Patient-centered rehabilitation and dexterous assistive devices for stroke patients using bionic exoskeletons controlled by non-invasive electromyography

项目概要/摘要 中风是全球残疾的主要原因之一，最常见的中风相关损害是 上肢轻偏瘫，影响80%的中风患者急性和40%的慢性。完全恢复不太可能 因此，中风降低了生活质量，增加了医疗费用， 给看护者带来负担这个项目的长期目标是利用辅助仿生设备来恢复 运动功能和促进长期神经再生，最终取代更昂贵，更少 有效的康复方法，以患者为中心的康复策略。本提案的目的 是控制辅助仿生外骨骼并通过肌电（EMG）记录量化中风恢复 麻痹手臂的残余肌肉活动。我们的中心假设是， 矫形器--帮助个人进行日常生活活动--可用作患者特定的康复工具 可以促进中风恢复目标1将适应上肢矫形器的灵巧肌电控制算法， 然后证明中风患者的手部灵活性和功能性活动性得到改善。目标2将利用大型EMG 随着时间的推移，数据集，以精确量化肌肉力量和痉挛在整个恢复过程中的变化， 通过深度学习为辅助设备提供强大的长期控制。目标3包括一项试点研究， 确定患者特定辅助设备驱动康复的可行性。拟议的研究是 创新，因为它将解决对合并辅助和康复设备至关重要的知识差距。 这些发现意义重大，因为它们将使设备能够立即同时 促进使用，加强肌肉，并提供闭环视觉反馈-从而合并多个 将有效的康复策略整合为单一的整体方法。这一建议将产生积极影响， 通过提高康复依从性，促进独立性和改善康复结果， 中风患者，最终降低医疗成本，提高患者的生活质量。

PROJECT SUMMARY / ABSTRACT Stroke is one of the leading causes of disability worldwide and the most common stroke-related impairment is upper-limb hemiparesis, affecting 80% of stroke patients acutely and 40% chronically. Full recovery is unlikely with current rehabilitation approaches, and as a result, stroke reduces quality of life, increases healthcare costs, and burdens caregivers. The long-term goal of this project is to leverage assistive bionic devices to restore motor function and promote long-term neuro-regeneration, ultimately replacing more expensive and less effective rehabilitation approaches with a patient-centered rehabilitation strategy. The objective of this proposal is to control assistive bionic exoskeletons and quantify stroke recovery with electromyographic (EMG) recordings of residual muscle activity from the paretic arm. Our central hypothesis is that an EMG-controlled powered orthosis – that assists individuals in activities of daily living – can be used as a patient-specific rehabilitative tool that improves stroke recovery. Aim 1 will adapt dexterous EMG-control algorithms for upper-limb orthoses, and then demonstrate improved hand dexterity and functional mobility for stroke patients. Aim 2 will utilize large EMG datasets over time to precisely quantify changes in muscle strength and spasticity throughout recovery and to provide robust long-term control of assistive devices via deep learning. Aim 3 consists of a pilot study to determine the feasibility of patient-specific assistive-device-driven rehabilitation. The proposed research is innovative because it will address gaps in knowledge critical to merging assistive and rehabilitative devices. These findings are significant because they will enable devices that can immediately and simultaneously promote usage, strengthen muscles, and provide closed-loop visual feedback – thereby merging multiple effective rehabilitation strategies into a single holistic approach. This proposal will have a positive impact on society by increasing rehabilitation compliance, promoting independence and improving recovery outcomes for stroke patients, ultimately reducing healthcare costs and improving patients’ quality of life.