Advanced technologies in rehabilitation programs: Role of AI in diagnosis-an updated review

Abstract

Background: Cognitive decline, particularly associated with aging and neurodegenerative disorders, significantly affects individuals' ability to perform daily activities. Cognitive Rehabilitation Therapy (CRT) offers a non-pharmacological intervention that focuses on regaining or compensating for lost cognitive functions. The integration of Artificial Intelligence (AI) into rehabilitation programs has shown transformative potential in enhancing diagnosis, personalized care, and improving outcomes for patients with cognitive impairments. Aim: This updated review explores the role of AI in personalized rehabilitation programs, particularly focusing on diagnosis and Cognitive Rehabilitation Therapy (CRT) and assistive technologies. The aim is to assess how AI technologies, including machine learning (ML) and reinforcement learning (RL), can be leveraged to personalize cognitive rehabilitation interventions and improve patient outcomes. Methods: The review synthesizes studies on AI-driven rehabilitation interventions, including personalized rehabilitation applications, virtual reality-based treatments, and assistive robotic technologies. It examines the efficacy of reinforcement learning and AI-powered platforms in creating adaptive, personalized rehabilitation environments. The review also explores applications for diverse neurological conditions such as dementia, multiple sclerosis (MS), and autism spectrum disorder (ASD). Results: The review identifies several AI-driven interventions, such as personalized apps for dementia and MS, virtual reality treatments for cognitive impairments, and social robots that aid memory training.