|
|
柔性手部可穿戴康复运动辅助系统
|
Abstract:
随着我国人口老龄化加剧，脑卒中患者数量逐年上升，手部运动功能障碍成为常见后遗症。设计一款柔性手部可穿戴康复运动辅助系统，解决现有手部康复设备价格昂贵、安全性低、力重比不足、气压需求较高以及患者参与度低等问题。以帮助脑卒中患者进行居家康复训练以及辅助患者完成日常生活任务。本文系统核心由柔性手部屈曲执行器和气动控制系统组成。执行器采用涂有TPU (Thermoplastic Polyurethane)涂层的尼龙织物，具备良好的柔顺性和舒适性；气动控制系统由微型气泵、高频电磁阀和控制电路板构成。此外，系统配备微信小程序和液晶触摸屏的人机交互界面，用户可选择不同的康复模式、获取医疗资讯及历史康复数据等。实验结果表明，当手部屈曲执行器的输入气压达到最大300 kPa时，指尖终端输出力可达到11.6 N。证明了柔性手部可穿戴康复运动辅助系统在居家康复中的有效性，为脑卒中患者自理能力的恢复提供了有力支持。经实验验证，基于柔性织物材料的手部屈曲执行器具备舒适柔软的穿戴体验，并具有较高的安全性，有效避免了对患者的二次伤害。此外，该执行器在较低气压下仍能实现较高的指尖终端输出力。通过引入基于表面肌电信号的主动康复模式，使患者能够精确控制康复训练动作，充分发挥自主意识的作用。与被动康复和镜像康复模式结合，形成了一种适用于康复全周期的手部可穿戴康复运动辅助系统。
Given the exacerbation of the aging population in China, the incidence of stroke patients is progressively increasing, leading to hand motor dysfunction as a prevalent sequela. This study aims to develop a flexible hand wearable rehabilitation motion assistance system to address the issues of high cost, low safety, inadequate force-to-weight ratio, excessive pressure requirements, and low patient engagement associated with current hand rehabilitation devices. The objective is to facilitate home-based rehabilitation training for stroke patients and assist them in performing daily activities. The core components of the proposed system include a flexible hand buckling actuator and a pneumatic control system. The actuator is fabricated from nylon fabric coated with TPU (Thermoplastic Polyurethane), ensuring excellent flexibility and comfort. The pneumatic control system comprises a micro air pump, high-frequency solenoid valves, and a control circuit board. Additionally, the system features a WeChat mini-program and an LCD touch screen for user-friendly human-computer interaction, enabling users to select various rehabilitation modes, access medical information, and review historical rehabilitation data. Experimental findings indicate that when the input pressure of the hand flexion actuator reaches a maximum of 300 kPa, the output force at the fingertip terminal can attain up to 11.6 N. These results substantiate the efficacy of the flexible hand wearable rehabilitation motion assistance system in home rehabilitation settings, providing substantial support for the restoration of stroke patients’ self-care capabilities. The experimental results demonstrate that the hand flexion actuator constructed from flexible fabric materials offers a comfortable and soft wearing experience, ensuring high safety and effectively preventing secondary injuries in patients.
| [1] | Report on Stroke Prevention and Treatment in China Writing Group. 《中国脑卒中防治报告2021》概要[J]. 中国脑血管病杂志, 2023, 20(11): 783-793. |
| [2] | 刘勤, 冯灵, 汪锐, 周乾晓, 等. 康复机器人在脑梗死偏瘫患者中应用的研究进展[J]. 中国临床研究, 2024, 37(4): 621-625. |
| [3] | Qassim, H.M. and Wan Hasan, W.Z. (2020) A Review on Upper Limb Rehabilitation Robots. Applied Sciences, 10, Article No. 6976. https://doi.org/10.3390/app10196976 |
| [4] | Liang, R., Zhang, Q., He, B. and Li, L. (2024) Visual Representation of the Compactness of a Stephenson-II Six-Bar Linkage Exoskeleton Using Solution Region Synthesis Theory. IEEE Robotics and Automation Letters, 9, 4415-4422. https://doi.org/10.1109/lra.2024.3354625 |
| [5] | Chowdhury, A., Nishad, S.S., Meena, Y.K., Dutta, A. and Prasad, G. (2019) Hand-Exoskeleton Assisted Progressive Neurorehabilitation Using Impedance Adaptation Based Challenge Level Adjustment Method. IEEE Transactions on Haptics, 12, 128-140. https://doi.org/10.1109/toh.2018.2878232 |
| [6] | Li, H., Cheng, L., Sun, N. and Cao, R. (2022) Design and Control of an Underactuated Finger Exoskeleton for Assisting Activities of Daily Living. IEEE/ASME Transactions on Mechatronics, 27, 2699-2709. https://doi.org/10.1109/tmech.2021.3120030 |
