ArticleSensors (Basel, Switzerland)2018
A High-Level Control Algorithm Based on sEMG Signalling for an Elbow Joint SMA Exoskeleton.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Myoelectric Control Systems for Upper Limb Wearable Robotic Exoskeletons and Exosuits-A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Indexes for motor performance assessment in job integration/reintegration of people with neuromuscular disorders: A systematic review.Frontiers in neurology · 2022Pooled it
- Review
- Myoelectric Control in Rehabilitative and Assistive Soft Exoskeletons: A Comprehensive Review of Trends, Challenges, and Integration with Soft Robotic Devices.Biomimetics (Basel, Switzerland) · 2025Review
- Resistance Feedback of a Ni-Ti Alloy Actuator at Room Temperature in Still Air.Micromachines · 2024Article
- Exo Supportive Devices: Summary of Technical Aspects.Bioengineering (Basel, Switzerland) · 2023Review
- Shape Memory Alloy-Based Wearables: A Review, and Conceptual Frameworks on HCI and HRI in Industry 4.0.Sensors (Basel, Switzerland) · 2022Review
- A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human-Machine Interactivities and Biomedical Applications.Biosensors · 2022Review
- Sensors and Actuation Technologies in Exoskeletons: A Review.Sensors (Basel, Switzerland) · 2022Review
- Design of a Bio-Inspired Gait Phase Decoder Based on Temporal Convolution Network Architecture With Contralateral Surface Electromyography Toward Hip Prosthesis Control.Frontiers in neurorobotics · 2022Article
- Reducing Waste in 3D Printing Using a Neural Network Based on an Own Elbow Exoskeleton.Materials (Basel, Switzerland) · 2021Article
- Critical Issues and Imminent Challenges in the Use of sEMG in Return-To-Work Rehabilitation of Patients Affected by Neurological Disorders in the Epoch of Human-Robot Collaborative Technologies.Frontiers in neurology · 2020Article
- Hand Movement Classification Using Burg Reflection Coefficients.Sensors (Basel, Switzerland) · 2019Article
- Assistance Robotics and Biosensors.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) was designed. It was applied to a shape memory alloy (SMA)-actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according to data collected online during the first seconds of a therapy session. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the reference position pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm was tested in simulations and with healthy people for control of an elbow exoskeleton in flexion⁻extension movements. The results indicate that sEMG signals from elbow muscles, in combination with pressure sensors that measure arm⁻exoskeleton interaction, can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according to a patient's intention.
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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.