Noise Removal in EMG Signal Using Data Fusion Techniques

Authors(2) :-R.Mahalakshmi, K.Rajeswari

One of the main challenges in processing the biomedical signals, such as ECG , EEG and EMG is noise removal as they are easily get affected by various noises arising from different environmental conditions. Filtering out the noise from EMG signal improves the accuracy and performance of signal processing systems. But in practice, it is very complicated to filter out noise from the desired EMG signals to obtain noise corrupted raw signal. This paper proposes a new data fusion techniques to reduce the effect of noise on electromyography signals, that are to be further processed to get the required information. The proposed method results in EMG signal enhancement when a corrupted emg signal with an additive white Gaussian noise is the only available information. The main idea is to utilize the kalman filter to remove the noise and enhance the performance of electromyography signals.

Authors and Affiliations

Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, TamilNadu, India
Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, TamilNadu, India

EMG, Datafusion, Kalman Filter.

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Publication Details

Published in : Volume 3 | Issue 5 | May-June 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 90-94
Manuscript Number : ICASCT2515
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

R.Mahalakshmi, K.Rajeswari, " Noise Removal in EMG Signal Using Data Fusion Techniques", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 5, pp.90-94 , May-June-2017.
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