membership portfolio. We arepleased to have Medtronic, Biostrap, Triad Semiconductor,Vadum, and Olftech join us as our newest members. As youreview this research portfolio, I invite you to reach out to us forpotential collaboration opportunities. Finally, COVID has shown that the outcomes for many infectedwith the virus were significantly worsened if they had chronicdiseases. Join us in our mission to build always-on devices thathelp us manage chronic conditions and improve our healthand resilience.Sincerely,Dr. Veena MisraDistinguished Professor, NC State UniversityDirector, ASSIST Center

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FROM OURINNOVATIONECOSYSTEMDIRECTOR:In the pages that follow, you’ll see research that is more thanacademic. It targets real-world use cases, with the goal oftranslating a new generation of wearable technologies fromthe university to the clinic, the battlefield, and the market.Achieving this requires partners and supporters from across theuniversity, large and small companies, clinics, and supportingorganizations. These partners create an Innovation Ecosystemwhere research drives impact.The impact goes beyond commercializing technologies. Itincludes transferring knowledge, preparing students, andfostering new ideas and opportunities from relationships.Some of our most important relationships are with our industrymembers. ASSIST membership provides organizations accessto intellectual property, preferred commercializationopportunities, engagement with faculty and students, andnetworking with other organizations in the same technologyand application spaces. In addition, our members participate in the Center’s growth.This past year, we welcomed Medtronic, Biostrap, Olftech,Triad Semiconductor, and Vadum as new membercompanies. We expanded the breadth of research we sharewith our members to include projects funded outside of ASSIST.We built new opportunities for industry member engagementwithin the Center, holding member company seminars,introducing member companies’ products to students andfaculty, and providing access to student recruitingopportunities. With ASSIST support, member company Onda Vision Technologies earned their first SBIR award. Wewere awarded a Partnerships for Innovation grant to exploremarket opportunities for ASSIST's flexible thermoelectricgenerator (TEG) technology. We also ramped up translationalprototyping, creating demonstration devices for technologyshowcases and conferences. Finally, we expanded discussionswith member companies to advance ASSIST technologies andevaluate commercialization opportunities.In the coming year, we will be providing our membercompanies with new engagement opportunities, providingaccess to even more research, and driving commercializationof ASSIST technologies in new ways. We also look forward toexpanding our ecosystem with new members to generateeven greater impact. While many of you are already part of ASSIST, if your companyor organization is not yet involved but aligns with our researchareas, or if you’re interested in joining the ecosystem in otherways, we’d welcome a conversation, and we invite you tojoin us.Sincerely, Dr. Adam CurryInnovation Ecosystem Director, ASSIST CenterASSIST Member Companies

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Over the past 10 years, ASSIST's education programs haveengaged students from middle school to graduate school in avariety of innovative programs focused on technical,professional, and translational skills. At every level, we offerhands-on, immersive experiences that spark students' curiosityand propel them towards future career success. The Wearable Device Challenge Competition for Middle andHigh School Students challenges teams to design and build awearable device to address an issue at the intersection ofhuman, animal, and environmental health. This event hasgrown every year since its inception in 2015, with teachers fromlocal schools near NC State, Penn State, and University ofVirginia coaching teams and hosting local competitions.Between 20 and 30 teams of students compete in the finalevent hosted at NC State in April of each year. Their uniquedesigns demonstrate understanding of the engineering designprocess and as well as remarkable creativity and technicalaccomplishment. ASSIST's Young Scholars (YS) and Research Experiences forTeachers (RET) programs provide immersive summer researchopportunities for high school students and middle and highschool teachers. To date, we have hosted more than 200Young Scholars and teachers in our labs, giving them a uniqueopportunity to experience life on a college campus and in aresearch laboratory. In addition to conducting an independentresearch project, participants also design and build their ownwearable device and participate in a variety of technical andprofessional development activities. For undergraduate students, ASSIST provides 10-week summerresearch opportunities as well as academic term researchfellowships. These programs allow students to apply theirtheoretical classroom knowledge to an independent researchproject under the mentorship of a graduate student and facultyadvisor. ASSIST also sponsors projects in Capstone Design Courses,providing senior-level engineering students practicalengineering challenges focused on ASSIST's strategic technicalthrusts. At the curriculum level, ASSIST has developed a multi-disciplinary minor program in nano-science and technology.FROM OUREDUCATIONDIRECTOR:Graduate students are one of the Center's greatest assets, andwe are very proud to be a foundation and springboard for theirfuture success. In addition to research, our TranslationalEngineering Skills Program (TESP) aims to provide graduatestudents with key skills for future success including: systemsthinking, entrepreneurship, industry experience, mentoring andleadership, communication skills, ethics, diversity and inclusion,and more. We work closely with our innovation ecosystem toprovide students opportunities to engage with industry partners.To date, the Center has graduated over 80 PhD students whohave gone on to successful and impactful careers in bothacademia and industry. Sincerely,Dr. Elena VeetyAssistant Teaching Professor, NC State UniversityEducation Director, ASSIST Center

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Flexible Thermoelectric Generators forBody Heat HarvestingObjective: The objective of this program is to build high-performanceflexible thermoelectric generators, which can conform tothe human body, providing both performance andaesthetics. Thermoelectric generators (TEGs) that canconvert body heat to electricity are of interest to realize self-powered wearable sensor systems, which can providehassle-free, long-term, continuous monitoring. Such devicescan significantly improve management of chronic diseasessuch as cardiovascular diseases and increase patients’quality of life.Key Accomplishments:Our group was the first to propose flexible TEGs that reliedon rigid thermoelectric pellets used in commercial rigidTEGs. Our group was also the first to propose the use ofliquid metal interconnects in flexible thermoelectricgenerators. To date, our team has developed several newelastomer composites to improve the thermal engineeringof our devices, including a high thermal conductivityelastomer for EGaIn encapsulation and a low thermalconductivity elastomer between the pellets for reducedheat leakage.6Approach: Our unique patented approach employs industry standardrigid semiconductor pellets, which are embedded in aflexible elastomer. The pellets are connected in series usingEutectic Gallium-Indium (EGaIn) liquid metal interconnects,which provide excellent flexibility, stretchability, andelectrical conduction. By employing rigid pellets currentlyused in commercial rigid TEGs, the approach eliminates theneed for new thermoelectric material development,thereby providing a low-cost-of-ownership flexible TEGoption to existing TEG manufacturers.Impact: Our latest devices provide best-in-class performanceamong published flexible generators and rival theperformance of rigid thermoelectric modules, providing acontinuous supply of energy to realize self-poweredwearable monitoring devices.Principal Investigators:Dr. Mehmet Ozturk, Dr. Daryoosh Vashaee, Electrical & Computer Engineering, NC State UniversityDr. Michael Dickey, Chemical & Biomolecular Engineering, NC State UniversityPostdocs:Dr. Farzad MohaddesDr. Yasaman SargolzaeiavalFunding sources:NSF ASSIST CenterNSF PFI programA cross-sectional image of a flexible thermoelectric generator made with high thermal conductivity encapsulation and liquid metalinterconnects (left). A data acquisition system to capture power generated by a flexible TEG under various modes of activity (right).

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Modeling of Thermoelectric Generatorsfor Body Heat HarvestingObjective: The objective of this program is to develop efficientanalytical models to accurately predict the performance ofthermoelectric generators (TEGs) on the human body undervarious contextual scenarios. Thermoelectric generators thatcan convert body heat to electricity are of interest to realizeself-powered wearable sensor systems, which can providehassle-free, long-term, continuous monitoring. Such devicescan significantly improve management of chronic diseasessuch as asthma, cardiovascular disease, and diabetes,increasing patients’ quality of life.7Approach: Our approach includes the use of both highly-efficientanalytic and 3-D numerical simulations. The analytic modelsthat we develop provide the ability to quickly understandthe impact of different design parameters on deviceperformance, while the 3-D numerical models provide amore in-depth understanding of the TEG operation. Themodels include the contributions of the device architecture,physical dimensions, thermoelectric materials, and parasiticthermal/electrical resistances. The models are alsodesigned to take into account the impact of the humanthermoregulatory system, which determines the metabolicrate and core body temperature, allowing time-dependentsimulations of the TEG output.Impact: Our latest analytical model can not only guide designengineers in improving their device design, but alsoprovide the ability to factor in the user’s age, sex, weight,and height. As an example, our results indicate that olderindividuals will generate approximately 30% less powerthan younger ones, which is significant because older userswill likely benefit significantly from self-powered operationenabling continuous, long-term monitoring. The modelingof the impact of physical activity is especially important forsports performance monitoring.Principal Investigator:Dr. Mehmet Ozturk, Electrical & Computer Engineering, NC State UniversityPostdocs:Dr. Farzad MohaddesDr. Yasaman SargolzaeiavalFunding source:NSF ASSIST CenterKey Accomplishments:Our model published in 2016 was the first 3-D analyticalmodel for TEG simulation. These simulations werecomplemented by 3-D numerical simulations usingCOMSOL simulation environment. Our latest model, whichis a first of its kind, includes the impact of the humanthermoregulatory system and physical activity.TMExcellent agreement is obtained between measured andcalculated output voltages of a flexible TEG duringwalking/running at different speeds. Calculated values includethe rise in metabolic rate and core body temperature, as wellas convective cooling, at different speeds.

