Latest AI and machine learning research in sports medicine for healthcare professionals.
The development of brain-computer interface-controlled exoskeletons promises new treatment strategies for neurorehabilitation after stroke or spinal cord injury. By converting brain/neural activity into control signals of wearable actuators, brain/neural exoskeletons (B/NEs) enable the execution of movements despite impaired motor function. Beyond the use as assistive devices, it was shown that-up...
Structural health monitoring (SHM) techniques often require a large number of sensors to evaluate and monitor the structural health. In this paper, we propose a deep neural network (DNN)-based SHM method for accurate crack detection and localization in real time using a small number of strain gauge sensors and confirm its feasibility based on experimental data. The proposed method combines a DNN m...
Radiologists today play a central role in making diagnostic decisions and labeling images for training and benchmarking artificial intelligence (AI) a...
Silent communication based on biosignals from facial muscle requires accurate detection of its directional movement and thus optimally positioning min...
Understanding the fine-grained temporal structure of human actions and its semantic interpretation is beneficial to many real-world tasks, such as spo...
Here we report and comment on the magnitudes of post-stroke impairment reduction currently observed using new neurotechnologies. We argue that neurote...
BACKGROUND: A robotic rehabilitation gym can be defined as multiple patients training with multiple robots or passive sensorized devices in a group se...
The primary goal of this research article is to apply ELECTRE I, a fundamental multi-criteria group decision-making technique, in an m-polar fuzzy N-s...
Soft robotics locomotion at the liquid-air interface has become more and more important for an intelligent society. However, existing locomotion of so...
Robotic developments in the field of rehabilitation and assistance have seen a significant increase in the last few years [...].
Comparing a family structure to a company, one can often think of parents as leaders and adolescents as employees. Stressful family environments and a...
A wide range of application domains,s such as remote robotic control, rehabilitation, and remote surgery, require capturing neuromuscular activities. ...
End-effector type upper limb rehabilitation robots (ULRRs) are connected to patients at one distal point, making them have simple structures and less ...
Electronic skins have attracted significant research interest in the biomedical engineering field including wearable devices, artificial prostheses, s...
The number of older people needing healthcare is a growing global phenomenon. The assistance in long-term care comprises a complex of medical, nursing...
Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based rehabilitation through human-in-the-loop control to ta...
The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems of insufficient physiological information and uns...
A stroke is a common disease that can easily lead to lower limb motor dysfunction in the elderly. Stroke survivors can effectively train muscle streng...
This study proposed a control method, a data-driven predictive control (DDPC), for the hand exoskeleton used for active, passive, and resistive rehabi...
BACKGROUND: Left ventricular (LV) volumes, ejection fraction (EF), and myocardial strain have been shown to be predictive of clinical and subclinical ...