这项工作得到了国家自然科学基金U1913207资助和华中科技大学学术前沿青年团队项目的支持。作者要感谢这些基金会的支持。

该协议已获得华中科技大学同济医学院协和医院伦理审查委员会的批准。选择符合诊断标准并在提交人医院康复科门诊和住院部接受治疗的上肢功能障碍患者作为受试者。根据 Brunnstrom 恢复阶段21 评估患者的运动功能恢复情况，选择 3-5 阶段的患者参与实验。从参与研究的患者那里获得了书面知情同意书。该程序包括气动夹持器的模具设计、基于固化硅橡胶的气动夹持器的制造工艺、便携式设备的集成以及用于抓取意图检测的软硬件实现。除硅橡胶和普通织物外，所有可穿戴组件均采用3D打印技术生产（参见 补充编码文件1-5）。
1. 气动夹具的设计与制造
<ol><li>如图1A，B所示组装预先设计的模具22。然后使用热熔胶将玻璃纤维固定在模具中的指定位置，如图1C所示。确保使用热熔胶密封任何可能导致硅胶泄漏的潜在区域。</li>
	<li>称取适量的有机硅弹性体组分A和组分B（按重量计9：1）（见 材料表），按规定比例混合。混合后，使用具有可变离心力的真空混合脱气机，由机器的内部预设程序确定。混合物准备好后，立即将其注入组装好的模具中，如 图 1D 所示。 注意： 可变离心力由真空混合脱气机通过其内部预设程序控制（见 材料表）。离心力必须逐渐增加，以确保硅橡胶的彻底混合并去除任何滞留的气泡。</li>
	<li>让模具静置约 30 秒，然后将其放入真空干燥器中约 1 分钟，以使硅橡胶中的任何小气泡逸出。从干燥器中取出模具，将其整体置于30°C的恒温室中12小时，使硅橡胶固化。</li>
	<li>重复第二步中概述的步骤，将混合的硅橡胶注入 图1E所示的模具中。接下来，将 图1F 所示的脱模橡胶体放入填充硅橡胶的模具中。将整个组件置于30°C的恒温室中12小时，以使硅橡胶固化。</li>
	<li>从模具中取出固化的硅橡胶主体，并修剪掉多余的硅橡胶。柔性夹持器的制造现已完成。 注意： 腔体由两组相互独立的气动网格组成。由于玻璃纤维和波纹结构之间的弹性模量存在显着差异，气动夹持器在充气时会向内弯曲，从而可以进行包络抓取动作。指尖设计有类似象鼻的突起，可以进行指尖抓握动作。</li>
</ol>2. 可穿戴柔性编外机器人肢体的组装
注意：可穿戴的编外机器人肢体包括一个迷你气泵、空气阀、一个单芯片微机、气动夹持器、电源、柔性弯曲传感器、一个可穿戴手套以及用于气动和电气连接的附件（见 材料表），如 图 2 所示。
<ol><li>在裁缝的帮助下精心手工制作可穿戴手套。确保它根据佩戴者的反馈和裁缝的经验进行多次迭代和改进。</li>
	<li>用 3D 打印部件固定气动抓手，并使用胶带将其固定在手套上的适当位置。</li>
	<li>如图 3 所示，将三个柔性弯曲传感器（参见材料表）嵌入手套中。将它们分别放在食指、中指和无名指上，使它们与手指背面对齐。使用数据采集卡记录来自传感器的信号。</li>
	<li>放大传感器信号并将它们路由到Arduino（参见 材料表）。使用 Arduino23 中的滑动窗口和最小二乘滤波处理这些信号。利用这些估计值作为意图检测的基线数据。</li>
