A Biomimetic Approach Towards a Dexterous Neuroprosthesis

灵巧神经假体的仿生方法

• 批准号: 9792278
• 负责人: MICHAEL L. BONINGER
• 金额: $ 167.16万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9792278
• 关键词: Activities of Daily Living; Address; Algorithms; Basic Science; Biomimetics; Bypass; Cervical spinal cord injury; Chicago; Chronic; Common Data Element; Development; Devices; Electric Stimulation; Employment Opportunities; Ensure; Esthesia; Eye; Feedback; Fingers; Freedom; Frequencies; Goals; Hand; Hand functions; Human; Hybrids; Institutes; Intuition; Kinetics; Learning; Limb Prosthesis; Limb structure; Longevity; Manuals; Methods; Mind; Motor; Motor Cortex; Movement; Muscle; Neurons; Output; Participant; Pattern; Performance; Persons; Positioning Attribute; Prosthesis; Quadriplegia; Robotics; Scheme; Sensorimotor functions; Sensory; Signal Transduction; Somatosensory Cortex; Spinal cord injury; Tactile; Task Performances; Testing; Tissues; Touch sensation; United States National Institutes of Health; Universities; Work; Wrist; arm; arm function; arm movement; base; brain computer interface; care costs; clinical translation; cost; design; dexterity; experience; grasp; improved; injured; kinematics; limb movement; microstimulation; microsystems; mind control; neuronal patterning; neuroprosthesis; neurotechnology; novel; prosthesis control; prosthetic hand; relating to nervous system; restoration; robot control; sensor; sensory feedback; somatosensory; spatiotemporal; success; synergism

PROJECT SUMMARY Cervical spinal cord injury results in the loss of arm and hand function, which significantly limits independence and results in costs over the person’s lifespan. A brain-computer interface (BCI) can be used to bypass the injured tissue to enable control of a robotic arm and to provide somatosensory feedback. Two primary limitations of current state-of-the-art BCIs for arm and hand control are: (1) the inability to control the forces exerted by the prosthetic hand and (2) the lack of somatosensory feedback from the hand. In the proposed study, we seek to considerably improve dexterous control of prosthetic limbs by implementing decoding strategies that enable the user to not only control the movements of the arm and hand, but also the forces transmitted through the hand. We anticipate that our biomimetic approach to decoding will yield intuitive, dexterous control of the prosthetic hand. Tactile sensations will be conveyed to the user through intracortical microstimulation (ICMS) of somatosensory cortex. The spatiotemporal patterns of stimulation will be based on our basic scientific understanding of how tactile information is encoded in somatosensory cortex, which we expect will result in more natural and intuitive sensations. In order to achieve our goal of developing a dexterous neuroprosthesis, we have brought together a team with human BCI experience from the University of Pittsburgh along with the basic science expertise at both Pitt and the University of Chicago. We will collaborate with experts in implantable neurotechnology (Blackrock Microsystems) and robotics (The Biorobotics Institute) to ensure that the device hardware allows us to take a biomimetic approach for control and feedback with an eye toward clinical translation. A total of 4 participants will be tested in a multisite study to accomplish the following three specific aims. Aim 1: Evoke natural and intuitive tactile sensations through ICMS of somatosensory cortex. We expect that biomimetic ICMS will evoke sensations that more closely resemble everyday tactile sensations and intuitively convey information about contacted objects than does standard fixed-frequency ICMS. Aim 2: Derive kinematic and kinetic signals from motor cortex for hand control. We will assess the degree to which motor cortical neurons encode forces exerted on objects. Based on these observations, we will develop hybrid decoders that enable controlling both the movement and force using a synergy-based approach. Aim 3: Demonstrate improved arm and hand function with a biomimetic sensorimotor BCI that combines the sensory feedback developed in Aim 1 with the hybrid decoding developed in Aim 2. A battery of functional assessments will be used including novel metrics designed specifically for sensorimotor prosthetics along with well-established tests identified in the NIH Common Data Elements. We anticipate that subjects will substantially improve their dexterity using a biomimetic BCI as compared to non-biomimetic BCIs or BCIs without somatosensory feedback.

项目概要 颈脊髓损伤导致手臂和手功能丧失，严重限制独立性 并导致人的一生的成本，可以使用脑机接口（BCI）来绕过。 受伤的组织来控制机械臂并提供体感反馈有两个主要限制。 当前用于手臂和手控制的最先进的脑机接口有：（1）无法控制由手臂和手部施加的力 假肢手和（2）缺乏来自手的体感反馈在拟议的研究中，我们寻求 通过实施解码策略，显着提高假肢的灵巧控制 用户不仅可以控制手臂和手的运动，还可以控制通过手传递的力。 我们预计我们的仿生解码方法将产生对假肢的直观、灵巧的控制 触觉将通过皮质内微刺激（ICMS）传递给用户。 体感皮层的刺激时空模式将基于我们的基本科学。 了解触觉信息如何在体感皮层中编码，我们预计这将带来更多 为了实现开发灵巧的神经假体的目标，我们有自然和直观的感觉。 汇集了来自匹兹堡大学的具有人类 BCI 经验和基础知识的团队 我们将与皮特大学和芝加哥大学的科学专家合作。 神经技术（Blackrock Microsystems）和机器人技术（The Biorobotics Institute）确保该设备 硬件使我们能够采用仿生方法进行控制和反馈，着眼于临床转化。 共有 4 名参与者将在多地点研究中进行测试，以实现以下三个具体目标 1： 通过体感皮层的 ICMS 唤起自然直观的触觉，我们期待仿生。 ICMS 将唤起更接近日常触觉的感觉并直观地传达 目标 2：导出运动学和 来自运动皮层的运动信号用于手部控制我们将评估运动皮层神经元的程度。 基于这些观察，我们将开发混合解码器，以实现对施加在物体上的力的编码。 使用基于协同的方法控制运动和力量 目标 3：展示改进的手臂。 以及具有仿生感觉运动 BCI 的手部功能，该 BCI 结合了目标 1 中开发的感觉反馈 与目标 2 中开发的混合解码一起使用。将使用一系列功能评估，包括新颖的 专为感觉运动假肢设计的指标以及 NIH 确定的成熟测试 通用数据元素。我们预计受试者使用仿生技术将大大提高他们的灵活性。 BCI 与非仿生 BCI 或无体感反馈的 BCI 相比。