TDPRO: Ultra-low Power ECG Processor with High-Precision Time-Domain Computing Engine

Liang Chang, Siqi Yang, Huinan Wang, Jianbo Xiao, Xin Zhao, Shuisheng Lin, Jun Zhou

Abstract: In wearable biomedical signal detection, the low-power consumption is a critical requirement. However, the process of biomedical signal detection with traditional neural-network processor is uneconomical for large data movements. A typical solution is the near memory computing (NMC) method, locating more data near the computing engine to save energy, where the detecting accuracy and power consumption is difficult to be optimized simultaneously. In addition, a suitable computing engine is needed to match both power and computation budget. In this work, we combine the NMC-based ECG processor equipped with a high-precision time-domain engine to perform the detection of arrhythmia, namely TDPRO. The proposed TDPRO supports high precision multiplication and addition operation with 8-bit input and weight parameters. Also, we propose TD-zero-jumping and idle-shutdown technique to further reduce 63%$\sim$ 91% power consumption of the time-domain engine. The error rate of 8-bit MAC operation in the TDPRO is 1.18%, which is suitable for the ECG detection.