PFI-RP: Brain-controlled Upper-Limb Robot-Assisted Rehabilitation Device for Stroke Survivors.

PFI-RP：用于中风幸存者的脑控上肢机器人辅助康复装置。

• 批准号: 1827769
• 负责人: Jose Contreras-Vidal
• 金额: $ 75万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1827769&HistoricalAwards=false
• 关键词: PFI; RP; Brain; controlled; Upper

The broader impact/commercial potential of this PFI project is to advance the national health by accelerating the development, efficacy and use of brain-controlled robotic rehabilitation after stroke by capitalizing on the benefits of non-invasive brain interfaces that extract information about the patient?s motor intent and the real-time assessment of impairment and recovery of motor function. Stroke is the leading cause of neurological disability in the United States with approximately 795,000 people suffering a stroke each year. Arm paresis is a primary cause of disability because of the limitations it creates in performing activities of daily living (ADL). Approximately 80% of all stroke survivors suffer from upper limb paresis and only 18% of these individuals gain full motor recovery with conventional treatments in the year following stroke. Thus, rehabilitation of the impaired limb is essential for improving ADLs and quality of life after stroke, yet only 31% of stroke survivors receive outpatient rehabilitation. Brain-controlled robotic devices are excellent candidates for engaging the patients and delivering the repetitive and intensive practice stroke survivors require for rehabilitation. Our innovative robotic rehabilitation solution will offer increased efficiency, lower expenses, and new sensing capabilities to the therapist while reducing the socioeconomic burden of disability. The proposed project addresses a pressing need for accessible, safe and effective stroke rehabilitation devices for in-clinic and at-home use for sustainable long-term therapy, a global market size expected to reach $31B by 2021. Unfortunately, current devices fail to engage the patients, are hard to match to their needs, are costly to use and maintain, or are limited to clinical settings. Our patient-in-the-loop system solution consists of our patented noninvasive brain-robot technology that translates the user's brain activity into motor commands to drive powered, assist-as-needed, upper-limb robotics for stroke rehabilitation. Feedback of performance will be provided to both the patient and the clinician, and stored for monitoring and diagnostics, through a user interface that also serves to provide engaging real-time feedback of task and associated completion performance. System validation will occur in a clinical setting and at home. The Intellectual Merits include addressing the challenges of fault-tolerant system integration, low-cost device prototyping, usability, shared-control, acquiring validation data, and accelerating the translation to the patient for a new class of biomedical devices. The deliverable is an accessible, safe and effective brain-controlled therapeutical robot system that is multi-functional with real-time self-monitoring, self-diagnostics and self-correcting capabilities, and that promotes neurorecovery of function.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.

这个PFI项目的更广泛的影响/商业潜力是通过利用提取患者信息的非侵入性大脑接口的好处，加速中风后脑控机器人康复的开发、功效和使用，来促进国民健康。的运动意图和运动功能的损伤和恢复的实时评估。中风是美国神经系统残疾的主要原因，每年约有795，000人患有中风。手臂轻瘫是残疾的主要原因，因为它在进行日常生活活动（ADL）时造成限制。大约80%的中风幸存者患有上肢轻瘫，这些人中只有18%的人在中风后的一年内通过常规治疗获得完全运动恢复。因此，受损肢体的康复对于改善卒中后的ADL和生活质量至关重要，但只有31%的卒中幸存者接受门诊康复治疗。脑控机器人设备是吸引患者并提供中风幸存者康复所需的重复和密集练习的绝佳候选人。我们创新的机器人康复解决方案将为治疗师提供更高的效率，更低的成本和新的传感能力，同时减少残疾的社会经济负担。拟议的项目解决了对可访问，安全和有效的中风康复设备的迫切需求，用于诊所和家庭可持续的长期治疗，预计到2021年全球市场规模将达到310亿美元。不幸的是，目前的设备无法吸引患者，难以匹配他们的需求，使用和维护成本高，或者仅限于临床环境。我们的患者在环系统解决方案由我们的专利非侵入性脑机器人技术组成，该技术将用户的大脑活动转化为运动指令，以驱动动力、按需辅助的上肢机器人，用于中风康复。将通过用户界面向患者和临床医生提供性能反馈，并存储用于监测和诊断，该用户界面还用于提供任务和相关完成性能的实时反馈。系统确认将在临床环境和家中进行。其智力优势包括解决容错系统集成、低成本设备原型设计、可用性、共享控制、获取验证数据以及加速将新型生物医学设备转化为患者的挑战。该交付成果是一个可访问的、安全有效的脑控治疗机器人系统，具有实时自我监测、自我诊断和自我纠正功能，并促进神经功能恢复。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Characterization and real-time removal of motion artifacts from EEG signals

• DOI: 10.1088/1741-2552/ab2b61
• 发表时间: 2019-10-01
• 期刊: JOURNAL OF NEURAL ENGINEERING
• 影响因子: 4
• 作者: Kilicarslan, Atilla;Vidal, Jose Luis Contreras
• 通讯作者: Vidal, Jose Luis Contreras

A Novel Headset System Synchronizing Vision and EEG testing for a Rapid Assessment and Diagnosis of Concussions and Other Brain Injuries

一种同步视觉和脑电图测试的新型耳机系统，用于快速评估和诊断脑震荡和其他脑损伤

• DOI: 10.54941/ahfe1002125
• 发表时间: 2022
• 期刊: AHFE International
• 作者: Edquilang, David;Feng, Jeff
• 通讯作者: Feng, Jeff

Optimization of Electrode Configuration for the Removal of Eye Artifacts with Adaptive Noise Cancellation

通过自适应噪声消除消除眼部伪影的电极配置优化

• 发表时间: 2023
• 期刊: and Cybernetics (SMC
• 作者: Gonzalez-Espana, Jose J.;Craik, Alexander;Ramirez, Carolina;Alamir, Ayman;and Contreras-Vidal, Jose
• 通讯作者: and Contreras-Vidal, Jose

Brain-eNet: Towards an Enabling Technology for BCI-IoT Systems

• DOI: 10.1109/smc53992.2023.10394117
• 发表时间: 2023-10
• 期刊: 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
• 作者: Juan José González-España;Lianne Sánchez Rodríguez;Alexander Craik;Sarah Wong;Jeff Feng;J. Contreras-Vidal

Design Principles for Mobile Brain-Body Imaging Devices with Optimized Ergonomics

具有优化人体工程学的移动脑体成像设备的设计原理

• DOI: 10.1007/978-3-030-80091-8_1
• 发表时间: 2021
• 期刊: Wearable and Assistive Technology
• 作者: Gorman, Niell;Louw, Antoinette;Craik, Alex;Gonzalez, Jose;Feng, Jeff;Contreras-Vidal, Jose L.
• 通讯作者: Contreras-Vidal, Jose L.