A 0.5 nW Analog ECG Processor for Real Time R-wave Detection Based on Pan-Tompkins Algorithm

Abstract

Noninvasive ubiquitous health-monitoring applications necessitate real-time, accurate, and energy-efficient computation of health-related parameters. R-waves are critical features for cardiac health assessment using ECG. In this paper, an energy-efficient application specific integrated circuit (ASIC) processor for real-time R-wave detection based on the Pan-Tompkins algorithm is presented. R-wave detection through processing in the analog domain is demonstrated using simulation results. The processor is designed in a 65 nm CMOS technology and consumes 0.5 nW from a 1 V supply. Based on simulation results using the MIT-BIH arrhythmia database, the processor achieves average R-wave detection sensitivity and positive predictive values of 98.98% and 98.9%, respectively.