Latest AI and machine learning research in sports medicine for healthcare professionals.
Passive and active exoskeletons have been used over recent decades. However, regarding many physiological systems, we see that the majority explore both active and passive elements to minimize energy consumption while retaining proper motion control. In light of this, we propose a design that combines compliant mechanisms as passive support for gravity balancing of the hand's weight and soft actua...
This paper presents our approach to predicting future error-related events in a robot-mediated gamified physical training activity for stroke patients. The ability to predict future error under such conditions suggests the existence of distinguishable features and separated class characteristics between the casual gameplay state and error prune state in the data. Identifying such features provides...
Robotic-based rehabilitation administered by means of serious games certainly represents the frontier of rehabilitation treatments, offering a high de...
Early rehabilitation is beneficial for stroke patients, but it is often delayed since the patients are often bedbound due to their general condition. ...
Joint attention is the capacity of sharing attention between two agents and an aspect of the environment, through the use of different cues, namely ga...
Currently, therapists struggle with interaction of rehabilitation robots due to non-intuitive interfaces. Therefore their acceptance of these robots a...
There is a growing need to deliver rehabilitation care to patients remotely. Long term demographic changes, geographic shortages of care providers, an...
In order to promote early rehabilitation, we proposed a system which provides full-body arm-leg training for patients in a bed-lying position. As the ...
Robotic assistance systems offer new therapeutic perspectives for patient mobilization. This work aims to investigate the chances and risks of robotic...
Patients with deep burns are prone to suffer cicatrix hyperplasia or contracture, leading to problems including dysfunction in limbs, which impacts pa...
Can you imagine to receive treatment through a robot? When talking about the future of healthcare, this is the vision many people have. Currently, the...
This study aims to explore the clinical efficacy of arthroscopic-assisted reduction combined with robot-navigated nail placement in the treatment of t...
The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because...
OBJECTIVES: To apply the convolutional neural network (CNN) Inception_v3 model in automatic identification of acceleration and deceleration injury bas...
Spatiotemporal gait parameters provide important information for the rehabilitation of patients with gait dysfunction. These parameters are often obta...
This study reviews the recent progress of machine learning for the early diagnosis of thyroid disease. Based on the results of this review, different ...
Recent research using machine learning and data mining to determine predictors of prolonged opioid use after arthroscopic surgery showed that Artifici...
Aiming at the problems of individual differences in the asynchrony process of human lower limbs and random changes in stride during walking, this pape...
To investigate the feasibility and the clinical efficiency of robot navigation combined with wrist arthroscopy in minimally invasive treatment of nond...
Based on the biomechanical mechanism of human upper limb, the disadvantages of traditional rehabilitation training and the current status of upper lim...