An Energy Efficient ECG Signal Processor Detecting Cardiovascular Diseases on Smartphone

Abstract

A novel disease diagnostic algorithm for ECG signal processing based on forward search is implemented in Application Specific Integrated Circuit (ASIC) for cardiovascular disease diagnosis on smartphone. An ASIC is fabricated using 130-nm CMOS low leakage process technology. The area of our PQRST ASIC is 1.21 mm. The energy dissipation of PQRST ASIC is 96 pJ with a supply voltage of 0.9 V. The outputs from the ASIC are fed to an Android application that generates diagnostic report and can be sent to a cardiologist via email. The ASIC and Android application are verified for the detection of bundle branch block, hypertrophy, arrhythmia and myocardial infarction using Physionet PTB diagnostic ECG database. The failed detection rate is 0.69%, 0.69%, 0.34% and 1.72% for bundle branch block, hypertrophy, arrhythmia and myocardial infarction respectively. The AV block is detected in all the three patients in the Physionet St. Petersburg arrhythmia database. Our proposed ASIC together with our Android application is the most suitable for an energy efficient wearable cardiovascular disease detection system.

Predicting Ventricular Fibrillation Through Deep Learning

“…Transmitting signals to more powerful mobile devices (such as smartphones) for computation is an alternative. Recently, researchers have also tried to develop energy-efficient processors to detect cardiovascular diseases on smartphones [35]. A method to reduce the power and cycle requirement for FFT of ECG signals through low-level arithmetic optimizations was also proposed [36].…”

Recent Progress of Biomedical Processor SoC for Wearable Healthcare Application: A Review

“…The reciprocal of the RR interval is the instantaneous heart rate (IHR). Heart rate variability represents a spectrum analysis of IHR and reflects the heart rate fluctuation [5].…”

“…a) E-mail: yosimoto@cs.kobe-u.ac.jp DOI: 10.1587/transele.2018CDI0001 fill these requirements, many researchers worldwide have undertaken VLSI and SoC development for digital health applications [5]- [27]. This paper describes technical trends of wearable processor SoC to meet the requirements above for healthcare application.…”

A Low gate count reconfigurable architecture for biomedical signal processing applications

“…Advances in Integrated Circuit (IC) technology have resulted in miniaturized devices useful for wearable biomedical applications. Custom and configurable solutions for Electrocardiogram (ECG) processing have been discussed extensively in the literature [1][2][3][4]. As an example, [5] discusses a low-energy microprocessor ( P ) for R-wave detection, heart rate calculation and arrhythmia based on the R-R interval with a 78% detection accuracy.…”