ArticleMicromachines2022
Study on Flexible sEMG Acquisition System and Its Application in Muscle Strength Evaluation and Hand Rehabilitation.
Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The trial behind it
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- From Signal Stacking to Dynamic Coupling: A Critical Review of Wearable EEG-EMG Fusion Brain-Computer Interfaces for Stroke Rehabilitation.Micromachines · 2026Review
- Flexible wearable medical devices: from material innovations and data processing to intelligent healthcare applications.Journal of advanced research · 2026Review
- Head and Neck Muscle Activity in Post-Stroke Dysphagia Patients: Muscle Dynamics and Implications for Rehabilitation.Journal of oral rehabilitation · 2025Article
- Surface EMG Sensing and Granular Gesture Recognition for Rehabilitative Pouring Tasks: A Case Study.Biomimetics (Basel, Switzerland) · 2025Article
- High-Accuracy Clock Synchronization in Low-Power Wireless sEMG Sensors.Sensors (Basel, Switzerland) · 2025Article
- sEMG-based gesture recognition using multi-stream adaptive CNNs with integrated residual modules.Frontiers in bioengineering and biotechnology · 2025Article
- A Review on Assisted Living Using Wearable Devices.Sensors (Basel, Switzerland) · 2024Review
- Graphene-Doped Piezoelectric Transducers by Kriging Optimal Model for Detecting Various Types of Laryngeal Movements.Micromachines · 2024Article
- Empowering Hand Rehabilitation with AI-Powered Gesture Recognition: A Study of an sEMG-Based System.Bioengineering (Basel, Switzerland) · 2023Article
- Dynamic Analysis and Experimental Study of Lasso Transmission for Hand Rehabilitation Robot.Micromachines · 2023Article
- Low-Density sEMG-Based Pattern Recognition of Unrelated Movements Rejection for Wrist Joint Rehabilitation.Micromachines · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Wearable devices based on surface electromyography (sEMG) to detect muscle activity can be used to assess muscle strength with the development of hand rehabilitation applications. However, conventional acquisition devices are usually complicated to operate and poorly comfortable for more medical and scientific application scenarios. Here, we report a flexible sEMG acquisition system that combines a graphene-based flexible electrode with a signal acquisition flexible printed circuit (FPC) board. Our system utilizes a polydimethylsiloxane (PDMS) substrate combined with graphene transfer technology to develop a flexible sEMG sensor. The single-lead sEMG acquisition system was designed and the FPC board was fabricated considering the requirements of flexible bending and twisting. We demonstrate the above design approach and extend this flexible sEMG acquisition system to applications for assessing muscle strength and hand rehabilitation training using a long- and short-term memory network training model trained to predict muscle strength, with 98.81% accuracy in the test set. The device exhibited good flexion and comfort characteristics. In general, the ability to accurately and imperceptibly monitor surface electromyography (EMG) signals is critical for medical professionals and patients.
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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.