AIMC Topic: Electromyography
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Human Motion Intent Description Based on Bumpless Switching Mechanism for Rehabilitation Robot.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 30, 2021
This paper aims to improve the performance of an electromyography (EMG) decoder based on a switching mechanism in controlling a rehabilitation robot for assisting human-robot cooperation arm movements. For a complex arm movement, the major difficulty...
Real-time optimization of an ellipsoidal trajectory orientation using muscle effort with Extremum Seeking Control.
Medical engineering & physics
Mar 29, 2021
We present an approach for real-time model-free optimization of the orientation of the elliptical trajectory. The performance is evaluated in simulation and experimental stages. Our model-free approach is based on the use of Extremum Seeking Control ...
Effective recognition of human lower limb jump locomotion phases based on multi-sensor information fusion and machine learning.
Medical & biological engineering & computing
Mar 21, 2021
Jump locomotion is the basic movement of human. However, no thorough research on the recognition of jump sub-phases has been carried so far. This paper aims to use multi-sensor information fusion and machine learning to recognize the human jump phase...
Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges.
Sensors (Basel, Switzerland)
Mar 16, 2021
Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of e...
Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison.
Journal of neuroengineering and rehabilitation
Feb 25, 2021
BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculatur...
Exploring the Relationship Between EMG Feature Space Characteristics and Control Performance in Machine Learning Myoelectric Control.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 25, 2021
In myoelectric machine learning (ML) based control, it has been demonstrated that control performance usually increases with training, but it remains largely unknown which underlying factors govern these improvements. It has been suggested that the i...
A Machine Learning Processing Pipeline for Reliable Hand Gesture Classification of FMG Signals with Stochastic Variance.
Sensors (Basel, Switzerland)
Feb 22, 2021
ForceMyography (FMG) is an emerging competitor to surface ElectroMyography (sEMG) for hand gesture recognition. Most of the state-of-the-art research in this area explores different machine learning algorithms or feature engineering to improve hand g...
Robot-assisted rehabilitation of hand function after stroke: Development of prediction models for reference to therapy.
Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
Feb 16, 2021
BACKGROUND: Recovery of hand function after stroke represents the hardest target for clinicians. Robot-assisted therapy has been proved to be effective for hand recovery. Nevertheless, studies aimed to refer patients to the best therapy are missing.
EMG-Based 3D Hand Motor Intention Prediction for Information Transfer from Human to Robot.
Sensors (Basel, Switzerland)
Feb 12, 2021
(1) Background: Three-dimensional (3-D) hand position is one of the kinematic parameters that can be inferred from Electromyography (EMG) signals. The inferred parameter is used as a communication channel in human-robot collaboration applications. Al...
User training for machine learning controlled upper limb prostheses: a serious game approach.
Journal of neuroengineering and rehabilitation
Feb 12, 2021
BACKGROUND: Upper limb prosthetics with multiple degrees of freedom (DoFs) are still mostly operated through the clinical standard Direct Control scheme. Machine learning control, on the other hand, allows controlling multiple DoFs although it requir...
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