Electromyography (EMG) has already been broadly used in human-machine interaction
(HMI) applications. Determining how to decode the information inside EMG signals robustly …

The surface electromyography (sEMG)-based gesture recognition with deep learning
approach plays an increasingly important role in human-computer interaction. Existing deep …

The analysis and recognition of sign languages are currently active fields of research
focused on sign recognition. Various approaches differ in terms of analysis methods and the …

Sign languages are developed around the world for hearing-impaired people to
communicate with others who understand them. Different grammar and alphabets limit the …

Sign language recognition has made significant advances in recent years. Many
researchers show interest in encouraging the development of different applications to …

The control performance of myoelectric prostheses would not only depend on the feature
extraction and classification algorithms but also on interactions of dynamic window-based …

To improve the accuracy of surface electromyography (sEMG)-based gesture recognition,
we present a novel hybrid approach that combines real sEMG signals with corresponding …

Recognition and understanding of sign language can aid communication between nondeaf
and deaf people. Recently, research groups have developed sign language recognition …

Wearable technology is attracting most attention in healthcare for the acquisition of
physiological signals. We propose a stand-alone wearable surface ElectroMyoGraphy …

Sign Language recognition systems aid communication among deaf people, hearing
impaired people, and speakers. One of the types of signals that has seen increased studies …