Sleep Indicators and staging: A Functional Near-Infrared Spectroscopy Study in Healthy Young Adults

Yong Cao; Xingwei An; Wenxiao Zhong; Jin Jiang; Hongzuo Chu; Xuejun Jiao; Xiaoping Chen; Yufeng Ke; Bo Wang

doi:10.1016/j.neuroimage.2025.121368

Sleep Indicators and staging: A Functional Near-Infrared Spectroscopy Study in Healthy Young Adults

Neuroimage. 2025 Jul 10:121368. doi: 10.1016/j.neuroimage.2025.121368. Online ahead of print.

Authors

Yong Cao¹, Xingwei An², Wenxiao Zhong², Jin Jiang³, Hongzuo Chu⁴, Xuejun Jiao³, Xiaoping Chen³, Yufeng Ke², Bo Wang⁵

Affiliations

¹ National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, 100094, China. Electronic address: caoyong_93@163.com.
² Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China.
³ National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, 100094, China.
⁴ National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, 100094, China; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China.
⁵ National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, 100094, China. Electronic address: wowbob@139.com.

PMID: 40651677
DOI: 10.1016/j.neuroimage.2025.121368

Abstract

Functional near-infrared spectroscopy(fNIRS)-based sleep staging has attracted considerable interest due to its portability and limited interference with sleep. However, few studies have systematically examined sleep indicators or formulated sleep staging models based on fNIRS features labelled by polysomnography(PSG). This study aimed to address these shortcomings and promote the application of fNIRS in sleep monitoring. 37 volunteers participated in our experiment, with 6-channel prefrontal fNIRS data and standard PSG data collected simultaneously. Sleep indicators were extracted from time-domain, frequency-domain, and entropy perspectives. Sleep staging was developed based on these indicators using human-scored PSG as reference. Our findings indicated deeper sleep was correlated with a decrease in amplitude of time-domain features, while entropy features showed a contrasting trend. The fNIRS-based sleep staging achieved a Cohen's kappa(κ) of 0.76±0.12, 0.72±0.09, 0.71±0.07, with accuracies of 94.2±2.4%, 87.8±3.2%, and 82.2±4.1%, for 2-class(Wake/Sleep), 3-class(Wake/NREM/REM), 4-class (Wake/N1+N2/N3/REM) classifications, respectively. Sleep statistics derived from fNIRS closely aligned with those from PSG, with differences in sleep onset latency, wake after sleep onset, total wake/sleep time within 5 min and sleep efficiency below 3%. The substantial agreement in both detailed (epoch-by-epoch) and comprehensive (total) sleep statistics with PSG suggests fNIRS is a reliable tool for long-term sleep monitoring in everyday settings.

Keywords: functional near-infrared spectroscopy; polysomnography; sleep indicators; sleep staging; sleep statistics.