ArticleACS applied materials & interfaces2025
Full Body-Worn Textile-Integrated Nanomaterials and Soft Electronics for Real-Time Continuous Motion Recognition Using Cloud Computing.
Article in ACS applied materials & interfaces, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Multidimensional and Multifunctional Laser-Induced Graphene (LIG) for Point-of-Care and Wearable Biosensing, Theranostics, and Bioactive Interfaces Toward Personalized Healthcare and Regenerative Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Advances in biomaterials for sports injury prevention and rehabilitation: current status and future perspectives.Nanoscale advances · 2026Review
- Effects of sensor geometry, placement, and cycle detection on wearable respiration monitoring with textile printed strain sensors.Discover sensors · 2026Article
- High-dimensional continuous action space control via trust region optimized deep reinforcement learning.Scientific reports · 2025Article
- Flexible Smart Insole and Plantar Pressure Monitoring Using Screen-Printed Nanomaterials and Piezoresistive Sensors.ACS applied materials & interfaces · 2025Article
- Wireless Flexible Potentiometric Microsensors for Temperature-Compensated Sweat Electrolyte Monitoring.ACS applied materials & interfaces · 2025Article
Corrections and comments
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Authors and funding
13 authors.
Funding
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Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.