Robotic Stroke Rehabilitation Using Perceptual Feedback

使用感知反馈的机器人中风康复

• 批准号: 7031314
• 负责人: YOKY MATSUOKA
• 金额: $ 15.73万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-19 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7031314
• 关键词: artificial intelligence; biomechanics; biomedical equipment development; clinical research; computer human interaction; computer simulation; fingers; functional ability; human subject; human therapy evaluation; longitudinal human study; medical rehabilitation related tag; motion perception; patient oriented research; perceptual distortions; quality of life; rehabilitation; robotics; sensory feedback; sensory thresholds; stroke therapy

DESCRIPTION (provided by applicant): Due to advances in modern medicine, the elderly population is growing worldwide, and, along with this growth, there is a growing need for physical rehabilitation after strokes, which have an average onset of over 65 years of age. Given the magnitude of this problem and its societal ramifications, the time is ripe to explore the extent to which robotic devices and virtual environments can be used as a means of rehabilitation to improve the quality of life for both the elderly and the physically disabled. According to recent studies in robotics, robot-assisted stroke rehabilitation enhances arm movement recovery. Moreover, robot-assisted rehabilitation improves patients' mobility and strength to the point where it is equal to, or greater than, that which is achieved by human-assisted therapy. However, none of the currently available systems addresses patients' perceptual or cognitive deficits. Furthermore, these systems neglect to address the fact that many patients do not reach their full mobility potential using these systems. To remedy these problems, a virtual robotic environment that explores the full potential needs and abilities of patients must be developed. We will coin this strategy, "rehabilitation by distortion." To develop an environment to rehabilitate by distortion, however, there are two fundamental issues to address. First, it is necessary to quantify the perceptual gap that can be created between virtual and actual movements that is not perceptible to patients. To do so, we will first quantify the lowest sensory resolution, also known as just noticeable difference (JND), of force and position. As we explain below, the JND will act as the lowest bound of the perceptual gap. In addition, we will quantify the size of the perceptual gap with the existence of visual feedback distortion. Second, having identified a perceptual gap that is not noticeable, we must prove that mobility and strength of stroke patients can be extended by undetected distortion. For this proposed work, we will isolate working with one finger. Fingers are one of the parts of the body that are most commonly affected by strokes; thus testing the basic concepts about the perceptual gap between virtual and actual movements using fingers is appropriate. After we prove that rehabilitation by distortion is therapeutic for a finger, we can expand our work to other limbs. In addition, to show that this strategy is effective for patients who already received traditional therapy, we will work with patients who have already completed their traditional therapy and are at least one year after the onset of strokes. If we prove that we can allow patients to move beyond what they thought was possible after traditional therapeutic techniques, the results will be groundbreaking and will lead to an R01 grant to develop a new robotic virtual therapeutic strategy, "rehabilitation by distortion," that extends the force production and range of motion for motor impaired patients recovering from stroke.

描述（由申请人提供）：由于现代医学的进步，全世界的老年人口正在增长，随着这种增长，中风后对身体康复的需求越来越大，平均年龄超过65岁。鉴于这个问题的幅度及其社会后果，探索机器人设备和虚拟环境的程度已经成熟了，可以用作改善老年人和身体残疾的生活质量的一种康复手段。根据机器人技术的最新研究，机器人辅助中风康复可增强手臂运动的恢复。此外，机器人辅助康复可以提高患者的活动能力和力量，以使其等于或大于通过人类辅助治疗实现的程度。但是，当前可用的系统都没有解决患者的感知或认知缺陷。此外，这些系统忽略了这样一个事实，即许多患者没有使用这些系统发挥其全部流动潜力。为了解决这些问题，必须开发一个虚拟机器人环境，以探索患者的全部潜在需求和能力。我们将在这种策略中“造成扭曲的康复”。但是，要开发一个通过扭曲来恢复的环境，但是有两个基本问题要解决。首先，有必要量化可以在患者无法察觉的虚拟运动和实际运动之间产生的感知差距。为此，我们将首先量化力和位置的最低感觉分辨率（也称为JND）。正如我们在下面解释的那样，JND将充当感知差距的最低界限。此外，我们将使用视觉反馈失真的存在来量化感知差距的大小。其次，在确定了一个不明显的感知差距后，我们必须证明中风患者的活动能力和强度可以通过未发现的失真来扩展。对于这项建议的工作，我们将隔离一根手指。手指是最常见的中风影响的身体部分之一。因此，测试有关使用手指虚拟运动和实际运动之间感知差距的基本概念是合适的。在证明扭曲的康复对手指的治疗是治疗的，我们可以将工作扩展到其他四肢。此外，为了证明该策略对于已经接受了传统疗法的患者有效，我们将与已经完成传统疗法并且中风发作至少一年的患者合作。如果我们证明我们可以允许患者在传统的治疗技术之后超越他们认为的可能性，那么结果将是开创性的，并将导致R01赠款，以制定新的机器人虚拟治疗策略，“通过失真进行修复”，扩大了从Stroke中恢复的运动障碍患者的力量和运动范围。