View article

Wireless Sensor Nodes (WSN) have a wide range of applications in health care and life style monitoring. Their severe energy constraint is often addressed through minimizing the amount of transmitted data by way of energy-efficient on-node signal processing. The rationale for this approach is that a large portion of WSN energy is consumed by the radio communication even for very low-data-rate situations [1]. Efficient on-node processing has been the subject of recent work, with the common element being aggressive voltage scaling into the sub-threshold region [2–4]. A major assumption of the existing works is that the amount of required computation is low, justifying an on-node processor with limited computational capability. While this might be the case for many applications of WSNs, emerging ambulatory biomedical signal processing applications exceed the performance offered by today's on-node processors.