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Open Access

Heart-Rate Analysis of Healthy and Insomnia Groups with Detrended Fractal Dimension Feature in Edge

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
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Abstract

Insomnia, whether situational or chronic, affects over a third of the general population in today’s society. However, given the lack of non-contact and non-inductive quantitative evaluation approaches, most insomniacs are often unrecognized and untreated. Although Polysomnographic (PSG) is considered as one of the assessment methods, it is poorly tolerated and expensive. In this paper, with the recent development of Internet-of-Things devices and edge computing techniques, we propose a detrended fractal dimension (DFD) feature for the analysis of heart-rate signals, which can be easily acquired by many wearables, of good sleepers and insomniacs. This feature was derived by calculating the fractal dimension (FD) of detrended signals. For the trend component removal, we improved the null space pursuit algorithm and proposed an adaptive trend extraction algorithm. The experimental results demonstrated the efficacy of the proposed DFD index through numerical statistics and significance testing for healthy and insomnia groups, which renders it a potential biomarker for insomnia assessment and management.

Keywords

insomniafractal dimensionadaptive signal separationhypothesis testing

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Tsinghua Science and Technology
Volume 27 Issue 2,
April 2022
Pages 325-332
DOI: 10.26599/TST.2021.9010030
Cite this article:
Wang X, Zhou Y, Zhao C. Heart-Rate Analysis of Healthy and Insomnia Groups with Detrended Fractal Dimension Feature in Edge. Tsinghua Science and Technology, 2022, 27(2): 325-332. https://doi.org/10.26599/TST.2021.9010030

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Received: 25 January 2021
Revised: 02 March 2021
Accepted: 17 March 2021
Published: 29 September 2021
© The author(s) 2022

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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