In view of the key role of undergraduate experimental teaching reform in cultivating high-quality talents with both innovative spirit and practical ability,this paper deeply discusses multi-dimensional reform strategi...In view of the key role of undergraduate experimental teaching reform in cultivating high-quality talents with both innovative spirit and practical ability,this paper deeply discusses multi-dimensional reform strategies.Specifically,the teaching mode of"double teachers for every student"is innovatively introduced,and scientific research projects are deeply integrated into undergraduate experimental teaching,aiming at realizing the modern development of teaching content and the diversified expansion of teaching methods.By designing and applying the undergraduate experimental teaching platform for intelligent limb rehabilitation training based on the concept of"medical-engineering interdisciplinary crossing",it not only builds a bridge for students to contact cutting-edge scientific research and strengthen practical skills,but also provides valuable ideas and practical models for the innovation of undergraduate experimental teaching.In the future,with the continuous optimization and upgrading of platform functions,it is expected to provide students with a richer and richer learning experience and comprehensively promote students'overall quality.展开更多
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
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
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
Degeneration of joint disease is one of the problems that threaten global public health.Currently,the therapies of the disease are mainly conservative but not very effective.To solve the problem,we need to find effect...Degeneration of joint disease is one of the problems that threaten global public health.Currently,the therapies of the disease are mainly conservative but not very effective.To solve the problem,we need to find effective,convenient and inexpensive therapies.With the rapid development of artificial intelligence,we innovatively propose to combine Traditional Chinese Medicine(TCM)with artificial intelligence to design a rehabilitation assessment system based on TCM Daoyin.Our system consists of four subsystems:the spine movement assessment system,the posture recognition and correction system,the background music recommendation system,and the physiological signal monitoring system.We incorporate several technologies such as keypoint detection,posture estimation,heart rate detection,and deriving respiration from electrocardiogram(ECG)signals.Finally,we integrate the four subsystems into a portable wireless device so that the rehabilitation equipment is well suited for home and community environment.The system can effectively alleviate the problem of an inadequate number of physicians and nurses.At the same time,it can promote our TCM culture as well.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析...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
康复治疗专业是一门注重理论联系实践的专业,在医学影像学这门课程中,实验课是学生掌握影像技能、初步学习如何解决临床实际问题的重要途径。康复治疗专业属于非影像专科,学生的影像基础知识相对薄弱,学生在有限的时间内需要掌握的专业...康复治疗专业是一门注重理论联系实践的专业,在医学影像学这门课程中,实验课是学生掌握影像技能、初步学习如何解决临床实际问题的重要途径。康复治疗专业属于非影像专科,学生的影像基础知识相对薄弱,学生在有限的时间内需要掌握的专业相关的影像知识内容较多,教师在教学过程中实施科学有效的教学方法对教学效果影响较大。在高等学校不断进行教育教学模式创新及改革的背景下,康复治疗专业的教育教学改革步伐也将逐步推进。文章试从基于慕课等互联网资源的线上教学、传统讲授式教学法(lecturebased learning,LBL)、以问题为基础的教学法(problembased learning,PBL)、案例教学法(case-based learning,CBL)、基于医学影像存储与传输系统(picture archiving and communication system,PACS)病例库的多模态联合一体化教学、人工智能辅助教学等教学方式方法进行了探讨,为高校培养影像诊断思维缜密、理论知识扎实、实践能力强、综合素质高的康复治疗师人才提供参考。展开更多
基金Supported by Undergraduate Teaching Research and Reform Project of University of Shanghai for Science and Technology in 2024(JGXM24281)University-Level First-Class Undergraduate Course Construction Project of University of Shanghai for Science and Technology in 2024(YLKC202424394).
文摘In view of the key role of undergraduate experimental teaching reform in cultivating high-quality talents with both innovative spirit and practical ability,this paper deeply discusses multi-dimensional reform strategies.Specifically,the teaching mode of"double teachers for every student"is innovatively introduced,and scientific research projects are deeply integrated into undergraduate experimental teaching,aiming at realizing the modern development of teaching content and the diversified expansion of teaching methods.By designing and applying the undergraduate experimental teaching platform for intelligent limb rehabilitation training based on the concept of"medical-engineering interdisciplinary crossing",it not only builds a bridge for students to contact cutting-edge scientific research and strengthen practical skills,but also provides valuable ideas and practical models for the innovation of undergraduate experimental teaching.In the future,with the continuous optimization and upgrading of platform functions,it is expected to provide students with a richer and richer learning experience and comprehensively promote students'overall quality.
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.
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National Key R&D Program of China(No.2019YFC1711800,2020AAA0108300)National Natural Science Founda⁃tion of China(No.62072112)Fudan University-CIOMP Joint Fund(No.FC2019-005).
文摘Degeneration of joint disease is one of the problems that threaten global public health.Currently,the therapies of the disease are mainly conservative but not very effective.To solve the problem,we need to find effective,convenient and inexpensive therapies.With the rapid development of artificial intelligence,we innovatively propose to combine Traditional Chinese Medicine(TCM)with artificial intelligence to design a rehabilitation assessment system based on TCM Daoyin.Our system consists of four subsystems:the spine movement assessment system,the posture recognition and correction system,the background music recommendation system,and the physiological signal monitoring system.We incorporate several technologies such as keypoint detection,posture estimation,heart rate detection,and deriving respiration from electrocardiogram(ECG)signals.Finally,we integrate the four subsystems into a portable wireless device so that the rehabilitation equipment is well suited for home and community environment.The system can effectively alleviate the problem of an inadequate number of physicians and nurses.At the same time,it can promote our TCM culture as well.
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。
文摘康复治疗专业是一门注重理论联系实践的专业,在医学影像学这门课程中,实验课是学生掌握影像技能、初步学习如何解决临床实际问题的重要途径。康复治疗专业属于非影像专科,学生的影像基础知识相对薄弱,学生在有限的时间内需要掌握的专业相关的影像知识内容较多,教师在教学过程中实施科学有效的教学方法对教学效果影响较大。在高等学校不断进行教育教学模式创新及改革的背景下,康复治疗专业的教育教学改革步伐也将逐步推进。文章试从基于慕课等互联网资源的线上教学、传统讲授式教学法(lecturebased learning,LBL)、以问题为基础的教学法(problembased learning,PBL)、案例教学法(case-based learning,CBL)、基于医学影像存储与传输系统(picture archiving and communication system,PACS)病例库的多模态联合一体化教学、人工智能辅助教学等教学方式方法进行了探讨,为高校培养影像诊断思维缜密、理论知识扎实、实践能力强、综合素质高的康复治疗师人才提供参考。
