Towards Transforming Neurorehabilitation: The Impact of Artificial Intelligence on Diagnosis and Treatment of Neurological Disorders

This systematic review examines how AI and ML systems influence diagnosis and treatment in neurorehabilitation among neurological disorders. Recent advancements in AI and ML are revolutionizing motor rehabilitation and diagnosis for conditions like stroke, SCI, and PD, offering new opportunities for personalized care and improved outcomes. AI helps to enhance the precision of diagnostic tools and develop more personalized treatment approaches, shaping a new era of care for people with these conditions. These technologies enable early detection and quite accurate disease progression monitoring, with adaptive rehabilitation protocols that grow with the patient’s recovery for optimal short- and long-term outcomes. AI and ML are making neurorehabilitation even more accessible by becoming part of telerehabilitation platforms. This advance enables constant monitoring and personalized treatment, even for patients residing in remote locations. AI-powered systems may provide instant feedback during therapy sessions, that is, by changing exercises and guidance that do not require a therapist to be on-site.

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  AI-based devices, including those with EMG-based robotic hands, have demonstrated significant improvements in upper limb motor function with a reduction of spasticity in stroke patients, reporting long-lasting results.
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  Gait analysis in PD is improved by the application of ML models for greater accuracy, while functional recovery in stroke and SCI is driven forward more effectively with prediction.
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  The analysis of complex kinematic data allows for a more precise classification of the degree of disability in stroke cases. Moreover, all these technologies improved diagnostic accuracy and personalized rehabilitation strategies and enabled remote monitoring.