A review of physical and mathematical methods for reconstructing the functional networks of
the brain based on recorded brain activity is presented. Various methods are considered, as …

Understanding the solid biomechanics of the human body is important to the study of
structure and function of the body, which can have a range of applications in health care …

仿生机器人是指依据仿生学原理, 模仿生物结构, 运动特性等设计的性能优越的机电系统,
已逐渐在反恐防爆, 太空探索, 抢险救灾等不适合由人来承担任务的环境中凸显出良好的应用 …

Background and objective Epilepsy is a prevalent disorder that affects the central nervous
system, causing seizures. In the current study, a novel algorithm is developed using …

In order to realize the force control, when the prosthetic hand grasps the object, the forearm
electromyography signal is collected by the multi-channel surface electromyography (sEMG) …

A key challenge associated with myoelectric prosthesis limbs is the acquisition of a good
quality gesture intent signal from the residual anatomy of an amputee. In this study, the …

The present study addresses the cardiac arrhythmia (CA) classification problem using the
deep learning (DL)-based method for electrocardiography (ECG) data analysis. Recently …

Background: Electronic fetal monitoring (EFM) is widely applied as a routine diagnostic tool
by clinicians using fetal heart rate (FHR) signals to prevent fetal hypoxia. However, visual …

Surface electromyogram (sEMG) provides a non-invasive way to collect EMG signals. The
sEMG signals acquired from the muscles of the forearm can be used to recognize the hand …

Electromyogram (EMG) signals have had a great impact on many applications, including
prosthetic or rehabilitation devices, human-machine interactions, clinical and biomedical …