PhyMask: Robust Sensing of Brain Activity and Physiological Signals During Sleep with an All-textile Eye Mask

Author:

Rostaminia Soha1ORCID,Homayounfar Seyedeh Zohreh1,Kiaghadi Ali1ORCID,Andrew Trisha1,Ganesan Deepak1ORCID

Affiliation:

1. University of Massachusetts Amherst, Amherst, MA

Abstract

Clinical-grade wearable sleep monitoring is a challenging problem since it requires concurrently monitoring brain activity, eye movement, muscle activity, cardio-respiratory features, and gross body movements. This requires multiple sensors to be worn at different locations as well as uncomfortable adhesives and discrete electronic components to be placed on the head. As a result, existing wearables either compromise comfort or compromise accuracy in tracking sleep variables. We propose PhyMask, an all-textile sleep monitoring solution that is practical and comfortable for continuous use and that acquires all signals of interest to sleep solely using comfortable textile sensors placed on the head. We show that PhyMask can be used to accurately measure all the signals required for precise sleep stage tracking and to extract advanced sleep markers such as spindles and K-complexes robustly in the real-world setting. We validate PhyMask against polysomnography (PSG) and show that it significantly outperforms two commercially-available sleep tracking wearables—Fitbit and Oura Ring.

Funder

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Health Information Management,Health Informatics,Computer Science Applications,Biomedical Engineering,Information Systems,Medicine (miscellaneous),Software

Reference120 articles.

1. https://aasm.org/clinical-resources/practice-standards/ 2020 American Academy of Sleep Medicine

2. 2020. Cyton + Daisy Biosensing Boards (16-Channels). Retrieved 15 June 2022 from https://shop.openbci.com/products/cyton-daisy-biosensing-boards-16-channel.

3. 2020. Embla RemLogic PSG Software for sleep and micro-events annotations. Retrieved from https://neuro.natus.com/products-services/embla-remlogic-software.

4. 2020. Go Direct Respiration Belt Vernier. Retrieved from https://www.vernier.com/product/go-direct-respiration-belt/.

5. 2020. Gold Cup Electrodes. Retrieved from https://shop.openbci.com/products/openbci-gold-cup-electrodes?variant=9056028163.

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3