A novel approach for removing ECG interferences from surface EMG signals using a combined ANFIS and wavelet |
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| Affiliation: | 1. School of Innovation, Design and Engineering, Mälardalen University, 721 23, Högskoleplan 1, Västerås, Sweden;2. Department of Biomedical Engineering, Amirkabir University of Technology, 424 Hafez Ave, Tehran, Iran;3. School of Engineering, Computing and Mathematical Sciences, Auckland University of Technology, 1142 Auckland, New Zealand;1. Department of Chemical and Biomolecular Engineering, Sogang University, 1 Shinsoo-dong, Mapo-gu, Seoul, 04107, Republic of Korea;2. Department of Smart Green Technology Engineering, Pukyong National University, Busan, 48513, Republic of Korea;3. Department of Chemistry, Pukyong National University, Busan, 48513, Republic of Korea;4. Department of Advanced Materials Engineering for Information & Electronics, Integrated Education Institute for Frontier Science & Technology (BK21 Four), Kyunghee University, Gyeonggi-do, 17104, Republic of Korea;5. Advanced Materials Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea;6. Department of Chemistry and Research Center of New Generation Light Driven Photovoltaic Modules, National Central University, Taoyuan, 32001, Taiwan;1. School of Information Science and Engineering, Central South University, Changsha 410083, China;2. School of Automation, China University of Geosciences, Wuhan 430074, China;3. School of Automation, Guangdong University of Technology, Guangzhou 510006, China;4. School of Computer Science, Tokyo University of Technology, Tokyo 192-0982, Japan;1. Grupo de Investigación en Materiales Avanzados y Energía, Facultad de Ingeniería, Instituto Tecnológico Metropolitano, Medellín, Colombia;2. Grupo de Investigación e Innovación Biomédica, Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano, Medellín, Colombia;1. Centre for Health Sciences Research, University of Salford, Salford, United Kingdom;2. Faculty of Health Sciences, University of Ottawa, Ottawa, Canada;1. Rehabilitation Science Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA;2. Physical Therapy Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA;1. School of Electrical Engineering, University of Belgrade, Serbia;2. School of Medicine, University of Belgrade, Serbia |
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| Abstract: | 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). |
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| Keywords: | EMG signal ECG interference ANFIS Wavelet Noise removal |
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