Literature DB >> 24111421

A portable real-time ECG recognition system based on smartphone.

Tzu-Hao Yen, Chung-Yu Chang, Sung-Nien Yu.   

Abstract

This paper proposed an smartphone-based real-time ECG monitoring and recognition system. The ECG signal was acquired by a MSP430FG4618 low-power microprocessor and was converted via a Bluetooth module for wireless transmission to a smartphone. A noise-tolerant ECG heartbeat recognition algorithm based on discrete wavelet transform and higher-order statistics was employed to identify different types of heartbeats. This system achieved a high accuracy of 98.34 % in identifying seven heartbeat types, which was demonstrated to outperform other studies in the literature. The heartbeat types were recognized in real-time; only 78 ms was required to identify a heartbeat. The portability, real-time processing, and high recognition rate of the system demonstrate the efficiency and effectiveness of the device as a practical computer-aided diagnosis (CAD) system.

Mesh:

Year:  2013        PMID: 24111421     DOI: 10.1109/EMBC.2013.6611234

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection.

Authors:  Juyoung Park; Mingon Kang; Jean Gao; Younghoon Kim; Kyungtae Kang
Journal:  J Med Syst       Date:  2016-11-26       Impact factor: 4.460

2.  Comparison of smartphone application-based vital sign monitors without external hardware versus those used in clinical practice: a prospective trial.

Authors:  John C Alexander; Abu Minhajuddin; Girish P Joshi
Journal:  J Clin Monit Comput       Date:  2016-05-12       Impact factor: 2.502

Review 3.  The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review.

Authors:  Ka Hou Christien Li; Francesca Anne White; Gary Tse; Timothy Tipoe; Tong Liu; Martin Cs Wong; Aaron Jesuthasan; Adrian Baranchuk; Bryan P Yan
Journal:  JMIR Mhealth Uhealth       Date:  2019-02-15       Impact factor: 4.773

4.  Real-Time Heart Arrhythmia Detection Using Apache Spark Structured Streaming.

Authors:  Sadegh Ilbeigipour; Amir Albadvi; Elham Akhondzadeh Noughabi
Journal:  J Healthc Eng       Date:  2021-04-22       Impact factor: 2.682

  4 in total

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