PROGRESS IN REHABILITATION ROBOT ASSISTED GAIT RECONSTRUCTION TRAINING FOR STROKE PATIENTS
Volume 2, Issue 1, Pp 1-7, 2024
DOI: 10.61784/wjbs240141
Author(s)
Jinwoo Jung
Affiliation(s)
Yonsei University, Seoul 120-749, Korea.
Corresponding Author
Jinwoo Jung
ABSTRACT
It elaborated on the high disability rate of stroke and the important position of rehabilitation robots in assisted rehabilitation training. It introduced in detail the possible mechanisms, clinical research and key technologies of different rehabilitation robots to assist stroke patients in improving hemiplegic gait, and pointed out that rehabilitation robots assist The advantages and disadvantages of gait reconstruction in stroke patients in clinical application are discussed, and it is expected that rehabilitation robots should develop towards intelligent, precise, convenient and family-oriented in the future to better assist the gait reconstruction training of stroke patients.
KEYWORDS
Rehabilitation robot; Stroke; Gait reconstruction; Hemiplegic gait; Rehabilitation training
CITE THIS PAPER
Jinwoo Jung. Progress in rehabilitation robot assisted gait reconstruction training for stroke patients. World Journal of Biomedical Sciences. 2024, 2(1): 1-7. DOI: 10.61784/wjbs240141.
REFERENCES
[1] CHUMNEY D, NOLLINGER K, SHESKO K. Ability of functional independence measure to accurately predict functional outcome of stroke-specific population: systematic re-view. J Rehabil Res Dev, 2010, 47(1): 17-29.
[2] WU S,WU B.LIU M. Stroke in China: advances and challenges in epidemiology, prevention, and management. Lancet Neurol, 2019, 18(4): 394-405.
[3] AN B, WOO Y, PARK K. Effects of insole on the less affected side during execution of treadmill walking training on gait ability in chronic stroke patients: a preliminary study. Restor Neurol Neuros, 2020, 38(5): 375-384.
[4] CHEN K, ZHENG YH, WEI J A. Exercise training improves motorskill learning via selective activation of mTOR. Sci Adv, 2019, 5(7): eaaw1888.
[5] Zhang Tong, Zhao Jun, Bai Yulong. Chinese Clinical Management Guidelines for Cerebrovascular Disease (Extracted Version) Stroke Rehabilitation Management. Chinese Journal of Stroke, 2019, 14(8): 823-831.
[6] KWAKKEL G, KOLLEN B, KREBS H I. Effects of robot assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabil Neural Repair, 2008, 22(2): 111-121.
[7] SWINNEN E, BECKW魪E D, MEEUSEN R. Does robotassisted gait rehabilitation improve balance in stroke patients? A systematic review. Top Stroke Rehabil, 2014, 21(2): 87100.
[8] MASIERO S, POLI P, ROSATI G. The value of robotic systems in stroke rehabilitation. Expert Rev Med Devic , 2014, 11(2): 187-198.
[9] GASSERT R, DIETZ V. Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective. J Neuroeng Rehabil, 2018, 15(1): 46.
[10] TENNANT KA, TAYLOR SL, WHITE E R. Optogenetic rewiring of thalamocortical circuits to restore function in the stroke injured brain. Nat Commun, 2017, 8: 15879.
[11] SUN H, LI A, HOU T T. Neurogenesis promoted by the CD200/CD200R signaling pathway following treadmill exercise enhances post-stroke functional recovery in rats. Brain Behav Immun, 2019, 82: 354-371.
[12] Li Kunbin, Wu Zhiyuan, Wu Yanzhi. Preliminary observation of the impact of lower limb rehabilitation robot training on brain function reconstruction in patients with ischemic stroke. Journal of Stroke and Neurological Diseases, 2019, 36(5): 420-424.
[13] XIE QF, CHENG JY, PAN G Y. Treadmill exercise ameliorates focal cerebral ischemia/reperfusion-induced neurological deficit by promoting dendritic modification and sy-naptic plasticity via upregulating caveolin-1/VEGF signaling pathways. Exp Neurol, 2019, 313: 60-78.
[14] Lu Liping, Sander Chun, Ji Shufeng. Effect of lower limb rehabilitation robot training on motor ability and daily living activities of patients with hemiplegia after stroke. Chinese Rehabilitation Theory and Practice, 2016, 22(10): 1 200-1 203.
[15] Liu Chang, Qie Shuyan, Wang Hanming. Effect of lower limb rehabilitation robot on lower limb motor function and walking ability in stroke and hemiplegic patients. Chinese Rehabilitation Theory and Practice, 2017, 23(6): 696-700.
