TY - JOUR
T1 - An ultra low energy biomedical signal processing system operating at near-threshold
AU - Hulzink, Jos
AU - Konijnenburg, Mario
AU - Ashouei, Maryam
AU - Breeschoten, Arjan
AU - Berset, Torfinn
AU - Huisken, Jos
AU - Stuyt, Jan
AU - de Groot, Harmke
AU - Barat, Francisco
AU - David, Johan
AU - Van Ginderdeuren, Johan
PY - 2011/12/1
Y1 - 2011/12/1
N2 - This paper presents a voltage-scalable digital signal processing system designed for the use in a wireless sensor node (WSN) for ambulatory monitoring of biomedical signals. To fulfill the requirements of ambulatory monitoring, power consumption, which directly translates to the WSN battery lifetime and size, must be kept as low as possible. The proposed processing platform is an event-driven system with resources to run applications with different degrees of complexity in an energy-aware way. The architecture uses effective system partitioning to enable duty cycling, single instruction multiple data (SIMD) instructions, power gating, voltage scaling, multiple clock domains, multiple voltage domains, and extensive clock gating. It provides an alternative processing platform where the power and performance can be scaled to adapt to the application need. A case study on a continuous wavelet transform (CWT)-based heart-beat detection shows that the platform not only preserves the sensitivity and positive predictivity of the algorithm but also achieves the lowest energy/sample for ElectroCardioGram (ECG) heart-beat detection publicly reported today.
AB - This paper presents a voltage-scalable digital signal processing system designed for the use in a wireless sensor node (WSN) for ambulatory monitoring of biomedical signals. To fulfill the requirements of ambulatory monitoring, power consumption, which directly translates to the WSN battery lifetime and size, must be kept as low as possible. The proposed processing platform is an event-driven system with resources to run applications with different degrees of complexity in an energy-aware way. The architecture uses effective system partitioning to enable duty cycling, single instruction multiple data (SIMD) instructions, power gating, voltage scaling, multiple clock domains, multiple voltage domains, and extensive clock gating. It provides an alternative processing platform where the power and performance can be scaled to adapt to the application need. A case study on a continuous wavelet transform (CWT)-based heart-beat detection shows that the platform not only preserves the sensitivity and positive predictivity of the algorithm but also achieves the lowest energy/sample for ElectroCardioGram (ECG) heart-beat detection publicly reported today.
KW - Biomedical signal processing
KW - ElectroCardioGram (ECG) processing
KW - Low power
KW - Low voltage
KW - Multi-power domain
KW - Multi-voltage domain
KW - Near-threshold design
UR - http://www.scopus.com/inward/record.url?scp=84855355075&partnerID=8YFLogxK
U2 - 10.1109/TBCAS.2011.2176726
DO - 10.1109/TBCAS.2011.2176726
M3 - Article
C2 - 23852552
AN - SCOPUS:84855355075
VL - 5
SP - 546
EP - 554
JO - IEEE Transactions on Biomedical Circuits and Systems
JF - IEEE Transactions on Biomedical Circuits and Systems
SN - 1932-4545
IS - 6
M1 - 6104198
ER -