Heart Rate Variability Recording System Using Photoplethysmography Sensor

N. Aimie-Salleh, Nurul Aliaa Abdul Ghani, Nurhafiezah Hasanudin, Siti Nur Shakiroh Shafie
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引用次数: 9

Abstract

Heart rate variability (HRV) is a physiological measurement that can help to monitor and diagnose chronic diseases such as cardiovascular disease, depression, and psychological stress. HRV measurement is commonly extracted from the electrocardiography (ECG). However, ECG has bulky wires where it needs at least three surface electrodes to be placed on the skin. This may cause distraction during the recording and need longer time to setup. Therefore, photoplethysmography (PPG), a simple optical technique, was suggested to obtain heart rate. This study proposes to investigate the effectiveness of PPG recording and derivation of HRV for feature analysis. The PPG signal was preprocessed to remove all the noise and to extract the HRV. HRV features were collected using time-domain analysis (TA), frequency-domain analysis (FA) and nonlinear time-frequency analysis (TFA). Five out of 22 HRV features, which are HR, RMSSD, LF/HF, LFnu, and HFnu, showed high correlation (rho > 0.6 and prho < 0.05) in comparison to standard 5-min excerpt while producing significant difference (p-value < 0.05) during the stressing condition across all interval HRV excerpts. This simple yet accurate PPG recording system perhaps might useful to assess the HRV signal in a short time, and further can be used for the ANS assessment.
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利用光电容积脉搏波传感器的心率变异性记录系统
心率变异性(HRV)是一种生理测量,可以帮助监测和诊断慢性疾病,如心血管疾病、抑郁症和心理压力。HRV测量通常是从心电图(ECG)中提取的。然而,心电图有笨重的电线,它需要至少三个表面电极放置在皮肤上。这可能会导致在录制过程中分心,需要更长的时间来设置。因此,我们建议使用一种简单的光学技术——光容积脉搏波描记法(PPG)来测量心率。本研究旨在探讨PPG记录和HRV推导在特征分析中的有效性。对PPG信号进行预处理,去除所有噪声,提取HRV。采用时域分析(TA)、频域分析(FA)和非线性时频分析(TFA)收集HRV特征。22个HRV特征中的5个HRV特征(HR、RMSSD、LF/HF、LFnu和HFnu)与标准5分钟摘录具有高相关性(rho > 0.6, prho < 0.05),而在应力条件下,所有间隔HRV摘录均产生显著差异(p值< 0.05)。这种简单而准确的PPG记录系统可能有助于在短时间内评估HRV信号,并进一步用于ANS评估。
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