REST: Reconfigurable lower limb Exoskeleton for effective Stroke Treatment in residential settings

REST:可重构下肢外骨骼,可在住宅环境中有效治疗中风

基本信息

  • 批准号:
    EP/S019219/1
  • 负责人:
  • 金额:
    $ 135.76万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2019
  • 资助国家:
    英国
  • 起止时间:
    2019 至 无数据
  • 项目状态:
    已结题

项目摘要

According to the UK Guidelines for stroke rehabilitation, the national standard for stroke rehabilitation is at least 45 minutes per day of each relevant therapy for a minimum of 5 days per week to people who have the ability to participate. However, this standard has never been met due to the decreasing availability of rehabilitation services and increasing pressures on the NHS. In the UK, over 600,000 people with stroke live further than 20km from a stroke support group, the majority of whom live with severe mobility issues. It would be very challenging and costly, or even impossible for them to travel and receive rehabilitation treatments regularly in hospitals or rehabilitation centres. The NHS Five Year Forward View therefore made recommendations in 2017 to bring rehabilitation to people in their own homes and care homes.People with stroke commonly experience post-stroke movement disorders, particularly weakness, disordered movement patterns, including post-stroke dystonia and spasticity. The majority of stroke patients are disabled and dependent on their family members or others for some or all of their daily living activities.Leveraging our previous success in robotic exoskeletons, our ambition is to deliver innovative rehabilitation through exoskeletons that are modular and reconfigurable to meet individual needs, and have the required intelligence to monitor recovery, personalise treatments and deliver effective rehabilitation in patients' own homes. We will pursue this goal by: 1) introducing new soft muscles and novel reconfigurable robotic mechanisms for the lower limb exoskeletons, enabling them for home rehabilitation use and easy to manufacture, maintain and repair; 2) developing standardised exercise programmes, with innovative disability assessment methods and intelligent personalised treatment strategies. The intelligent lower limb exoskeleton controller will learn the patients' recovery status and continually update the rehabilitation strategy to meet the patients' changing needs and deliver the best possible outcome. Personalised treatment methods will be investigated to enable adaptive rehabilitation training for patients in their own homes; 3) evaluating the functionality, acceptability, robustness, reliability and sustainability of the robotic exoskeletons, initially in laboratory settings, and then in the Leeds Teaching Hospital rehabilitation service and residential settings; and 4) assembling the required pre-clinical documentation to initiate future clinical trials.Our long-term goal is to develop a nationwide robot-assisted home-based rehabilitation programme, which builds upon the technology and the experimental evidence originated from this proposal. Our project partners Devices for Dignity (D4D), Steeper Group, DIH/Hocoma, AiTreat and the National Demonstration Centre for Rehabilitation at Leeds Teaching Hospital NHS Trust will provide adequate links and resources for this project. This project will establish a transferable technology for stroke survivors' rehabilitation at home, with a potential impact on millions of people in the UK and worldwide.
根据英国中风康复指南,中风康复的国家标准是每周至少5天,每天至少45分钟的每种相关治疗,有能力参与的人。然而,由于康复服务的可用性不断下降,国民保健服务的压力越来越大,这一标准从未达到。在英国,超过60万中风患者居住在距离中风支持小组20公里以外的地方,其中大多数人都有严重的行动不便问题。他们要经常前往医院或康复中心接受康复治疗,是非常困难和昂贵的,甚至不可能。因此,NHS五年前瞻性观点在2017年提出建议,让人们在自己的家中和护理院进行康复。中风患者通常会经历中风后运动障碍,特别是虚弱,运动模式紊乱,包括中风后肌张力障碍和痉挛。大多数中风患者都是残疾人,部分或全部日常生活活动都依赖家人或其他人。利用我们之前在机器人外骨骼方面的成功,我们的目标是通过模块化和可重新配置的外骨骼提供创新的康复服务,以满足个人需求,并具有所需的智能来监控恢复,个性化治疗,并在患者家中提供有效的康复服务。我们将通过以下方式实现这一目标:1)为下肢外骨骼引入新的软肌肉和新型可重新配置的机器人机制,使其能够用于家庭康复,易于制造,维护和维修; 2)开发标准化的运动计划,采用创新的残疾评估方法和智能个性化治疗策略。智能下肢外骨骼控制器将了解患者的康复状态,并不断更新康复策略,以满足患者不断变化的需求,并提供最佳的康复效果。将研究个性化的治疗方法,以使患者能够在自己的家中进行适应性康复训练; 3)评估机器人外骨骼的功能性、可接受性、鲁棒性、可靠性和可持续性,最初在实验室环境中,然后在利兹教学医院康复服务和住宅环境中;以及4)收集所需的临床前文件,以启动未来的临床试验。我们的长期目标是开发一个全国性的机器人辅助家庭康复计划,其建立在源自该提议的技术和实验证据的基础上。我们的项目合作伙伴尊严设备(D4 D),陡峭集团,DIH/Hocoma,AiTreat和利兹教学医院NHS信托的国家康复示范中心将为该项目提供足够的链接和资源。该项目将为中风幸存者的家庭康复建立一种可转移的技术,对英国和全球数百万人产生潜在影响。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Automatic detection and classification of peri-prosthetic femur fracture.
A deep Kalman filter network for hand kinematics estimation using sEMG
  • DOI:
    10.1016/j.patrec.2021.01.001
  • 发表时间:
    2021-01-21
  • 期刊:
  • 影响因子:
    5.1
  • 作者:
    Bao, Tianzhe;Zhao, Yihui;Zhang, Zhiqiang
  • 通讯作者:
    Zhang, Zhiqiang
CNN Confidence Estimation for Rejection-Based Hand Gesture Classification in Myoelectric Control
  • DOI:
    10.1109/thms.2021.3123186
  • 发表时间:
    2021-11-15
  • 期刊:
  • 影响因子:
    3.6
  • 作者:
    Bao, Tianzhe;Zaidi, Syed Ali Raza;Zhang, Zhi-Qiang
  • 通讯作者:
    Zhang, Zhi-Qiang
LSTM-AE for Domain Shift Quantification in Cross-Day Upper-Limb Motion Estimation Using Surface Electromyography
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Shane Xie其他文献

Intelligent Manufacturing in Digital Manufacturing Science
数字制造科学中的智能制造
  • DOI:
    10.1007/978-0-85729-564-4_5
  • 发表时间:
    2011
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zude Zhou;Shane Xie;Dejun Chen
  • 通讯作者:
    Dejun Chen
Fundamentals of Digital Manufacturing Science
数字制造科学基础
  • DOI:
  • 发表时间:
    2011
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zude Zhou;Shane Xie;Dejun Chen
  • 通讯作者:
    Dejun Chen

Shane Xie的其他文献

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