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A comprehensive study on the efficacy of a wearable sleep aid device featuring closed-loop real-time acoustic stimulation.


ABSTRACT: Difficulty falling asleep is one of the typical insomnia symptoms. However, intervention therapies available nowadays, ranging from pharmaceutical to hi-tech tailored solutions, remain ineffective due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, and an ability to keep people asleep during the night. This paper aims to enhance the efficacy of such an intervention by proposing a novel sleep aid system that can sense multiple physiological signals continuously and simultaneously control auditory stimulation to evoke appropriate brain responses for fast sleep promotion. The system, a lightweight, comfortable, and user-friendly headband, employs a comprehensive set of algorithms and dedicated own-designed audio stimuli. Compared to the gold-standard device in 883 sleep studies on 377 subjects, the proposed system achieves (1) a strong correlation (0.89 ± 0.03) between the physiological signals acquired by ours and those from the gold-standard PSG, (2) an 87.8% agreement on automatic sleep scoring with the consensus scored by sleep technicians, and (3) a successful non-pharmacological real-time stimulation to shorten the duration of sleep falling by 24.1 min. Conclusively, our solution exceeds existing ones in promoting fast falling asleep, tracking sleep state accurately, and achieving high social acceptance through a reliable large-scale evaluation.

SUBMITTER: Nguyen A 

PROVIDER: S-EPMC10579321 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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A comprehensive study on the efficacy of a wearable sleep aid device featuring closed-loop real-time acoustic stimulation.

Nguyen Anh A   Pogoncheff Galen G   Dong Ban Xuan BX   Bui Nam N   Truong Hoang H   Pham Nhat N   Nguyen Linh L   Nguyen-Huu Hoang H   Bui-Diem Khue K   Vu-Tran-Thien Quan Q   Duong-Quy Sy S   Ha Sangtae S   Vu Tam T  

Scientific reports 20231016 1


Difficulty falling asleep is one of the typical insomnia symptoms. However, intervention therapies available nowadays, ranging from pharmaceutical to hi-tech tailored solutions, remain ineffective due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, and an ability to keep people asleep during the night. This paper aims to enhance the efficacy of such an intervention by proposing a novel sleep aid system that can sense multiple physiological signals continuous  ...[more]

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