A fast approximate entropy algorithm for heart rate variability analysis
by Haiping Yang; Lijuan Chou; Yongxin Chou; Jicheng Liu
International Journal of Modelling, Identification and Control (IJMIC), Vol. 44, No. 1, 2024

Abstract: Approximate entropy is widely used in medical biological signal processing. However, due to the high complexity and time-consumption of approximate entropy calculation, it is generally only used for offline signal processing. In this study, the calculation process of approximate entropy is optimised. The goal is to shorten the running time of the algorithm without changing the approximate entropy value. The correctness and timeliness of the improved algorithm are verified by random number, and the improved algorithm is applied to HRV signal. Simulation results show that the improved algorithm can shorten the running time by 27-99 times, and the longer the cache length, the better the improvement effect. This makes it possible to process real-time biological signals with approximate entropy.

Online publication date: Mon, 18-Dec-2023

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