Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Vol. 13, 30 November 2023
* Author to whom correspondence should be addressed.
A rigid exoskeleton has been developed for decades, and its feasibility has been proven in many areas, such as rehabilitation. Unlike the rigid exoskeleton, the soft exosuit provides a new insight for wearable robotics development and has drawn much attention as the external muscles instead of exoskeletons, especially for supporting users’ activities of daily living (ADL) and human body augmentation. This paper reviews the upper-limb soft exosuit studies in the last three years, including the core technologies and the current challenges that need to be addressed. Then, the actuator designs were described, including motor-tendon unit, pneumatic artificial muscle, hydraulic artificial muscle, and textile-based actuation. Their advantages and disadvantages were given and the applications were listed. Also, as the other part of core technologies described in this paper, the controller design which contains low-level and high-level control was discussed. Finally, the challenges were listed, which could be the further directions of research.
Soft Exosuit, Upper-Limb Exoskeleton, Wearable Robotics
1. M. Mihelj, T. Nef, and R. Riener, “A novel paradigm for patient-cooperative control of upper-limb rehabilitation robots,” Advanced Robotics, vol. 21, no. 8, pp. 843–867, 2007. doi:10.1163/156855307780851975
2. R. Morales, F. J. Badesa, N. García-Aracil, J. M. Sabater, and C. Pérez-Vidal, “Pneumatic robotic systems for Upper Limb Rehabilitation,” Medical & Biological Engineering & Computing, vol. 49, no. 10, pp. 1145–1156, 2011. doi:10.1007/s11517-011-0814-3
3. K. Yonezawa et al., “Extension force control considering contact with an object using a wearable robot for an upper limb,” 2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013. doi:10.1109/smc.2013.606
4. V. Klamroth-Marganska, J. Blanco, K. Campen, A. Curt, V. Dietz, T. Ettlin, M. Felder, B. Fellinghauer, M. Guidali, and A. Kollmar, ‘‘Three dimensional, task-specific robot therapy of the arm after stroke: A multicentre, parallel-group randomised trial,’’ Lancet Neurol., vol. 13, no. 2, pp. 159–166, 2014.
5. A. T. Asbeck, R. J. Dyer, A. F. Larusson, and C. J. Walsh, “Biologically-inspired soft exosuit,” in IEEE International Conference on Rehabilitation Robotics, Seattle, WA, 2013.
6. T. Proietti, E. Ambrosini, A. Pedrocchi, and S. Micera, “Wearable robotics for impaired upper-limb assistance and rehabilitation: State of the art and future perspectives,” IEEE Access, vol. 10, pp. 106117–106134, 2022. doi:10.1109/access.2022.3210514
7. E. Galofaro, E. D’Antonio, N. Lotti, and L. Masia, “A hybrid assistive paradigm based on neuromuscular electrical stimulation and force control for upper limb exosuits,” 2022 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), 2022. doi:10.1109/biorob52689.2022.9925466
8. D. Burchielli et al., “Adaptive hybrid fes-force controller for Arm Exosuit,” 2022 International Conference on Rehabilitation Robotics (ICORR), 2022. doi:10.1109/icorr55369.2022. 9896493
9. J. L. Samper-Escudero, S. Coloma, M. A. Olivares-Mendez, M. A. Gonzalez, and M. Ferre, “A compact and portable exoskeleton for shoulder and elbow assistance for workers and prospective use in space,” IEEE Transactions on Human-Machine Systems, pp. 1–10, 2022. doi:10.1109/thms.2022.3186874
10. F. Missiroli et al., “Rigid, soft, passive, and active: A hybrid occupational exoskeleton for bimanual multijoint assistance,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 2557–2564, 2022. doi:10.1109/lra.2022.3142447
11. N. Lotti, E. Tricomi, F. Missiroli, X. Zhang, and L. Masia, “Machine learning techniques in soft robotic suits for whole Body Assistance,” 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), 2022. doi:10.1109/dasc/picom/cbdcom/cy55231.2022.9927957
12. N. Lotti, E. Tricomi, F. Missiroli, X. Zhang, and L. Masia, “Machine learning techniques in soft robotic suits for whole Body Assistance,” 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), 2022. doi:10.1109/dasc/picom/cbdcom/cy55231.2022.9927957
13. R. F. Natividad, T. Miller-Jackson, and R. Y. Chen-Hua, “A 2-DOF shoulder exosuit driven by modular, pneumatic, fabric actuators,” IEEE Transactions on Medical Robotics and Bionics, vol. 3, no. 1, pp. 166–178, 2021. doi:10.1109/tmrb.2020.3044115
14. N. Tacca, J. Nassour, and G. Cheng, “Model predictive control of a soft elbow exosuit reduces interaction torque,” 2023 11th International IEEE/EMBS Conference on Neural Engineering (NER), 2023. doi:10.1109/ner52421.2023.10123906
15. L. Sy et al., “M-sam: Miniature and soft artificial muscle-driven wearable robotic fabric exosuit for upper limb augmentation,” 2021 IEEE 4th International Conference on Soft Robotics (RoboSoft), 2021. doi:10.1109/robosoft51838.2021.9479333
16. S. J. Park, K. Choi, H. Rodrigue, and C. H. Park, “Soft exosuit based on fabric muscle for upper limb assistance,” IEEE/ASME Transactions on Mechatronics, vol. 28, no. 1, pp. 26–37, 2023. doi:10.1109/tmech.2022.3194975
17. F. Cleary, W. Srisa-an, D. C. Henshall, and S. Balasubramaniam, “Dynamic field-programmable logic-driven soft exosuit,” IEEE Sensors Journal, vol. 23, no. 10, pp. 10935–10949, 2023. doi:10.1109/jsen.2023.3265514
18. C. Ott, R. Mukherjee, and Y. Nakamura, “Unified impedance and admittance control,” 2010 IEEE International Conference on Robotics and Automation, 2010.
19. J. L. Samper-Escudero, A. F. Contreras-González, M. Ferre, M. A. Sánchez-Urán, and D. Pont-Esteban, “Efficient multiaxial shoulder-motion tracking based on flexible resistive sensors applied to exosuits,” Soft Robotics, vol. 7, no. 3, pp. 370–385, 2020. doi:10.1089/soro.2019.0040
20. A. Ghosh, K. Nath, M. K. Bera, and S. H. Laskar, “Design of Adaptive Gravity Compensation Controller for upper limb exosuit: The concurrent learning-based approach,” 2022 Eighth Indian Control Conference (ICC), 2022. doi:10.1109/icc56513.2022.10093439
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).