	<li>将气泵、空气阀、控制板和电源等组件放入背包中，便于携带。有关磨损效果的可视化表示，请参阅 图 4 。</li>
</ol>3. 检测抓取意图
注意： 当佩戴者的手指产生运动时，传感器反馈信号会相应变化。它的工作原理是随着组件弯曲得更多而增加电路中的电阻。 图 5 显示了一名志愿者手指运动期间柔性弯曲传感器记录的信号值。这三条曲线对应于从放置在三个手指上的传感器获得的信号。偏瘫患者的手指活动度通常有限，但传感器能够检测到显着变化。
<ol><li>收集有关手指移动期间传感器变化的范围和模式的数据。根据检测到的传感器振幅选择适当的阈值来控制泵的激活。指导参与者在他们的能力范围内自由移动手指。将阈值确定为传感器反馈的峰值和谷值的平均值。 注意： 当传感器信号超过设定的阈值时，泵开始运行。随着手指进一步弯曲，气压增加。相反，当手指的弯曲角度减小，并且传感器检测到低于阈值的信号时，空气阀将压力释放到零，气动夹持器释放。</li>
	<li>要求用户观察气动夹持器的状态，并确定停止充气和停止进一步手指弯曲的适当时间。</li>
	<li>重复上述测试以建立合理的阈值并熟悉使用此设备。</li>
</ol>4. 与健康志愿者一起测试设备
<ol><li>招募三名具有正常上肢运动能力的健康志愿者进行研究，以确认原型的磨损和抓握效果。</li>
	<li>将气动夹持器的最大气压设置为 100 kPa。指导参与者弯曲和伸展手指。让参与者戴上原型，并使用前面提到的方法对各种形状的物体进行抓取和释放实验。</li>
	<li>征求佩戴者对佩戴体验的反馈，并根据他们的建议调整佩戴方案。 注意：如 图 6 所示，参与者使用原型成功地包裹和抓取了不同尺寸的圆柱形物体。此外，他们还完成了对矩形块状物体的指尖抓取任务。</li>
</ol>5. 为患者提供康复和抓握协助
<ol><li>由医疗专业人员根据 Brunnstrom 恢复阶段21 评估患者的运动功能恢复情况。只允许第3-5阶段的患者参加实验进行康复训练或日常协助。</li>
	<li>招募六名慢性偏瘫患者来验证原型的可靠性和有效性。指导患者独立佩戴手套（不包括背包）并在其校准阈值的能力范围内移动手指。</li>
	<li>在康复阶段，鼓励患者进行各种抓握任务以锻炼手指肌肉。让患者坐在桌子边缘，使用原型进行一系列抓握活动，包括抓握水瓶、香蕉、立方体和牙刷。</li>
	<li>要求患者在实验后根据他们的个人经历填写相关的调查问卷（补充文件1）。评估以下六种主观感受：对系统功能的信心;易用性;佩戴的方便性和舒适性;康复的有效性和有用性;在日常生活中的有效性和有用性;仍需改进的领域。</li>
	<li>以 1 到 5 的等级对他们的回答进行评分，其中 1 代表非常不同意，5 代表非常同意。记录数据并根据调查问卷分析原型的问题和潜在的改进领域。 注意：这不仅增加了康复训练的兴趣，而且增强了患者参与康复过程的意愿。如果患者病情稳定，但仍难以用手指执行抓握任务，则使用机器人肢体可以帮助执行日常生活所需的某些日常抓握动作。</li>
</ol>