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Self-Powered Smart Insoles for Balanceand Gait DetectionObjective: This project seeks to develop a self-powered sensing array in ashoe insole for gait detection. The larger aim is to developtechnologies to provide accurate, just-in-time assessment ofrisk of injury for conditions in which balance, gait, posture, andphysical activity are key predictors. Such conditions include,but are not limited to, old age, physically demanding jobspaces, Parkinson’s disease, and diabetes. Key Accomplishments:We have fabricated our first piezoelectric-on-foil sensingarrays and tested them on a material testing machine. Wehave thus demonstrated the basic pressure sensingtechnology. We have demonstrated our first energyharvester and tested it in a shoe. It can produceapproximately 20 milliwatts under normal walking conditions.Finally, we have fabricated the silicon pyramid arrays needed for the transition to flexoelectric transducers.Funding source:NSF ASSIST CenterPrincipal Investigators:Dr. Susan Trolier-McKinstry, Materials Science & Engineering, Penn State UniversityDr. Shad Roundy, Mechanical Engineering, University of UtahStudents:Issak Allaire-McDonaldSujay HosurTravis Peters8Approach:Our approach is two-fold: 1) develop thin film piezoelectric-on-foil pressure sensing arrays to be inserted in the shoe insoleand 2) power these via an energy harvester placed in theheel of the shoe, eventually moving to just the insole. Manysmart insoles for use in clinical environments exist. However,these are expensive and power hungry, limiting their potentialoutside the clinic. By using piezoelectric-on-foil technology,we aim to create a very low-power sensing array that can beself-powered and therefore used for longer term studiesoutside the clinic and eventually as an assistive care product.The energy harvester is initially being developed with leadzirconate titanate (PZT) piezoelectric transducers. However,we will transition to a new technology, space-chargeenhanced flexoelectric transducers, that are lead free,potentially very low cost (i.e., made from silicon), and havehigher electromechanical coupling.Impact:Tens of millions of people have an elevated risk of falling,including the elderly, persons with mobility disorders, andindividuals with diabetes. Falls resulted in 3 million emergencyroom visits and 28,000 deaths in 2014 in the United States. Theannual cost burden is estimated to be $50B. This work willenable long-term studies on the relationship between gaitpatterns and injuries from falls. Our ultimate goal is for thetechnology to be used in real-time assistive systems to predictrisk of fall and warn users before falls occur.Flexoelectric transducers (left) embedded in the heel of the shoe will provide self-powered operation of the piezoelectric thin filmsensing arrays (right) distributed throughout the shoe insole, enabling long-term real-time assessment of gait and balance.

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New Mode of Mechanical-to-ElectricalEnergy HarvestingObjective: Mechanical energy is often wasted (i.e. not harvested) inthe form of vibrations, wind, and ocean waves. We seek anew, simple approach to energy harvesting by creating anew type of “variable area soft capacitor” in which anymechanical inputs (compression, stretching, twisting, etc.)can generate electricity. The device is built entirely from softmaterials, thus making it compatible with the human bodyand wearable devices. It also is distinguished by the use ofsalt water, making it compatible with harvesting energy inthe ocean or in the presence of sweat.9Approach: We convert mechanical motion to electricity using acompletely new soft “variable area electrochemicalsupercapacitor.” Mechanical input from stretching,deforming, or oscillating the device causes charges tomove (i.e., generate electricity) in/out of a circuit. The ideais to utilize a non-toxic metal alloy with a low meltingtemperature as a stretchable electrode to fabricatevariable area capacitors that convert mechanical toelectrical energy. When metals are placed in saltwater,they form a so-called “electrical double layer” at theirsurface (positive and negative charges). This principle isImpact: This energy-harvesting device is completely soft andtherefore is comfortable for wearables. It also means it canconvert any mode of mechanical deformation(compression, strain, twisting, etc) to electricity. The scalingphysics suggest a path forward to increase the poweroutput by increasing the surface area of the metal.Principal Investigator:Dr. Michael Dickey, Chemical & Biomolecular Engineering, NC State UniversityStudent:Veena VallemFunding sources:NSF ASSIST CenterNano-Bio Materials Consortium (NBMC)Representation of electricity generation when a soft, stretchable hydrogel supercapacitor is mechanically deformed. Theopposite charges in the double layer are shown as red and blue. used commercially in supercapacitors to store largeamounts of energy. Whereas conventional supercapacitorsuse rigid, porous carbon electrodes to store energy, wepropose to make such electrodes out of stretchable liquidmetal to generate energy because of liquid metal’s abilityto change geometry. When the geometry changes (due tomechanical energy input), the capacitance changes, andcharge moves through a circuit as electricity. Key Accomplishments:We have published a paper in (Vallem,et al. ‘A Soft Variable-Area Electrical Double Layer EnergyHarvester’) that shows how combining gallium alloys withhydrogels can create a device that converts motion toelectricity.Advanced Materials

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Printing of Stretchable ConductorsEnabled by Highly TunableMultiphase Liquid Metal PastesObjective: Liquid metals (LMs) are of great interest for manyapplications given their excellent electrical and mechanicalproperties that allow significant stretchability. However, theirdeployment is currently inhibited by manufacturing issuesstemming from the large surface tension of LMs, whichmakes it difficult to pattern and adhere to surfaces. Theobjective of this project is to demonstrate a novel class ofmultiphase LM pastes whose properties can be designedthrough systematic incorporation of solid additives and fluidmicro-capsules with nanometer thin oxide shells.Introduction of these easily tunable pastes could enablelarge-scale adoption of the materials in stretchableelectronic, thermal management, and medicalapplications.(such as polymers), but non-trivial to do the opposite. Themixing of secondary fluids or solids into LM is a surprisinglynon-trivial task due to the high cohesive energy density ofthe metal. Based on our preliminary results, we assert thatthe rapid surface oxidation of LMs enables a generalpathway for achieving this task.Key Accomplishments:To date, we have demonstrated it is possible to createliquid metal pastes that can be 3D printed. We form thesepastes using oxide or particle inclusions to modify therheology of the otherwise Newtonian liquid.10Approach: By incorporating solid and fluid fillers, this project seeks torender LMs easier to pattern by additive manufacturing,broaden their range of physical and chemical properties,and, by decreasing the overall metallic content, increasetheir economic appeal. To date, researchers have shown itis easy to distribute liquid metal droplets in other materialsImpact: This project will create soft metallic materials withcompletely new properties while retaining electricalconductivity to make them more manufacturable. Ourpersonal interest is tuning the rheological properties toenable facile printing of metallic materials at roomtemperature that are soft, stretchable and flexible. Yet,there are many other properties, such as adhesion, thatcan be tuned by forming foams and pastes.Principal Investigator:Dr. Michael Dickey, Chemical & Biomolecular Engineering, NC State UniversityStudents:Febby KrisnadiJoe VongFunding source:NSF Arizona State UniversityThis project seeks to transitionfrom typical liquid metalprinting (left) to paste-likeextrusion (right) by novelmaterials engineering.

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Development of Sweat BioCapacitor forSelf-Powered Multimodal MetaboliteSensors11Principal Investigators:Dr. Michael Daniele, Electrical & Computer Engineering, Biomedical Engineering, NC State UniversityDr. Koji Sode, Biomedical Engineering, UNC-CH, NC State UniversityPostdocs and Students:Dr. Inyoung LeeKartheek Batchu, Kentaro Hiraka,Thy Le, David ProbstFunding source:Nano-Bio Materials ConsortiumObjective: The objective of this study is to develop a self-poweredmultimodal metabolite sensor which is operated frombioelectrochemical energy harvested from organiccompounds (glucose and lactate) existing in sweat. Theinherent challenges to harvesting energy from biochemicalsources are 1) the current density and theoretical limit forgenerating electrochemical potential are both low, and 2)the lactate concentration in sweat is too high to beefficiently catalyzed by the conventionally-utilized enzymefor lactate oxidation. This challenge calls for thedevelopment of technologies that fully and efficiently utilizebiochemical compounds in sweat for energy harvesting andconsequent powering of health sensors.Key Accomplishments:Engineering of lactate oxidizing enzyme resulted in theconstruction of an ideal lactate oxidizing enzyme which isheat stable (stable up to 70°C), with high Km value (~10 mM)and DET and quasi-DET ability with electrode. Through thecombination of DET-type glucose dehydrogenase andflexible thin-film multiplexed electrodes, simultaneousdetection of lactate (1 – 10 mM) and glucose (0.5 – 50 mM)was achieved in artificial sweat. Continuous operation ( ̴10hours) of a lactate BioCapacitor was also achieved. Approach: Our approach is based on an innovative bio-electrochemical device, “BioCapacitor”, and engineereddirect electron transfer (DET) type engineered redoxenzymes. The enzyme fuel cells in BioCapacitor arecomposed of engineered DET-type redox enzymes, whichare able to efficiently utilize glucose and lactate in sweat,and thereby realize the Dual-BioCapacitor, which providessufficient electricity to operate multimodal sensors and awireless signal transmission system.Impact: The success of this study will accelerate the realization ofself-powered wearable sensors for health care and disease-monitoring systems, which may include the addition ofadvanced technologies for sampling (e.g. sweat samplingor reversed iontophoresis-based interstitial fluid sampling).Sweat collecting patch and redox enzymes for lactate and glucose(top). BioCapacitor incorporated with support electronics including amicroprocessor, memory, and transmitter (middle). Charge anddischarge cycles of the dual cell BioCapacitor (bottom).

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Ultrasonic Energy/Data Transfer forImplantablesObjective: Implantable medical devices offer significant opportunitiesfor sensing, stimulating, and data transfer. However, a bigchallenge for these implanted devices is related to theirpower consumption and power management, which canlimit long term usage. Ultrasonic power transfer providessubstantially higher power density and reaches muchdeeper in tissue compared to alternative sources usinginductive coupling or radio-frequency (RF). A keyadvantage of ultrasonic energy transfer over the competingRF technology is that the maximum allowed power level intissue for diagnostic ultrasound is 7.2 mW/mm2, which isabout 70x higher compared to RF energy limits. Furthermore,attenuation of ultrasonic signals in tissue is far less than RF,and the wavelength of the ultrasonic energy in tissue is onthe order of millimeters. These advantages translate to asmall device size and excellent range in biological systems.In this project, we aim to develop a miniature ultrasonicallypowered device integrated into an endo-vascularaneurysm repair (EVAR) stent-graft that could provide on-demand diagnostic information about the presence ofendoleak (a condition leading to pressure buildup in theaneurysm sac), based on measurements of the aneurysmsac dimensions, and of the stent-graft inside the vessellumen.Key Accomplishments:To date, our team has demonstrated the feasibility of thepresented approach, which includes key concepts for animplantable intravascular ultrasound device tomonitor/diagnose endoleak in endovascular aneurysmrepair stent-grafts. In benchtop studies using externallybiased CMUTs and off-the-shelf discrete components, wedemonstrated 1) greater than 1 mW power recovery froma 3 mm2 device with incident ultrasound intensity of 5mW/mm2, which is less than the spatial-peak temporal-average ultrasound intensity (ISPTA) limit of 7.2 mW/mm2set for diagnostic devices. 2) Ultrasonic biphasiccommunication concept with potential for high data rateand 3) pulse-echo ranging from sensor to EVAR structureshave also been shown. We also designed and fabricatedpre-charged CMUTs and integrated circuits for powertransfer.12Approach: Our approach to implement the described implantabledevice relies on using a capacitive micromachinedultrasonic transducer (CMUT) with integrated electronic Impact: The results accomplished to date show the potential ofCMUT-based powering, sensing, and wirelesscommunication for implantables in a broad range ofapplications ranging from cardiovascular health to neuralsensing and stimulation.Principal Investigator:Dr. Omer Oralkan, Electrical & Computer Engineering, NC State UniversityOther Faculty, Postdocs and Students:Dr. Yaoyao JiaDr. F. Yalcin YamanerMuhammet Annayev, Linran ZhouFunding source:NSF ASSIST Center(Center-2-Centre Grant)Implantable system (left) including CMUT device (top right image detail) and integrated electronics (bottom right image detail).circuits to function as an ultrasonic power receiver, adistance measurement sensor, and a transmitter for wirelessdata transfer to an external unit.

