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A Novel Approach for Removing ECG Interferences from Surface EMG signals Using a Combined ANFIS and Wavelet
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-8294-861X
Amirkabir University of Technology, Tehran, Iran.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1940-1747
Auckland University of Technology, Auckland, New Zealand.
2015 (English)In: Journal of Electromyography & Kinesiology, ISSN 1050-6411, E-ISSN 1873-5711, Vol. 26, 52-59 p.Article in journal (Refereed) Published
Abstract [en]

In recent years, the removal of electrocardiogram (ECG) interferences from electromyogram (EMG) signals has been given large consideration. Where the quality of EMG signal is of interest, it is important to remove ECG interferences from EMG signals. In this paper, an efficient method based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and wavelet transform is proposed to effectively eliminate ECG interferences from surface EMG signals. The proposed approach is compared with other common methods such as high-pass filter, artificial neural network, adaptive noise canceller, wavelet transform, subtraction method and ANFIS. It is found that the performance of the proposed ANFIS-wavelet method is superior to the other methods with the signal to noise ratio and relative error of 14.97 dB and 0.02 respectively and a significantly higher correlation coefficient (p < 0.05).

Place, publisher, year, edition, pages
2015. Vol. 26, 52-59 p.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-32779DOI: 10.1016/j.jelekin.2015.11.003ISI: 000370187700008Scopus ID: 2-s2.0-84960226613OAI: oai:DiVA.org:mdh-32779DiVA: diva2:955414
Projects
ESS-H - Embedded Sensor Systems for Health Research Profile
Available from: 2016-08-25 Created: 2016-08-24 Last updated: 2017-11-28Bibliographically approved

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