[16] CALABRO RS, NARO A, RUSSO M. Shaping neuroplasticity by using powered exoskeletons inpatients with stroke: a randomized clinical trial. J Neuroeng Rehabil, 2018, 15(1):35.
[17] Chen Peishun, Li Taotao, Guan Hongli. Effect of foot drop walking aid combined with movable platform training on foot drop gait after stroke. Nerve Injury and Functional Reconstruction, 2020, 15(11): 670-672.
[18] Li Jianan, Meng Dianhuai. Clinical applications of gait analysis. Chinese Journal of Physical Medicine and Rehabilitation, 2006, 28(7): 500-503.
[19] Lu Wen, Zhang Jinming, Lu Zheng. Application of surface electromyography in the analysis of lower limb muscle dynamics in patients with hemiplegia. Medical Review, 2020, 26(24): 4 8834 886, 4 891.
[20] Lin Haidan, Zhang Tao, Chen Qing. Rehabilitation robot-assisted walking training is endless Effects on walking ability of patients with total spinal cord injury. Journal of Automation, 2016, 42(12): 1 832-1 838.
[21] Redebaugh, Wu Xiaolin, Zhu Rui. The impact of lower limb robot training on the test results of the three-dimensional gait analysis system in stroke and hemiplegic patients. Journal of Clinical and Experimental Medicine, 2019, 18(12): 1 323-1 327.
[22] Cheng Xue, Zhang Tao, Bai Dingqun. A preliminary study on the rehabilitation effect of A3 lower limb rehabilitation robot on assisted gait training for chronic stroke. West China Medicine, 2020, 35(5): 579-584.
[23] TOMIDA K, SONODA S, HIRANO S. Randomized Controlled trial of gait training using gait exercise assist robot (GEAR) in stroke patients with hemiplegia. J Stroke Cerebrovasc, 2019, 28(9): 2 421-2 428.
[24] OGINOT, KANATA Y, UEGAKI R. Improving abnormal gait patterns by using a Gait Exercise Assist Robot(GEAR) in chronic stroke subjects: a randomized, controlled, pilot trial. Gait Posture, 2020, 82: 45-51.
[25] WANG YJ, MUKAINO M, HIRANO S. Persistent effect of gait exercise assist robot training on gait ability and lower limb function of patients with subacute stroke: a matched case-control study with three-dimensional gait analysis. Front Neurorobotics, 2020, 14: 42.
[26] KATOH D, TANIKAWA H, HIRANO S. The effect of using Gait Exercise Assist Robot(GEAR)on gait pattern in stroke patients: a cross-sectional pilot study. Top Stroke Rehabil, 2020, 27(2): 103-109.
[27] Zheng Huanchi, Wang Junhua, Wang Chengling. A review of walking rehabilitation robots. Massage and Rehabilitation Medicine, 2019, 10(20): 1-5.
[28] Dai Jun. Effect of LOKOMAT lower limb rehabilitation robot combined with cognitive rehabilitation on the walking ability of stroke patients. Wuhan: Wuhan Institute of Physical Education, 2018.
[29] Chen Fei, Xu Jing, Guo Cuiying. Observation on the efficacy of scalp acupuncture combined with Lokomat lower limb robot in the treatment of lower limb motor dysfunction in patients with cerebral infarction. Clinical Journal of Traditional Chinese Medicine, 2021, 33(2): 326-330.
[30] U AR DE, PAKER N, BU GDAYCI D. Lokomat: a therapeutic chance for patients with chronic hemiplegia. Neuro Rehabilitation, 2014, 34(3): 447-453.
[31] VANNUNENM PM, GERRITS KHL, KONIJNENBELT M. Recovery of walking ability using a robotic device in subacute stroke patients: a randomized controlled study. Disabil Rehabil Assist Technol, 2015, 10(2): 141-148.
[32] VAN KAMMEN K, BOONSTRA A M, VAN DER WOUDE L H V. The combined effects of guidance force, bodyweight support and gait speed on muscle activity during able-bodied walking in the Lokomat. Clin Biomech(Bristol, Avon), 2016, 36: 65-73.
[33] VAN KAMMEN K, BOONSTRA A M, VAN DER WOUDE L H V. Lokomat guided gait in hemiparetic stroke pa tients: the effects of training parameters on muscle activity and temporal symmetry. Disabil Rehabil, 2020, 42(21): 2 9772 985.