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High Energy Density Lithium-IonCapacitor for Wearable TechnologiesObjective: This project aims at developing a high energy densitylithium-ion capacitor (LIC) with low self-dischargecharacteristics and long cycle life as a promising energystorage solution for the design of self-powered wearabletechnologies for continuous health monitoring. Thetechnology improves the volumetric energy density ofexisting state-of-the-art capacitor technologies by ~3x. Thelong cycle life (>10,000 cycles), high energy density, and fastcharging/discharging capabilities make it a suitablealternative for the lithium polymer batteries that are used incurrent wearable device platforms. for use in conjunction with low power energy harvestingand sensor technologies. The technology can be usedeither as a standalone energy storage solution or inconjunction with batteries for continuous health monitoringwearable devices and Internet-of-Things (IoT) basedsystems.Key Accomplishments:Currently, we have fabricated lithium-ion capacitors thathave a cell capacitance of 4–5 F packaged in a 2016 coincell prototype and a volumetric energy density of ~13Wh/L.The cells were capable of being charged between 2.2Vand 3.8V. In comparison with a commercial 3.6V lithium-ionrechargeable (LIR) battery of similar form factor, thecapacitor shows higher capacity retention at fast chargingand discharging rates. Long-term stability tests underconstant current conditions showed that our capacitorlasted three times longer (~550 hours) relative to batterieswhen charged and discharged at 8 mA. These results showthat LICs can provide an energy efficient solution for fastcharging or high pulsed current loading conditions. Tofurther demonstrate the functionality of our LIC, we haveshown that the capacitor can be used to power a MaximIntegrated Health Sensor platform. The capacitor, whencharged with a flexible solar cell powered by indoorlighting, can continuously power the sensor platform forseveral days.13Approach: The technology is based on a high capacity porous carboncathode and a prelithiated graphite anode. The highsurface area porous carbon cathode, with its uniquebimodal pore size distribution, provides accessible surfacearea with adequate transport porosity that enables thefabrication of ultrathick electrodes that are > 0.5 mm thick.The prelithiation process, when combined with themicrostructure of graphite anode, facilitates fast chargingand discharging rates as high as 10 C-rate. Additionally, theassembled capacitors show a low self-discharge rate with90% capacity retention over 2 months, making it attractive Impact: A high energy density lithium-ion capacitor packaged in asmall form factor, such as a coin cell prototype, can offersignificant advantages over rechargeable and primarybatteries of similar form factor in terms of current ratings,cycle life, and energy efficiency. Successful developmentof the technology into various form factors that includeflexible pouch cells can offer the potential to fabricatecells/modules with different capacities and extend itsapplication as a standalone energy storage device or itsuse in conjunction with batteries. The developed productscan have major applications in wearables, Internet ofThings (IoT) systems for industrial use, renewable energysectors, and automotive industries. Principal Investigators:Dr. Ramakrishnan Rajagopalan, Department of Engineering, Applied Materials, Penn State UniversityDr. Clive Randall, Materials Science & Engineering, Penn State UniversityStudent:Linsea ParadisFunding source:NSF ASSIST CenterComparison of ASSIST coin-cell Capacitor (image insert) tosimilar form factor Li-ion battery, demonstrating highercapacity retention at fast charging/discharging rates.

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High-Performance Three-DimensionalThin-Film Thermoelectric Generators14Objective: Harvesting power from body heat via thermoelectricgenerators (TEGs) is a promising route to realizing self-powered wearables for continuous, long-term monitoring ofhealth and environmental parameters. This research focuseson developing a novel thermoelectric device structure thatenables high-efficiency thermoelectric generators speciallydesigned for power generation from low temperaturegradients. Such generators are relevant for harvestingenergy from the body, which may differ from the ambienttemperature by only a few degrees.Approach: In contrast to conventional devices made of only dozens ofmillimeter-scale thermoelectric elements, the new deviceconsists of several thousand micro-scale elements. As aresult, it can generate >1000X larger voltage from a similartemperature gradient. The project focuses on developing awafer-scale microfabrication process on inexpensive siliconwafers. The fabrication relies on mature processes andtechniques used in microelectromechanical systems(MEMS) fabrication. The research covers both materialsdevelopment and device fabrication.Key Accomplishments:A wafer-level fabrication process has been developed,and the proof-of-concept devices are currently beingmanufactured. Nanocomposite and heterostructurethermoelectric materials with high efficiency have beendeveloped for device fabrication. The films are grown by ahybrid cross-beam Pulsed Laser Deposition – MolecularBeam Epitaxy (PLD-MBE) system to enable an extensiverange of growth process parameters and achieve high-quality films. Heterostructured materials offer higherefficiency compared to homogeneous films and areoptimized for device prototyping testing.Impact: The envisioned devices will provide significantly moreelectrical power than conventional devices while reducingthe area needed for thermal energy harvesting. Thedevices will be small enough to be seamlessly integratedinto wearable monitoring devices.Principal Investigator:Dr. Daryoosh Vashaee, Electrical & Computer Engineering, NC State UniversityPostdocs and Students:Dr. Jie LiuPrithu BhatnagarFunding source:NSFSilicon wafer with multiple micro TEG chips (left). Top view of a single TEG with close-up (middle). N- and P-type materials deposited bypulsed laser deposition (right).

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Key Accomplishments:To date, our team has fabricated several MOx sensorsincluding n-type SnO, n-type ZnO, p-type CuO, p-type SnO,and their composites. In the area of air quality, our sensorshave been able to detect ozone concentrations at a fewppb levels. These sensors have been utilized in humansubject studies related to asthma, given that ozone is aknown trigger for asthma attacks. Our sensors have alsobeen used to measure breath acetone and breathethanol under various user scenarios. Different MOxsurfaces showed differences in breath analysis for regulardiet, 30-hour fasting, and for ethanol. We have also usedthese arrays to measure mixtures of different VOCs. Thepower consumption of these sensors is the lowest reportedto date.Ultra-Low Power Metal Oxide ElectronicNose Arrays for Environmental andBreath MonitoringObjective: An individual’s exposure to certain gases in the environmentcan have a direct impact on health, and volatile organiccompounds (VOCs) emitted in breath can indicate thestate of metabolic activity. To understand these factors andexplore new biomarkers, we seek to build a wearabledevice that can monitor a person’s immediate environmentas well as their breath over extended periods of time andcorrelate these measures with results from other healthsensors. 16Approach: Our unique approach utilizes multiple metal-oxide (MOx)sensors that are made using a novel monolithic processbased on complimentary metal-oxide-semiconductor(CMOS) processing, microelectromechanical systems(MEMS), and atomic layer deposition. This novel route canbe used to produce a large number of metal oxide surfacesin a single device, thereby providing the discernability of anelectric nose (e-nose) array. This e-nose array has ultra-lowpower operation (<1 mW) and, through machine learning,can differentiate between a variety of gases and correlatethese to air quality or metabolic state.Impact: These results illustrate the potential of these gas sensortechnologies to identify disease patterns as well as providewarnings to vulnerable individuals when exposed to poorair quality. Since these wearables are also monitoringhealth vitals, this allows the direct correlation of health andenvironment. In addition, detection of VOCs in breathdirectly can provide insight into the metabolic state of thebody. Principal Investigators:Dr. Veena Misra, Electrical & Computer Engineering, NC State UniversityDr. Bongmook Lee, Electrical & Computer Engineering, NC State UniversityPostdocs and Students:Dr. Farzad MohaddesSmriti Rao, Yilu ZhouFunding source:NSF ASSIST CenterWrist-worn wearable device (left) enables continuous, low-power detection of environmental gasesand breath using novel MOx sensor arrays (right).

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Capacitive Micromachined UltrasonicTransducer based Gas and BreathSensingObjective: Monitoring different pollutants in the environment in realtime and correlating this with physiological parameters in anindividual opens the opportunity to manage wellness anddisease in a personalized manner. Volatile organiccompounds (VOCs) represent a large class of gases thatcan present a health hazard, especially in indoorenvironments. Furthermore, volatiles in the breath havebeen shown to be early indicators of disease. For this reason,a wearable device that can monitor a person’senvironment as well as their breath is significant. Key Accomplishments:To date, our team has fabricated 8-channel sensorprototypes integrated with custom-designed low-powerintegrated circuits as a battery-powered wireless unit.These prototypes have been shown to selectively sensevolatiles such as ethanol, toluene, p-xylene, styrene, andothers in ppb- to ppm-level concentrations. These sensorshave also been shown to be capable of differentiatingbetween breath samples collected at different metabolicstates.17Approach: Our approach to implement the described sensor systemrelies on achieving high specificity and sensitivity by using amechanically resonant mass-loading sensor coated withselective functionalization layers. The mechanical resonatorof choice is a capacitive micromachined ultrasonictransducer (CMUT), which is suitable for arrayimplementation and achieves a high quality factor enabledby a vacuum cavity on the backside of a vibrating platestructure. The array approach is especially important toachieve high selectivity by functionalizing different elementsof the array with different materials.Impact: The results accomplished to date show the potential of theCMUT-based gas sensor systems in a broad range ofapplications ranging from environmental sensing to healthmonitoring. Principal Investigator:Dr. Omer Oralkan, Electrical & Computer Engineering, NC State University Other Faculty, Postdocs and Students:Dr. Yalcin YamanerDr. Erdem SennikZack Coutant, Ali BilirogluFunding source:NSF ASSIST CenterWearable multichannel VOC sensor transmits raw data to a cellphone (left). Specific VOC detection (center). VOC chipintegrated into the wearable electronics (right).

