迈向机器人辅助微监督手部治疗平台:设计与试点可用性评估

Venkata dinesh Reddy kalli
{"title":"迈向机器人辅助微监督手部治疗平台:设计与试点可用性评估","authors":"Venkata dinesh Reddy kalli","doi":"10.60087/jaigs.v4i1.137","DOIUrl":null,"url":null,"abstract":"Background \n  \nRobot-assisted therapy has the potential to enhance therapy doses post-stroke, addressing the often insufficient treatment of hand function in clinical settings and after discharge. Traditionally, these systems have been complex and required therapist supervision. To better leverage robot-assisted therapy, we propose a platform designed for minimal therapist supervision and present a preliminary evaluation of its immediate usability, addressing a key challenge often neglected in real-world applications. This approach could increase therapy doses by enabling a single therapist to train multiple patients simultaneously, as well as supporting independent training in clinics or at home. \n  \n Methods \n  \nWe implemented design changes on a hand rehabilitation robot, focusing on enabling minimally-supervised therapy. This involved developing new physical and graphical user interfaces and creating two functional therapy exercises aimed at training hand motor coordination, somatosensation, and memory. Ten participants with chronic stroke evaluated the platform's usability and reported their perceived workload during a minimally-supervised therapy session. The ability to use the platform independently was assessed using a checklist. \n  \nResults \n  \nAfter a brief familiarization period, participants were able to independently perform the therapy session, needing assistance in only 13.46% (range: 7.69–19.23%) of the tasks. They rated the user interface and exercises highly on the System Usability Scale, with scores of 85.00 (75.63–86.88) and 73.75 (63.13–83.75) out of 100, respectively. Nine participants indicated they would use the platform frequently. The perceived workload was within acceptable ranges. The most challenging tasks identified were object grasping with simultaneous control of forearm pronosupination and stiffness discrimination. \n  \nDiscussion \n  \nOur findings indicate that a robot-assisted therapy device can be safely and intuitively used with minimal supervision upon first exposure by adhering to usability and workload requirements. The preliminary usability evaluation highlighted specific challenges that need to be addressed to enable real-world minimally-supervised use. This platform could complement conventional therapy, providing increased therapy doses with existing resources and establishing a continuum of care that transitions from the clinic to the home.","PeriodicalId":517201,"journal":{"name":"Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023","volume":"39 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards a Platform for Robot-Assisted Minimally Supervised Hand Therapy: Design and Pilot Usability Evaluation\",\"authors\":\"Venkata dinesh Reddy kalli\",\"doi\":\"10.60087/jaigs.v4i1.137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background \\n  \\nRobot-assisted therapy has the potential to enhance therapy doses post-stroke, addressing the often insufficient treatment of hand function in clinical settings and after discharge. Traditionally, these systems have been complex and required therapist supervision. To better leverage robot-assisted therapy, we propose a platform designed for minimal therapist supervision and present a preliminary evaluation of its immediate usability, addressing a key challenge often neglected in real-world applications. This approach could increase therapy doses by enabling a single therapist to train multiple patients simultaneously, as well as supporting independent training in clinics or at home. \\n  \\n Methods \\n  \\nWe implemented design changes on a hand rehabilitation robot, focusing on enabling minimally-supervised therapy. This involved developing new physical and graphical user interfaces and creating two functional therapy exercises aimed at training hand motor coordination, somatosensation, and memory. Ten participants with chronic stroke evaluated the platform's usability and reported their perceived workload during a minimally-supervised therapy session. The ability to use the platform independently was assessed using a checklist. \\n  \\nResults \\n  \\nAfter a brief familiarization period, participants were able to independently perform the therapy session, needing assistance in only 13.46% (range: 7.69–19.23%) of the tasks. They rated the user interface and exercises highly on the System Usability Scale, with scores of 85.00 (75.63–86.88) and 73.75 (63.13–83.75) out of 100, respectively. Nine participants indicated they would use the platform frequently. The perceived workload was within acceptable ranges. The most challenging tasks identified were object grasping with simultaneous control of forearm pronosupination and stiffness discrimination. \\n  \\nDiscussion \\n  \\nOur findings indicate that a robot-assisted therapy device can be safely and intuitively used with minimal supervision upon first exposure by adhering to usability and workload requirements. The preliminary usability evaluation highlighted specific challenges that need to be addressed to enable real-world minimally-supervised use. This platform could complement conventional therapy, providing increased therapy doses with existing resources and establishing a continuum of care that transitions from the clinic to the home.