Pulse rate variability estimation method based on sliding window iterative DFT and hilbert transform

doi:10.5405/jmbe.1684

	Pulse rate variability estimation method based on sliding window iterative DFT and hilbert transform
	Chou, Yongxin 1,2; Zhang, Aihua 1,2; Wang, Ping 1,2; Gu, Jason 3
刊名	Journal of Medical and Biological Engineering
	2014
卷号	34 期号:4 页码:347-355
关键词	Biomedical signal processing Discrete Fourier transforms Frequency domain analysis Iterative methods Low pass filters Photoplethysmography Signal sampling Signal to noise ratio Hilbert transform Photoplethysmography (PPG) Pulse rate Pulse rate variability Real time Sliding Window
ISSN号	16090985
DOI	10.5405/jmbe.1684
英文摘要	An approach for deriving pulse rate variability (PRV) from photoplethysmography (PPG) signals is proposed. By combining sliding window iterative discrete Fourier transform (DFT) with the Hilbert transform algorithm, this method effectively reduces the influence of noise and sampling frequency compared with those of traditional methods. First, the fundamental component of the PPG signal is computed with the sliding window iterative DFT algorithm. Then, it is processed by an integer coefficient low-pass filter and the Hilbert transform to produce an instantaneous pulse rate (IPR). Finally, PRV is extracted from IPR in the frequency domain. PRV is also derived from the PPG signal in the time domain for comparison with that derived using the proposed method. Furthermore, PRV obtained from PPG signals at various sampling frequencies and with various noise levels is investigated. The results show that the proposed method can accurately derive PRV from PPG signals, even if the PPG signal has a low sampling frequency (4Hz) and high noise (e.g., SNR is about 3.0). The experimental results indicate that the proposed method can be used to estimate PRV when the subjects are in different states (rest, sleeping, or visual fatigue). Moreover, the proposed method is efficient and thus suitable for detecting PRV in real time. It has potential for PRV assessment in various medical fields, such as home health and clinical and hospital environments.
资助项目	National Natural Science Foundation of China[81360229]
WOS研究方向	Engineering
语种	英语
出版者	Biomedical Engineering Society
WOS记录号	WOS:000345220400007
状态	已发表
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/113668]
专题	电气工程与信息工程学院
通讯作者	Zhang, Aihua
作者单位	1.Key Lab Gansu Adv Control Ind Proc, Lanzhou 730050, Peoples R China 2.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China 3.Dalhousie Univ, Dept Elect & Comp Engn, Halifax, NS B3H 4R2, Canada
推荐引用方式 GB/T 7714	Chou, Yongxin,Zhang, Aihua,Wang, Ping,et al. Pulse rate variability estimation method based on sliding window iterative DFT and hilbert transform[J]. Journal of Medical and Biological Engineering,2014,34(4):347-355.
APA	Chou, Yongxin,Zhang, Aihua,Wang, Ping,&Gu, Jason.(2014).Pulse rate variability estimation method based on sliding window iterative DFT and hilbert transform.Journal of Medical and Biological Engineering,34(4),347-355.
MLA	Chou, Yongxin,et al."Pulse rate variability estimation method based on sliding window iterative DFT and hilbert transform".Journal of Medical and Biological Engineering 34.4(2014):347-355.