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Multimodal Biosensing System forElectrochemical and PhotonicMonitoring of HealthObjective: The objective of this project is to engineer a wearablemultimodal biosensor platform for continuous monitoring ofglucose, lactate, pH, skin temperature, and tissueoxygenation. Integration of multimodal sensors providesmore impactful physiological data, and it provides moreaccurate sensor data by enabling sensor-to-sensorcalibration and validation.Key Accomplishments:The integration and testing of the multimodal biosensorplatform demonstrated 1) the simultaneous measurementof fluid pH and temperature to correct enzymaticmeasurements in real-time for the operation of enzymaticglucose, lactate, and urea sensors, 2) electrochemicalsensing of metabolites in collected or actively extractedsweat samples, and 3) combined electrochemical andphotonic sensing for local tissue or arterial oxygenationmeasurements. In benchtop measurements using standardinstrumentation, the electrochemical sensors are shown tohave sensitivities of 26.31 μA·mM-1·cm-2 for glucose, 1.49μA·mM-1·cm-2 for lactate, 54 mV·pH-1 for pH, and 0.002 V·°C-1 for temperature. With the custom wearable system,these values were 0.84 ± 0.03 mV·μM-1·cm-2 for glucose,31.87 ± 9.03 mV·mM-1·cm-2 for lactate, 57.18 ± 1.43 mV·pH-1 for pH, and 63.4 μV·°C-1 for temperature. The wearablesystem demonstrated comparable performance to themuch more expensive and cumbersome benchtophardware.18Approach: The sensor system combines a multiplexed array ofelectrochemical sensors to measure glucose, lactate, andpH in a wearable form factor, and it incorporates thesesensors with the necessary optoelectronics for simultaneousphotoplethysmography or pulse oximetry.Impact: This innovation enables real-time correction and extendeduse of the biosensors. Multimodal sensing will provide newcorrelative data streams for analyzing the user’s physiology.For example, combining lactate sensing with pulseoximetry can be applied to identification and evaluationof 1) cardiopulmonary issues or 2) performance issues likefatigue. Other use cases include chronic pulmonarydisease, infectious respiratory diseases, and humanperformance monitoring and/or prediction. Principal Investigators:Dr. Alper Bozkurt, Electrical & Computer Engineering, NC State UniversityDr. Michael Daniele, Electrical & Computer Engineering, Biomedical Engineering, NC State University Students:Kaila PetersonTanner SongkakulFunding source:NSF ASSIST CenterConventional electrochemical sensors can becombined with optical sensors for multimodalsensing and internal calibration.

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Chemical composition of biocompatible elastomer substrates,as-formed films, and stretchable circuit boards.Vascularized cardiac therapeutic patch implants on porcine heartpromotes tissue repair after myocardial infarction.Novel Biomaterials and Bioelectronicsfor Implantable CardiovascularTherapiesObjective: The objective of this collaborative project with the Centrefor Research in Medical Devices (CÚRAM) is to developbiomaterials for use in instrumented cardiac patches whichmonitor regenerative performance by integrating cardiacstem/stromal cell (CSC) patches with biodegradable circuitboards and thin-film electronics. Sustaining reliable,cytocompatible, tissue-integrating bioelectronics requiresnovel substrate materials that 1) can perform alongside thedelivered therapy (i.e., regenerative cell therapy) and 2) arecompatible with bioelectronic fabrication processes.Key Accomplishments:We have engineered pre-vascularized CSC patches anddemonstrated their efficacy in both rodent and porcinemodels. Specifically, patches implanted into an immune-competent porcine model of acute myocardial infarct (MI)have 1) improved angiogenesis at the host-patch interfaceand in the risk region and 2) improved myocardial viabilityand augmented cardiac function. We have fabricatedand characterized thin-films for biodegradable circuitboards using poly(octamethylene maleate (anhydride)citrate) (POMaC), a soft, elastic, biodegradable material.POMaC was formed into thin-films with both thermal andphoto-curing processes. Accordingly, we have fabricatedstretchable thin-films from POMaC via conventional softand photo-lithography methods.19Approach: The sensor system combines a vascularized engineeredtissue construct with biocompatible elastomers for deliveryof both cell therapies and bioelectronics. To do so, wefabricated cardiac regenerative cell patches andsynthesized a biocompatible elastomer to perform as thesystem substrate.Impact: Integration of sensing modalities with cardiac cell therapiescan provide routes to therapy optimization, improvedperformance, and outcome prediction. Moreover, thegenerally demonstrated biomaterial circuit boards can bedelivered in myriad applications, including implantablemedical devices, transient electronics, and stretchableelectronics.Principal Investigators:Dr. Ke Cheng, Molecular Biomedical Sciences, Biomedical Engineering, NC State UniversityDr. Michael Daniele, Electrical & Computer Engineering, Biomedical Engineering, NC State UniversityDr. Frances Ligler, Biomedical Engineering, NC State UniversityDr. Stefano Menegatti, Chemical & Biomolecular Engineering, NC State UniversityDr. Manus Biggs, Biomedical Engineering, NUI-GalwayPostdocs and Students:Dr. Teng SuDr. Carolina VargasBrendan TurnerFunding source:NSF ASSIST Center (Center-2-Centre Grant)

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Ultra-Low Power PhotoPlethysmoGraphy(PPG) for Wearable ApplicationsObjective: This project focuses on developing ultra-low power andnovel biophotonic techniques for wearable physiologicalsensing. State-of-the-art circuit designs reduce powerconsumption using techniques like logarithmic amplifier,heartbeat locked loop, etc. However, most of these systemswere evaluated on a benchtop or on the finger. This projectdemonstrated that compressive sensing is one of the lowest-power consuming alternative techniques for measurementsperformed not only at the fingertip but also on the wrist forcontinuous passive data collection.rate from the sparse PPG signal, with the whole systemconsuming 1.66 mW power for continuous streaming ofheart rate data over the commercial off-the-shelfBluetooth Low Energy radio of ASSIST's Health and ExposureTracker (HET) engineered system. We were able todemonstrate a wrist-worn system as an efficient platformfor future evaluation of the compressive-sensing basedPPG technique through in-vivo clinical studies under theHET testbed environment.20Approach: This project resulted in a compressive-sensing-basedapplication-specific integrated circuit (ASIC) forphotoplethysmography (PPG). We worked onminiaturization and integration of this novel compressive-sensing-based ultra-low power PPG ASIC into a wearablewristband and evaluated its usability to track heart rate onthe wrist.Impact: Photonic measurements, such as PPG and pulse oximetry,are the most common methods in wearable systems totrack physiology. On the other hand, these are some of themost power consuming modalities due to the necessity ofgenerating a large number of photons (i.e., generatingsufficiently bright light). Although most of this light is lost dueto absorption and scattering in the tissue, importanthemodynamic parameters are assessed in return. An ultra-low power ASIC for PPG is required for overcomingtranslational barriers related to use of these systems as apart of self-powered or extended battery life operation.Principal Investigator:Dr. Alper Bozkurt, Electrical & Computer Engineering, NC State UniversityPostdoc:Dr. Parvez AhmmedFunding source:NSF ASSIST CenterPPG block diagram (top left). ASIC (top middle)and assembled board (top right), wrist-wornsystem (bottom).Key Accomplishments:The system miniaturization for a wearable form-factor wasachieved with no compromise in the performance of theASIC. The ASIC consumes 172 μW of power to extract heart

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Principal Investigators:Dr. Ke Cheng, Molecular Biomedical Sciences, Biomedical Engineering, NC State UniversityDr. Spyridon Pavlidis, Electrical & Computer Engineering, NC State UniversityDr. Koji Sode, Biomedical Engineering, UNC-CHPotentiometric Detection ofNeuropeptides for Non-InvasiveMonitoring of StressObjective: Neuropeptide Y (NPY) plays a central role in a variety ofemotional and physiological functions in humans. Mostnotably, it has been found to possess anxiolytic properties,thus forming a part of the body’s response to stress, anxiety,post-traumatic stress disorder, and drug/alcohol addiction.Clinical studies have confirmed pg/mL concentrations ofNPY in sweat. The current state-of-the-art detectiontechniques are not suitable for point-of-care deployment.This project seeks to reliably detect NPY, a biomarker forstress found in human sweat, using gold-basedpotentiometric sensors. Key Accomplishments:Detection of NPY down to the targeted pg/mL range hasbeen achieved using potentiometry. The impact of non-specific adhesion was mitigated by using a PEG-basedbackfill of the aptamer-functionalized surface. We havealso demonstrated detection using a field effect transistor(FET)-based approach, which can be explored for bothtraditional complimentary metal-oxide-semiconductor(CMOS) and non-traditional semiconductor platforms. Wehave also translated our functionalization protocol to goldmicroelectrodes on flexible substrates and achieved pM-range detection of NPY using electrochemical impedancespectroscopy.21Approach: In this project, we are developing a gold microelectrodebased potentiometric sensor capable of ~pg/mL detectionof NPY in artificial sweat. Selectivity for NPY is achieved viaDNA aptamer immobilization. This approach is compatiblewith ASSIST’s Health and Exposure Tracker (HET) platform,which already performs potentiometric measurements ofsweat on both rigid and flexible substrates, thus enablingwearable, non-invasive sensing.Impact: Reliable and sensitive detection of NPY through wearablebiosensors can provide early insight into various emotionaland physiological functions and enable effectivemanagement of stress-related responses.Students:Grace MaddocksKaila PetersonHayley RichardsonFunding sources:NSF ASSIST CenterNano-Bio Materials ConsortiumNPY in pg/mL concentrations can be detected in sweat. Selectivity for NPY is achieved via DNA aptamer immobilization.

