| The Artificial intelligence (AI) Revolution in Diagnosing, Managing, and Rating the Severity of Parkinson's Disease: A Narrative Review |
| Paper ID : 1072-ISCSR3 (R2) |
| Authors |
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Shams Ahmed Abdo *1, Nada Khaled Said1, Renad Mohamed Bader1, Mohab Walid Saleh1, Mohand Kamal El-Said2, Yehia Ahmed Mohamed2, Seif Ahmed Ramadan2, Engy Abdalal Esmail2, Mohamed Hossam Mohamed2 1Helwan National University Faculty of physical therapy 2Helwan National University Faculty of physical therapy |
| Abstract |
| Background Parkinson’s disease (PD) is a neurodegenerative motor and non-motor disorder that severely impacts mobility and quality of life. Traditional pharmacological and surgical treatments don’t always fully address the broad array of symptoms. New developments in AI and machine learning are opening up new possibilities for PD diagnosis, monitoring, and individualized treatment—such as AI-assisted physical rehabilitation. Objective This review covers the AI uses in PD diagnosis, disease severity assessment, and treatment planning, highlighting its use in physiotherapy sessions. It addresses the AI-based technologies usage, such as video analysis and adaptive deep brain stimulation (aDBS), to enhance personalized rehabilitation methods. Methods An enyclopedic search of Google Scholar, Science Direct, PubMed, Mpdi, and PhysioPedia Articles published from 2017 to 2024 were included in the research. Research papers, analyzed studies of the AI revolution in diagnosing and managing PD using Finger-Tapping, Wearble sensors, aDPS , and machine learning studies were reviewed. Other Language articles, studies not agreed on by experts, and unpublished manuscripts were excluded. Results More than 27 studies were included after a review process of AI quantitation of webcam videos of finger tapping accurately quantified PD severity at a mean absolute error (MAE) of 0.58 points, which outweighed ratings by non-experts (0.83 MAE) and rivaled those by neurologists (0.53 MAE). ADBS is treated to produce persistent stable clinical benefits, increased control over motor symptoms, improved quality of life, and no side effects. Beta-band brain activity did not alter. The evidence used is based on a case study report ,and a case series. Conclusion These findings are indicative of exciting innovations in PD treatment. Webcam-finger tapping allows for accurate remote monitoring, and aDBS offers adaptive, individualized therapy according to physiotherapy goals—a big advance in PD therapy. Keywords Artificial intelligence, Parkinson’s Disease, visual Stimulation, and detecting sensors |
| Keywords |
| Artificial intelligence, Parkinson’s Disease, Visual Stimulation, Detecting sensors, Analysis. |
| Status: Abstract Accepted |