A Review on Hybrid FES-Robotic Control Strategies of Lower-Limb Exoskeleton Robots for Gait Rehabilitation
Meng Lin1, Hou Jie1, Dong Hongtao1, Liu Yuan1, Xu Rui2, Ming Dong1,2#*
1(Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China 300072) 2(School of Precision Instrument and Optoelectrionics Engineering, Tianjin University, Tianjin, China 300072)
Abstract:Motion rehabilitation plays a significant role in encouraging neuroplasticity and improving motor functions of patients with spinal cord injuries or strokes. In recent years, the incorporation of functional electrical stimulation (FES) and exoskeleton robots has gradually become a research hotspot in the field as the method takes advantages of both rehabilitation technologies while complementing each other. This article introduced a comprehensive review of hybrid FES-robotic control strategies by analyzing technical difficulties from the aspects ofunidirectional FES-orthosis control strategies and cooperative FES-exoskeleton control strategies. We discussed the key problems and potential solutions to design an optimized cooperative control strategy based on a closed-loop human-computer interaction to realize dynamic control allocation and therefore maximize active rehabilitation performance of patients. Finally, we prospected future development of the hybrid rehabilitation technology.
作者简介: #中国生物医学工程学会会员(Member, Chinese Society of Biomedical Engineering)
引用本文:
孟琳, 侯捷, 董洪涛, 刘源, 徐瑞, 明东. 融合功能性电刺激的助行康复外骨骼机器人混合控制策略研究进展[J]. 中国生物医学工程学报, 2022, 41(3): 328-338.
Meng Lin, Hou Jie, Dong Hongtao, Liu Yuan, Xu Rui, Ming Dong. A Review on Hybrid FES-Robotic Control Strategies of Lower-Limb Exoskeleton Robots for Gait Rehabilitation. Chinese Journal of Biomedical Engineering, 2022, 41(3): 328-338.
[1] Avan A, Digaleh H, Napoli MD, et al. Socioeconomic status and stroke incidence, prevalence, mortality, and worldwide burden: An ecological analysis from the Global Burden of Disease Study 2017 [J]. BMC Medicine, 2019, 17(1): 191. [2] Arnao V, Acciarresi M, Cittadini E, et al. Stroke incidence, prevalence and mortality in women worldwide [J]. International Journal of Stroke, 2016, 11(3): 287-301. [3] Shmuel S, Yocheved L, Becher, et al. Dual-channel functional electrical stimulation improvements in speed-based gait classifications [J]. Clinical Interventions in Aging, 2013, 8: 271-277. [4] Mountain A, Lindsay MP, Teasell R, et al. Canadian stroke best practice recommendations: Rehabilitation, recovery, and community participation following stroke. Part two: transitions and community participation following stroke [J]. International Journal of Stroke, 2020, 15(7): 789-806. [5] Schaechter JD. Motor rehabilitation and brain plasticity after hemiparetic stroke [J]. Progress in Neurobiology, 2004, 73(1): 61-72. [6] Hara Y. Rehabilitation with functional electrical stimulation in stroke patients [J]. International Journal of Physical Medicine & Rehabilitation, 2013, 1(6): 1-6. [7] Lynch CL, Popovic MR. Functional electrical stimulation [J]. Scand J Rehabil Med Suppl, 2008, 28(2): 40-50. [8] Popovi DB. Advances in functional electrical stimulation (FES) [J]. Journal of Electromyography & Kinesiology Official Journal of the International Society of Electrophysiological Kinesiology, 2014, 24(6): 795-802. [9] Lieberson WT, Holmquest HJ, Scott D, et al. Functional electrotherapy: Stimulation of the peroneal nerve synchronized with the swing phase of the gait of hemiplegic patients [J]. Archives of Physical Medicine and Rehabilitation, 1961, 42: 101-105. [10] Auchstaetter N, Luc J, Lukye S, et al. Physical therapists' use of functional electrical stimulation for clients with stroke: Frequency, barriers, and facilitators [J]. Physical Therapy, 2016, 96(7): 995-1005. [11] Melo PL, Silva MT, Martins JM, et al. Technical developments of functional electrical stimulation to correct drop foot: Sensing, actuation and control strategies [J]. Clinical Biomechanics, 2015, 30(2): 101-113. [12] Marquez-Chin C, Popovic MR. Functional electrical stimulation therapy for restoration of motor function after spinal cord injury and stroke: A review [J]. Biomedical Engineering Online, 2020, 19(1): 34. [13] Houston DJ, Lee JW, Unger J, et al. Functional electrical stimulation plus visual feedback balance training for standing balance performance among individuals with incomplete spinal cord injury: A case series [J]. Frontiers in Neurology, 2020, 11: 680. [14] Kapadia N, Moineau B, Popovic MR. Functional electrical stimulation therapy for retraining reaching and grasping after spinal cord injury and stroke [J]. Frontiers in Neuroscience, 2020, 14: 718. [15] 刘加鹏, 王卫宁, 梁思捷, 等. 