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Improving the Performance and Designof Potentiometric Biosensors for theDetection of Extracellular Histones inBlood with Deep LearningObjective: The objective of this project is to combine potentiometricbiosensors with standard machine learning techniques andstate-of-the-art deep learning techniques to detectcirculating blood-borne histones, which contribute to thedevelopment of Multiple Organ Dysfunction Syndrome(MODS), a potentially fatal condition in critically ill patients.This information will also be used to improve sensor sensitivityand drive design optimization.Key Accomplishments:We have demonstrated physiologically relevant nMdetection of calf thymus histone (CTH) using ourpotentiometric sensors. We have also used surfaceplasmon resonance (SPR) to understand howimmobilization protocols impact sensitivity, selectivity, andstability in response to regeneration. Regression analysis isbeing applied to these experimental data to unveil non-linear relations on the data. These analyses have also beenperformed with human histones (H4). Finite elementmodeling is being used to accelerate data generation.22Approach: Gold sensing electrodes are functionalized with RNAaptamers to detect extracellular histones with extendedgate sensors. These devices are being evaluated in buffer,serum, and whole blood as benchmarks for point-of-care(POC) deployment. We will then leverage deep learningtechniques to reveal intricate relationships and trends tocompensate for the conventional losses in sensitivityobserved in blood-based tests. These findings drive theoptimal design of the potentiometric sensors, thusestablishing design rules that can accelerate thedevelopment of these sensors across the community. Amajor obstacle to the application of machine/deeplearning techniques to biosensing is the generation ofadequate training data. A multiplexed potentiometricbiosensing platform, made possible by the use of theextended gate approach, and computer simulations will bedeveloped in order to identify time- and resource-efficientapproaches to algorithm training.Impact: Most demonstrations of potentiometric sensors stall duringthe translation from testing well-controlled laboratorysolutions to operating in serum or whole blood. Ourintegrated approach aims to overcome this to providebetter sensitivity and reliability. The use of machine learningremains nascent in this field. Therefore, we will establish astandardized protocol that other researchers in the fieldcan leverage in order to accelerate the adoption ofpotentiometric biosensors in new applications.Principal Investigators:Dr. Edgar Lobaton, Electrical & Computer Engineering, NC State UniversityDr. Spyridon Pavlidis, Electrical & Computer Engineering, NC State UniversityDr. Francis Miller, Dept. of Medicine, Duke UniversityStudents:Hayley RichardsonJeffrey BarahonaFunding source:NSFThe system uses machine learning for modeling, prediction, anduncertainty quantification in blood samples for histone detection.

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Use Case: Long-Term Wound Monitoringwith Multimodal Patches23Key Accomplishments: Our platform has been developed on a completely flexibleand skin-conformable substrate using high throughputfabrication techniques. Our design has allowed us toachieve consistent sensor performance with limited sensorcalibrations. The development of the entire platform on aconformable substrate enables the placement of thepatch directly over the wound without causing any patientdiscomfort. We have demonstrated biocompatibility of theplatform (ISO 10993, MEM elution L929 48 h) and areconducting human subject trials.Approach:Our technology provides a unique platform that measuresuric acid to quantify biochemical changes in the woundenvironment; lactic acid to evaluate the formation ofbacterial biofilms; and pH/temperature to evaluate thewound environment and quantify analyte levels. Objective: Diabetic wounds are a leading cause of amputations, withmillions of people suffering around the world. As a result ofinefficient wound monitoring techniques, wound care costsexceed $15 billion per year in the United States alone. Ourtechnology aims at developing a smart bandage for real-time wound monitoring for personalized wound care. Thereal-time monitoring aspect of our platform is meant toinform the patient’s wound care plan to mitigatecomplications associated with chronic conditions anddecrease the risk of infection and traumatic amputation.Existing wound care techniques require direct patientinteraction and are limited to objective analyses, such aswound width and depth.Impact: In line with our use case, development of smart bandagetechnologies will promote better wound caremanagement, improve clinical outcomes by detectinginfections in a timely manner, and enhance quality of lifefor patients with chronic wounds. Furthermore, theelectrochemical sensing methodologies and the flexibleelectronics integrated within our platform can be utilized todevelop a myriad of truly wearable systems, includingsystems for active wound healing.Principal Investigators:Dr. Alper Bozkurt, Electrical & Computer Engineering, NC State UniversityDr. Michael Daniele, Electrical & Computer Engineering, Biomedical Engineering, NC State UniversityDr. Vladimir Pozdin, Electrical & Computer Engineering, Florida International UniversityPostdocs and Students:Dr. Pulak BhushanZiwei (Adam) MaoTanner SongkakulFunding source:NSF ASSIST CenterFlexible, wireless, biocompatible patch, shown integrated with standardwound dressing, continuously monitors key indicators of wound health.

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Zero-Power Wearable Sweat Assaysand Long-term Sensing DeviceInterfaces Using Osmotic Pumpingand Paper MicrofluidicsObjective: Our team has pioneered a unique sweat extractiontechnique that can operate over periods of multiple daysby a novel, non-invasive osmotic-capillary method thatdoes not require any electrical power, and which caninterface with on-device sensors or benchtop assays.Key Accomplishments:We focus as the first major outcome of the project on thedevelopment of simple inexpensive non-invasive skinpatches for testing of sweat for cortisol levels, interleukins,other stress biomarkers, ionic balance, and toxins. Thisplatform can be used in integrated wearable systems forlong-term sweat and interstitial fluid (ISF) sampling andprolonged analysis of hormones, glucose, and other ISFbiomolecules.24Approach: Our technique gently extracts sweat from the skin using ahydrogel patch infused with benign solute. The solutecreates an osmotic pressure gradient that pulls sweat fromthe sweat glands (sweat glands naturally expel sweat byosmotic principles; thus, the technique is biomimetic). Thecollected sweat is then transported toward sensors bysimple and reliable paper-based microfluidics, which usewicking and capillarity to transport fluids without the needfor external electrical power. Engineered evaporation padsplaced at the end of the paper strips continually drive thetransport of fluids for days; in contrast, state of the artpaper-based assays are typically single-use devices andhave a short operating time.Impact: The osmotic-capillary principles that we have pioneered tointerface the skin could form the basis of a stunningtechnology breakthrough in the field, as they arebiomimetic, non-invasive, and do not require any electricalpower or any active sweating. The ability to continuouslyharvest sweat in a non-invasive and non-irritating way forlong durations enables performing a variety of bioassays ina non-invasive, user-friendly manner, and without anexternal power source.Principal Investigators:Dr. Michael Dickey, Chemical & Biomolecular Engineering, NC State UniversityDr. Orlin Velev, Chemical & Biomolecular Engineering, NC State UniversityStudents:Sneha Mukherjee, Tamoghna Saha,Tanner Songkaku, Murat YokusFunding source:Nano-Bio Materials ConsortiumDemonstration of paper microfluidic sweat collection devices (left), low-power electronics integration (middle), and overall system design (right).

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Ultra-Low Power System-on-Chip(SoC) Objective: This project seeks to develop an ultra low powercoreelectronics platform for integrating technologies from otherASSIST themes into a unified self-powered wearable sensingsystem with a total power sustainable by energy harvesting.This project targets a power budget less than 50 μW whileproviding flexible, multi-modal capabilities for ASSIST’s self-powered armband that monitors the wearer’selectrocardiogram (ECG), pulse via photoplethysmography(PPG), activity, and ozone environment. This armband,known as the self-powered adaptive platform (SAP) Gen 2,is the second device built on ASSIST’s Self-poweredAdaptive Platform (SAP). Demonstrated new SoC with RISC-V microcontroller unit(MCU), 8 kB memory, boot ROM, and on-chip clocks,for < 1 µW power consumption. Demonstrated a new flexible analog front end (AFE)with 4 modalities (V/I/R/C), consuming: 3 nW ECG; 13nW respiration; 9.35 µW PPG w/ LED; 16.7 µW SpO2 w/ 2LEDs; and 57 nW gas sensing.Event-driven system operation for analog front end(AFE) of 6.4 µW (Respiration, heart rate, SpO2, pulsetransit time, and ozone).Energy-harvesting power management unit (EH-PMU)with concurrent harvesting from light, heat flux,piezoelectrics, and 4 regulated VDDs (supply voltage),using 1 inductor, requiring 100 nA IDDQ (quiescentcurrent).Python system model for duty-cycled, hierarchical self-powered systems.Key Accomplishments:26Approach: The multi-chip platform, centered around a system on chip(SoC), includes circuits for data collection, data storage,data processing, node control, power management, powerharvesting, power delivery, and wireless communication.This project plays a key role in the strategic plan of theCenter, since low-power electronics are an importantcomponent in systems able to be powered by energyharvested from the body. Impact: This work is enabling the ASSIST SAP Gen 2 and future SAPsystems to operate entirely from harvested energy, due tothe low power operation and flexible functionality of thecustom chips.Principal Investigator:Dr. Benton Calhoun, Electrical & Computer Engineering, University of VirginiaStudents:Rishika Agarwala, Henry Bishop, Jacob Breiholz, Anjana Dissanayake,Katy Flynn, Shourya Gupta, Sumanth Kamineni, Peter Le,Shuo Li, Xinjian Liu, Natalie Ownby, Daniel Truesdell, Peng WangFunding source:NSF ASSIST CenterSystem on Chip (SoC) testing setup demonstratingharvesting and management of power fromsimultaneous thermoelectric, piezoelectric, andphotovoltaic sources.

