Literature DB >> 23366534

Automatic QRS complex detection algorithm designed for a novel wearable, wireless electrocardiogram recording device.

Dorthe B Nielsena1, Kenneth Egstrup, Jens Branebjerg, Gunnar B Andersen, Helge B D Sorensen.   

Abstract

We have designed and optimized an automatic QRS complex detection algorithm for electrocardiogram (ECG) signals recorded with the DELTA ePatch platform. The algorithm is able to automatically switch between single-channel and multi-channel analysis mode. This preliminary study includes data from 11 patients measured with the DELTA ePatch platform and the algorithm achieves an average QRS sensitivity and positive predictivity of 99.57% and 99.57%, respectively. The algorithm was also evaluated on all 48 records from the MIT-BIH Arrhythmia Database (MITDB) with an average sensitivity and positive predictivity of 99.63% and 99.63%, respectively.

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Year:  2012        PMID: 23366534     DOI: 10.1109/EMBC.2012.6346573

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


  1 in total

1.  Automatic Real-Time Embedded QRS Complex Detection for a Novel Patch-Type Electrocardiogram Recorder.

Authors:  Dorthe B Saadi; George Tanev; Morten Flintrup; Armin Osmanagic; Kenneth Egstrup; Karsten Hoppe; Poul Jennum; Jørgen L Jeppesen; Helle K Iversen; Helge B D Sorensen
Journal:  IEEE J Transl Eng Health Med       Date:  2015-04-10       Impact factor: 3.316

  1 in total

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