通过增强抓握和手指恢复来彻底改变中风康复

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作者没有什么可透露的。

本研究提出了一种创新、灵活、可穿戴的编外机器人肢体，旨在帮助慢性中风患者进行手指康复和抓握任务。该机器人系统优先考虑便携性，并提供信封抓握和指尖抓取功能。它集成了一个灵活的弯曲传感器，用于用户友好的人机交互控制。静态抓取实验验证了所设计机构在两种不同抓取模式下的抓取能力。该研究涉及对偏瘫患者的实验，以确认抓握功能并评估用户体验，展示该机器人在康复和?...

根据之前的研究1，截至2019年，全球有超过1亿例中风病例。这些病例中约有三分之二导致偏瘫后遗症，超过80%的严重偏瘫中风患者无法完全恢复手部和手臂功能2。此外，预计未来几十年人口老龄化将继续增长，导致潜在中风患者人数显着增加。卒中后持续的上肢损伤会显着影响日常生活活动 （ADL），手部康复已被临床公认为增强慢性卒中患者活动和参与的关键目标3。
传统的电机驱动的机器人上肢设备可以提供巨大的驱动力，但它们的刚性结构通常转化为大尺寸和高重量。此外，如果它们发生故障，它们可能会对人体造成不可逆转的伤害。相比之下，软气动执行器在康复4、辅助5 和外科应用6 中显示出相当大的潜力。它们的优点包括安全性、轻质结构和固有的合规性。
近年来，围绕软气动执行器出现、设计和开发了许多灵活的可穿戴机器人。这些机器人旨在为中风患者的上肢提供康复和康复后援助。它们主要包括手部外骨骼 7,8 和多余肢体 9,10。尽管两者都用于可穿戴机器人和康复领域，但前者直接与人体相互作用，可能限制肌肉或关节，而后者则补充人类的工作空间或运动，而没有直接约束11,12。开发了基于伺服电机的可穿戴编外机器人手指，以协助职业治疗师进行日常生活活动 （ADL） 培训9。在其他研究中也可以找到类似的方法10.这两类机械手指为此类机器人在偏瘫患者康复援助中的应用带来了新的可能性。尽管如此，值得注意的是，这些机器人设计中采用的刚性结构可能会引入有关用户舒适度和安全性的潜在考虑因素。介绍了软可穿戴机器人手套的设计、制造和评估13，可用于功能性磁共振成像 （fMRI） 期间的手部康复和特定任务训练。该手套利用由硅橡胶弹性体制成的软气动致动器来产生手指关节运动，并且该设备与 MR 兼容，不会在 fMRI 图像中造成伪影。Yun 等人介绍了 Exo-Glove PM，这是一种可定制的软气动辅助手套，采用基于组装的方法14。这种创新设计具有小模块和可调节的距离，允许用户使用垫片根据其指骨长度定制手套。这种方法最大限度地提高了舒适度和性能，而无需定制制造。研究人员展示了由弹性材料组成的软致动器，其集成通道可用作气动网络15。这些执行器产生的弯曲运动可以安全地符合人类手指的运动。此外，研究人员还推出了 AirExGlove，这是一种轻巧且适应性强的充气软外骨骼设备16。该系统具有成本效益，可针对不同的手部尺寸进行定制，并已成功适应不同程度肌肉痉挛的患者。与刚性连接机器人系统相比，它提供了更符合人体工程学和灵活的解决方案。虽然这些研究为柔性可穿戴手部康复和辅助机器人的发展做出了重大贡献，但值得注意的是，它们都没有实现完全的便携性和人机交互控制。
许多研究已经探索了生物信号（如脑电图 （EEG）17 或肌电图 （EMG） 信号18）与人类意图之间的相关性。然而，这两种方法在现有设备和技术条件的限制下都有一定的局限性。侵入性电极需要对人体进行外科手术，而非侵入性电极则存在高噪声水平和信号采集不可靠性等问题。关于这些局限性的详细讨论可以在文献19,20 中找到。因此，对柔性可穿戴编外机器人肢体的便携性和用户友好型人机交互能力的研究仍然具有高度相关性。
在这项研究中，设计并制造了一种独特的柔性可穿戴编外机器人肢体，以帮助慢性脑卒中患者进行手指康复和抓握辅助。这种机器人肢体的特点是重量轻、安全、合规、防水和令人印象深刻的输出重量/压力比。实现了两种抓取模式，即信封和指尖抓取，同时保持了便携性并确保了用户友好的人机交互。该协议详细介绍了气动夹持器的设计和制造过程以及可穿戴方案。此外，还提出了一种基于柔性弯曲传感器的人机交互方法，通过阈值分割实现方便和用户友好的控制。所有这些方面都已通过实际实验得到验证。
