Title: Prediction of instantaneous heart rate using adaptive algorithms

Authors: Sarita Kansal; Prashant P. Bansod; Abhay Kumar

Addresses: Department of Electronics and Communication, MITM/SOE, Indore, M.P., India ' Department Biomedical Engineering, SGSITS, Indore, M.P., India ' SoE, D.A.V.V., Indore, M.P., India

Abstract: In this paper, adaptive filter based on adaptive algorithms like least mean square (LMS), normalised least mean square (NLMS) and recursive least square (RLS) are used for the prediction of instantaneous heart rate in ECG signal. The adaptive algorithms work on the principle of optimising the least square error by achieving wiener solution. The weights of the filter coefficients are changing, as per the changes in the signal. The performance of adaptive filter is measured by mean square error (MSE) and the prediction accuracy is observed by mean absolute error (MAE). The simulation results show that the adaptive algorithms NLMS and RLS have faster convergence rate with less number of iteration but the forecasting accuracy is higher in LMS compared to NLMS and RLS algorithms.

Keywords: ECG; instantaneous heart rate; IHR; adaptive algorithm; least mean square; LMS; normalised least mean square; NLMS; recursive least square; RLS.

DOI: 10.1504/IJAIS.2019.108397

International Journal of Adaptive and Innovative Systems, 2019 Vol.2 No.4, pp.267 - 281

Accepted: 07 Sep 2018
Published online: 13 Jul 2020 *