Design Concept of a Wearable Device for Sleep Related Brain Wave Detection and Stimulation

This paper presents a design concept of an innovative wearable device for brain wave detection and stimulation to aid sleep. Sleep's importance for a healthy life emphasizes the value of studying the application of technology to improve sleep quality for individuals unable to receive a good night's rest. Utilizing electroencephalography (EEG) for accurate sleep tracking, the device aims to be portable and efficient. It includes the EEG sensing and processing module, adaptive control and machine learning module, and electronic stimulation module, working together to guide the brain toward relaxation. Preliminary results demonstrate promising performances or necessities of the subsystems of the proposed design.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icdsca63855.2024.10860034
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
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Design Concept of a Wearable Device for Sleep Related Brain Wave Detection and Stimulation

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EEG and Brain-Computer Interfaces
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Design Concept of a Wearable Device for Sleep Related Brain Wave Detection and Stimulation

Yangfan Deng, Zhi‐Hong Mao, Zhengwen Zhang, Dun Mao, Yifan Guo, S Li, Haoliang Cheng, Helen X. Mao, Jijun Yin, Ariel R. Yin
article en

Abstract

This paper presents a design concept of an innovative wearable device for brain wave detection and stimulation to aid sleep. Sleep's importance for a healthy life emphasizes the value of studying the application of technology to improve sleep quality for individuals unable to receive a good night's rest. Utilizing electroencephalography (EEG) for accurate sleep tracking, the device aims to be portable and efficient. It includes the EEG sensing and processing module, adaptive control and machine learning module, and electronic stimulation module, working together to guide the brain toward relaxation. Preliminary results demonstrate promising performances or necessities of the subsystems of the proposed design.

Allegheny Intermediate Unit (US), University of Pittsburgh (US), Purdue University West Lafayette (US), University High School (US), Yale University (US)
Openalex Percentile: Top 73%
EEG and Brain-Computer Interfaces
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