\",\"PeriodicalId\":517201,\"journal\":{\"name\":\"Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023\",\"volume\":\"39 13\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.60087/jaigs.v4i1.137\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.60087/jaigs.v4i1.137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

背景 机器人辅助治疗有可能提高中风后的治疗剂量,解决临床环境和出院后手部功能治疗不足的问题。传统上,这些系统比较复杂,需要治疗师的监督。为了更好地利用机器人辅助治疗,我们提出了一种只需最少治疗师监督的平台,并对其即时可用性进行了初步评估,以解决实际应用中经常被忽视的关键挑战。这种方法能让一名治疗师同时训练多名患者,并支持在诊所或家中进行独立训练,从而提高治疗剂量。 方法 我们对手部康复机器人进行了设计变更,重点是实现最小监督治疗。这包括开发新的物理和图形用户界面,以及创建两个旨在训练手部运动协调、躯体感觉和记忆的功能性治疗练习。十名慢性中风患者对平台的可用性进行了评估,并报告了他们在最小监督治疗过程中感知到的工作量。独立使用平台的能力则通过核对表进行评估。 结果 经过短暂的熟悉后,参与者能够独立完成治疗过程,仅有 13.46%(范围:7.69-19.23%)的任务需要协助。他们在系统可用性量表中对用户界面和练习给予了很高的评价,满分分别为 85.00(75.63-86.88)和 73.75(63.13-83.75)。九名参与者表示会经常使用该平台。感知工作量在可接受范围内。最具挑战性的任务是抓取物体,同时控制前臂前伸和硬度辨别。 讨论 我们的研究结果表明,通过遵守可用性和工作量要求,机器人辅助治疗设备在首次接触时只需最少的监护就能安全、直观地使用。初步可用性评估强调了在现实世界中实现最小监督使用所面临的具体挑战。该平台可作为传统疗法的补充,利用现有资源增加治疗剂量,建立从诊所到家庭的连续护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Towards a Platform for Robot-Assisted Minimally Supervised Hand Therapy: Design and Pilot Usability Evaluation
Background   Robot-assisted therapy has the potential to enhance therapy doses post-stroke, addressing the often insufficient treatment of hand function in clinical settings and after discharge. Traditionally, these systems have been complex and required therapist supervision. To better leverage robot-assisted therapy, we propose a platform designed for minimal therapist supervision and present a preliminary evaluation of its immediate usability, addressing a key challenge often neglected in real-world applications. This approach could increase therapy doses by enabling a single therapist to train multiple patients simultaneously, as well as supporting independent training in clinics or at home.    Methods   We implemented design changes on a hand rehabilitation robot, focusing on enabling minimally-supervised therapy. This involved developing new physical and graphical user interfaces and creating two functional therapy exercises aimed at training hand motor coordination, somatosensation, and memory. Ten participants with chronic stroke evaluated the platform's usability and reported their perceived workload during a minimally-supervised therapy session. The ability to use the platform independently was assessed using a checklist.   Results   After a brief familiarization period, participants were able to independently perform the therapy session, needing assistance in only 13.46% (range: 7.69–19.23%) of the tasks. They rated the user interface and exercises highly on the System Usability Scale, with scores of 85.00 (75.63–86.88) and 73.75 (63.13–83.75) out of 100, respectively. Nine participants indicated they would use the platform frequently. The perceived workload was within acceptable ranges. The most challenging tasks identified were object grasping with simultaneous control of forearm pronosupination and stiffness discrimination.   Discussion   Our findings indicate that a robot-assisted therapy device can be safely and intuitively used with minimal supervision upon first exposure by adhering to usability and workload requirements. The preliminary usability evaluation highlighted specific challenges that need to be addressed to enable real-world minimally-supervised use. This platform could complement conventional therapy, providing increased therapy doses with existing resources and establishing a continuum of care that transitions from the clinic to the home.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
LLM-Cloud Complete: Leveraging Cloud Computing for Efficient Large Language Model-based Code Completion Utilizing the Internet of Things (IoT), Artificial Intelligence, Machine Learning, and Vehicle Telematics for Sustainable Growth in Small and Medium Firms (SMEs) Role of Artificial Intelligence and Big Data in Sustainable Entrepreneurship Impact of AI on Education: Innovative Tools and Trends Critique of Modern Feminism
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1