Machine Learning in Rehabilitation Sciences

Owing to the advancement of computational technology as well as the ubiquitous nature of sensor technology, the employment of artificial intelligence, particularly machine learning and its associative architectures (deep learning, reinforcement learning, amongst others) in facilitating the act of rehabilitation is non-trivial. The employment of such a technique is increasingly used to develop personalised treatment plans for patients, as well as to improve the accuracy of diagnoses and prognoses. Consequently, this does not only improve the effectiveness of treatment, but also allows for more efficient and cost-effective care.

This Research Topic is dedicated to cater for any form of contribution or advances concerning the utilisation of machine learning to the broader domain of rehabilitation sciences.

We welcome original articles, briefs/short communications as well as systematic literature reviews, of the following (but not limited to):

Precision Medicine/Rehabilitation

Rehabilitation Intervention

Functional Recovery Prediction

Injury Risk Assessment

Smart Health Monitoring System

Assistive Technology

Rehabilitation Psychology

Speech-language Pathology