多通道功能性电刺激踏车训练对脑卒中患者步行功能的影响 [J]. 中国康复医学杂志, 2021, 362): 182-185. [16] Kastalskiy IA, Khoruzhko KA, Skvortsov DV. A functional electrical stimulation system for integration in an exoskeleton [J]. Sovremennye Tehnologii V Medicine, 2018, 10(3): 104-108. [17] Hobbs B, Artemiadis P. A review of robot-assisted lower-limb stroke therapy: Unexplored paths and future directions in gait rehabilitation [J]. Frontiers in Neurorobotics, 2020, 14: 19. [18] 褚梦秋, 佀国宁, 李根生, 等. 下肢康复机器人控制系统研究进展 [J]. 北京生物医学工程, 2018, 37(6): 643-649, 656. [19] Ekelem A, Goldfarb M. Supplemental stimulation improves swing phase kinematics during exoskeleton assisted gait of SCI subjects with severe muscle spasticity [J]. Frontiers in Neuroscience, 2018, 12: 374. [20] Reyes RD, Kobetic R, Nandor M, et al. Effect of joint friction compensation on a "muscle-first" motor-assisted hybrid neuroprosthesis [J]. Frontiers in Neurorobotics, 2020, 14: 588950. [21] Vallery H, Stützle T, Buss M, et al. Control of a hybrid motor prosthesis for the knee joint [J]. IFAC Proceedings Volumes, 2005, 38(1): 76-81. [22] del-Ama AJ, Koutsou AD, Moreno JC, et al. Review of hybrid exoskeletons to restore gait following spinal cord injury [J]. Journal of Rehabilitation Research and Development, 2012, 49(4): 497-514. [23] Kobetic R, To CS, Schnellenberger JR, et al. Development of hybrid orthosis for standing, walking, and stair climbing after spinal cord injury [J]. Journal of Rehabilitation Research & Development, 2015, 46(3): 447-462. [24] Cousin CA, Rouse CA, Duenas VH, et al. Position and torque control via rehabilitation robot and functional electrical stimulation [C]//International Conference on Rehabilitation Robotics (ICORR). London: IEEE, 2017: 38-43. [25] Durfee WK, Rivard A. Design and simulation of a pneumatic, stored-energy, hybrid orthosis for gait restoration [J]. Journal of Biomechanical Engineering-Transactions of the Asme, 2005, 127(6): 1014-1019. [26] Krishnamoorthy V, Hsu W, Scholz J, et al. Gait training after stroke: A pilot study combining a gravity-balanced orthosis, functional electrical stimulation, and visual feedback [J]. Journal of Neurologic Physical Therapy(JNPT), 2008, 32(4): 192-202. [27] Farris RJ, Quintero HA, Withrow TJ, et al. Design of a joint-coupled orthosis for FES-aided gait [C]//International Conference on Rehabilitation Robotics(ICORR). Kyoto: IEEE, 2009: 285-291. [28] Bulea TC, Kobetic R, Audu ML, et al. Finite state control of a variable impedance hybrid neuroprosthesis for locomotion after paralysis [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2013, 21(1): 141-151. [29] Chang SR, Nandor MJ, Li L, et al. A muscle-driven approach to restore stepping with an exoskeleton for individuals with paraplegia [J]. Journal of Neuroengineering & Rehabilitation, 2017, 14(48): 1-12. [30] Seel T, Werner C, Raisch J, et al. Iterative learning control of a drop foot neuroprosthesis - generating physiological foot motion in paretic gait by automatic feedback control [J]. Control Engineering Practice, 2016, 48: 87-97. [31] Jailani R, Tokhi MO, Gharooni SC, et al. FES-assisted walking with spring brake orthosis: simulation studies [J]. Applied Bionics and Biomechanics, 2011, 8(1): 115-126. [32] Stauffer Y, Allemand Y, Bouri M, et al. The walktrainer - a new generation of walking reeducation device combining orthoses and muscle stimulation [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2009, 17(1): 38-45. [33] Kirsch N, Alibeji N, Fisher L, et al. A semi-active hybrid neuroprosthesis for restoring lower limb function