| [7] | Park, S., Weber, L., Bishop, L., Stein, J. and Ciocarlie, M. (2018) Design and Development of Effective Transmission Mechanisms on a Tendon Driven Hand Orthosis for Stroke Patients. 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, 21-25 May 2018, 2281-2287. https://doi.org/10.1109/icra.2018.8461069 |
| [8] | Copaci, D., Cerro, D.S.D., Guadalupe, J.A., Lorente, L.M. and Rojas, D.B. (2024) sEMG-Controlled Soft Exo-Glove for Assistive Rehabilitation Therapies. IEEE Access, 12, 43506-43518. https://doi.org/10.1109/access.2024.3380469 |
| [9] | Hadi, Y.W., Sunarya, B.A.Y., Alifdhyatra, A.F., Hidayat, E., Salomo, J., Purwidyantri, A., et al. (2023) Programmable Soft Robotics Actuator with Pneumatic Networks (PneuNets). IEEE Sensors Journal, 23, 19382-19389. https://doi.org/10.1109/jsen.2023.3297402 |
| [10] | Polygerinos, P., Wang, Z., Galloway, K.C., Wood, R.J. and Walsh, C.J. (2015) Soft Robotic Glove for Combined Assistance and At-Home Rehabilitation. Robotics and Autonomous Systems, 73, 135-143. https://doi.org/10.1016/j.robot.2014.08.014 |
| [11] | Yang, Y., Zhang, Y., Meng, Q. and Yu, H. (2024) A Novel Pneumatic Soft Exoskeleton Rehabilitation Glove for Extension Training to Hand Rehabilitation. 2024 9th International Conference on Automation, Control and Robotics Engineering (CACRE), Jeju Island, 18-20 July 2024, 225-230. https://doi.org/10.1109/cacre62362.2024.10635045 |
| [12] | Fidinillah, T., Risangtuni, A.G., Kurnia Putra, N., Virdyawan, V., Suprijanto, S. and Putri, S.M. (2023) Design of Soft Pneumatic Actuator in Hand Rehabilitation Robot with Fem-Based Modeling. 2023 8th International Conference on Instrumentation, Control, and Automation (ICA), Jakarta, 9-11 August 2023, 109-113. https://doi.org/10.1109/ica58538.2023.10273084 |
| [13] | Li, K., Zhang, J., Wang, L., Zhang, M., Li, J. and Bao, S. (2020) A Review of the Key Technologies for sEMG-Based Human-Robot Interaction Systems. Biomedical Signal Processing and Control, 62, Article ID: 102074. https://doi.org/10.1016/j.bspc.2020.102074 |
| [14] | 孟云, 韩建海, 李向攀, 等. 手型识别的手功能康复动作快速规划研究[J]. 中国康复医学杂志, 2024, 39(1): 96-99. |
| [15] | Duan, F., Ren, X. and Yang, Y. (2021) A Gesture Recognition System Based on Time Domain Features and Linear Discriminant Analysis. IEEE Transactions on Cognitive and Developmental Systems, 13, 200-208. https://doi.org/10.1109/tcds.2018.2884942 |
| [16] | Narayan, Y. (2021) SEMG Signal Classification Using KNN Classifier with FD and TFD Features. Materials Today: Proceedings, 37, 3219-3225. https://doi.org/10.1016/j.matpr.2020.09.089 |
| [17] | Bützer, T., Lambercy, O., Arata, J. and Gassert, R. (2021) Fully Wearable Actuated Soft Exoskeleton for Grasping Assistance in Everyday Activities. Soft Robotics, 8, 128-143. https://doi.org/10.1089/soro.2019.0135 |
| [18] | Hu, D., Zhang, J., Yang, Y., Li, Q., Li, D. and Hong, J. (2020) A Novel Soft Robotic Glove with Positive-Negative Pneumatic Actuator for Hand Rehabilitation. 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Boston, 6-9 July 2020, 1840-1847. https://doi.org/10.1109/aim43001.2020.9158826 |
| [19] | Wang, F., Chen, Y., Wang, Y., Liu, Z., Tian, Y. and Zhang, D. (2022) A Soft Pneumatic Glove with Multiple Rehabilitation Postures and Assisted Grasping Modes. Sensors and Actuators A: Physical, 347, Article ID: 113978. https://doi.org/10.1016/j.sna.2022.113978 |
| [20] | 周平, 陈思韵, 李文兮, 等. 促进康复动机的策略在卒中康复中的应用进展[J]. 中国康复医学杂志, 2024, 39(2): 280-287. |
