Illuminance Color Independent in Remote Photoplethysmography for Pulse Rate Variability and Respiration Rate Measurement

Q3 Decision Sciences
Suryasari Suryasari, Aminuddin Rizal, Sri Kusumastuti, Taufiqqurrachman Taufiqqurrachman
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引用次数: 0

Abstract

Remote photoplethysmography (rPPG) is now becoming a new trend method to measure human physiological parameters. Especially due to it noncontact measurement which safe dan suitable to use in this new era condition. Pulse rate variability (PRV) and respiration rate (RR) included as parameters can be measured by using rPPG. PRV and RR are used to measure both physical and psychological wellness of the subject. However, current performance challenges in rPPG algorithm in measuring PRV and RR are illuminance invariant and motion. Especially in different light condition which represent real-life environment, signal-to-noise ratio (SNR) will be affected and directly reduce the measurement accuracy. Therefore in this study, we develop rPPG algorithm and then investigate the performance rPPG in different illuminance scenarios. We perform PRV and RR measurement under each scenario. On this study, for the pulse signal extraction, we were using algorithm is based on the modification of plane orthogonal-to-skin (POS) algorithm. While, for respiration signal extraction is done in CIE Lab color space. Our experimental results show the mean absolute error (MAE) of each measured parameters are 3.25 BPM and 2 BPM for PRV and RR respectively compared with clinical apparatus. The proposed method proved to be more reliable to use in real environments measurement. However, limitation of our proposed algorithm is still running in offline mode, hence for the future we want try to make our algorithm run in real time.
用于脉搏率变异性和呼吸率测量的远程光容积脉搏图的照度颜色独立
远程光容积脉搏波(rPPG)是一种测量人体生理参数的新方法。特别是由于它是一种安全的非接触式测量方法,适合在新时代条件下使用。脉搏变异性(PRV)和呼吸速率(RR)作为参数可通过rPPG测量。PRV和RR用于测量受试者的生理和心理健康状况。然而,目前rPPG算法在测量PRV和RR方面的性能挑战是光照不变性和运动性。特别是在代表现实环境的不同光照条件下,信噪比会受到影响,直接降低测量精度。因此,在本研究中,我们开发了rPPG算法,然后研究了rPPG在不同照度场景下的性能。我们在每个场景下执行PRV和RR测量。在本研究中,对于脉冲信号的提取,我们使用的算法是基于改进的平面正交皮肤(POS)算法。而呼吸信号的提取是在CIE Lab色彩空间中进行的。实验结果表明,与临床仪器相比,PRV和RR各测量参数的平均绝对误差分别为3.25 BPM和2 BPM。该方法在实际环境测量中具有较高的可靠性。然而,我们提出的算法的局限性仍然是在离线模式下运行,因此,为了将来我们希望尝试使我们的算法实时运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JOIV International Journal on Informatics Visualization
JOIV International Journal on Informatics Visualization Decision Sciences-Information Systems and Management
CiteScore
1.40
自引率
0.00%
发文量
100
审稿时长
16 weeks
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