in paraplegics [C] //IEEE Engineering in Medicine and Biology Society Conference Proceedings. Chicago: IEEE, 2014: 2557-2560. [34] Murray SA, Farris RJ, Golfarb M, et al. FES coupled with a powered exoskeleton for cooperative muscle contribution in persons with paraplegia [C]//IEEE Engineering in Medicine and Biology Society Conference Proceedings. Honolulu: IEEE, 2018: 2788-2792. [35] Kurokawa N, Yamamoto N, Tagawa Y, et al. Development of hybrid FES walking assistive system - Feasibility study [C] //International Journal of Advanced Mechatronic Systems. Tokyo: IEEE, 2012: 93-97. [36] Alouane MA, Rifai H, Kim K, et al. Hybrid impedance control of a knee joint orthosis [J]. Industrial Robot - the International Journal of Robotics Research and Application, 2019, 46(2): 192-201. [37] Ha KH, Quintero HA, Farris RJ, et al. Enhancing stance phase propulsion during level walking by combining FES with a powered exoskeleton for persons with paraplegia [C] //IEEE Engineering in Medicine and Biology Society Conference Proceedings. San Diego: IEEE, 2012: 344-347. [38] Ha KH, Murray SA, Goldfarb M. An approach for the cooperative control of FES with a powered exoskeleton during level walking for persons with paraplegia [J]. IEEE Transactions on Neural Systems & Rehabilitation Engineering, 2016, 24(4): 455-466. [39] del-Ama, Antonio J, et al. Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton [J]. Journal of NeuroEngineering & Rehabilitation (JNER), 2014, 11(1): 1-29. [40] Quintero HA, Farris RJ, Ha K, et al. Preliminary assessment of the efficacy of supplementing knee extension capability in a lower limb exoskeleton with FES [C]//IEEE Engineering in Medicine and Biology Society Conference Proceedings. San Diego: IEEE, 2012: 3360-3363. [41] Kirsch NA, Alibeji NA, Sharma N. Model predictive control-based dynamic control allocation in a hybrid neuroprosthesis [C] //Proceedings of the ASME Dynamic Systems and Control Conference. San Antonio: IEEE, 2014: 6133-6140. [42] Kirsch NA, Alibeji NA, Sharma N. Nonlinear model predictive control of functional electrical stimulation [J]. Control Engineering Practice, 2017, 58: 319-331. [43] Bao X, Kirsch NA, Dodson A, et al. Model predictive control of a feedback-linearized hybrid neuroprosthetic system with a barrier penalty [J]. Journal of Computational and Nonlinear Dynamics, 2019, 14(10) : 101009. [44] Kirsch NA, Bao X, Alibeji NA, et al. Model-based dynamic control allocation in a hybrid neuroprosthesis [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2018, 26(1): 224-232. [45] Alibeji NA, Kirsch NA, Sharma N. An adaptive low-dimensional control to compensate for actuator redundancy and FES-induced muscle fatigue in a hybrid neuroprosthesis [J]. Control Engineering Practice, 2017, 59: 204-219. [46] Alibeji NA, Andrew KN, Nitin S. A muscle synergy-inspired adaptive control scheme for a hybrid walking neuroprosthesis [J]. Frontiers in Bioengineering and Biotechnology, 2015, 3: 1-13. [47] Alibeji NA, Vahidreza M, Dicianno BE, et al. A control scheme that uses dynamic postural synergies to coordinate a hybrid walking neuroprosthesis: Theory and experiments [J]. Frontiers in Neuroscience, 2018, 12: 159. [48] Romero-Sánchez F, Bermejo-García J, Barrios-Muriel J, et al. Design of the cooperative actuation in hybrid orthoses: A theoretical approach based on muscle models [J]. Frontiers in Neurorobotics, 2019, 13: 1-15. [49] 任勇. 融合功能性电刺激的下肢外骨骼机器人协同控制研究 [D]. 上海:上海交通大学, 2015. [50] Zhang Dingguo, Ren Yong, Gui Kai, et al. Cooperative control for a hybrid rehabilitation system combining functional electrical stimulation and robotic exoskeleton [J]. Frontiers in Neuroscience, 2017, 11: 725. [51] Chen Yixiong, Hu Jin, Peng Long, et al. The FES-assisted control for a lower limb rehabilitation robot: Simulation and experiment [J]. Robotics and Biomimetics, 2014, 1(1): 1-20. [52] Ferrarin M, Palazzo F, Riener R, et al. Model-based control of FES-induced single joint movements [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2001, 9(3): 245-257. [53] Riener R, Fuhr T. Patient-driven control of FES-supported