Application of min-max normalization on subject-invariant EMG pattern recognition
Surface electromyography (EMG) is one of the promising signals for the recognition of the
intended hand movement of an amputee. Nevertheless, there are several barriers to its …
intended hand movement of an amputee. Nevertheless, there are several barriers to its …
Surgical Instrument Signaling Gesture Recognition Using Surface Electromyography Signals
Surgical Instrument Signaling (SIS) is compounded by specific hand gestures used by the
communication between the surgeon and surgical instrumentator. With SIS, the surgeon …
communication between the surgeon and surgical instrumentator. With SIS, the surgeon …
A novel signal normalization approach to improve the force invariant myoelectric pattern recognition of transradial amputees
Variation in the electromyogram pattern recognition (EMG-PR) performance with the muscle
contraction force is a key limitation of the available prosthetic hand. To alleviate this …
contraction force is a key limitation of the available prosthetic hand. To alleviate this …
Optimizing the performance of convolutional neural network for enhanced gesture recognition using sEMG
Deep neural networks (DNNs) have demonstrated higher performance results when
compared to traditional approaches for implementing robust myoelectric control (MEC) …
compared to traditional approaches for implementing robust myoelectric control (MEC) …
How do sEMG segmentation parameters influence pattern recognition process? An approach based on wearable sEMG sensor
JJAM Junior, CE Pontim, TS Dias… - … Signal Processing and …, 2023 - Elsevier
Processing surface electromyography (sEMG) data in real-time to control robotic devices in
applications involving upper-limb prostheses is challenging, especially when the problem …
applications involving upper-limb prostheses is challenging, especially when the problem …
Evaluation of windowing techniques for intramuscular EMG-based diagnostic, rehabilitative and assistive devices
Objective. Intramuscular electromyography (iEMG) signals, invasively recorded, directly from
the muscles are used to diagnose various neuromuscular disorders/diseases and to control …
the muscles are used to diagnose various neuromuscular disorders/diseases and to control …
On the Intersection of Signal Processing and Machine Learning: A Use Case-Driven Analysis Approach
Recent advancements in sensing, measurement, and computing technologies have
significantly expanded the potential for signal-based applications, leveraging the synergy …
significantly expanded the potential for signal-based applications, leveraging the synergy …
FORS-EMG: A Novel sEMG Dataset for Hand Gesture Recognition Across Multiple Forearm Orientations
U Rumman, A Ferdousi, MS Hossain, MJ Islam… - arXiv preprint arXiv …, 2024 - arxiv.org
Surface electromyography (sEMG) signal holds great potential in the research fields of
gesture recognition and the development of robust prosthetic hands. However, the sEMG …
gesture recognition and the development of robust prosthetic hands. However, the sEMG …
Optimizing electrode positions on forearm to increase SNR and myoelectric pattern recognition performance
With the advances in electromyography-based human–computer interaction, particularly in
myoelectric prosthetic hands, the position of electromyography electrodes has gained less …
myoelectric prosthetic hands, the position of electromyography electrodes has gained less …
Forearm orientation and muscle force invariant feature selection method for myoelectric pattern recognition
Electromyogram (EMG) signal-based prosthetic hand can restore an amputee's missing
functionalities, which requires a faithful electromyogram pattern recognition (EMG-PR) …
functionalities, which requires a faithful electromyogram pattern recognition (EMG-PR) …