Efficacy of robotic training gloves in improving hand function and movement in stroke patients
Abstract
Robotic training gloves are designed to assist with hand movements by providing resistance, support, or guidance. The efficacy of robotic training gloves on hand function in stroke patients, particularly when using the mirror mode, is an intriguing topic in rehabilitation therapy. This study aimed to investigate the effect of assistive robotic rehabilitation devices on hand function in stroke patients. A controlled randomized study was conducted with thirty (9 males and 21 female) stroke patients, who were selected from the outpatient clinic of Al-Delingat Central Hospital - Al-Buhaira Governorate. These patients were randomly assigned to two groups: the study group (A), which received the selected physical therapy program and mirror therapy assisted by a robotic rehabilitation glove, and the control group (B), which received only the conventional physical therapy program. When comparing between both groups, the results indicate that the patients in group A that underwent the combined therapy had a statistically significant improvement in grip strength when tested by the Jamar dynamometer (MD= 1.87 [0.39, 3.35], P=0.015) and in motor function when evaluated by the Fugl-Meyer scale than the group who had only conventional physical therapy (Group B) (MD= 16.67 [3.9, 29.4], p=0.012). This controlled randomized study provides evidence that combining robotic rehabilitation with a standard physical therapy program yields superior improvements in grip strength and motor function compared to standard physical therapy alone.
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References
Alayat, M. S., Almatrafi, N. A., Almutairi, A. A., El Fiky, A. A. R., & Elsodany, A. M. (2022). The effectiveness of telerehabilitation on balance and functional mobility in patients with stroke: A systematic review and meta-analysis. International Journal of Telerehabilitation, 14(2), 1-24. https://doi.org/10.5195/telerehab.2022.6532
Calabrò, R. S., Sorrentino, G., Cassio, A., Mazzoli, D., Andrenelli, E., Bizzarini, E., et al. (2021). Robotic-assisted gait rehabilitation following stroke: A systematic review of current guidelines and practical clinical recommendations. European Journal of Physical and Rehabilitation Medicine, 57(3), 334–345.
Campbell, A., Gustafsson, L., Grimley, R., Gullo, H., Rosbergen, I., & Summers, M. (2023). Mapping the trajectory of acute mild-stroke cognitive recovery using serial computerized cognitive assessment. Brain Impairment, 24(3), 629–648. https://doi.org/10.1017/S1443964622000249
Cappello, L., Meyer, J. T., Galloway, K. C., Peisner, J. D., Granberry, R., Wagner, D. A., et al. (2018). Assisting hand function after spinal cord injury with a fabric-based soft robotic glove. Journal of NeuroEngineering and Rehabilitation, 15(1), 1-10. https://doi.org/10.1186/s12984-018-0391-x
Carr, P., Moser, D., Williamson, S., Robinson, G., & Kintz, S. (2022). Improving functional communication outcomes in post-stroke aphasia via telepractice: An alternative service delivery model for underserved populations. International Journal of Telerehabilitation, 14(2), 1-20. https://doi.org/10.5195/telerehab.2022.6531
Chan, A. (2022). A technical report on a novel robotic lower limb rehabilitation device - Is ROBERT® a cost-effective solution for rehabilitation in Hong Kong? Hong Kong Physiotherapy Journal, 42(2), 75–80. https://doi.org/10.1142/S1013702522710019
Colombo, R., Pisano, F., Mazzone, A., Delconte, C., Micera, S., & Carrozza, M. C., (2007). Design strategies to improve patient motivation during robot-aided rehabilitation. Journal of NeuroEngineering and Rehabilitation, 4(1), 1-12. https://doi.org/10.1186/1743-0003-4-3
De Iaco, L., Veerbeek, J. M., Ket, J. C. F., & Kwakkel, G. (2024). Upper limb robots for recovery of motor arm function in patients with stroke. Neurology, 103(2), 1-9. https://doi.org/10.1212/WNL.0000000000209495
