Controllable variable rigidity system for rehabilitation exoskeletons
DOI:
https://doi.org/10.17979/ja-cea.2025.46.12209Keywords:
Biomedical Mechatronics, Human and Robot mechatronics, Smart structures, Motion control systems, Human-centered computing, Modeling of human performance, Analytic designAbstract
The growing need for effective rehabilitation therapies has driven the development of robotic exoskeletons, particularly soft exoskeletons, due to their greater adaptability and comfort compared to conventional rigid systems. This work presents the design of a smart variable rigidity system (VRS) applicable to soft rehabilitation exoskeletons, controlled by shape memory alloy (SMA) actuators and sensorised in force and position. The proposed VRS allows switching between stiffness and flexibility states to assist both passive and active therapies, providing controlled resistance and selective immobilization of degrees of freedom, thus promoting neuroactivation and muscle strengthening. In addition, the integration of sensors allows the quantification of relevant metrics for objective clinical assessment of patient progress. The paper presents the design of the system architecture and the evaluation of the system’s design criteria, scalability, and feasibility, highlighting its potential to improve the effectiveness of rehabilitation programs and to promote its standardization and accessibility.
References
Banyai, A.D., Bris, an, C., 2024. Robotics in physical rehabilitation: Systematic review. Healthcare 2024, Vol. 12, Page 1720 12, 1720. doi:10.3390/HEALTHCARE12171720.
Chen, L., Zhou, D., Leng, Y., 2024. A systematic review on rigid exoskeleton robot design for wearing comfort: Joint self-alignment, attachment interface, and structure customization. IEEE Transactions on Neural Systems and Rehabilitation Engineering 32, 3815–3827. doi:10.1109/TNSRE.2024.3479283.
Cieza, A., Causey, K., Kamenov, K., Hanson, S.W., Chatterji, S., Vos, T., 2020. Global estimates of the need for rehabilitation based on the global burden of disease study 2019: a systematic analysis for the global burden of disease study 2019. The Lancet 396, 2006–2017. doi:10.1016/S0140- 6736(20)32340-0.
Dewang, Y., Sharma, V., Baliyan, V.K., Soundappan, T., Singla, Y.K., 2025. Research progress in electroactive polymers for soft robotics and artificial muscle applications. Polymers 2025, Vol. 17, Page 746 17, 746. doi:10.3390/POLYM17060746.
Diller, S., Majidi, C., Collins, S.H., 2016. A lightweight, low-power electroadhesive clutch and spring for exoskeleton actuation. Proceedings - IEEE International Conference on Robotics and Automation 2016-June, 682– 689. doi:10.1109/ICRA.2016.7487194.
El-Atab, N., Mishra, R.B., Al-Modaf, F., Joharji, L., Alsharif, A.A., Alamoudi, H., Diaz, M., Qaiser, N., Hussain, M.M., 2020. Soft actuators for soft robotic applications: A review. Advanced Intelligent Systems 2, 2000128. doi:10.1002/AISY.202000128.
Federici, S., Meloni, F., Bracalenti, M., Filippis, M.L.D., 2015. The effectiveness of powered, active lower limb exoskeletons in neurorehabilitation: A systematic review. NeuroRehabilitation 37, 321–340. doi:10.3233/NRE- 151265.
Henke, M., Gerlach, G., 2016. A multi-layered variable stiffness device based on smart form closure actuators. Journal of Intelligent Material Systems and Structures 27, 375–383. doi:10.1177/1045389X15577645.
Khalid, S., Alnajjar, F., Gochoo, M., Renawi, A., Shimoda, S., 2023. Roboticassistive and rehabilitation devices leading to motor recovery in upper limb: a systematic review. Disability and Rehabilitation: Assistive Technology 18, 658–672. doi:10.1080/17483107.2021.1906960.
