As healthcare systems around the world face challenges such as escalating costs, limited
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …

Motor Imagery (MI) Electroencephalography (EEG) is one of the most common Brain-
Computer Interface (BCI) paradigms that has been widely used in neural rehabilitation and …

This article presents a 3-D medical simulation that employs reinforcement learning (RL) and
interactive RL (IRL) to teach and assess the procedure of donning and doffing personal …

The use of machine learning in Healthcare has the potential to improve patient outcomes as
well as broaden the reach and affordability of Healthcare. The history of other application …

Freezing of gait (FOG) leads to an increased risk of falls and limited mobility in individuals
with Parkinson's disease (PD). However, existing research ignores the fine-grained …

Motor imagery electroencephalograph (MI-EEG) decoding plays a crucial role in developing
motor imagery brain-computer interfaces (MI-BCIs). However, decoding intentions from MI …

This article presents an innovative solution for electromyography (EMG)-based human
motion analysis systems, addressing challenges of sensor comfort, interindividual variations …

With the evolution of biometric technology, this research embarks on a multidimensional
exploration, encompassing design innovation, ethical scrutiny, and the application of …