Abstract
This paper focuses on developing an adaptive heart rate monitoring algorithm for wrist-based rehabilitation systems. Due to the characteristics of the wrist, the heartbeat measurements are unstable. To improve the preprocessing efficiency and perform measurement calibration, a novel joint algorithm incorporating automatic multiscale-based peak detection and fuzzy logic control (AMPD-Fuzzy) is proposed. The monitoring approach consists of two phases: (1) Preprocessing and (2) Detection and Calibration. Phase 1 explores the parameter settings, threshold, and decision rules. Phase 2 applies fuzzy logic control and the Laplacian model to provide signal reshaping. Experimental results show that the proposed algorithm can effectively achieve heart rate monitoring for wearable healthcare devices.
Author supplied keywords
Cite
CITATION STYLE
Kuo, T. H., Teng, C. M., Wu, M. F., & Wen, C. Y. (2021). An adaptive heart rate monitoring algorithm for wearable healthcare devices. Electronics (Switzerland), 10(17). https://doi.org/10.3390/electronics10172092
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.