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PFI-RP: Intelligent Robot with Hologram-enhanced Virtual Reality for Effective Body Rehabilitation

PFI-RP: Intelligent Robot with Hologram-enhanced Virtual Reality for Effective Body Rehabilitation
PFI-RP:具有全息增强虚拟现实功能的智能机器人,可实现有效的身体康复
批准号:
1918534
负责人:
Fei Hu
金额:
$54.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-01 至 2024-07-31

项目摘要

项目成果

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中文摘要
翻译
该PFI项目更广泛的影响/商业潜力是通过开发具有自适应上躯干支持和基于全息图的虚拟现实训练场景的智能康复机器人,使数百万需要有效身体康复的中风后患者和其他残疾人受益。现有的商业康复产品不能有效地支持严重躯干残疾患者的上肢,也没有智能、精细分辨率的机器人控制来训练不同损伤程度的两条腿。在线康复培训不需要经常亲自去物理治疗师(PT)的办公室,可以降低医疗成本。这个以商业化为导向的项目将满足这些市场需求。它还将开发和实施名为“8C + 5F”的新客户渠道模式,由8个不同类型客户的沟通渠道组成,并提供该平台的5个技术层面。为了加强学术界与工业界的合作关系,该团队提出了一种称为nexus organization (NEO)的有效模式,以实现大学与工业界之间的跨学科、无冲突的合作。为了培养未来的创新和创业领袖,该团队提出了一种新的教育模式,称为创新和市场导向的复兴铸造(IMRF),以培养具有强大创业和创新技能的博士生和博士后研究人员。提出的项目旨在建立一个全息智能康复机器人技术来训练中风后患者。它有3个面向市场的新设计:i)(带有三维连杆和弹性阻抗控制的上肢外骨骼):将为机器人系统开发一种紧凑、轻便、经济的上肢外骨骼,以改善康复过程中上肢的稳定性控制。ii)(步态内周期各阶段的智能平台控制,解决双腿损伤不对称问题):目前的跑步机控制只是根据用户的速度或测量的压力中心改变跑步机在每个步态周期中的速度/力。然而,许多患者在他/她的两条腿之间的损伤程度不同。该PFI将使用低成本的热/声传感器和基于深度学习的3D腿部轨迹分析来实现细粒度的四阶段康复机器人控制。iii)(基于全息远程医疗的自参与混合现实康复环境):该团队将把之前开发的基于虚拟现实(VR)的设计扩展到基于全息的混合现实(MR)平台,该平台具有先进的远程医疗功能,可用于虚拟患者对pt或患者对患者的共同康复培训。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The broader impact/commercial potential of this PFI project is to benefit millions of post-stroke patients and other disabled people who need effective body rehabilitation, by developing an intelligent rehabilitation robot with adaptive upper trunk support and hologram-based virtual reality training scenes. The existing commercial rehabilitation products cannot efficiently support the upper torso of the patients with serious trunk disability, and do not have intelligent, fine-resolution robot control to train two legs with different impairment levels. An online rehabilitation training without frequent in-person visits to the office of the physical therapist (PT) would reduce the medical cost. This commercialization-oriented project will address those market needs. It will also develop and implement a new customer channel model called "8C + 5F", consisting of 8 communication channels with different types of customers and offering 5 technical facets of this platform. To enhance the academia-industry partnership, the team proposes an effective model called nexus organization (NEO), to achieve transdisciplinary, conflict-free collaborations between the university and the industry. To train future leaders in innovation and entrepreneurship, the team proposes a new education model called Innovation and Marketing-oriented Renaissance Foundry (IMRF) to prepare PhD students and postdoctoral researchers with strong entrepreneurship and innovation skills.The proposed project aims to build a Holographic intelligent Rehabilitation robotic technology to train post-stroke patients. It has 3 marketing-oriented new designs: i) (Upper trunk exoskeleton with 3D linkage and elastic impedance control): A compact, light-weight and economic upper trunk exoskeleton will be developed for a robot system to improve the upper trunk stability control during rehabilitation. ii) (Intelligent platform control in each phase of intra-gait cycle to handle two-leg impairment asymmetry): Current treadmill control simply changes the speed/force of the treadmill in each gait cycle based on the user's speed or measured center of pressure. However, many patients have different impairment levels between his/her two legs. This PFI will use low-cost thermal/acoustic sensors with deep-learning-based 3D leg trajectory analysis to achieve fine-granularity 4-phase rehabilitation robot control. iii) (Self-engaging mixed reality rehabilitation environment based on holographic telemedicine): The team will extend their previously developed virtual reality (VR)-based design to a hologram-based mixed reality (MR) platform with the advanced telemedicine functions for virtual patient-to-PT or patient-to-patient co-rehab training.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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