Literature DB >> 18002800

ECG R-R peak detection on mobile phones.

F Sufi1, Q Fang, I Cosic.   

Abstract

Mobile phones have become an integral part of modern life. Due to the ever increasing processing power, mobile phones are rapidly expanding its arena from a sole device of telecommunication to organizer, calculator, gaming device, web browser, music player, audio/video recording device, navigator etc. The processing power of modern mobile phones has been utilized by many innovative purposes. In this paper, we are proposing the utilization of mobile phones for monitoring and analysis of biosignal. The computation performed inside the mobile phone's processor will now be exploited for healthcare delivery. We performed literature review on RR interval detection from ECG and selected few PC based algorithms. Then, three of those existing RR interval detection algorithms were programmed on Java platform. Performance monitoring and comparison studies were carried out on three different mobile devices to determine their application on a realtime telemonitoring scenario.

Mesh:

Year:  2007        PMID: 18002800     DOI: 10.1109/IEMBS.2007.4353134

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


  7 in total

1.  A new feature detection mechanism and its application in secured ECG transmission with noise masking.

Authors:  Fahim Sufi; Ibrahim Khalil
Journal:  J Med Syst       Date:  2009-04       Impact factor: 4.460

2.  Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems.

Authors:  Mohamed Elgendi; Björn Eskofier; Socrates Dokos; Derek Abbott
Journal:  PLoS One       Date:  2014-01-07       Impact factor: 3.240

3.  R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope.

Authors:  Jeong-Seon Park; Sang-Woong Lee; Unsang Park
Journal:  J Healthc Eng       Date:  2017-07-05       Impact factor: 2.682

4.  Performance Analysis of Ten Common QRS Detectors on Different ECG Application Cases.

Authors:  Feifei Liu; Chengyu Liu; Xinge Jiang; Zhimin Zhang; Yatao Zhang; Jianqing Li; Shoushui Wei
Journal:  J Healthc Eng       Date:  2018-05-08       Impact factor: 2.682

5.  Multiclass Classifier based Cardiovascular Condition Detection Using Smartphone Mechanocardiography.

Authors:  Zuhair Iftikhar; Olli Lahdenoja; Mojtaba Jafari Tadi; Tero Hurnanen; Tuija Vasankari; Tuomas Kiviniemi; Juhani Airaksinen; Tero Koivisto; Mikko Pänkäälä
Journal:  Sci Rep       Date:  2018-06-19       Impact factor: 4.379

6.  Scoping Review of Healthcare Literature on Mobile, Wearable, and Textile Sensing Technology for Continuous Monitoring.

Authors:  N Hernandez; L Castro; J Medina-Quero; J Favela; L Michan; W Ben Mortenson
Journal:  J Healthc Inform Res       Date:  2021-02-01

7.  An assessment of pulse transit time for detecting heavy blood loss during surgical operation.

Authors:  Chien-Hao Wang; Cheng-Wei Lu; Tzu-Yu Lin; Maysam F Abbod; Jiann-Shing Shieh
Journal:  Open Biomed Eng J       Date:  2012-12-28
  7 in total

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