The proposed framework consists of logarithmic spectrogram-based graph signal (LSGS), AdaBoost k-means (AB-k-means) and an ensemble of feature selection (FS) ...

This intention of this study was to design an EMG signal-based expert model for hand-grasp classification that could enhance prosthetic hand movements for ...

Oct 22, 2024 · The proposed framework consists of logarithmic spectrogram-based graph signal (LSGS), AdaBoost k-means (AB-k-means) and an ensemble of feature ...

A new framework for classification of multi-category hand grasps using EMG signals ... Full text for this resource is not available from the Research Repository.

A new framework for classification of multi-category hand grasps using EMG signals ... Authors: Firas Sabar Miften; Mohammed Diykh; Shahab Abdulla; Siuly Siuly ...

Dec 28, 2020 · A new framework for classification of multi-category hand grasps using EMG signals. Artif. Intell. Med. Pub Date : 2020-12-28. DOI : 10.1016/j ...

This intention of this study was to design an EMG signal-based expert model for hand-grasp classification that could enhance prosthetic hand movements for ...

Highlights：. • Adaptive Boost k-means (AB-k-means) is designed to classify EMG signals. • Logarithmic Spectrogram Image is employed to extract EMG features.

May 30, 2024 · This research aims to provide the groundwork for smartly categorizing hand movements for use with prosthetic hands.

A classification framework for hand gestures using Electromyography (EMG) signals in prosthetic hands is presented. Leveraging the multi-scale characteristics ...