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Network Biology, 2018, 8(1): 12-24
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Removal of electromyography noise from ECG for high performance biomedical systems

Navdeep Prashar, Jyotsna Dogra, Meenakshi Sood, Shruti Jain
Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan, India

Received 13 October 2017;Accepted 20 December 2017;Published 1 March 2018
IAEES

Abstract
This paper presents the review of the biomedical system which consists of an energy source, signal processing, signal conditioning and signal transmission. These blocks are designed by various optimization techniques to achieve high operating speed, compressed area and minimum energy consumption. These techniques are mainly divided in to four aspects: (a) increasing the longevity of device using energy harvesting approaches; (b) reducing the delay to enhance the operating frequency; (c) reducing the data storage using data compression; (d) increasing the data rate transmission with reduced power consumption. This review paper briefly summarizes the various techniques and device performance achieved by these techniques. To attain these high performance systems input played a vital role. This paper also presents the different low pass IIR filter approximation method techniques to remove Electromyography noise from ECG input signal. For this purpose, we have taken MIT-BIH Arrhythmia database. We have calculated signal to noise ratio and power spectral density. On comparing their performance parameters of different low pass IIR filters, Elliptic filter has found best suited to remove this type of noise.

Keywords energy harvesting;implantable devices;inductive coupling;SNR;PSD;ECG;IIR.

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