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A solution for co-frequency and low SNR problems in heart rate estimation based on photoplethysmography signals

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Abstract

In order to realize high-accuracy heart rate (HR) estimation based on photoplethysmography (PPG) under the scenes of low signal-to-noise ratio (SNR) and co-frequency caused by motion artifacts (MAs), this paper presents a novel framework integrating two-stage variational mode decomposition (VMD) denoising method, noise compensation technology, and hidden Markov model (HMM)-based tracking algorithm. The two-stage VMD denoising method is designed to separate the HR signal from MA under low SNR scene. The noise compensation technology is applied to solve the problem of co-frequency. HMM-based HR tracking method is adopted to obtain the global optimization performance of HR estimation. The effectiveness and superiority of the proposed framework in solving problems of low SNR and co-frequency associated with motion artifacts have been verified by the HR estimation experiments carried out on three public high-SNR PPG databases (ISPC, BAMI I, BAMI II) and a self-built low-SNR database (WeData). Compared with the two classical frameworks namely joint sparse spectrum reconstruction (JOSS) and convolutional neural network-long short-term memory network (CNN-LSTM), the proposed framework obtains the lowest HR estimation errors (0.94 beats per minute (BPM) and 1.81 BPM respectively) on both BAMI 2 with the highest SNR (0.40 dB) and WeData with the lowest SNR (− 9.07 dB). For the low-SNR database Wedata, the average absolute error (AAE) decreases by more than 21 BPM. The research result of this study provides a solution for the realization of high-accuracy PPG-based HR estimation in exercise scenarios.

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Funding

This work was supported by the National Nature Science Foundation of China under Grants 61871360 and 61671417.

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Authors and Affiliations

  1. Dept Elect Sci & Technol, University of Science and Technology of China, Hefei, 230027, Anhui, China

    Jiaqi Zhao, Xiang Chen, Xu Zhang & Xun Chen

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  1. Jiaqi Zhao
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  2. Xiang Chen
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  3. Xu Zhang
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  4. Xun Chen
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Correspondence to Xiang Chen.

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This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by Ethics Review Committee of First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China, under Application No. PJ 2014–08-04.

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Zhao, J., Chen, X., Zhang, X. et al. A solution for co-frequency and low SNR problems in heart rate estimation based on photoplethysmography signals. Med Biol Eng Comput 60, 3419–3433 (2022). https://doi.org/10.1007/s11517-022-02678-x

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