Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligen...Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.展开更多
Bipolar disorder presents significant challenges in clinical management, characterized by recurrent episodes of depression and mania often accompanied by impairment in functioning. This study investigates the efficacy...Bipolar disorder presents significant challenges in clinical management, characterized by recurrent episodes of depression and mania often accompanied by impairment in functioning. This study investigates the efficacy of pharmacological interventions and rehabilitation strategies to improve patient outcomes and quality of life. Utilizing a randomized controlled trial with multiple treatment arms, participants will receive pharmacotherapy, polypharmacotherapy, rehabilitation interventions, or combination treatments. Outcome measures will be assessed using standardized scales, including the Hamilton Depression Scale, Yale-Brown Obsessive Compulsive Scale (Y-BOCS), and Mania Scale. Preliminary data suggest improvements in symptom severity and functional outcomes with combination treatments. This research aims to inform clinical practice, guide treatment decisions, and ultimately enhance the quality of care for individuals living with bipolar disorder. Findings will be disseminated through peer-reviewed journals and scientific conferences to advance knowledge in this field.展开更多
In view of the uncertainty and complexity,the intelligent model of rehabilitation training program for stroke was proposed,combining with the case-based reasoning(CBR) and interval type-2 fuzzy reasoning(IT2FR).The mo...In view of the uncertainty and complexity,the intelligent model of rehabilitation training program for stroke was proposed,combining with the case-based reasoning(CBR) and interval type-2 fuzzy reasoning(IT2FR).The model consists of two parts:the setting model based on CBR and the feedback compensation model based on IT2FR.The former presets the value of rehabilitation training program,and the latter carries on the feedback compensation of the preset value.Experimental results show that the average percentage error of two rehabilitation training programs is 0.074%.The two programs are made by the intelligent model and rehabilitation physician.That is,the two different programs are nearly identical.It means that the intelligent model can make a rehabilitation training program effectively and improve the rehabilitation efficiency.展开更多
Artificial intelligence(AI)and machine learning(ML)are powerful technologies with the potential to revolutionize motor recovery in rehabilitation medicine.This perspective explores how AI and ML are harnessed to asses...Artificial intelligence(AI)and machine learning(ML)are powerful technologies with the potential to revolutionize motor recovery in rehabilitation medicine.This perspective explores how AI and ML are harnessed to assess,diagnose,and design personalized treatment plans for patients with motor impairments.The integration of wearable sensors,virtual reality,augmented reality,and robotic devices allows for precise movement analysis and adaptive neurorehabilitation approaches.Moreover,AI-driven telerehabilitation enables remote monitoring and consultation.Although these applications show promise,healthcare professionals must interpret AI-generated insights and ensure patient safety.While AI and ML are in their early stages,ongoing research will determine their effectiveness in rehabilitation medicine.展开更多
目的:分析近十年国内外智能可穿戴运动康复系统在康复医学领域的研究热点及趋势。方法:采用CiteSpace软件对2014年10月—2023年10月中国知网及Web of Science(WoS)数据库中关于智能可穿戴运动康复系统在康复医学领域的研究进行可视化分...目的:分析近十年国内外智能可穿戴运动康复系统在康复医学领域的研究热点及趋势。方法:采用CiteSpace软件对2014年10月—2023年10月中国知网及Web of Science(WoS)数据库中关于智能可穿戴运动康复系统在康复医学领域的研究进行可视化分析,主要分析内容包括发文量、作者、机构、共被引、研究热点等,同时绘制相应的知识图谱。结果:共纳入中文文献527篇(年均53篇),10个中文关键词:聚类和18个突现词,其Q值为0.5527,S值为0.8561;共纳入英文文献633篇(年均63篇),8个中文关键词:聚类和18个突现词,其Q值为0.3824,S值为0.7096。结论:智能可穿戴运动康复系统可运用人工智能技术增强康复效果,并结合人机交互和虚拟现实,提高临床治疗效率。未来可视化、一体化、数字化、个体化和家庭化的智能运动康复系统是我国在智能可穿戴运动康复系统的重要研究方向和发展趋势。展开更多
文摘Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.
文摘Bipolar disorder presents significant challenges in clinical management, characterized by recurrent episodes of depression and mania often accompanied by impairment in functioning. This study investigates the efficacy of pharmacological interventions and rehabilitation strategies to improve patient outcomes and quality of life. Utilizing a randomized controlled trial with multiple treatment arms, participants will receive pharmacotherapy, polypharmacotherapy, rehabilitation interventions, or combination treatments. Outcome measures will be assessed using standardized scales, including the Hamilton Depression Scale, Yale-Brown Obsessive Compulsive Scale (Y-BOCS), and Mania Scale. Preliminary data suggest improvements in symptom severity and functional outcomes with combination treatments. This research aims to inform clinical practice, guide treatment decisions, and ultimately enhance the quality of care for individuals living with bipolar disorder. Findings will be disseminated through peer-reviewed journals and scientific conferences to advance knowledge in this field.
基金Project(2010020176-301)supported by Liaoning Science and Technology Program,ChinaProject(F10-2D5-1-57)supported by Shenyang Municipal Fund,China
文摘In view of the uncertainty and complexity,the intelligent model of rehabilitation training program for stroke was proposed,combining with the case-based reasoning(CBR) and interval type-2 fuzzy reasoning(IT2FR).The model consists of two parts:the setting model based on CBR and the feedback compensation model based on IT2FR.The former presets the value of rehabilitation training program,and the latter carries on the feedback compensation of the preset value.Experimental results show that the average percentage error of two rehabilitation training programs is 0.074%.The two programs are made by the intelligent model and rehabilitation physician.That is,the two different programs are nearly identical.It means that the intelligent model can make a rehabilitation training program effectively and improve the rehabilitation efficiency.
文摘Artificial intelligence(AI)and machine learning(ML)are powerful technologies with the potential to revolutionize motor recovery in rehabilitation medicine.This perspective explores how AI and ML are harnessed to assess,diagnose,and design personalized treatment plans for patients with motor impairments.The integration of wearable sensors,virtual reality,augmented reality,and robotic devices allows for precise movement analysis and adaptive neurorehabilitation approaches.Moreover,AI-driven telerehabilitation enables remote monitoring and consultation.Although these applications show promise,healthcare professionals must interpret AI-generated insights and ensure patient safety.While AI and ML are in their early stages,ongoing research will determine their effectiveness in rehabilitation medicine.
文摘目的:分析近十年国内外智能可穿戴运动康复系统在康复医学领域的研究热点及趋势。方法:采用CiteSpace软件对2014年10月—2023年10月中国知网及Web of Science(WoS)数据库中关于智能可穿戴运动康复系统在康复医学领域的研究进行可视化分析,主要分析内容包括发文量、作者、机构、共被引、研究热点等,同时绘制相应的知识图谱。结果:共纳入中文文献527篇(年均53篇),10个中文关键词:聚类和18个突现词,其Q值为0.5527,S值为0.8561;共纳入英文文献633篇(年均63篇),8个中文关键词:聚类和18个突现词,其Q值为0.3824,S值为0.7096。结论:智能可穿戴运动康复系统可运用人工智能技术增强康复效果,并结合人机交互和虚拟现实,提高临床治疗效率。未来可视化、一体化、数字化、个体化和家庭化的智能运动康复系统是我国在智能可穿戴运动康复系统的重要研究方向和发展趋势。
