Title: Energy-aware multi-path transmission of ECG signals for the classification of arrhythmia in wireless sensor network

Authors: V. Bhagyalakshmi; R.V. Pujeri; Geetha D. Devanagavi

Addresses: REVA University, Rukmini Knowledge Park, Kattigenahalli, Yelahanka, Bengaluru, Karnataka 560064, India ' MIT-ADT University, Rajbaug, Loni Kalbhor, Pune-412201, Maharashtra India ' REVA University, Rukmini Knowledge Park, Kattigenahalli, Yelahanka, Bengaluru, Karnataka 560064, India

Abstract: Electrocardiogram (ECG) transmission and classification of arrhythmia stand as an effective area for dealing with the cardiac-related diseases since the world is reporting a higher rate of heart patients. Remote monitoring of the patients, being an effective solution in providing an effective diagnosis solution, wireless technology plays a significant role in ECG transmission. However, routing seems to be a hectic challenge, and hence, the paper proposes an effective routing protocol, termed as fractional artificial bee colony BAT (FBeeBAT) algorithm that is the integration of fractional concept, artificial bee colony (ABC) algorithm, and bat optimisation algorithm. The proposed algorithm enables the energy-aware multi-path routing in the wireless body area network (WBAN), in which the ECG signal of the patient is transmitted to the destination. The received ECG signal is subjected to arrhythmia classification using the genetic bat-support vector neural network (GB-SVNN). The effectiveness of the proposed algorithm is analysed by establishing the simulation environment using 50 and 100 nodes in transmitting and classifying the ECG signal. The proposed method assured a classification accuracy of 0.98 and the goodput of 0.058 that is better compared with the existing methods.

Keywords: wireless sensor networks; routing protocol; arrhythmia classification; electrocardiogram signal transmission; energy-aware routing.

DOI: 10.1504/IJNBM.2019.104940

International Journal of Nano and Biomaterials, 2019 Vol.8 No.3/4, pp.253 - 276

Received: 05 Jul 2018
Accepted: 14 Feb 2019
Published online: 07 Feb 2020 *

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