SynthesisSensors (Basel, Switzerland)2022
Myoelectric Control Systems for Upper Limb Wearable Robotic Exoskeletons and Exosuits-A Systematic Review.
Synthesis in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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Who cites it
15 citing papers in PubMed.
- Hearing It Right, Doing It Safely: A Reflex-Inspired Safety Gatekeeper for Voice-Controlled Exoskeleton Arm Manipulation.Biomimetics (Basel, Switzerland) · 2026Article
- Surface Electrical Impedance Myography in Assessment of Morphofunctional Changes in Biological Tissues and Biofeedback Interfaces.Sensors (Basel, Switzerland) · 2026Review
- Spiking neural network decoders of finger forces from high-density intramuscular microelectrode arrays.Nature communications · 2026Article
- ULTRA-MoCap: A Multimodal IMU and sEMG Dataset for Upper Body Joint Kinematics Analysis.Scientific data · 2026Article
- Preliminary Investigation of Myoelectric Control of an Assistive Neck Exoskeleton by Individuals With Amyotrophic Lateral Sclerosis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026Article
- Predicting Motor Intent from Residual Neck Muscle Activity in Individuals with Neck Weakness from ALS.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025Article
- Electromyography Signal Acquisition, Filtering, and Data Analysis for Exoskeleton Development.Sensors (Basel, Switzerland) · 2025Review
- Myoelectric Control in Rehabilitative and Assistive Soft Exoskeletons: A Comprehensive Review of Trends, Challenges, and Integration with Soft Robotic Devices.Biomimetics (Basel, Switzerland) · 2025Review
- Hand kinematics, high-density sEMG comprising forearm and far-field potentials for motion intent recognition.Scientific data · 2025Article
- Machine Learning- and Deep Learning-Based Myoelectric Control System for Upper Limb Rehabilitation Utilizing EEG and EMG Signals: A Systematic Review.Bioengineering (Basel, Switzerland) · 2025Review
- Simultaneous and Proportional Myoelectric Control of Multiple Degrees of Freedom in Individuals With Chronic Hemiparesis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025Article
- An Optimized Stimulation Control System for Upper Limb Exoskeleton Robot-Assisted Rehabilitation Using a Fuzzy Logic-Based Pain Detection Approach.Sensors (Basel, Switzerland) · 2024Article
- Optimizing the performance of convolutional neural network for enhanced gesture recognition using sEMG.Scientific reports · 2024Article
- From Simulation to Reality: Predicting Torque With Fatigue Onset via Transfer Learning.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024Article
- Delayed Muscle Activity in Stroke Survivors with Upper-Limb Hemiparesis.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, myoelectric control systems have emerged for upper limb wearable robotic exoskeletons to provide movement assistance and/or to restore motor functions in people with motor disabilities and to augment human performance in able-bodied individuals. In myoelectric control, electromyographic (EMG) signals from muscles are utilized to implement control strategies in exoskeletons and exosuits, improving adaptability and human-robot interactions during various motion tasks. This paper reviews the state-of-the-art myoelectric control systems designed for upper-limb wearable robotic exoskeletons and exosuits, and highlights the key focus areas for future research directions. Here, different modalities of existing myoelectric control systems were described in detail, and their advantages and disadvantages were summarized. Furthermore, key design aspects (i.e., supported degrees of freedom, portability, and intended application scenario) and the type of experiments conducted to validate the efficacy of the proposed myoelectric controllers were also discussed. Finally, the challenges and limitations of current myoelectric control systems were analyzed, and future research directions were suggested.
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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.