AIMC Topic: Electromyography
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A Novel Point-in-Polygon-Based sEMG Classifier for Hand Exoskeleton Systems.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 28, 2021
In the early 2000s, data from the latest World Health Organization estimates paint a picture where one-seventh of the world population needs at least one assistive device. Fortunately, these years are also characterized by a marked technological driv...
Wearable Sensor-Based Sign Language Recognition: A Comprehensive Review.
IEEE reviews in biomedical engineering
Jan 26, 2021
Sign language is used as a primary form of communication by many people who are Deaf, deafened, hard of hearing, and non-verbal. Communication barriers exist for members of these populations during daily interactions with those who are unable to unde...
Deep Learning for Robust Decomposition of High-Density Surface EMG Signals.
IEEE transactions on bio-medical engineering
Jan 20, 2021
Blind source separation (BSS) algorithms, such as gradient convolution kernel compensation (gCKC), can efficiently and accurately decompose high-density surface electromyography (HD-sEMG) signals into constituent motor unit (MU) action potential trai...
Elbow Motion Trajectory Prediction Using a Multi-Modal Wearable System: A Comparative Analysis of Machine Learning Techniques.
Sensors (Basel, Switzerland)
Jan 12, 2021
Motion intention detection is fundamental in the implementation of human-machine interfaces applied to assistive robots. In this paper, multiple machine learning techniques have been explored for creating upper limb motion prediction models, which ge...
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications.
IEEE transactions on biomedical circuits and systems
Dec 31, 2020
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge. This can fa...
An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques.
Sensors (Basel, Switzerland)
Nov 12, 2020
In recent years the advances in Artificial Intelligence (AI) have been seen to play an important role in human well-being, in particular enabling novel forms of human-computer interaction for people with a disability. In this paper, we propose a sEMG...
A Random Forest Machine Learning Framework to Reduce Running Injuries in Young Triathletes.
Sensors (Basel, Switzerland)
Nov 9, 2020
BACKGROUND: The running segment of a triathlon produces 70% of the lower limb injuries. Previous research has shown a clear association between kinematic patterns and specific injuries during running.
A Multimodal Intention Detection Sensor Suite for Shared Autonomy of Upper-Limb Robotic Prostheses.
Sensors (Basel, Switzerland)
Oct 27, 2020
Neurorobotic augmentation (e.g., robotic assist) is now in regular use to support individuals suffering from impaired motor functions. A major unresolved challenge, however, is the excessive cognitive load necessary for the human-machine interface (H...
Myoelectric digit action decoding with multi-output, multi-class classification: an offline analysis.
Scientific reports
Oct 9, 2020
The ultimate goal of machine learning-based myoelectric control is simultaneous and independent control of multiple degrees of freedom (DOFs), including wrist and digit artificial joints. For prosthetic finger control, regression-based methods are ty...
Robotic Rehabilitation in Spinal Cord Injury: A Pilot Study on End-Effectors and Neurophysiological Outcomes.
Annals of biomedical engineering
Sep 11, 2020
Robot-aided gait training (RAGT) has been implemented to provide patients with spinal cord injury (SCI) with a physiological limb activation during gait, cognitive engagement, and an appropriate stimulation of peripheral receptors, which are essentia...
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