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Sensors Research at the NSF-Assist Nanosystems Engineering Research Center: Correlated Sensing of Environmental and Physiological Parameters Using Low-Power Wearable Sensors

Monday, May 12, 2014: 10:00
Sarasota, Ground Level (Hilton Orlando Bonnet Creek)
O. Oralkan (North Carolina State University), S. Bhansali (Florida International University), A. Bozkurt, M. D. Dickey, B. Lee (North Carolina State University), T. Mayer (Pennsylvania State University), V. Misra (North Carolina State University), J. H. Moon (Florida International University), J. F. Muth, O. D. Velev, and Y. Zhu (North Carolina State University)
This presentation will provide an overview of the technology and system development effort for low-power wearable sensors in the NSF Nanosystems Engineering Research Center (NERC) for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST). We employ nanotechnology as an enabling factor to achieve low-power, highly specific, multifunctional sensing on compact wearable platforms. Minimizing the power consumption by the sensors and supporting electronic circuits is a critical goal, as these sensors would be powered by harvested energy. To achieve these goals we develop a systems-based approach that optimizes the overall system performance instead of focusing solely on individual components. We envision that nanotechnology-enabled long-term sensing will enable patients, physicians, and scientists to make direct correlations between health and environmental toxins leading to chronic disease prediction, management, and treatment. Furthermore, the self-powered, wearable, correlated sensing platforms we develop will accelerate environmental health research and clinical trials as well as inform environmental policy.

Based on the targeted sensing parameter, ASSIST sensors can be grouped in two categories: 1) Environmental sensors (i.e., for sensing pollutant gases and particulate matter); 2) Physiological sensors (i.e., for sensing heart rate, hormonal biomarkers, oxygen saturation, body sounds, and hydration levels). An alternative classification is based on the sensing mechanism: 1) Chemical/particulate sensing (i.e., for sensing gases such as ozone, nitric oxide, nitrogen dioxide, hydrogen sulfide, volatile organic compounds, and particulate matter); 2) Biochemical sensing (i.e., for sensing hormonal biomarkers such as cortisol and epinephrine, as well as electrolytes); 3) Bioelectrical sensing (i.e., electrocardiogram and skin conductivity); 4) Optical and acoustic sensing (i.e., pulse oximetry and body sounds).

For sensing the pollutant gases in the environment we develop four different types of sensor technologies: 1) Metal-oxide nanowires deterministically assembled on a custom low-power CMOS integrated circuit. Nanowires offer advantages such as low-power heating and increased surface-to-volume ratio for improved sensitivity. These nanowires are fabricated by coating silicon nanowires by a metal-oxide shell using atomic layer deposition (ALD). After these nanowires are released in a solution they are assembled on a CMOS chip. An alternative approach to make metal oxide nanowires is laser interference lithography. 2) An ALD metal-oxide layer by itself can also function as a gas sensor, which provides a large sensing surface area and low power heating. 3) Mechanically resonant devices with selective polymer coatings can sense gas. We use tuning fork type crystal resonators as well as electrostatically actuated flextensional transducers with nano-patterned selective polymers as functionalization layers. 4) AlGaN/GaN heterostructures to make open gate transistors with metal-oxide or nanoparticle functionalization layers. The high mobility in these heterostructures with specific functionalization layers has the potential to realize a low-power, highly sensitive chemical sensor. For sensing the particulate matter we develop an optical fiber based particle counting system that is suitable for micron-size particle detection. 

Our biochemical sensing strategy has three main components: 1) Sample extraction. We currently develop hydrogel-based microfluidic interfaces to skin to be able to sample sweat and interstitial fluids for further analysis. 2) Antibody-based functionalization for cortisol detection. 3) Transduction to an electrical signal by electrochemical impedance spectroscopy using nanowire enhanced interdigitated electrodes or tunneling field effect transistors. The major challenges for the described biochemical sensors are: 1) Noninvasive access to interstitial fluid; 2) Assuring antibody stability; 3) Achieving reversible binding of target analyte or finding a way to replenish antibodies for long-term usability of the sensor.

The hydrogel-based skin interfaces are designed as multifunctional devices that can provide sweat sampling and facilitate direct measurement of skin conductivity by incorporating metal electrodes in the structure. Furthermore, pH sensing and other electrochemical sensing modalities can be integrated in this device.

We have also implemented a low-profile wireless pulse oximetry system in the form of a smart bandage using commercial off-the-shelf components. Future generations of this device will include custom designed optoelectronic components for low-power operation.

In summary, we are developing a wide variety of sensing modalities for continuous environmental and physiological monitoring. Low-power operation, compact and comfortable form factor, and multifunctionality are the common features in all of the described sensor systems. The technologies and systems we are developing in ASSIST have a great potential to improve global health by correlating personal health and personal environment. 

Acknowledgments: 

This material is based upon work supported by the National Science Foundation under Grant No. 1160483.