Literature DB >> 28114077

An Energy Efficient ECG Signal Processor Detecting Cardiovascular Diseases on Smartphone.

Sanjeev Kumar Jain, Basabi Bhaumik.   

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 mm2. 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.

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Year:  2016        PMID: 28114077     DOI: 10.1109/TBCAS.2016.2592382

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  1 in total

1.  Printed and Flexible ECG Electrodes Attached to the Steering Wheel for Continuous Health Monitoring during Driving.

Authors:  Joana M Warnecke; Nagarajan Ganapathy; Eugen Koch; Andreas Dietzel; Maximilian Flormann; Roman Henze; Thomas M Deserno
Journal:  Sensors (Basel)       Date:  2022-05-31       Impact factor: 3.847

  1 in total

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