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|Title:||QRS detection based on multiscale mathematical morphology for wearable ECG devices in body area networks||Authors:||Zhang, F.
|Keywords:||Body area networks (BANs)
Wearable electro cardiograph (ECG) device
|Issue Date:||2009||Citation:||Zhang, F., Lian, Y. (2009). QRS detection based on multiscale mathematical morphology for wearable ECG devices in body area networks. IEEE Transactions on Biomedical Circuits and Systems 3 (4) : 220-228. ScholarBank@NUS Repository. https://doi.org/10.1109/TBCAS.2009.2020093||Abstract:||A novel wearable electrocardiograph (ECG) QRS detection algorithm for wearable ECG devices in body area networks is presented in this paper, which utilizes the multistage multiscale mathematical morphology filtering to suppress the impulsive noise and uses the multiframe differential modulus accumulation to remove the baseline drift and enhance the signal. The proposed algorithm, verified with data from the MIT/BIH Arrhythmia Database and wearable ECG devices, achieves an average QRS detection rate of 99.61%, a sensitivity of 99.81%, and a positive prediction of 99.80%. It compares favorably to the published methods. © 2009 IEEE.||Source Title:||IEEE Transactions on Biomedical Circuits and Systems||URI:||http://scholarbank.nus.edu.sg/handle/10635/71531||ISSN:||19324545||DOI:||10.1109/TBCAS.2009.2020093|
|Appears in Collections:||Staff Publications|
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