This review discusses the critical issues and recommended practices from the perspective of
myoelectric interfaces. The major benefits and challenges of myoelectric interfaces are …

This manuscript presents a hybrid study of a comprehensive review and a systematic
(research) analysis. Myoelectric control is the cornerstone of many assistive technologies …

Decision tree algorithms are extensively used in machine learning field to classify
biomedical signals. De-noising and feature extraction methods are also utilized to get higher …

In recent years, surface electromyography (sEMG) signals have been increasingly used in
pattern recognition and rehabilitation. In this paper, a real-time hand gesture recognition …

Due to the increment in hand motion types, electromyography (EMG) features are
increasingly required for accurate EMG signals classification. However, increasing in the …

An algorithmic framework is proposed to process acceleration and surface
electromyographic (SEMG) signals for gesture recognition. It includes a novel segmentation …

The smooth and natural interaction between human and lower limb exoskeleton is
important. However, one of the challenges is that obtaining the joint rotation angles in time …

The performance of intelligent electromyogram (EMG)-driven prostheses, functioning as
artificial alternatives to missing limbs, is influenced by several dynamic factors including …

Extraction of potential electromyography (EMG) features has become one of the important
roles in EMG pattern recognition. In this paper, two EMG features, namely, enhanced …

Affect detection combined with a system that dynamically responds to a person's emotional
state allows an improved user experience with computers, systems, and environments and …