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Wireless Wakeup for Energy Reductionin Plugged-In MELs (MiscellaneousElectric Loads)Objective: The overarching objective of this project is to develop aflexible wireless connectivity module that takes advantageof differentiating component capabilities to substantiallyreduce the power consumption of miscellaneous electricloads (MELs). MELs are plugged-in appliances and devices,which the Department of Energy (DOE) has identified toconsume over 30% and 36% of electricity consumption inresidential and commercial buildings, respectively. an ultra-low power WiFi wakeup receiver with powerconsumption of 578 µW, vs. 80,000 µW for a commercialoff-the-shelf (COTS) devicea 5G / NB-IoT (Narrow Band - Internet of Things) wakeupreceiver with 2.1 mW of power consumption (best inclass by 10x)a custom integration System-on-Chip (SoC) with 0.5 - 10µW active power and 50 nW sleep power (vs. 50 µWtarget and >1,000 µW for COTS)phantom energy reduction to <1 mW with wake-on-wireless and predicted turn-on capabilities, resulting in>87% reduction in MELs standby energy.Key Accomplishments:Through this work, to date, we have demonstrated:27Approach: MELs typically consume many watts in phantom power,which is continuous power consumption even when thedevice is not in use or even “off.” Our team is prototyping aconnectivity module based on a new custom radiofrequency integrated circuit (RFIC) system and assessinghow the connectivity module would reduce MELs powerconsumption across several dozen MELs appliances. Thesystem comprises a wakeup radio (to receive a wakeupsignal), an always-on processor for node control, and anelectrical interface to the MELs device(s). The system cutsoff power to idle MELs and uses either a wireless wakeupsignal or a predictive model to turn on the MELs device intime to prepare it for use. Impact: This work is demonstrating substantial savings in MELsstandby energy and phantom power. If adopted, thistechnology could reduce nationwide power consumptionby a meaningful percentage. Also, the componentsdeveloped in this work have made power reductions byorders of magnitude in standards-compatible wakeupreceivers.Principal Investigators:Dr. Benton Calhoun, Electrical & Computer Engineering, University of VirginiaDr. David Wentzloff, Electrical Engineering & Computer Science, University of MichiganStudents:Omar Abdelatty, Shourya Gupta,Shuo Li, Xinjian Liu,Trevor OdelbergFunding source:US Department of Energy

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Novel, Flexible, High Efficiency andMultifunctional Wearable AntennasObjective: Our goal is to develop advanced, ground-breaking, cutting-edge wearable antenna technologies whose customdesigns outperform the available commercial off-the-shelf(COTS) antennas as well as provide new antennas withmultifunctional capabilities that currently have no COTScounterparts.miniaturized capacitor-loaded metasurface-enabledantennas, a highly-flexible PDMS and silver nanowire compositecircularly polarized (CP) metasurface-enabledantenna, dual-band circularly polarized antennas, a miniature yet broadband proximity-fed antenna foreasy garment integration, a large bandwidth dual-port full-duplex textile antenna(can support both Rx and Tx modes in a singleantenna), a high-isolation full-duplex antenna with isolation up to40 dB, small form-factor highly-integrated filtering antennas(filtennas), an omnidirectional dual-polarized armband textileantenna array that operates at 6 GHz and the 2.45 GHzISM band, and a textile endfire leaky-wave antenna that can supportboth on-body and off-body communication modes.Key Accomplishments:Our groundbreaking wearable antenna technology mainlytargets high-efficiency in a small form factor as well asadvanced multifunctional capabilities which include full-duplex operation for enabling wearable systems operatingin both receiving (Rx) and transmitting (Tx) modes, andreconfigurable multi-mode functionality for on- and off-body communications. We have successfully developedseveral transformative wearable antenna designs, such as:Furthermore, we have a portfolio of patents filed/awardedon our wearable antenna technology.28Approach: The design challenges include 1) effectively minimizing thedegradation in antenna performance caused by humanbody loading, 2) developing antenna designs that arerobust to deformations due to body motion and location ofplacement, 3) achieving efficient coupling of wearableantennas to on-body and/or off-body propagation modes,and 4) maintaining high radiation efficiency in a small formfactor. Impact: To meet the demanding requirements for present andfuture body-area networks, we have developed a suite ofbest-in-class custom designed broadband, small form-factor, low-profile and/or multifunctional wearableantennas for easy textile/garment integration. Through theiroptimized design, these antennas reduce the powerneeded to operate wireless transmitters/receivers on thebody.Principal Investigator:Dr. Douglas Werner, Electrical Engineering & Computer Science, Penn State UniversityPostdocs and Students:Dr. Saber SoltaniConnor HaneyYuhao WuFunding source:NSF ASSIST CenterFlexible antenna using stretchable EGaIn liquid metal conductinglines (top), miniature broadband antenna for textile integration(center), and textile antenna wrapped around a cylinderrepresenting an arm (bottom).

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Principal Investigators:Dr. Shekhar Bhansali, Dr. Shubhendu Bhardwaj, Dr. Vladimir Pozdin, Dr. John VolakisElectrical & Computer Engineering, Florida International UniversityDr. Douglas Werner, Electrical Engineering & Computer Science, Penn State UniversityBody Worn Flexible Antenna forApplications in Communication and RFEnergy HarvestingObjective: The overarching objective of this project is to demonstrateantennas, rectifiers, and circuits optimized for sensorpowering, data-modulation, and data-extraction systemson textiles. This caters to the need for integrating passiveand active sensor components into fabric surfaces forcomfortable wearables. Indeed, integration into textiles isthe highest form of integration towards the most ergonomicuse-cases. Current technologies that use textiles-based electronics arelimited to antenna and passive components, and they havegenerally utilized ink-based printing. Our objective in thisproject is to explore embroidery-based methods which havelower radio frequency (RF) losses for the antenna as well asactive circuits. Using this approach, we have demonstratedthe first all-textile based wearable systems for wirelesspowering as well as sensor-electronics, which support notonly powering but data extraction as well.Key Accomplishments:One key accomplishment of this project was todemonstrate a textile-integrated RF powered surface withnear-zone based power transfer jacket and far-zone basedpower transfer jacket. For the near-zone scenario,ergonomic use of the jacket was demonstrated whileshowing integration with items of daily use such as chairs.Recently, a near-zone RF powered surface was integratedwith a voltage controlled oscillator based data modulationand data extraction circuit for wound sensing (viamonitoring uric acid levels). 29Approach: The approach for achieving textile integrated antennas andcircuits is to use embroidery of conductive thread onsurfaces such as organza and denim. With the precisionavailable from off-the-shelf embroidery machines, circuits inthe 2.4 GHz range are possible. RF power harvestingantennas, circuits, and data-modulation circuits, such asthose based on voltage-controlled oscillators, aredemonstrated, having optimized embroidery parameters.Impact: The impact of this project is that, in demonstrating ourtextile RF powering, data-modulation and data-extractionsystem, we have enabled the first completely textile RFIDsensors. The success of this project provides a new way topower and gather data from textiles-based wearables,with applications in the medical treatment industry andacademic research.Students:Pulak BhusanPawan GaireDieff VitalFunding sources:NSF ASSIST CenterAuestechWiGlRepresentations of various textile based antennadesigns for RF Energy TransferRectifier + Anchor -shaped RX AntennaLEDsTXLEDs on

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Key Accomplishments:Our team has determined a means for evaluating theimpact of electrode location and contact pressure on theECG sensing performance on the upper left arm. We alsoevaluated how the size of the armband form factor affectsits ECG sensing performance. Our experimental resultsconfirm that armbands exhibiting modeled contactpressures of 500 Pa to 1500 Pa can acquire ECG signals.However, armband sizes exhibiting experimental contactpressures of 1297 ± 102 Pa demonstrated the bestperformance, with signal-to-noise ratios (SNR) comparablewith wet electrode benchmarks. These results will beapplied in an Institutional Review Board (IRB)-approvedstudy with law enforcement in a local municipality (Town ofCary, NC). Our team is also creating an information portalfor existing e-textile commercial products that incorporatesteardown of the products to inspect materials and designtrade-offs.Transformative Textiles Designs for Self-Powered, Multi-Modal SensingGarmentsObjective: The objective of this project is to apply macroscalestrategies for innovative materials design andmanufacturing to solve the tradeoff issues that existbetween textile and device performance in the field ofelectronic textiles (e-textiles). The fundamental researchexplores mechanical burdens placed upon textiles by theincorporation of electronic materials and devices and thelow cost means by which to resolve these burdens. Solutionssought through this effort primarily focus on commerciallyready materials and processes, enabling rapid translation ofthe innovations to industry.32Approach: Our team is establishing garment design methods tovalidate the biometric performance of wearable systems.Systematic studies are designed for testing the quality ofASSIST’s shirt and armband platforms, including a use caseof law enforcement officer stress monitoring throughbiometrics analysis.Impact: Biometric data quality of an e-textile smart garment isheavily reliant on the design strategy for fabrication of thegarment and can vary from user to user. This projectidentifies the key factors in achieving design, comfort, andperformance of smart textiles using methods that aremanufacturable in the textile industry.Principal Investigators:Dr. Jesse Jur, Textile Engineering, Chemistry, & Science, NC State UniversityDr. Amanda Mills, Textile Engineering, Chemistry, & Science, NC State University Students:Tashana Flewwellin, Isabel Hines, Beomjun Ju,Furkan Kose, Braden Li, Marissa Noon,Busra Sennik, Olivia Turschak, Vince VarjuFunding source:NSF ASSIST CenterArm sleeve test platform (left) and example comparison data (right) between ECG collected from the sleeve with Ag/AgCldry electrodes and that obtained from the chest with Ag/AgCl wet electrodes.

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Method of Automated Handling ofTextiles for Improved Efficiency andAccuracy to Enable E-TextileManufacturingObjective: Automation through fabric handling and assembly is a nec-essary means for bringing textile manufacturing back to theUnited States. This method reduces the amount of labornecessary and enables new capabilities in textile productmanufacturing to lower the end product cost. The cost issueis heightened for electronic textile products, lending to anincreased need for automation. Currently, textilemanufacturing is highly dependent on manual constructiondue to the challenges in automating the handling of fabricbecause of its flexibility and drape. Automated handlingcan provide more reliable and consistent construction. Thegoal of this work is to use this automated handlingtechnique to provide accurate placement of fabric,enabling new opportunities in e-textile product construction.Key Accomplishments:We have successfully automated the grasping andtransferring of the part pieces to construct an ImprovedOuter Tactical Vest (IOTV) cummerbund. Currently thisproduct is being constructed manually with an average of169 seconds spent just transferring the part piecesthroughout the construction process for each productionbatch. With the insertion of automated handling, this timecan be reduced, and the process to construct the IOTVcummerbund can be streamlined. 33Approach: We have developed an electromagnetic end-effectorgripper that latches and connects to the rigidferromagnetic components of the e-textile systems as ameans for material handling. Instead of trying to grasp thefabric itself, we have developed a method of graspingeither permanent or temporary connectors within the textileto handle and transfer different textile part pieces.Automating the handling of the textile part piecesgenerates higher accuracy, consistency, and speed withinconstruction of textile products, creating opportunities foradvanced materials integration for applications such aswearable technology.Impact: The implementation of automated handling in theconstruction of textile products will reduce the amount oflabor required, allowing for shorter lead times as well as amore economically viable method for manufacturingdomestically. Additionally, it will provide an avenue tointegrate more advanced materials such as e-textilesystems because of the improved consistency within theconstruction from automated handling.Principal Investigator:Dr. Jesse Jur, Textile Engineering, Chemistry, & Science, NC State UniversityStudents:Zoë RosenbergFunding sources:UNC General AdministrationARMY DEVCOM-CCDCElectromagnetic end-effector gripper that latchesand connects to the rigid ferromagneticcomponents of the e-textile system.

