Coordination of human grasp and manipulation forces

人类抓握力和操纵力的协调

基本信息

批准号：
10593716
负责人：
MARCO SANTELLO
金额：
$ 20.07万
依托单位：
ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-02-06 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10593716
关键词：
Address Basic Science Carpal Tunnel Syndrome Clinical Clinical Assessment Tool Coupled Data Devices Digit structure Electromyography Exertion Feedback Focal Dystonias Foundations Funding Goals Hand Human Impairment Injury Intervention Joints Knowledge Laboratories Lifting Mathematics Memory Muscle Nerve compression syndrome Nervous System Trauma Patients Performance Peripheral Nervous System Diseases Positioning Attribute Prevention Property Recovery of Function Rehabilitation device Research Resistance Robotics Role Self-Help Devices Sensorimotor functions Spinal cord injury Stimulus Surface Tactile Testing Time Torque Translating Translations Traumatic injury United States National Institutes of Health Work clinical application clinical translation cost design dexterity experience grasp hand rehabilitation high reward high risk improved insight median nerve neglect nervous system disorder neuromuscular system novel novel strategies preservation prevent sensorimotor control mechanism sensory feedback sensory integration tool

项目摘要

PROJECT SUMMARY The hand’s sophisticated neuromuscular system enables us to interact with the world in a myriad of ways, one of which is dexterous manipulation. The hand’s incredible versatility, however, comes at a cost: when peripheral neuropathies, neurological disorders or traumatic injury occur, our ability to improve sensorimotor function is severely challenged by our limited understanding of the hand’s sensorimotor control mechanisms. Therefore, improving our understanding of these mechanisms could enhance the impact of clinical intervention. This notion has driven extensive research over the past four decades aiming at unravelling how the hand’s sensorimotor control mechanisms operate. Previous research has provided significant insights into the coordination of digit forces required to prevent object slip. Surprisingly, however, this previous work neglected to address another important component of manipulation: the ability to control object position and orientation, i.e., pose. This is a critical gap because dexterous manipulation often requires both object slip prevention and dexterous control of object pose. To address this gap, in the past decade our laboratory has developed an experimental paradigm that allows subjects to choose where to grasp the object and contains a dexterity component, i.e., lifting an object straight while preventing it from tilting. Nevertheless, the major limitation of this work is that the modulation of load and grip forces cannot be decoupled to identify their relative contribution to object slip prevention and pose control. To fill this gap, we propose an approach that will allow us, for the first time, to identify the control mechanisms underlying grasp and manipulation. Our approach combines a task with a dexterity component, surface electromyography of digit muscles, and a novel application of digit force analysis developed for robotic manipulation. Our task requires subjects to coordinate digit forces to simultaneously prevent object slip and minimize object tilt. Our analysis can mathematically decouple digit forces into grasp force (object slip prevention) and manipulation force (object pose control). We will pursue two aims: (1) To determine the causal relation between grasp and manipulation forces, and (2) To quantify the effect of predictability of object properties on the coordination between grasp and manipulation forces. If successful, this new knowledge will enable clinicians to extract information about the state of the hand’s sensorimotor function that cannot otherwise be extracted by clinical assessment tools. Our long-term objective is to improve the theoretical constructs of dexterous manipulation control and their translation to clinical applications, including tools for quantifying recovery of hand function following clinical intervention, as well as design of assistive and/or rehabilitation devices.

项目概要手复杂的神经肌肉系统使我们能够以多种方式与世界互动，然而，其中之一是灵巧的操作，手的多功能性是有代价的：什么时候。发生周围神经病变、神经系统疾病或创伤性损伤时，我们改善感觉运动的能力由于我们对手部感觉运动控制机制的了解有限，功能受到了严重挑战。因此，提高我们对这些机制的理解可以增强临床干预的影响。在过去的四十年里，这一概念推动了广泛的研究，旨在揭示手是如何工作的。先前的研究对感觉运动控制机制的运作提供了重要的见解。然而，令人惊讶的是，之前的工作忽略了防止物体滑动所需的手指力量的协调。解决操纵的另一个重要组成部分：控制物体位置和方向的能力，即姿势，这是一个关键的差距，因为灵巧的操作通常需要防止物体滑动和为了解决这一差距，在过去的十年中，我们的实验室开发了一种允许受试者选择在哪里抓住物体并包含灵巧性的实验范式组件，即笔直举起物体同时防止其倾斜。然而，它的主要局限性是。这项工作是负载和抓力的调制不能解耦以确定它们的相对贡献为了填补这一空白，我们提出了一种方法，使我们能够第一次，确定掌握和操纵背后的控制机制。具有灵活性的任务、手指肌肉的表面肌电图以及数字的新颖应用我们的任务要求受试者协调数字力以进行机器人操作。同时防止物体滑动并最大限度地减少物体倾斜我们的分析可以在数学上解耦数字。我们将追求两种力：抓握力（防止物体滑动）和操纵力（物体姿势控制）。目标：（1）确定抓握力和操纵力之间的因果关系，以及（2）量化物体属性的可预测性对抓握力和操纵力之间协调的影响。如果成功的话，这种新知识将使上级能够提取有关手部状态的信息我们的长期目标无法通过其他方式提取感觉运动功能。旨在改进灵巧操作控制的理论构建及其临床转化应用程序，包括量化临床干预后手部功能恢复的工具，以及辅助和/或康复设备的设计。