چکیده مقاله
In recent decades, neurorehabilitation, a key area in biomedical engineering, has increasingly focused on helping people with movement disorders recover lost functions However, the capabilities of artificial intelligence AI have paved the way for new advances in enhancing these treatments This paper reviews the current status of artificial intelligence based neurorehabilitation techniques, emphasizing the roles of machine learning ML , deep learning DL , Functional Electrical Stimulation FES methods, assistive robots, and biofeedback systems Additionally, artificial intelligence techniques, including electromyography EMG and electroencephalography EEG data processing, human motion monitoring, and adaptive robotic support, have shown considerable promise in optimizing and personalizing therapeutic interventions Despite these advances, important challenges remain, such as ensuring data integrity, improving the generalizability of AI models, addressing ethical issues, and effectively integrating AI technologies into clinical practice Overcoming these barriers is critical to implementing AI innovations in clinical settings This study also explores potential research avenues aimed at addressing these challenges and further increasing the impact of AI in neurorehabilitation
کلیدواژهها
نویسندگان
شیوه ارجاع
Zendehbad, Seyyed Ali and Kobravi, Hamidreza and Salmani Bajestani, Shahryar,1403,Exploring the Impact of Artificial Intelligence on Advancing Neurorehabilitation Techniques: A Comprehensive Survey in Biomedical Engineering,The 3th international conference on artificial intelligence and its future prospects in electrical, computer, mechanical and telecommunication engineering sciences.,Mashhad
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مجموعه مقالات سومین کنفرانس بین المللی هوش مصنوعی و چشم انداز آینده آن در علوم مهندسی برق ، کامپیوتر ، مکانیک و مخابرات29 شهریور 1403 · مشهد