Hands are vital in a wide range of fundamental daily activities, and neurological diseases
that impede hand function can significantly affect quality of life. Wearable hand gesture …

Surface EMG-based gestures recognition systems are helping the disable to enjoy a better
life. Academic institutes and commercial companies have been developing a lot of sEMG …

Objectives This study investigates the performance of the Support Vector Machine (SVM) to
classify non-real-time and real-time EMG signals. The study also compares training …

The classification of imbalanced datasets, especially in medicine, is a major problem in data
mining. Such a problem is evident in analyzing normal and abnormal subjects about knee …

Multimodal sensor fusion can improve the performance of human–machine interfaces
(HMIs). However, increased sensing modalities and sensor count often cause excess …

Despite rapid advancements in technology, handwritten characters still hold significant roles
in various fields, including education, communication, biometric signature verification, and …

Gestures of the human hand can be identified through processing of surface
electromyography (sEMG) signals. The human hand can perform many gestures via …

Sign languages has extensive applications among differently-abled to communicate with
their surroundings. With the development of different sensing technologies, several new …

The purpose of this study was to determine electromyographically if there are significant
differences in the movement associated with the knee muscle, gait, leg extension from a …

Handwriting is essential for the development of fine motor skills in children. Handwritten
character recognition has the potential to facilitate natural human–machine interactions …