Energy-Efficient Circuit and System Design for Body

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, farrar@lanl.gov, 665‐
0860.