Sleep-awakening classification based on wristband-collected blood volume pulse and triaxial acceleration of body movement
10.16289/j.cnki.1002-0837.2025.05011
- VernacularTitle:一种基于腕带血容量脉搏及体动三轴加速度的睡眠、觉醒分类方法
- Author:
Yanjun LI
1
;
Weibo LIU
;
Yan ZHANG
;
Congmiao SHAN
;
Zhongping CAO
;
Linghao XIONG
Author Information
1. 航天医学全国重点实验室,中国航天员科研训练中心,北京 100094
- Keywords:
automatic sleep stage classification;
sleep scoring;
blood volume pulse;
triaxial acceleration;
sleep quality;
DREAMT public database
- From:Space Medicine & Medical Engineering
2025;36(5):451-457
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the role in sleep staging from blood volume pulse(BVP)and triaxial acceleration(ACC)of body movement obtained by wristband.Methods The BVP and ACC obtained by Empatica E4 wristband were used from all 100 cases of sleep disorder subjects in the DREAMT public database.Two frequency domain characteristics(eS,LF/HF)and one time domain characteristic(vA)of the BVP baseline and the activity counts(CS)of the ACC were used for sleep-awakening classification based on random forest.Results The results of sleep-awakening classification of all 100 cases of sleep disorder subjects were obtained by leaving-one-out strategy.The accuracy is 79.8%and the Kappa coefficient is 0.56 by 4 features from BVP and ACC;the accuracy is 70.4%and the Kappa coefficient is 0.36 by 3 features of BVP;the accuracy is 75.1%and the Kappa coefficient is 0.47 based on activity counts.Conclusion The BVP and ACC obtained by the wristband can be used for the rough estimation of sleep and awakening for sleep disorder subjects,among which the importance of ACC is higher than that of BVP.