本研究的主要贡献总结如下：（1）设计并制造了一种轻量级、友好、可穿戴的慢性脑卒中患者柔性编外机器人肢体。（2）实现了基于柔性弯曲传感器的可靠人机交互方法。（3）进行了真实世界的实验，以验证所提出的机制和方法的有效性和可靠性，其中包括输出力测试，涉及6名慢性脑卒中患者。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Air Compressor</td>
			<td>Xinweicheng</td>
			<td>F35L-JJ-24V</td>
			<td>Provide air supply for the pneumatic gripper</td>
		</tr>
		<tr>
			<td>Arduino&#160;</td>
			<td>Emakefun</td>
			<td>Mega 2560</td>
			<td>Single-chip microcomputer/data acquisition card</td>
		</tr>
		<tr>
			<td>Backpack</td>
			<td>Mujin</td>
			<td></td>
			<td>Integrating external devices</td>
		</tr>
		<tr>
			<td>Flex Sensor</td>
			<td>Spectra Symbol</td>
			<td>Flex Sensor 2.2</td>
			<td>Flexible bending sensors</td>
		</tr>
		<tr>
			<td>Power supply</td>
			<td>Yisenneng</td>
			<td>YSN-37019200</td>
			<td>Provide power</td>
		</tr>
		<tr>
			<td>PU quick-plug connector</td>
			<td>Elecall</td>
			<td>PU-6</td>
			<td>Connector for PU tube</td>
		</tr>
		<tr>
			<td>PU tube</td>
			<td>Baishehui</td>
			<td>ZDmJKJJy</td>
			<td>Air line connection</td>
		</tr>
		<tr>
			<td>Silicone elastomer</td>
			<td>Wacker</td>
			<td>ELASTOSIL M4601 A/B</td>
			<td>Material of the pneumatic gripper</td>
		</tr>
		<tr>
			<td>Thermostatic chamber</td>
			<td>Ruyi</td>
			<td>101-00A</td>
			<td>Constant temperature to accelerate the curing of silicone</td>
		</tr>
		<tr>
			<td>Vacuum dryer</td>
			<td>Fujiwara</td>
			<td>PC-3</td>
			<td>Further defoaming</td>
		</tr>
		<tr>
			<td>Vacuum mixing and degassing machine</td>
			<td>Smida</td>
			<td>TMV-200T</td>
			<td>Mix silicone thoroughly and get it defoamed</td>
		</tr>
		<tr>
			<td>Valve</td>
			<td>SMC</td>
			<td>NTV1030-312CL</td>
			<td>Control the air pressure</td>
		</tr>
	</tbody>
</table>

