A Nano-Watt ECG Feature Extraction Engine in 65-nm Technology

This brief presents an ultralow power electrocardiography (ECG) feature extraction engine. ECG signal represents the cardiac cycle and contains key features, such as QRS complex, P-wave, and T-wave, which provide important diagnostic information about cardiovascular diseases. The ECG feature extraction is based on combined techniques of curve length transform (CLT) and discrete wavelet transform. A novel pipelined architecture for implementing CLT is proposed. The system was fabricated using GF-65-nm technology and consumed 642 nW only when operating at a frequency of 7.5 kHz from a supply voltage of 0.6 V. Ultralow power consumption of the SoC made it suitable for self-powered wearable devices.