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Engineering Institute Lecture Series Sponsored by EI, ASME, IEEE, ANS, and ASM UNCLASSIFIED – OPEN TO THE PUBLIC Energy‐Efficient Circuit and System Design for Body‐Worn Applications Presented by Alicia Klinefelter University of Virginia Tuesday, March 31, 2015 3:30 – 5:00 PM New Location: Collaboration Space at the Research Library (JRO 1/2) Abstract: Continuous health monitoring for early detection of chronic diseases or fitness tracking is an emerging trend due to smaller product form factors as a result of technology scaling. With an increase in life-expectancy, a large aging population, and a desire for autonomy among the elderly, research in the area of body sensor nodes (BSNs) is increasing to provide devices for unobtrusive and precise monitoring. To increase the adaptability of BSNs, they should be non-invasive, reliable, safe, secure, and have long lifetimes to avoid continuous battery replacement. Due to these criteria, BSNs and other ultra-low-power systems demand energy efficient signal processing to meet their stringent power requirements. An emerging class of systems run entirely on power harvested from body heat or solar panels requiring no battery. To enable this, the chip must consume an average power less than the power harvested, which is typically in the 30-50μW range. The strongest design knob for reducing energy on chip is to lower the supply voltage and operate digital circuits in the subthreshold region, which is using a supply that falls below the threshold voltage of the device. Although operating in subthreshold also leads to a large performance penalty, there are still many applications with low throughput requirements that can take advantage of subthreshold operation’s energy savings. Systems that process biomedical data such as EKG, EEG, and EMG require sampling rates less than 500Hz, making subthreshold operation attractive in this application space. Biography: Alicia Klinefelter is working towards her Ph.D in Electrical Engineering under Benton Calhoun at the University of Virginia. Her research interests include low-power circuit design for wireless body sensor nodes, subthreshold design techniques for digital signal processing, approximate computing, and the modeling of low-power system architectures. For more information, please contact the institutional host, Chuck Farrar, [email protected], 665‐ 0860.