@article{
 title = {An efficient new method for the detection of QRS in electrocardiogram},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 pages = {1717-1730},
 volume = {40},
 websites = {http://dx.doi.org/10.1016/j.compeleceng.2013.11.004},
 publisher = {Elsevier Ltd},
 id = {f54a114b-a6e6-3a08-88cb-2c6cc569d828},
 created = {2015-04-30T11:14:43.000Z},
 file_attached = {true},
 profile_id = {5e73f9af-1f10-3a70-a285-d3fbb699efe2},
 group_id = {e134fb94-8118-3ebe-b82d-bfbf0a8ae633},
 last_modified = {2015-04-30T12:45:19.000Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 abstract = {A simple and efficient new method for QRS detection in Electrocardiogram (ECG) is proposed in this paper. Initially data is preprocessed using two stage median filter for removing baseline drift. The second stage enhances the peaks of ECG wave components by using sixth power of signal. The next stage identifies the QRS complex by taking a variable window size. The detection sensitivity (Se) and positive predictivity (+P) of CSE (Common Standards for Quantitative Electrocardiography) measurement database, MIT/BIH (Massachusetts Institute of Technology/Beth Israel Hospital) Arrhythmia database, European ST-T database and QT database are Se 99.51 & +P 99.69%, Se 99.21 & +P 99.34%, Se 99.53 & +P 99.72% and Se 99.87 & +P 99.95% respectively. These four standard databases used to perform QRS detection considered 368 cases, tested 1,006,168 beats and achieved overall average sensitivity 99.52% and positive predictivity 99.69%. The MIT/BIH Noise Stress Test Database also tested by proposed method. © 2013 Elsevier Ltd. All rights reserved.},
 bibtype = {article},
 author = {Dohare, Ashok Kumar and Kumar, Vinod and Kumar, Ritesh},
 journal = {Computers and Electrical Engineering},
 number = {5}
}

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