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A 15µW 16 channel E×G processor with data transition memory-quad level vector for wearable healthcare platform | IEEE Conference Publication | IEEE Xplore

A 15µW 16 channel E×G processor with data transition memory-quad level vector for wearable healthcare platform


Abstract:

A low power 16 channel E×G processor (E×P) is proposed for wearable healthcare system. It adopts two low power accelerators named data transition memory quad level vector...Show More

Abstract:

A low power 16 channel E×G processor (E×P) is proposed for wearable healthcare system. It adopts two low power accelerators named data transition memory quad level vector (DTM-QLV) and coefficient interleaving FIR filter (CI-FIR). The proposed DTM-QLV reduces transmission power consumption by compressing the data size of 4 different kinds of ExG signals. It can decrease the memory capacity by 13% compared with the previous QLV, and results in power reduction by 1/80 of the conventional RISC processor. Moreover, the proposed CI-FIR can achieve 125 times power efficient operation by multiply-less architecture compared to the RISC processor. In addition, adaptive buffer-controlled gating (ABG) helps to operate only when signal should be processed so that the average power consumption can be significantly decreased to less than 15μW for 16 channel operation.
Date of Conference: 10-12 November 2011
Date Added to IEEE Xplore: 19 December 2011
ISBN Information:
Print ISSN: 2163-4025
Conference Location: San Diego, CA, USA

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