Upper limb amputation is a widespread problem worldwide, leading to massive loss of
functionality for the victims. While a few solutions exist, these are often very expensive and …

Purpose Human emotion recognition using electroencephalograms (EEG) is a critical area
of research in human–machine interfaces. Furthermore, EEG data are convoluted and …

Globally, 2.5% of upper limb amputations are transhumeral, and both mechanical and
electronic prosthetics are being developed for individuals with this condition. Mechanics …

Kinesiologists who study people's posture during walking depend on spreadsheets and
visual posture reviews. Gold-standard evaluation relies on expert evaluation, not mediated …

Brain signals have recently gained popularity in brain-computer interface (BCI) systems,
providing valuable insights into various brain functionalities. Analyzing brain activity signals …

This paper presents a novel approach to control and actuate a Continuous Passive Motion
(CPM) machine by integrating a deep learning-based control strategy using convolutional …

Brain-computer interface (BCI) technology uses electroencephalogram (EEG) signals to
create a direct interaction between the human body and its surroundings. Motor imagery (MI) …

Motor imagery-based electroencephalogram (MI-EEG) signal classification plays a vital role
in the development of brain-computer interfaces (BCIs), particularly in providing assistance …

In this paper, a low-cost prosthetic arm design approach is introduced through a non-
invasive technique for amputees. The arm is controlled by brain signals using …

Neuroprosthetics have experienced a remarkable evolution in recent times, particularly with
the advent of intelligent neuroprosthetics that leverages artificial intelligence (AI) technology …