Abstract: This paper presents a sensor-guided gait-synchronization system to help potential unilateral knee-injured people walk normally with a weight-supported lower-extremity-exoskeleton (LEE). This relieves the body weight loading on the knee-injured leg and synchronizes its motion with that of the healthy leg during the swing phase of walking. The sensor-guided gait-synchronization system is integrated with a body sensor network designed to sense the motion/gait of the healthy leg. Guided by the measured joint-angle trajectories, the motorized hip joint lifts the links during walking and synchronizes the knee-injured gait with the healthy gait by a half-cycle delay. The effectiveness of the LEE is illustrated experimentally. We compare the measured joint-angle trajectories between the healthy and knee-injured legs, the simulated knee forces, and the human-exoskeleton interaction forces. The results indicate that the motorized hip-controlled LEE can synchronize the motion/gait of the combined body-weight-supported LEE and injured leg with that of the healthy leg.

潜在用于单侧膝受伤患者的传感引导步态同步下肢外骨骼

[1]Barton G, Lisboa P, Lees A, et al., 2007. Gait quality assessment using self-organising artificial neural networks. Gait Post, 25(3):374-379.

[2]Brophy R, Silvers HJ, Gonzales T, et al., 2010. Gender influences: the role of leg dominance in ACL injury among soccer players. Br J Sports Med, 44(10):694-697.

[3]Chen B, Zhong CH, Zhao X, et al., 2019. Reference joint trajectories generation of CUHK-EXO exoskeleton for system balance in walking assistance. IEEE Access, 7:33809-33821.

[4]Chen G, Qi P, Guo Z, et al., 2017. Gait-event-based synchronization method for gait rehabilitation robots via a bioinspired adaptive oscillator. IEEE Trans Biomed Eng, 64(6):1345-1356.

[5]Dollar AM, Herr H, 2008. Lower extremity exoskeletons and active orthoses: challenges and state-of-the-art. IEEE Trans Robot, 24(1):144-158.

[6]Gupta R, Khanna T, Masih GD, et al., 2016. Acute anterior cruciate ligament injuries in multisport elite players: demography, association, and pattern in different sports. J Clin Orthop Trauma, 7(3):187-192.

[7]He Y, Li N, Wang C, et al., 2019. Development of a novel autonomous lower extremity exoskeleton robot for walking assistance. Front Inform Technol Electron Eng, 20(3):318-329.

[8]Herzog W, Read LJ, 1993. Lines of action and moment arms of the major force-carrying structures crossing the human knee joint. J Anat, 182(2):213-230.

[9]Hootman JM, Dick R, Agel J, 2007. Epidemiology of collegiate injuries for 15 sports: summary and recommendations for injury prevention initiatives. J Athl Train, 42(2):311-319.

[10]Kang I, Kunapuli P, Young AJ, 2020. Real-time neural network-based gait phase estimation using a robotic hip exoskeleton. IEEE Trans Med Robot Bion, 2(1):28-37.

[11]Kellis E, 2001. Tibiofemoral joint forces during maximal isokinetic eccentric and concentric efforts of the knee flexors. Clin Biomech, 16(3):229-236.

[12]Kim H, Shin YJ, Kim J, 2017. Design and locomotion control of a hydraulic lower extremity exoskeleton for mobility augmentation. Mechatronics, 46:32-45.

[13]Lee KM, Wang DH, 2015. Design analysis of a passive weight-support lower-extremity-exoskeleton with compliant knee-joint. Proc IEEE Int Conf on Robotics and Automation, p.5572-5577.

[14]Li GY, Liu T, Yi JG, et al., 2016. The lower limbs kinematics analysis by wearable sensor shoes. IEEE Sens J, 16(8):2627-2638.

[15]Li ZJ, Ren Z, Zhao KK, et al., 2020. Human-cooperative control design of a walking exoskeleton for body weight support. IEEE Trans Ind Inform, 16(5):2985-2996.

[16]Lin F, Wang AS, Zhuang Y, et al., 2016. Smart insole: a wearable sensor device for unobtrusive gait monitoring in daily life. IEEE Trans Ind Inform, 12(6):2281-2291.

[17]Liu Q, Qian GM, Meng W, et al., 2019. A new IMMU-based data glove for hand motion capture with optimized sensor layout. Int J Intell Robot Appl, 3:19-32.

[18]Liu XH, Wang QN, 2020. Real-time locomotion mode recognition and assistive torque control for unilateral knee exoskeleton on different terrains. IEEE/ASME Trans Mechatron, 25(6):2722-2732.

[19]Long Y, Du ZJ, Wang WD, et al., 2018. Physical human-robot interaction estimation based control scheme for a hydraulically actuated exoskeleton designed for power amplification. Front Inform Technol Electron Eng, 19(9):1076-1085.

[20]Lugade V, Lin V, Farley A, et al., 2014. An artificial neural network estimation of gait balance control in the elderly using clinical evaluations. PLoS ONE, 9(5):e97595.

[21]Malcolm P, Galle S, van den Berghe P, et al., 2018. Exoskeleton assistance symmetry matters: unilateral assistance reduces metabolic cost, but relatively less than bilateral assistance. J Neuroeng Rehabil, 15(1):74.

[22]Mizukami N, Takeuchi S, Tetsuya M, et al., 2018. Effect of the synchronization-based control of a wearable robot having a non-exoskeletal structure on the hemiplegic gait of stroke patients. IEEE Trans Neur Syst Rehabil Eng, 26(5):1011-1016.

[23]Thambyah A, Pereira BP, Wyss U, 2005. Estimation of bone-on-bone contact forces in the tibiofemoral joint during walking. Knee, 12(5):383-388.

[24]Tsukahara A, Hasegawa Y, Eguchi K, et al., 2015. Restoration of gait for spinal cord injury patients using HAL with intention estimator for preferable swing speed. IEEE Trans Neur Syst Rehabil Eng, 23(2):308-318.

[25]Uddin MZ, Hassan MM, Alsanad A, et al., 2020. A body sensor data fusion and deep recurrent neural network-based behavior recognition approach for robust healthcare. Inform Fus, 55:105-115.

[26]Wang DH, Lee KM, Ji JJ, 2016. A passive gait-based weight-support lower extremity exoskeleton with compliant joints. IEEE Trans Robot, 32(4):933-942.

[27]Wang TM, Pei X, Hou TG, et al., 2020. An untethered cable-driven ankle exoskeleton with plantarflexion-dorsiflexion bidirectional movement assistance. Front Inform Technol Electron Eng, 21(5):723-739.

[28]Wang ZL, Zhao HY, Qiu S, et al., 2015. Stance-phase detection for ZUPT-aided foot-mounted pedestrian navigation system. IEEE Trans Mechatron, 20(6):3170-3181.

[29]Yu H, Wang DH, Yang CJ, et al., 2010. A walking monitoring shoe system for simultaneous plantar-force measurement and gait-phase detection. Proc IEEE/ASME Int Conf on Advanced Intelligent Mechatronics, p.207-212.

[30]Zhang C, Liu GF, Li CL, et al., 2016. Development of a lower limb rehabilitation exoskeleton based on real-time gait detection and gait tracking. Adv Mech Eng, 8(1):1-9.

[31]Zhang T, Tran M, Huang H, 2018. Design and experimental verification of hip exoskeleton with balance capacities for walking assistance. IEEE/ASME Trans Mechatron, 23(1):274-285.

[32]Zheng NQ, Fleisig GS, Escamilla RF, et al., 1998. An analytical model of the knee for estimation of internal forces during exercise. J Biomech, 31(10):963-967.