standing up: A simulation study [J]. IEEE Transactions on Rehabilitation Engineering, 1998, 6(2): 113-124. [54] Chiovetto E, Berret B, Delis I, et al. Investigating reduction of dimensionality during single-joint elbow movements: a case study on muscle synergies [J]. Front Comput Neurosci, 2013, 7: 1-11. [55] Endo G, Morimoto J, Matsubara T, et al. Learning CPG-based biped locomotion with a policy gradient method: Application to a humanoid robot [J]. International Journal of Robotics Research, 2008, 27(2): 213-228. [56] Liu Chengju, Wang Danwei, Chen Qijun. Central pattern generator inspired control for adaptive walking of biped robots [J]. IEEE Transactions on Systems Man Cybernetics-Systems, 2013, 43(5): 1206-1215. [57] Bai Long, Hu Hao, Chen Xiaohong, et al. CPG-based gait generation of the curved-leg hexapod robot with smooth gait transition [J]. Sensors, 2019, 19(17): 3705. [58] Noda S, Sugai F, Kojima K, et al. Semi-passive walk and active walk by one bipedal robot: mechanism, control and parameter identification [J]. International Journal of Humanoid Robotics, 2020, 17(2): 2050012. [59] Hargrove LJ, Young AJ, Simon AM, et al. Intuitive control of a powered prosthetic leg during ambulation a randomized clinical trial [J]. Jama-Journal of the American Medical Association, 2015, 313(22): 2244-2252. [60] Wang Meng, Li Renjie, Zhang Ruofan, et al. A wearable SSVEP-based BCI system for quadcopter control using head-mounted device [J]. IEEE Access, 2018, 6(99): 26789-26798. [61] Irimia DC, Poboroniuc MS, Serea F, et al. Controlling a FES-exoskeleton rehabilitation system by means of brain-computer interface [C]//International Conference and Exposition on Electrical and Power Engineering. Lasi: IEEE, 2016: 352-355. [62] Poboroniuc MS, Irimia DC. FES&BCI based rehabilitation engineered equipment: Clinical tests and perspectives [C] //E-Health and Bioengineering Conference. Sinaia: IEEE, 2017: 77-80. [63] Clancy EA, Liu Lukai, Liu Pu, et al. Identification of constant-posture EMG-torque relationship about the elbow using nonlinear dynamic models [J]. IEEE Transactions on Biomedical Engineering, 2011, 59(1): 205-212. [64] Sartori M, Reggiani M, Pagello E, et al. Modeling the human knee for assistive technologies [J]. IEEE Transactions on Biomedical Engineering, 2012, 59(9): 2642-2649. [65] Sartori M, Farina D, Lloyd DG. Hybrid neuromusculoskeletal modeling to best track joint moments using a balance between muscle excitations derived from electromyograms and optimization [J]. Journal of Biomechanics, 2014, 47(15): 3613-3621. [66] Duenas VH, Cousin CA, Ghanbari V, et al. Torque and cadence tracking in functional electrical stimulation induced cycling using passivity-based spatial repetitive learning control [J]. Automatica, 2020, 115: 118852. [67] Wolpaw JR, Birbaumer N, Heetderks WJ, et al. Brain-computer interface technology: A review of the first international meeting [J]. IEEE Transactions on Rehabilitation Engineering, 2000, 8(2): 164-173. [68] 周晓宇, 许敏鹏, 肖晓琳, 等. 脑-机接口中脑电解码算法研究综述 [J]. 生物医学工程学杂志, 2019, 36(5): 856-861. [69] Krueger J, Reichert C, Duerschmid S, et al. Brain-computer interface-driven functional electrical stimulation for motor rehabilitation following stroke [J]. Klinische Neurophysiologie, 2020, 51(3): 144-155. [70] Kawala-Sterniuk A, Browarska N, Al-Bakri A, et al. Summary of over fifty years with brain-computer interfaces - a review [J]. Brain Sciences, 2021, 11(1): 43. [71] 姚林, 张定国, 王颖. 脑机接口控制的下肢功能性电刺激系统研究 [J]. 中国生物医学工程学报, 2012, 31(5): 690-696. [72] Guggenberger R, Heringhaus M, Gharabaghi A. Brain-machine neurofeedback: Robotics or electrical stimulation? [J]. Frontiers in Bioengineering and Biotechnology, 2020, 8: 639. [73] Miao Yangyang, Chen Shugeng, Zhang Xinru, et al. BCI-based rehabilitation on the stroke in sequela stage [J]. Neural Plasticity, 2020, 2020: 8882764. [74] Chung E, Park SI, Jang YY, et al. Effects of brain-computer interface-based functional electrical stimulation on balance and gait function in patients with stroke: Preliminary results [J]. Journal of Physical Therapy Science, 2015, 27(2): 513-516.