A dexterous soft hand exoskeleton restores intentional grasping in individuals with severe hand impairment

IF 29.8 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
John Nassour, Nicolas Berberich, Daniel Utpadel-Fischler, Tobias Wächter, Gordon Cheng
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Abstract

Soft hand exoskeletons have emerged as promising assistive devices for individuals with impaired hand function. However, most existing systems provide limited dexterity and primarily target users with moderate hand ability, leaving individuals with severe hand paralysis without effective solutions for reliable grasping of diverse objects. Here we report the translational development of a lightweight, textile-based soft robotic exoskeleton glove with wrist dorsiflexion and an active opposable and abductable thumb, designed to restore hand function in a patient with severe right-hand impairment due to amyotrophic lateral sclerosis. We followed a co-creation approach, enhancing dexterity by increasing hand articulations based on patient needs. Furthermore, to enhance the patient’s sense of control, a non-invasive surface electromyography-based grasp predictor (97% sensitivity) was combined with motion data and machine learning-based error correction to compensate for weak, noisy muscle signals, compared with healthy controls (n = 15). The exoskeleton enabled the patient to grasp objects, achieve a Box-and-Blocks Test score of 5 and perform meaningful tasks, including feeding himself. We further validated the exoskeleton in patients with stroke (n = 6). While exoskeleton assistance on average reduced Action Research Arm Test scores of moderately impaired patients by 9, severely impaired patients scored 17 points higher when using the exoskeleton. These results indicate that the dexterous soft hand exoskeleton is particularly effective for individuals with severe to near-complete hand paralysis, while its utility for patients with moderate residual function is limited and task dependent. Nassour, Berberich and colleagues present a soft robotic hand exoskeleton that restores grasping ability in individuals with severe hand paralysis, enabling meaningful tasks such as feeding. A lightweight textile glove with wrist dorsiflexion and an active opposable thumb increases hand articulations to enable more dexterous grasping.

Abstract Image

一个灵巧柔软的手外骨骼恢复有意抓取的个人严重手损伤
软手外骨骼已成为有前途的辅助装置,为个人的手功能受损。然而,大多数现有系统提供的灵活性有限,主要针对的是手部能力中等的用户,这使得手部严重瘫痪的个人没有有效的解决方案来可靠地抓取各种物体。在这里,我们报道了一种轻量的、基于纺织品的柔软机器人外骨骼手套的转化开发,该手套具有手腕背屈和主动对生可展拇指,旨在恢复因肌萎缩性侧索硬化症导致的严重右手损伤患者的手部功能。我们遵循共同创造的方法,根据患者的需要通过增加手部关节来提高灵活性。此外,为了增强患者的控制感,与健康对照组(n = 15)相比,将基于无创表面肌电图的抓握预测器(97%灵敏度)与运动数据和基于机器学习的纠错相结合,以补偿微弱、有噪声的肌肉信号。外骨骼使患者能够抓住物体,在Box-and-Blocks测试中获得5分,并执行有意义的任务,包括自己喂食。我们进一步在中风患者中验证了外骨骼(n = 6)。虽然外骨骼辅助平均使中度受损患者的行动研究臂测试分数降低了9分,但严重受损患者在使用外骨骼时得分提高了17分。这些结果表明,灵巧柔软的手外骨骼对严重到近乎完全的手部瘫痪的个体特别有效,而对中度残障患者的效用有限且依赖于任务。
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来源期刊
CiteScore
36.90
自引率
2.10%
发文量
127
期刊介绍: Nature Machine Intelligence is a distinguished publication that presents original research and reviews on various topics in machine learning, robotics, and AI. Our focus extends beyond these fields, exploring their profound impact on other scientific disciplines, as well as societal and industrial aspects. We recognize limitless possibilities wherein machine intelligence can augment human capabilities and knowledge in domains like scientific exploration, healthcare, medical diagnostics, and the creation of safe and sustainable cities, transportation, and agriculture. Simultaneously, we acknowledge the emergence of ethical, social, and legal concerns due to the rapid pace of advancements. To foster interdisciplinary discussions on these far-reaching implications, Nature Machine Intelligence serves as a platform for dialogue facilitated through Comments, News Features, News & Views articles, and Correspondence. Our goal is to encourage a comprehensive examination of these subjects. Similar to all Nature-branded journals, Nature Machine Intelligence operates under the guidance of a team of skilled editors. We adhere to a fair and rigorous peer-review process, ensuring high standards of copy-editing and production, swift publication, and editorial independence.
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