a flexible wearable supernumerary robotic limb for chronic stroke patients

在这项研究中，我们提出了一种灵活的可穿戴编外机器人肢体，可帮助慢性中风患者进行手指康复和抓握运动。这种创新肢体的设计灵感来自弯曲的气动肌肉和大象鼻尖的独特特性。它非常强调轻质结构、安全性、合规性、防水和实现高输出重量比/压力比等关键因素。所提出的结构使机器人肢体能够同时进行包络和指尖抓取。通过灵活的弯曲传感器促进人机交互，检测佩戴者的手指运动，并通过阈值分割方法将其连接到运动控制。此外，该系统是便携式的，适合多种日常使用。为了验证这项创新的有效性，我们进行了涉及六名慢性中风患者和三名健康志愿者的真实世界实验。通过问卷调查收到的反馈表明，所设计的机制在帮助慢性中风患者进行日常抓握活动方面具有巨大的前景，有可能改善他们的生活质量和康复结果。

According to previous research1, as of 2019, there were more than 100 million cases of stroke worldwide. Approximately two-thirds of these cases resulted in hemiplegic sequelae, and over 80% of severe hemiplegic stroke patients could not fully recover hand and arm function2. Furthermore, the aging population is expected to continue growing in the coming decades, leading to a significant increase in the number of potential stroke victims. The persistent upper extremity impairments following a stroke can significantly affect activities of daily living (ADLs), and hand rehabilitation has been clinically recognized as a critical objective for enhancing the activity and participation of chronic stroke patients3.
Traditional motor-driven robotic upper limb devices can provide substantial driving force, but their rigid structures often translate into large sizes and high weights. Moreover, they pose the risk of causing irreversible harm to the human body if they were to malfunction. In contrast, soft pneumatic actuators have demonstrated considerable potential in rehabilitation4, assistance5, and surgical applications6. Their advantages include safety, lightweight construction, and inherent compliance.
In recent years, numerous flexible wearable robots have emerged, designed and developed around soft pneumatic actuators. These robots have been intended for the rehabilitation and post-rehabilitation assistance of stroke patients&#39; upper limbs. They primarily encompass hand exoskeletons7,8, and supernumerary limbs9,10. Although both are used in the fields of wearable robotics and rehabilitation, the former directly interacts with the human body, potentially constraining muscles or joints, while the latter supplements the human workspace or movement without direct constraint11,12. Wearable supernumerary robotic fingers based on servo motors were developed to assist occupational therapists in activities of daily living (ADLs) training9. A similar approach can be found in other research10. These two categories of robotic fingers have introduced novel possibilities for the application of such robots in the rehabilitation assistance of hemiparetic patients. Nonetheless, it is worth noting that the rigid structure employed in these robotic designs may introduce potential considerations regarding user comfort and safety. The design, fabrication, and evaluation of a soft wearable robotic glove were presented13, which can be used for hand rehabilitation and task-specific training during functional Magnetic Resonance Imaging (fMRI). The glove utilizes soft pneumatic actuators made of silicone elastomers to generate finger joint motion, and the device is MR-compatible without causing artifacts in fMRI images. Yun et al. introduced the Exo-Glove PM, a customizable soft pneumatic assistive glove that utilizes an assembly-based approach14. This innovative design features small modules and adjustable distances between them, allowing users to customize the glove based on their phalange length using spacers. This approach maximizes comfort and performance without the need for custom manufacturing. Researchers presented soft actuators composed of elastomeric materials with integrated channels functioning as pneumatic networks15. These actuators generate bending motions that safely conform to human finger movements. Additionally, researchers introduced the AirExGlove, a lightweight and adaptable inflatable soft exoskeleton device16. This system is cost-effective, customizable for different hand sizes, and has successfully accommodated patients with varying levels of muscle spasticity. It offers a more ergonomic and flexible solution compared to rigid-linked robotic systems. While these studies have made significant contributions to the development of flexible wearable hand rehabilitation and assistive robots, it&#39;s worth noting that none of them have achieved complete portability and human-robot interaction control.
Numerous studies have explored the correlation between biological signals, such as electroencephalogram (EEG)17 or electromyogram (EMG) signals18, and human intention. However, both approaches have certain limitations within the constraints of existing devices and technological conditions. Invasive electrodes require surgical procedures on the human body, while non-invasive electrodes suffer from issues such as high noise levels and unreliability in signal acquisition. Detailed discussions of these limitations can be found in the literature19,20. Therefore, the pursuit of research into the portability and user-friendly human-machine interaction capabilities of flexible wearable supernumerary robotic limbs remains highly relevant.
In this study, a unique flexible wearable supernumerary robotic limb was designed and fabricated to assist chronic stroke patients in finger rehabilitation and gripping assistance. This robotic limb is characterized by its lightweight, safety, compliance, waterproofing, and impressive output-to-weight/pressure ratio. Two gripping modes, envelope and fingertip grasping, have been achieved while maintaining portability and ensuring a user-friendly human-robot interaction. The protocol details the design and fabrication process of the pneumatic gripper and the wearable scheme. Additionally, a human-robot interaction method based on flexible bending sensors has been proposed, allowing for convenient and user-friendly control through threshold segmentation. All these aspects have been validated through practical experiments.
The main contributions of this study are summarized as follows: (1) A lightweight, friendly, and wearable flexible supernumerary robotic limb for chronic stroke patients has been designed and fabricated. (2) A reliable method of human-robot interaction has been realized based on flexible bending sensors. (3) Real-world experiments have been conducted to verify the effectiveness and reliability of the proposed mechanism and method, which include output force testing and involve six chronic stroke patients.

