Similarity measures based recommender system for rehabilitation of people with disabilities

Abstract

This paper proposes a recommender system to predict and suggest a set of rehabilitation methods for patients with spinal cord injuries (SCI). The proposed system automates, stores and monitors the heath conditions of SCI patients. The International Classification of Functioning, Disability and Health classification (ICF) is used to stores and monitors the progress in health status. A set of similarity measures are utilized in order to get the similarity between patients and predict the rehabilitation recommendations. Experimental results showed that the proposed recommender system has obtained an accuracy of 98 % via implementing the cosine similarity measure.