Real-time hand gesture recognition using surface electromyography and machine learning: A systematic literature review
A Jaramillo-Yánez, ME Benalcázar… - Sensors, 2020 - mdpi.com
Today, daily life is composed of many computing systems, therefore interacting with them in
a natural way makes the communication process more comfortable. Human–Computer …
a natural way makes the communication process more comfortable. Human–Computer …
[HTML][HTML] From brain to movement: Wearables-based motion intention prediction across the human nervous system
Fueled by the recent proliferation of energy-efficient and energy-autonomous or self-
powered nanotechnology-based wearable smart systems, human motion intention …
powered nanotechnology-based wearable smart systems, human motion intention …
Effect of balancing data using synthetic data on the performance of machine learning classifiers for intrusion detection in computer networks
Attacks on computer networks have increased significantly in recent days, due in part to the
availability of sophisticated tools for launching such attacks as well as the thriving …
availability of sophisticated tools for launching such attacks as well as the thriving …
A review of EMG-, FMG-, and EIT-based biosensors and relevant human–machine interactivities and biomedical applications
Z Zheng, Z Wu, R Zhao, Y Ni, X Jing, S Gao - Biosensors, 2022 - mdpi.com
Wearables developed for human body signal detection receive increasing attention in the
current decade. Compared to implantable sensors, wearables are more focused on body …
current decade. Compared to implantable sensors, wearables are more focused on body …
An optimal approach for heart sound classification using grid search in hyperparameter optimization of machine learning
Heart-sound auscultation is one of the most widely used approaches for detecting
cardiovascular disorders. Diagnosing abnormalities of heart sound using a stethoscope …
cardiovascular disorders. Diagnosing abnormalities of heart sound using a stethoscope …
Automated diagnosis of muscle diseases from EMG signals using empirical mode decomposition based method
Muscle activity decreases due to various conditions like age factors and muscle diseases
namely, amyotrophic lateral sclerosis (ALS) and myopathy. Electromyogram (EMG) signals …
namely, amyotrophic lateral sclerosis (ALS) and myopathy. Electromyogram (EMG) signals …
[HTML][HTML] A systematic review on surface electromyography-based classification system for identifying hand and finger movements
The developments in engineering fields have extended the use of electromyography (EMG)
beyond traditional diagnostic applications to multifarious areas like movement analysis …
beyond traditional diagnostic applications to multifarious areas like movement analysis …
Review on electromyography based intention for upper limb control using pattern recognition for human-machine interaction
A Asghar, S Jawaid Khan, F Azim… - Proceedings of the …, 2022 - journals.sagepub.com
Upper limb myoelectric prosthetic control is an essential topic in the field of rehabilitation.
The technique controls prostheses using surface electromyogram (sEMG) and intramuscular …
The technique controls prostheses using surface electromyogram (sEMG) and intramuscular …
In situ process monitoring using acoustic emission and laser scanning techniques based on machine learning models
Abstract Fused Filament Fabrication (FFF) is a widely used additive manufacturing method
for obtaining prototypes with complex structures. On the other hand, Commercial FFF …
for obtaining prototypes with complex structures. On the other hand, Commercial FFF …
A novel methodology for classifying EMG movements based on SVM and genetic algorithms
Electromyography (EMG) processing is a fundamental part of medical research. It offers the
possibility of developing new devices and techniques for the diagnosis, treatment, care, and …
possibility of developing new devices and techniques for the diagnosis, treatment, care, and …