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A reliable and efficient machine learning pipeline for american sign language gesture recognition using EMG sensors
Sign languages has extensive applications among differently-abled to communicate with their surroundings. With the development of different sensing...
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Classification of hand movements based on EMD-CCT feature extraction method through EMG using machine learning
Internal and external noise frequently contaminates surface electromyography (sEMG) signals. These noises may impair the classifier’s ability to...
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A new approach for emotions recognition through EOG and EMG signals
In this paper, an approach for emotion recognition using physiological signals has been development. The main purpose of this paper is to provide...
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An EEG-EMG-Based Motor Intention Recognition for Walking Assistive Exoskeletons
Lower Limb Exoskeleton (LLE) has received considerable interests in strength augmentation, rehabilitation and walking assistance scenarios. For...
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Optimization of EMG-Derived Features for Upper Limb Prosthetic Control
Polyarticulated active prostheses constitute a promising solution for upper limb amputees. The bottleneck for their adoption though, is the lack of...
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EMG controlled adaptive multi-grasp prosthetic hand with an android interface
Human hand performs multiple grasp types during daily living activities. Adaptation of gras** force to avoid object slippage as employed by human...
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Expert System for Real Time Arm Movement Recognition Based on Surface EMG Signal
This paper presents classification of Electromyography (EMG) signals to distinguish between upper-limb motions. The system can help in the movement...
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Integration of a Lightweight Customized 2D CNN Model to an Edge Computing System for Real-Time Multiple Gesture Recognition
The human-machine interface (HMI) collects electrophysiology signals incoming from the patient and utilizes them to operate the device. However, most...
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Beta Artificial Bee Colony Algorithm for EMG Feature Selection
The electromyography (EMG) signals play a very important role in the muscular activity of the human body. Muscular activities can be measured and...
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EMG Denoising Based on CEEMDAN-PE-WT Algorithm
Raw Surface Electromyography (sEMG) generally contains baseline noise, random noise, power line interference and other noises. The performance of...
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A Systematic Review on ECG and EMG Biomedical Signal Using Deep-Learning Approaches
Biomedical signals play an indispensable role in many medical applications like diagnosis, prognosis, and defining treatment procedures. Recent...
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Research on Gesture Recognition of Surface EMG Based on Machine Learning
Gesture recognition pertains to recognizing meaningful expressions of motion by human, it is utmost important in medical rehabilitation, robot...
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Analysis of Hand Movement from Surface EMG Signals Using Artificial Neural Network
Fatal accidents are an inseparable part of life which often costs us loss of limbs especially hands and legs and turns any of our body asset into a...
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Real-time EMG based prosthetic hand controller realizing neuromuscular constraint
Development of prosthetic hands with human-like functionality and controllability is one of the major goals in the area of rehabilitation robotics....
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Feature Extraction Using Wavelet Scattering Transform Coefficients for EMG Pattern Classification
The Electromyogram (EMG) signal collected from the human muscles has been utilised for a long time to aid in diagnosing several medical conditions...
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Effective features extraction and selection for hand gesture recognition using sEMG signal
Surface Electromyographic (sEMG) signals are a promising approach to hand and finger gesture recognition. Most of the sEMG-based hand gesture...
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Auditive Emotion Recognition for Empathic AI-Assistants
This paper briefly introduces the Project “AudEeKA”, whose aim is to use speech and other bio signals for emotion recognition to improve remote, but...
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An approach to continuous hand movement recognition using SEMG based on features fusion
With the continuous development of EMG acquisition technology and artificial intelligence technology, EMG signal analysis has been extensively...
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Dynamic Gesture Recognition Based on Deep 3D Natural Networks
The process of establishing contact with a computer through gestures still faces many bottlenecks that need to be solved, one of which is how to...
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Two-Stream Spectral-Temporal Denoising Network for End-to-End Robust EEG-Based Emotion Recognition
Emotion recognition based on electroencephalography (EEG) is attracting more and more interest in affective computing. Previous studies have...