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Novel Textile-Based Sensors for InnerProsthetic Socket Environment MonitoringObjective: This project aims to develop a novel Flexible InneR-socketSensing Technology (FIRST) seamlessly, unobtrusively, andelegantly integrated into the lower-limb prosthesis socket.FIRST is based on an electronic-fabric structure in which thefibers of the fabric act as sensory elements that cansimultaneously track tactile forces, moisture/wetness,electromyography and body temperature at multiplesensing points around the residual limb. The major challengeis to develop a fundamental understanding of the couplingand interaction between multi-component fiber cross-sectional architecture, fabric structure, and its electro-mechanical response to achieve a multimodal sensor thatcan be unobtrusively integrated into 'textile-based' sensorydevices in general. The interpretation of the data is toidentify locations of skin problems to enable patient self-management and allow for more objective clinicalevaluation to avoid the occurrence of potential skinbreakdown and the resulting complications.Key Accomplishments:We manufactured arrays of multi-component fiber andseam-line based sensors connected to a wireless high-speed data recording and transmission system via textileinterconnects. We tested the sensors on an in vitro artificiallimb testing setup and two in vivo experiments involving anable-bodied subject donning a bent-knee adapter and abilateral transtibial amputee participant. In all these cases,the sensor array successfully detected pressure changeswithin the inner socket during weight-shifting and walkingexperiments.34Approach: Our collaborative research team works on melt-extrudedmulti-component fiber and seam-line based sensordevelopment in which we carefully engineer the fiber cross-section, fabric structure, and electrical response. This targetsa sensitive and specific multimodal response usingmicrofabricated and, ultimately, textile-based polymericfibers with ordered segments of conducting and insulatingareas in the fiber cross-sectional structure. We aim tounobtrusively integrate these into many electronic small- orlarge-area textile-based sensory devices and systems of thefuture, especially for health monitoring.Impact: Amputation is one of the major causes of disability. Socketsare the important prosthesis components and physicalinterface to integrate the prosthetic limbs mechanicallywith the amputee's residual limb to replace lost function.Objective monitoring of the inner socket environment (i.e.pressure, temperature, and humidity) and residual muscleactivity during daily prosthesis use requires flexible,unobtrusive, multi-modal sensors that can be integratedinto the socket structure without causing subjectdiscomfort. The lack of such an inner-socket sensortechnology has been a long-standing problem forevaluating the prosthesis socket, preventing thecomplications elicited by poor socket design and fit, andadvancing the socket technologies. Therefore, advancedsocket technologies are urgently needed and will bedeveloped under this project to significantly reduce thenumber of clinic visits, lower healthcare costs for amputees,and ultimately improve their quality of life.Principal Investigators:Dr. Alper Bozkurt, Electrical & Computer Engineering, NC State UniversityDr. Tushar Ghosh, Textile Engineering, Chemistry, & Science, NC State UniversityDr. Helen Huang, Biomedical Engineering, UNC-CHStudent:Brendan ThompsonFunding source:NSFSchematic depictions of the fiber andseam-line sensor arrays, images of theintegrated textile sensors, and examplesof integration and testing with humansubjects, demonstrating successfuldetection of pressure changes.

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Correlated Sensing of Health andExposure for Personalized AsthmaMonitoringObjective: This project seeks to combine physiological andenvironmental sensors in a low-power and portable formfactor. The combination of these sensing modalities allowsfor a unique perspective on an asthmatic individual’sresponse to local environment and air quality conditions.Current solutions for monitoring ozone exposure typically relyon nearby environmental monitoring stations, leading tomuch less granularity in terms of personal exposure.Key Accomplishments:This project has been used to showcase the custom ozonesensor developed within the ASSIST Center as well as take astep towards personalized gas exposure tracking. Thesedevices have been used to measure physiologicalresponses to controlled amounts of ozone with respect to agold standard (Shimmer3 ECG). This gold standard showeda correlation between an individual’s heart rate variabilityand their lung function. This project is now focusing onperforming similarly structured studies to show thesecorrelations in at-home settings over several weeks’ time.36Approach: The system comprises both a wristband and a chest patch.The chest patch is designed for physiological monitoring,including sensors for electrocardiography (ECG), pulse (viaphotoplethysmography, or PPG), and motion. The wristbandis designed for environmental exposure monitoring,including sensors for PPG, motion, ambient temperatureand humidity, ambient volume levels, ozone, and volatileorganic compounds (VOCs). The sensors allowing for ozoneand VOCs are custom technology to ASSIST and have beenintegrated into modular plug-in boards. These plug-inboards mate with the main board of the wristband, whichallows different sensors to be utilized.Impact: This research has the potential to transform the treatmentmethodology for patients with moderate to severe asthmaand other respiratory conditions that are triggered byenvironmental toxins. The eventual goal is to allow forpredictive algorithms to assess the risk of impendingexacerbations and allow for acute lifestyle alterations tomitigate these risks rather than relying on rescue inhalers.Principal Investigators:Dr. Alper Bozkurt, Dr. James Dieffenderfer, Dr. Bongmook Lee, Dr. Veena MisraElectrical & Computer Engineering, NC State UniversityPostdoc:Dr. Tahmid LatifFunding sources:NSF Smart Connected HealthNSF ASSIST CenterWearable device worn on the wrist (left) and a simplifieddiagram showing the individual components that make up thewearable device (right), .

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Health and Exposure Tracker (HET):Integration and Demonstration of aModular Wearable Monitoring System Objective: The Health and Exposure Tracker (HET) is a unique modularplatform enabling evaluation of various ASSIST technologies,from electrodes and optical devices to ultra-low powerelectronics and sensors. This system demonstrates ASSIST'svision of correlated health and environmental exposuretracking. The HET can host physiological sensors (e.g.,electrocardiography (ECG), photoplethysmography (PPG),and pulse oximetry), behavioral sensors (via inertialmeasurement units), environmental sensors (ozone, volatileorganic compounds, ambient temperature, and relativehumidity), and novel biochemical sensors (lactate, glucose,and pH) for a more comprehensive and correlated analysis.No other existing systems provide the multi-sensingcapability of the HET along with an open platform intowhich next generation sensing devices can be integrated.The flexible patch collects sweat via a zero-power osmoticpump connected to screen printed enzymatic glucoseand lactate sensors. Glucose and lactate concentrationmonitoring in sweat could help assess metabolic state,enabling automated and actionable feedback to supportdiet management for diabetic patients. 37Approach: The HET comprises a modular architecture with variouselectrophysiological, biophotonic, inertial, potentiostatic,amperometric, and environmental sensor front endstogether with a system-on-chip (microcontroller andBluetooth Low Energy transceiver). The system can bepowered by inductively rechargeable lithium batteries orenergy harvesting devices such as flexible solar cells orASSIST’s thermoelectric generators. This circuit architecturehas been packaged in several form factors includingwristband, chest-patch, flexible patch for various bodylocations, and bandage. A wristband form factor is outfitted with an ozone sensor tomonitor individual ozone exposure, accelerometers to measure activity, and PPG sensors to measure heart rate,thereby enabling correlated sensing of environmentalexposure and physiological response. Chest form factorsallow monitoring PPG, ECG, and cough frequency. Thesystem is being used in studies at the University of NorthCarolina and an Environmental Protection Agency testchamber. The bandage form factor is a wound monitoring systemwhich tracks uric acid levels near the wound site todetermine how well wounds are healing. Impact: Monitoring physiological and environmental conditionscould help individuals with asthma manage their exposureto irritants. Analysis of biochemical markers insweat/wounds could be a breakthrough in wearables.These capabilities could enable medical professionals totrack patient health remotely and support advanced dataanalytics to generate automated feedback.Principal Investigators:Dr. Alper Bozkurt, Dr. Michael Daniele, Dr. James Dieffenderfer, Dr. Edgar Lobaton, Dr. Veena Misra, Dr. Omer Oralkan, Electrical & ComputerEngineering, NC State University; Dr. Michael Dickey, Dr. Orlin Velev, Chemical & Biomecular Engineering, NC State UniversityDr. Michelle Hernandez, Department of Pediatrics, UNC-CHDr. Vladimir Pozdin, Electrical & Computer Engineering, Florida International UniversityPostdocs and Students:Dr. Tahmid LatifDevon Martin, Kaila PetersonTamoghna Saha, Tanner SongkakulFunding source:NSF ASSIST CenterKey Accomplishments:ASSIST's HET systems are part of various clinical experimentsfor asthma exacerbation prediction, sweat analysis, andwound sensing. Our prototypes have technology readinesslevels (TRLs) of 5 to 6 and sub-milliwatt power consumption.