Fujii, R., Tamari, M., Nonaka, Y., Tamiya, F., Hosokawa, H., & Tanaka, S. (2022). Influence of gait exercise using a walking-assist robot for swing-leg motion in hemiplegic stroke patients: A preliminary study focusing on the immediate effect. Japanese Journal of Comprehensive Rehabilitation Science, 13, 49–55. https://doi.org/10.11336/jjcrs.13.49
Grevet, E., Forge, K., Tadiello, S., Izac, M., Amadieu, F., Brunel, L., Pillette, L., Py, J., Gasq, D., & Jeunet-Kelway, C. (2023). Modeling the acceptability of BCIs for motor rehabilitation after stroke: A large scale study on the general public. Frontiers in Neuroergonomics, 3, 1-23. https://doi.org/10.3389/fnrgo.2022.1082901
Hsieh, Y., Wu, C., Liao, W., Lin, K., Wu, K., & Lee, C. (2011). Effects of treatment intensity in upper limb robot-assisted therapy for chronic stroke. Neurorehabilitation and Neural Repair, 25(6), 503–511. https://doi.org/10.1177/1545968311400083
Igarashi, T., Hayashi, S., Ogawa, K., Matsui, S., & Nishimatsu, T. (2022). Relationship between daily rehabilitation time and functional gain in inpatient rehabilitation medicine of hospitalized older adults with subacute stroke. Japanese Journal of Comprehensive Rehabilitation Science, 13, 56–63. https://doi.org/10.11336/jjcrs.13.56
Kawada, S., & Goto, R. (2017). Relationship between psychophysiological factors and prognosis for activities of daily living in patients with stroke in a recovery rehabilitation unit: A preliminary study. Journal of Physical Therapy Science, 29(12), 2206–2209. https://doi.org/10.1589/jpts.29.2206
Kim, D. H., Lee, K. D., Bulea, T. C., & Park, H. S. (2022). Increasing motor cortex activation during grasping via novel robotic mirror hand therapy: A pilot fNIRS study. Journal of NeuroEngineering and Rehabilitation, 19(1), 1-14. https://doi.org/10.1186/s12984-022-00988-7
Kottink, A. I. R., Nikamp, C. D., Bos, F. P., van der Sluis, C. K., van den Broek, M., & Onneweer, B., (2022). Therapeutic effect of a soft robotic glove for activities of daily living in people with impaired hand strength: Protocol for a multicenter clinical trial (iHand). JMIR Research Protocols, 11(4), 1-15. https://doi.org/10.2196/34200
Kwakkel, G., Kollen, B. J., & Krebs, H. I. (2008). Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review. Neurorehabilitation and Neural Repair, 22(2), 111–121. https://doi.org/10.1177/1545968307305457
Leerskov, K. S., Rikhof, C. J. H., Spaich, E. G., Dosen, S., Prange-Lasonder, G. B., Prinsen, E. C., Rietman, J. S., & Struijk, L. N. S. A. (2024). A robot-based hybrid lower limb system for Assist-As-Needed rehabilitation of stroke patients: Technical evaluation and clinical feasibility. Computers in Biology and Medicine, 179, 1-12. https://doi.org/10.1016/j.compbiomed.2024.108839
Li, M., Wang, T., Zhuo, Y., He, B., Tao, T., & Xie, J., (2020). A soft robotic glove for hand rehabilitation training controlled by movements of the healthy hand. In 2020 17th International Conference on Ubiquitous Robots (UR) (pp. 62–67). IEEE. https://doi.org/10.1109/UR49135.2020.9144753
Lo, A. C., Guarino, P. D., Richards, L. G., Haselkorn, J. K., Wittenberg, G. F., Federman, D. G., Ringer, R. J., Wagner, T. H., Krebs, H. I., Volpe, B. T., Bever, C. T., Jr, Bravata, D. M., Duncan, P. W., Corn, B. H., Maffucci, A. D., Nadeau, S. E., Conroy, S. S., Powell, J. M., Huang, G. D., & Peduzzi, P. (2010). Robot-assisted therapy for long-term upper-limb impairment after stroke. New England Journal of Medicine, 362(19), 1772–1783. https://doi.org/10.1056/NEJMoa0911341
Lo, B. P., Donnelly, M. R., Barisano, G., & Liew, S. L. (2023). A standardized protocol for manually segmenting stroke lesions on high-resolution T1-weighted MR images. Frontiers in Neuroimaging, 1, 1-9. https://doi.org/10.3389/fnimg.2022.1098604
Lu, J., Guo, Y., Wang, M., Luo, Y., Zeng, X., Miao, X., Zaman, A., Yang, H., Cao, A., & Kang, Y. (2024). Determining acute ischemic stroke onset time using machine learning and radiomics features of infarct lesions and whole brain. Mathematical Biosciences and Engineering, 21(1), 34–48. https://doi.org/10.3934/mbe.2024002
