Authors: Chandan Kumar Jha; Maheshkumar H. Kolekar
Addresses: Department of Electrical Engineering, Indian Institute of Technology Patna, Bihta – 801103, India ' Department of Electrical Engineering, Indian Institute of Technology Patna, Bihta – 801103, India
Abstract: This paper reports an efficient electrocardiogram (ECG) data compression algorithm for tele-monitoring of cardiac patients from rural area, based on combination of two encoding techniques with discrete cosine transform. The proposed technique provides good compression ratio (CR) with low percent root-mean-square difference (PRD) values. For performance evaluation of the proposed algorithm 48 records of ECG signals are taken from MIT-BIH arrhythmia database. Each record of ECG signal is of duration 1 minute and sampled at sampling frequency of 360 Hz. Noise of the ECG signal has been removed using Savitzky-Golay filter. To transform the signal from time domain to frequency domain, discrete cosine transform has been used which compacts energy of the signal to lower order of frequency coefficients. After normalisation and rounding of transform coefficients, signals are encoded using dual encoding technique which consists of run length encoding and Huffman encoding. The dual encoding technique compresses data significantly without any loss of information. The proposed algorithm offers average values of CR, PRD, quality score, percent root mean square difference normalised, RMS error and SNR of 11.49, 3.43, 3.82, 5.51, 0.012 and 60.11 dB respectively.
Keywords: transmission; e-health; electronic healthcare; discrete cosine transform; DCT; Huffman encoding; run length encoding; ECG signals; electrocardiograms; data compression; telemonitoring; cardiac patients; heart rhythm; rural area; India; arrhythmia; irregular heartbeats; Savitzky-Golay filter; patient monitoring; remote monitoring; health monitoring.
International Journal of Telemedicine and Clinical Practices, 2017 Vol.2 No.1, pp.31 - 41
Received: 22 Apr 2016
Accepted: 08 Jun 2016
Published online: 07 Feb 2017 *