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Self-Powered Platform forCardiovascular and Asthma MonitoringObjective: The objective of this project is to develop self-poweredwearables that track physiological and environmentalparameters, in order to improve monitoring ofcardiopulmonary performance and self-management ofrespiratory conditions such as asthma. Self-poweredwearables enable uninterrupted data collection, andenvironmental monitoring on the person ensures the mostrelevant measures of irritants to which the person is beingexposed. 38Approach: We have developed two wearables for these applications.The first is a self-powered electrocardiogram (ECG)-monitoring shirt that utilizes dry ECG electrodes and aflexible thermal energy harvester to provide a comfortableECG-monitoring solution suitable for daily wear. The secondis a self-powered armband that utilizes dry ECG electrodesand a combined thermal/solar energy harvester to providecontinuous monitoring of ECG, pulse (viaphotoplethysmography, also called PPG), and low powergas sensors that monitor ozone levels for assessing asthmarisk. These apparel-based monitors integrate advancementsacross ASSIST’s primary research areas of energy harvesting,low power sensors, low power electronics, e-textiles, andsystems integration.Impact: These wearable devices are having impact on multiplefronts. One is that they are filling performance gaps incurrently-available wearables by continuously monitoring for cardiac conditions such as atrial fibrillation, trackingcardiac performance during strenuous activity, and alertingindividuals with asthma to high ozone levels. A second isthat, by increasing the functionality of ASSIST’s self-powereddevices (i.e. advancing from powering ECG to poweringECG, PPG, and ozone sensors simultaneously), they drivenew technical achievements in ASSIST’s research. A third isthat these devices serve as platforms that can be tailored tospecific use cases and performance requirements incollaborations with clinical partners or companies.Principal Investigators:Dr. Alper Bozkurt, Dr. Michael Dickey, Dr. James Dieffenderfer, Dr. Edgar Lobaton,Dr. Veena Misra, Dr. Mehmet Ozturk, Electrical & Computer Engineering, NC State UniversityDr. Michael Daniele, Biomedical Engineering, Electrical & Computer Engineering, NC State UniversityDr. Jesse Jur, Textile Engineering, Chemistry, and Science, NC State UniversityDr. Benton Calhoun, Electrical & Computer Engineering, University of VirginiaDr. David Wentzloff, Electrical Engineering & Computer Science, University of MichiganDr. Douglas Werner, Electrical Engineering & Computer Science, Penn State UniversityPostdocs:Dr. Tahmid Latif Dr. Amanda MillsDr. Yasaman SargolzaeiavalFunding source:NSF ASSIST CenterKey Accomplishments:We have demonstrated an ECG-monitoring shirt streamingECG data continuously over Bluetooth to a mobileapplication, powered only by body heat. Due to ASSIST’slow power electronics and radio, coupled with ASSIST’sbody-optimized wearable antenna, the shirt consumes onlyabout 65 μW of average power. We have alsodemonstrated a self-powered armband that monitors ECG,PPG, and ozone levels. The armband currently usescommercial off-the-shelf electronics, rather than the customlow-power electronics we have developed for thisapplication, due to the custom electronics’ longerdevelopment timeline. Nonetheless, we have achieved self-powered operation through a combination of body heatand solar energy harvesting. Future generations utilizingASSIST’s newest low-power electronics are anticipated touse only body heat for power.Schematic of armband with self-powered ECG capability.Electronics module of ECGarmband with enablingfunctionality.

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SenSE: AI-Driven, Resilient and AdaptiveMonitoring of Sleep (AI-DReAMS)Objective: This project investigates the use of an artificial intelligence-driven, reconfigurable sleep monitoring system to transformsleep research in the clinic and at home. A sensor fusionstrategy backed by artificial intelligence to ultra-miniaturizethe sleep assessment instruments and explore novel sleep-related biomarker features has the potential to enable moreefficient and accurate diagnosis and treatment of sleepdisorders. There is a need for combining lower cost withimproved comfort and more efficient data analysis to pavethe way for rapid translation, adoption, and effectivedeployment of sleep technologies.Key Accomplishments:This project stems from an earlier clinical study funded byNational Institutes of Health to explore the use of nearinfrared spectroscopy and machine learning to bring anew perspective to sleep studies. The team demonstratedflexible devices to perform near infrared spectroscopy andelectroencephalography in the form factors of a flexiblebandage. The current efforts focus on constructing areconfigurable version of the hardware platform to collectdata at home and in sleep clinic studies and support thedevelopment of the proposed artificial intelligencetechniques for studying sleep more efficiently.39Approach: This project integrates two parallel efforts combininginnovations in hardware and data analytics: 1) enabling anadaptable and reconfigurable embedded system platformin the form factor of an adhesive patch, and 2) developingstate-of-the-art machine learning techniques incorporatingthe data-driven models necessary for improving sleepmonitoring system resilience. The hardware system fusesmultimodal wearable sensors, combining near infraredspectroscopy with other traditional sleep related signalsensors on skin-conformable substrates, to collect data onmultiple body locations. The data analytics platformincludes 1) signal processing to enable data-driven metricsfor signal quality assessment for a given inference task, 2)inference models based on transfer learning techniquesand diverse datasets for detection of sleep events anddisorders using new sensing modalities, and 3) BayesianNeural Network supported sensor selection for improvingthe resilience and adaptability of sleep sensor systems.Impact: A considerable percentage of the population in the USand around the world suffers from a chronic sleep disorder.However, most of these disorders are not diagnosed ortreated. There is a vital need for new wearabletechnologies to increase the capacity of sleep researchersto make further advances in investigating sleep,understanding sleep pathologies, and to improve theability of clinicians to reliably detect and treat sleepdisorders. The results from this research also have thepotential to positively influence the continuous-monitoringinstrumentation required for other chronic conditions suchas heart diseases. In addition to providing a novel, artificialintelligence-driven and reconfigurable tool design for sleepresearch, this effort will shed light into novel multimodalbiomarkers assessed noninvasively in wearable form factorsfor detection of sleep stages and disorders.Principal Investigators:Dr. Alper Bozkurt, Dr. James Dieffenderfer, Dr. Edgar Lobaton, Electrical & Computer Engineering, NC State UniversityDr. Michael Daniele, Electrical & Computer Engineering, Biomedical Engineering, NC State UniversityDr. Vladimir Pozdin, Electrical & Computer Engineering, Florida International UniversityPostdocs and Students:Dr. Parvez AhmmedDevon Martin, Kaila Peterson,Tamoghna Saha, Tanner Songkakul,Evan WilliamsFunding source:NSF ASSIST CenterPhotonic sensor and circuit for sleep studies, in an adhesive bandage form factor with wireless recharging capabilities.

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Bio-Electro-Photonic MicrosystemInterfaces for Small AnimalsObjective: This project is aimed at developing a wirelessly poweredinjectable capsule capable of wirelessly monitoringbiophotonic and bioelectrical physiological signals in smallanimals. This microsystem responds to the critical need for aminimally invasive class of devices for continuous recordingof key physiological parameters of animals in typicalenvironments without disturbing natural behavior.Key Accomplishments:The capsule system has been evaluated in a clinical settingfor tracking physiological signals in rats and chickens. Thecollar and harness system have been deployed in the fieldwith guide dog puppies, with the goal of improving thepuppy training program outcomes. Recent efforts focus ontraining dogs to follow or interact with unmanned-air-vehicles, with the goal of deploying this in working dogapplications such as search and rescue operations andagricultural pest detection.40Approach: This project develops two parallel physiological andbehavioral sensing platforms on two different form factors:an injectable subcutaneous capsule and a wearableharness system for animals. The capsule platform providesphotoplethysmography, electrocardiography, acceler-ometry, and thermometry measurements from under theskin. This is used to calculate heart rate, respiration rate,oxygen saturation, pulse transit time, and core bodytemperature. The harness system is for simple wearableapplications and provides electrocardiography,photoplethysmography, inertial sensing, and environmentalsensing integrated into a standard dog harness and collar.Principal Investigator:Dr. Alper Bozkurt, Electrical & Computer Engineering, NC State UniversityPostdocs and Students:Dr. Parvez Ahmmed James Reynolds, Caleb Readling, Devon Martin,Brendan Thompson, Evan WilliamsFunding source:NSFImpact: The microsystem under development is expected to opena physiological window to improve understanding of thephysiology of small animals in their natural environment. Thissystem would be impactful for the welfare of farm,companion, working, and wildlife animals in addition toproviding new bi-directional channels to communicatewith them.3D PrintedElectrodesRPI ZeroWirelessBattery andCharging CircuitFrontChestSupportCanine Chest StrapSmartCollarEnvironmentalAmbient temperature,humidity, barometricpressure, light, noiseBehavioralActivity level and barkingPhysiologicalSleep and resting heart rateand respiration

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Cough Detection Using Wearables andEmbedded Machine LearningObjective: The objective of this project is to develop an AutomaticCough Detection Algorithm (ACDA) for wearable devicesthat meets clinical monitoring requirements by fusingmultimodal sensor data. This ACDA should be able toextract features from a wearable and process the data in asmart device. Furthermore, we wish to ensure that privacy ismaintained so no speech is recognizable from the features,while maintaining enough details in the signal to detect andcharacterize different types of coughs.Key Accomplishments:Our CNN-based ACDA achieves a sensitivity of 92.7%, aspecificity of 92.3%, and an accuracy of 92.5% using asampling frequency of just 750 Hz. A low samplingfrequency allows us to preserve patients' privacy byobfuscating their speech. We have analyzed the trade-offbetween speech obfuscation for privacy and coughdetection accuracy and realized that the 750 Hz samplingrate is optimal.41Approach: Our group has developed an ACDA that meets clinicalmonitoring requirements, was developed using publiclyavailable data, reliably operates at a low samplingfrequency, and maintains user privacy. This ACDA isimplemented using a convolutional neural network (CNN). Arealization of this solution is shown in the figure, in which anacoustic signal is filtered by the embedded device, and it isused for cough detection in the smart device. We areworking on enhancing the system by incorporating multiplesensing modalities (e.g., ECG, PPG, audio, and inertial) inthe wearable device. By combining data from a wearable,we will be able to separate interfering sounds fromindividuals other than the main user. In addition, we will beable to correlate and fuse these measurements with theother modalities. Part of our focus for our cough detectionefforts has also been integration with the embeddedhardware, in which we are trying to minimize the amount ofdata to be transmitted and processed, thereby reducingpower consumption and addressing privacy concerns.Impact: Cough detection can serve as an important biomarker tomonitor chronic respiratory conditions. However, manualtechniques which require human expertise to countcoughs are both expensive and time-consuming. RecentACDAs have shown promise to meet clinical monitoringrequirements, but due to the required portability of sensingtechnologies and the extended duration of datarecording, only in recent years have they made their wayto non-clinical settings. More precisely, these ACDAsoperate at high sampling frequencies, which leads to highpower consumption and computing requirements, makingthem difficult to implement on a wearable device. Havingan ACDA capable of continuous monitoring whilemaintaining privacy would allow for new types of diagnosisand prevention of disease spread in communities.Principal Investigators:Dr. Edgar Lobaton, Electrical & Computer Engineering, NC State UniversityDr. Alper Bozkurt, Electrical & Computer Engineering, NC State UniversityDr. Michelle Hernandez, Department of Pediatrics, UNC-CHPostdocs and Students:Dr. Tahmid LatifDr. James DieffenderferJeffrey Barahona, Yuhan ChenFunding source:NSFThe cough detection system uses a wearable with an integrated microphone to capture, filter, and transmit audio signals to a smartphone, which runs the Automatic Cough Detection Algorithm (ACDA) .

2021 Research Portfolio

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