Lum, P. S., Burgar, C. G., Shor, P. C., Majmundar, M., & Van der Loos, M. (2002). Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Archives of Physical Medicine and Rehabilitation, 83(7), 952–959. https://doi.org/10.1053/apmr.2002.32839
Maclean, N. (2000). Qualitative analysis of stroke patients’ motivation for rehabilitation. BMJ, 321(7268), 1051–1054. https://doi.org/10.1136/bmj.321.7268.1051
Mehrholz, J., Pohl, M., Platz, T., Kugler, J., & Elsner, B. (2018). Electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke. Cochrane Database of Systematic Reviews, 2018(9), 1-165. https://doi.org/10.1002/14651858.CD006876.pub3
Nasrallah, F. A., Mohamed, A. Z., Yap, H. K., Lai, H. S., Yeow, C. H., & Lim, J. H. (2021). Effect of proprioceptive stimulation using a soft robotic glove on motor activation and brain connectivity in stroke survivors. Journal of Neural Engineering, 18(6), 1-12. https://doi.org/10.1088/1741-2552/ac456c
Patton, J., Dawe, G., Scharver, C., Mussa-Ivaldi, F., & Kenyon, R. (2006). Robotics and virtual reality: A perfect marriage for motor control research and rehabilitation. Assistive Technology, 18(2), 181–195. https://doi.org/10.1080/10400435.2006.10131916
Roberts, H. C., Denison, H. J., Martin, H. J., Patel, H. P., Syddall, H., Cooper, C., & Sayer, A. A. (2011). A review of the measurement of grip strength in clinical and epidemiological studies: Towards a standardized approach. Age and Ageing, 40(4), 423–429. https://doi.org/10.1093/ageing/afr051
Saragih, I. D., Everard, G., Tzeng, H.-M., Saragih, I. S., & Lee, B. O. (2023). Efficacy of robots-assisted therapy in patients with stroke. Journal of Cardiovascular Nursing, 38(6), 192–217. https://doi.org/10.1097/JCN.0000000000000945
Shankaranarayana, A. M., Pattan, Y. S., Hegde, N., Natarajan, M., Pai, A. R., Nayak, R., & Solomon, J. M. (2023). Activity monitoring of stroke patients by physiotherapist and caregivers in a hospital setting: A pilot study. F1000Research, 11, 1-24. https://doi.org/10.12688/f1000research.1227.2
Stinear, C. M., Barber, P. A., Petoe, M., Anwar, S., & Byblow, W. D. (2012). The PREP algorithm predicts potential for upper limb recovery after stroke. Brain, 135(8), 2527–2535. https://doi.org/10.1093/brain/aws146
Zheng, H., Cao, N., Yin, Y., & Feng, W. (2017). Stroke recovery and rehabilitation in 2016: A year in review of basic science and clinical science. Stroke & Vascular Neurology, 2(4), 222–229. https://doi.org/10.1136/svn-2017-000069
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The works and papers that are published in this Journal are subject to the following terms:
1. The Publication Service of the University of Murcia (the publisher) has the Publication Rights (Copyright) to the published papers and works, and favors and permits the reusing of the same under the license indicated in point 2.
© Servicio de Publicaciones, Universidad de Murcia, 2013
2. The papers and works are to be published in the digital edition of the Journal under the license Creative Commons Reconocimiento-No Comercial-Sin Obra Derivada 3.0 España (legal text). The copying, using, spreading, transmitting and publicly displaying of the papers, works or publication are permitted as long as: i) the authors and original sources (Journal, publisher and URL of the publication) are quoted; ii) it is not used for commercial benefit; iii) the existence and specifications of this users license are mentioned.
3. Conditions of Self-Archiving. It is permitted and encouraged that the authors spread electronically the pre-print (before printing) and/or post-print (the revised, evaluated and accepted) versions of their papers or works before their publication since this favors their circulation and early diffusion and therefore can help increase their citation and quotation, and also there reach through the academic community.
