A Proof-of-Concept 70 nA ECG Processor for Real-Time R-Wave and NN50 Detection

Abstract

Unobtrusive health monitoring applications necessitate accurate, real-time, and energy-efficient computation of health-related parameters. Two important parameters for cardiovascular and cardiac autonomic health assessment are heart rate (HR) and heart rate variability (HRV). In this paper, an energy-efficient mixed-signal processor ASIC for real-time monitoring of HR and NN50, a well-established HRV score for parasympathetic activity assessment, is presented. The proposed ASIC, designed in a 0.5 μm CMOS technology, detects R-waves of ECG signals and compares successive R-R intervals to identify the NN50 events in real-time. Post-layout simulation results using ECG signals of four recordings from the MIT-BIH arrhythmia database are compared with DSP calculations on MATLAB. Based on simulation results, the processor detects R-waves with an average accuracy of 99.1%, and NN50 events with average sensitivity and positive predictive values of 94.7% and 96.9%, respectively. The processor consumes 70 nA when supplied by ±1.6 V.