Khande, C.K., Verma, V., Regmi, A., Ifthekar, S., Sudhakar, P.V., Sethy, S.S., Kandwal, P., Sarkar, B., 2024. Effect on functional outcome of robotic assisted rehabilitation versus conventional rehabilitation in patients with complete spinal cord injury: a prospective comparative study. Spinal Cord 62, 228–236. doi:10.1038/S41393-024-00970-1.
Lee, K.H., Yu, M., Kim, Y.M., Jeong, L.H., Kwon, T.K., 2025. Muscle strength assistance of a shape memory alloy exoskeleton during lifting and lowering tasks. International Journal of Precision Engineering and Manufacturing 26, 1013–1022. doi:10.1007/S12541-024-01184-4/TABLES/2.
Mao, Z., Wang, C., Rui, Y., Huang, X., Zhang, Z., Li, Y., Yang, Y., 2022. Variable stiffness mechanism for single-joint lower limb wearable exoskeleton: A review. 2022 6th International Conference on Automation, Control and Robots, ICACR 2022 , 75–82. doi:10.1109/ICACR55854.2022.9935528.
Pagoli, A., Chapelle, F., Corrales-Ramon, J.A., Mezouar, Y., Lapusta, Y., 2021. Review of soft fluidic actuators: classification and materials modeling analysis. Smart Materials and Structures 31, 013001. doi:10.1088/1361-665X/AC383A.
Pan, M., Yuan, C., Liang, X., Dong, T., Liu, T., Zhang, J., Zou, J., Yang, H., Bowen, C., 2022. Soft actuators and robotic devices for rehabilitation and assistance. Advanced Intelligent Systems 4, 2100140. doi:10.1002/AISY.202100140.
Potcovaru, C.G., Salmen, T., Bˆıgu, D., S˘andulescu, M.I., Filip, P.V., Diaconu, L.S., Pop, C., Ciobanu, I., Cintez˘a, D., Berteanu, M., 2024. Assessing the effectiveness of rehabilitation interventions through the world health organization disability assessment schedule 2.0 on disability—a systematic review. Journal of Clinical Medicine 2024, Vol. 13, Page 1252 13, 1252. doi:10.3390/JCM13051252.
Seo, J., Kim, Y.C., Hu, J.W., 2015. Pilot study for investigating the cyclic behavior of slit damper systems with recentering shape memory alloy (sma) bending bars used for seismic restrainers. Applied Sciences 2015, Vol. 5, Pages 187-208 5, 187–208. doi:10.3390/APP5030187.
Serrano, D., Copaci, D., Arias, J., Moreno, L.E., Blanco, D., 2023. Sma-based soft exo-glove. IEEE Robotics and Automation Letters 8, 5448–5455. doi:10.1109/LRA.2023.3295994.
Wang, Z., Zhou, Z., Ruan, L., Duan, X., Wang, Q., 2023. Mechatronic design and control of a rigid-soft hybrid knee exoskeleton for gait intervention. IEEE/ASME Transactions on Mechatronics 28, 2553–2564. doi:10.1109/TMECH.2023.3245810.
Yang, S., Li, M., Wang, J., Shi, Z., He, B., Xie, J., Xu, G., 2023. A lowcost and portable wrist exoskeleton using eeg-semg combined strategy for prolonged active rehabilitation. Frontiers in Neurorobotics 17, 1161187. doi:10.3389/FNBOT.2023.1161187/BIBTEX.
Zhu, Y., Wu, Q., Chen, B., Xu, D., Shao, Z., 2022. Design and evaluation of a novel torque-controllable variable stiffness actuator with reconfigurability. IEEE/ASME Transactions on Mechatronics 27, 292–303. doi:10.1109/TMECH.2021.3063374.
Sittner, P., Heller, L., Pilch, J., Curfs, C., Alonso, T., Favier, D., 2014. Young’s modulus of austenite and martensite phases in superelastic niti wires. Journal of Materials Engineering and Performance 23, 2303–2314. doi:10.1007/S11665-014-0976-X.
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Copyright (c) 2025 Sofía Margarita Die Pancorbo, Dorin Copaci, Dolores Blanco
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