Analysis and Design of On-sensor ECG Processors for Realtime Detection of Cardiac Anomalies Including VF, VT, and PVC

  • Authors:

  • Hong-Hui Chen;Cheng-Yi Chiang;Tung-Chien Chen;Chien-Sheng Liu;Yu-Jie Huang;Shey-Shi Lu;Chii-Wann Lin;Liang-Gee Chen

  • Affiliations:

  • Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan;Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan

  • Venue:
  • Journal of Signal Processing Systems
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Cardiovascular disease remains the main cause of death, and great efforts are spent on the design of ECG (electrocardiogram) body sensors these years. Essential components such as analog frontend and wireless transceivers have been integrated on a compact IC with micro-Watt power consumption. To provide timely warning against the fatal vascular signs, based on the Chaotic Phase Space Differential (CPSD) algorithm, heterogeneous VLSI processors are implemented and integrated to extract the abnormal ECG characteristics for VF (Ventricular Fibrillation), VT (Ventricular Tachycardia) and PVC (Premature Ventricular Contraction). The on-sensor processing reduces 98.0% power of wireless data transmission for raw ECG signals. The application specific processor is designed to accelerate CPSD algorithm with 1.7μW power while the OpenRISC is integrated to provide the system flexibility. The architecture is realized on the FPGA platform to demonstrate the detection of the abnormal ECG signals in realtime.