[34] SWANK C, ALMUTAIRI S, WANG-PRICE S. Immediate kinematic and muscle activity changes after a single robotic exoskeleton walking session post-stroke. Top Stroke Rehabil, 2020, 27(7): 503-515.
[35] PARK I J, PARK J H, SEONG H Y. Comparative effects of different assistance force during robot-assisted gait training on locomotor functions in patients with subacute stroke: an assessor-blind, randomized controlled trial. Am J Phys Med Rehabil, 2019, 98(1): 58-64.
[36] KRISHNAN C, KOTSPOUIKIS D, DHAHER Y Y. Re-ducing robotic guidance during robot-assisted gait training improves gait function: a case report on a stroke survivor. Arch Phys Med Rehabil, 2013, 94(6): 1 202-1 206.
[37] Hu Jingran, Chen Xiaofei. Research on the impact of virtual reality technology combined with lower limb rehabilitation robot training on lower limb function and balance ability in patients with ischemic stroke. Chinese Rehabilitation, 2020, 35(12): 633-636.
[38] PARK J, CHUNG Y J. The effects of robot-assisted gait training using virtual reality and auditory stimulation on balance and gait abilities in persons with stroke. NeuroRehabilitation, 2018, 43(2): 227-235.
[39] Lu Fang, Zhu Lin, Song Weiqun. Effect of lower limb rehabilitation robot combined with virtual reality technology on lower limb function in stroke patients. Chinese Journal of Rehabilitation Medicine, 2018, 33(11): 1 301-1 306.
[40] BALLESTER BR, NIRME J, CAMACHO L. Domicliary VR -based therapy for functional recovery and cortical reorganization:randomized controlled trial in participants at the chronic stage post stroke. JMIR Serious Games, 2017, 5(3):e15.
[41] Zhang Zheng, Zhao Liping, Liang Yiwei. Research on the trajectory tracking control method of lower limb exoskeleton based on differential gear train. Coal Technology, 2015, 34(4): 305-307.
[42] Wu Qinghong, Li Jian, Liu Huan. Control technology of lower limb exoskeleton robot based on fuzzy PID. Journal of Guangxi University of Science and Technology, 2020, 31(4): 104-111.
[43] Huang Jintao, Li Ying, Zeng Jianping. Gait trajectory tracking control of lower limb exoskeleton robot in passive mode. Journal of Xiamen University (Natural Science Edition), 2020, 59 (1): 108-115.
[44] Zhang Xiaodong, Chen Jiangcheng, Yin Gui. Myoelectric sensing and human-computer interaction control method for lower limb rehabilitation robots. Vibration, Testing and Diagnosis, 2018, 38(4): 649-657,866.
[45] NAMY, KOO B, CICHOCKI A. GOM-face: GKP, EOG, and EMG-based multimodal interface with application to humanoid robot control. IEEE Trans Biomed Eng, 2014, 61 (2): 453-462.
[46] Zhang Bi, Yao Jie, Zhao Xingang. An adaptive human-computer interaction control method based on electromyographic signals. Control Theory and Applications, 2020, 37(12): 2 5602 570.
[47] Ma Xunju. Research on gait switching control method of lower limb rehabilitation exoskeleton robot based on surface myoelectric signals. Zhengzhou: North China University of Water Resources and Hydropower, 2019.
[48] Zheng Changkun, Wang Haixian, Gu Lingyun. Lower limb movement intention recognition method based on EEG and EMG signals. Chinese Medical Equipment, 2021, 36(5): 61-66.
[49] Wang Fei, Yang Guangda, Zhang Dan. Current research status of brain-computer interface applications in robot control. Robotics Technology and Applications, 2012 (6): 12-15.
[50] HUNG E, PARK SI, JANG Y Y. Effects of brain-computer interface-based functional electrical stimulation on balance and gait function in patients with stroke: preliminary results. JPhys Ther Sci, 2015, 27(2): 513-516.
[51] Li Longfei, Zhu Lingyun, Gou Xiangfeng. Research status and development trends of wearable lower limb exoskeleton rehabilitation robots. Medical and Health Equipment, 2019, 40(12): 89-97.
[52] Chen Yi, Shi Haitao, Mao Ling. Surface electromyography characteristics of lower limb muscles in each phase of the gait cycle in stroke patients. Chinese Rehabilitation Theory and Practice, 2019, 25 (8): 956-961.
[53] Wang Rongli, Wang Ninghua. Application principles of the motor relearning theoretical system in the field of neurological rehabilitation. West China Medicine, 2020, 35(5): 519-526.