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Micro and Nano Systems
 
(Faculty Participants: S. Bhansali, L. An, V. Bhetanabotla, A. Malik, S. Samson, J. Kapat, S. Hoath, R. Smallwood, M. Rahman, T. Weller, S. Hariharan, R. Schlaf )
 
We propose to develop, model, test and validate multiple MEMS based approaches to facilitate data collection from the skin and facilitating the development of a seamless transfer system between the MEMS systems and the skin that will enable this exchange.
 
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Bio-engineered Interfaces
 
(Faculty participants: Hoath, Mac Neil, Bhansali, Lindsey, Hilbelink, Arun Kumar, Malik) Areas: Skin, Clinical Sciences, Anatomy, MEMS, and Chemistry)
 
Many biological processes produce physical, electrical, or chemical alterations that may be monitored by close approximation of a micro sensor to the surface of the skin. Vital signals of the human body such as EEG, ECG, and EMG are regularly measured by the placing of non-invasive electrodes on appropriate parts of the skin. The primary long-term goal of the project is to understand the underlying phenomena and dynamics of the human body with the help of skin as the interface. The more intimate the skin/sensor interface the better the function of the sensor. Optimizing this interface without compromising the well being of the organism is a real challenge from both a biological and an engineering point of view. This group of studies will focus on how to best design sensors as minimally obtrusive devices and explore methods to produce a virtual skin model for incorporation into classic engineering design systems. Our objective is to optimize the capture of a wide range of signals (electrical activity, thermal conditions, skin hydration), and to process and analyze this data for correlated with the physiological state of an individual.
 
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Electronics and Information Processing
 
(Faculty: S. Bhansali, D. Hilbelink, K. Muffly, N. Ranganathan, R. Sankar, R. Schlaf, T. Weller, P. Wiley)
 
Our vision is to produce inexpensive sensing devices by means of sensor integration and electronic miniaturization using MEMS. These devices will monitor a wide variety of physiological parameters and will be equipped with significant processing and memory (i.e., sensor integration with DSP). They also will provide wireless communication capabilities where the sensors themselves become nodes in an ad-hoc network (i.e., sensor integration with RF communication).
 
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This material is based upon work Supported by the National Science
Foundation under Grant No., DGE- 0221681.  Any opinion, findings, and
conclusion or recommendation expressed in this material are those of the
author(s) and do not necessarily reflect the views of the National Science Foundation.
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