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A Review on Computation Methods Used in Photoplethysmography Signal Analysis for Heart Rate Estimation

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Abstract

Photoplethysmography (PPG) sensor-enabled wearable health monitoring devices can monitor realtime health status. PPG technology is a low-cost, noninvasive optical method used to measure a volumetric change in blood during a cardiac cycle. Continues analysis of change in light signal due to change in the blood helps medical professionals to extract valuable information regarding the cardiovascular system. Traditionally, an electrocardiogram (ECG) has been used as a dominant monitoring technique to detect irregularities in the cardiovascular system. However, in ECG for monitoring cardiac status, several electrodes have to be placed at different body locations, limiting its uses under medical assistantship and in a stationary position. Therefore, to fulfill the market demand for wearable and portable health monitoring devices, researchers are now showing interest in the PPG sensor enable wearable devices. However, the robustness of PPG sensor-enabled wearable devices is highly deviating due to motion artifacts. Therefore before extracting vital sign information like heart rate with PPG sensor, efficient removal of motion artifact is very important. This review orients the research survey on the principles and methods proposed for denoising and heart rate peak detection with PPG. The efficacy of each method related to heart rate peak detection with PPG technologies was compared in terms of mean absolute error, error percentage, and correlation coefficient. A comparative analysis is formulated to estimate heart rate based on the literature survey from the last ten years on PPG technology. This review article aims to explore different methods and challenges mentioned in state-of-the-art research related to motion artifacts removal and heart rate estimation from PPG-enabled wearable devices.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Bennett University, Greater Noida, India

    Pankaj & Rama Komaragiri

  2. School of Electronics Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India

    Ashish Kumar

  3. Department of Electronics and Communication Engineering, Delhi Technological University, Delhi, India

    Manjeet Kumar

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  1. Pankaj
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Correspondence to Manjeet Kumar.

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Pankaj, Kumar, A., Komaragiri, R. et al. A Review on Computation Methods Used in Photoplethysmography Signal Analysis for Heart Rate Estimation. Arch Computat Methods Eng 29, 921–940 (2022). https://doi.org/10.1007/s11831-021-09597-4

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