作者聚焦：使用灵活的机器人肢体增强偏瘫患者的抓握能力 

一种用于慢性脑卒中患者的柔性可穿戴编外机器人肢体

输出力实验 图 7 生动地描绘了我们执行器的结构设计和尺寸，并提供了横截面说明。该执行器由两组不同的气室组成，每组气室包含五个优雅弯曲的气室。值得注意的是，在执行器的末端，我们巧妙地集成了一个突出的结构，让人联想到大象的鼻尖，大大扩展了执行器的抓取半径。
为了评估软气动执行器的输出力，进行了一系列静态抓?...

Watch this Scientific Journal Video about Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs at JoVE.com

该协议引入了一种灵活的可穿戴编外机器人肢体，专为协助中风患者的手指康复而量身定制。该设计集成了一个弯曲传感器，以促进人机交互的无缝衔接。通过涉及健康志愿者和中风患者的实验进行验证，强调了拟议研究的有效性和可靠性。

In this study, we present a flexible wearable supernumerary robotic limb that helps chronic stroke patients with finger rehabilitation and grasping ...

我们的研究重点是开发多余的机器人肢体，以帮助偏瘫患者进行抓握运动。通过使用灵活的传感器，我们的目标是解释患者的意图，并使机器人能够执行各种抓取任务，最终提高患者的生活质量。本研究为慢性中风患者介绍了一种新型、灵活、可穿戴的机器人肢体。它有助于手指康复和抓握，具有轻便、安全、合规、防水以及令人印象深刻的输出重量或压力比。它提供信封和指尖抓取模式，保持便携性，并确保用户友好的交互。在我们即将到来的研究中，我们将主要关注人机交互控制领域，特别是在偏瘫患者掌握意图的背景下。此外，具体的研究目标涉及改进机械设计以提高抓取性能。

a-flexible-wearable-supernumerary-robotic-limb-for-chronic-stroke

Research

JoVE Journal

Engineering

A Flexible Wearable Supernumerary Robotic Limb for Chronic Stroke Patients

1.3K 次观看.  Huazhong University of Science and Technology. 我们的研究重点是开发多余的机器人肢体，以帮助偏瘫患者进行抓握运动。通过使用灵活的传感器，我们的目标是解释患者的意图，并使机器人能够执行各种抓取任务，最终提高患者的生活质量。本研究为慢性中风患者介绍了一种新型、灵活、可穿戴的机器人肢体。它有助于手指康复和抓握，具有轻便、安全、合规、防水以及令人印象深刻的输出重量或压力比。它提供?...

视频: 作者聚焦：使用灵活的机器人肢体增强偏瘫患者的抓握能力 

In this study, we present a flexible wearable supernumerary robotic limb that helps chronic stroke patients with finger rehabilitation and grasping movements. The design of this innovative limb draws inspiration from bending pneumatic muscles and the unique characteristics of an elephant's trunk tip. It places a strong emphasis on crucial factors such as lightweight construction, safety, compliance, waterproofing, and achieving a high output-to-weight/pressure ratio. The proposed structure enables the robotic limb to perform both envelope and fingertip grasping. Human-robot interaction is facilitated through a flexible bending sensor, detecting the wearer's finger movements and connecting them to motion control via a threshold segmentation method. Additionally, the system is portable for versatile daily use. To validate the effectiveness of this innovation, real-world experiments involving six chronic stroke patients and three healthy volunteers were conducted. The feedback received through questionnaires indicates that the designed mechanism holds immense promise in assisting chronic stroke patients with their daily grasping activities, potentially improving their quality of life and rehabilitation outcomes.

This protocol introduces a flexible wearable supernumerary robotic limb tailored to assist in finger rehabilitation for stroke patients. The design incorporates a bending sensor to facilitate seamless human-robot interaction. Validation through experiments involving both healthy volunteers and stroke patients underscores the efficacy and dependability of the proposed study.