The advantages of artificial intelligence-based gait assessment in detecting, predicting, and managing Parkinson's disease

Abstract

Background: Parkinson's disease is a neurological disorder that can cause gait disturbance, leading to mobility issues and falls. Early diagnosis and prediction of freeze episodes are essential for mitigating symptoms and monitoring the disease.

Objective: This review aims to evaluate the use of artificial intelligence (AI)-based gait evaluation in diagnosing and managing Parkinson's disease, and to explore the potential benefits of this technology for clinical decision-making and treatment support.

Methods: A thorough review of published literature was conducted to identify studies, articles, and research related to AI-based gait evaluation in Parkinson's disease.

Results: AI-based gait evaluation has shown promise in preventing freeze episodes, improving diagnosis, and increasing motor independence in patients with Parkinson's disease. Its advantages include higher diagnostic accuracy, continuous monitoring, and personalized therapeutic interventions.

Conclusion: AI-based gait evaluation systems hold great promise for managing Parkinson's disease and improving patient outcomes. They offer the potential to transform clinical decision-making and inform personalized therapies, but further research is needed to determine their effectiveness and refine their use.

Keywords: Parkinson’s disease (PD); artificial intelligence; freezing of gait; machine learning; motor evaluation.