Full Body-Worn Textile-Integrated Nanomaterials and Soft Electronics for Real-Time Continuous Motion Recognition Using Cloud Computing
Recognizing human body motions opens possibilities for real-time observation of users’ daily activities, revolutionizing continuous human healthcare and rehabilitation. While some wearable sensors show their capabilities in detecting movements, no prior work could detect full-body motions with wirel...
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Published in | ACS applied materials & interfaces Vol. 17; no. 5; pp. 7977 - 7988 |
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Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
05.02.2025
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Subjects | |
Online Access | Get full text |
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Summary: | Recognizing human body motions opens possibilities for real-time observation of users’ daily activities, revolutionizing continuous human healthcare and rehabilitation. While some wearable sensors show their capabilities in detecting movements, no prior work could detect full-body motions with wireless devices. Here, we introduce a soft electronic textile-integrated system, including nanomaterials and flexible sensors, which enables real-time detection of various full-body movements using the combination of a wireless sensor suit and deep-learning-based cloud computing. This system includes an array of a nanomembrane, laser-induced graphene strain sensors, and flexible electronics integrated with textiles for wireless detection of different body motions and workouts. With multiple human subjects, we demonstrate the system’s performance in real-time prediction of eight different activities, including resting, walking, running, squatting, walking upstairs, walking downstairs, push-ups, and jump roping, with an accuracy of 95.3%. The class of technologies, integrated as full body-worn textile electronics and interactive pairing with smartwatches and portable devices, can be used in real-world applications such as ambulatory health monitoring via conjunction with smartwatches and feedback-enabled customized rehabilitation workouts. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1944-8244 1944-8252 1944-8252 |
DOI: | 10.1021/acsami.4c17369 |