Chinese Journal of Tissue Engineering Research ›› 2025, Vol. 29 ›› Issue (24): 5127-5133.doi: 10.12307/2025.757

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A wearable exoskeleton with posture feedback improves abnormal gait in patients with stroke 

Cao Haijie, Song Huijie, Sun Yalu, Zhang Guangyou, Li Xiang   

  1. Department of Rehabilitation Medicine, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
  • Received:2024-07-01 Accepted:2024-09-21 Online:2025-08-28 Published:2025-01-24
  • Contact: Li Xiang, Associate professor, Department of Rehabilitation Medicine, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
  • About author:Cao Haijie, MS, Technologist-in-charge, Department of Rehabilitation Medicine, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong Province, China
  • Supported by:
    Seedling Project of Affiliated Hospital of Jining Medical University, No. MP-MS-2021-009 (to SHJ)

Abstract: BACKGROUND: Increasing evidence has indicated that early reinforcement of correct posture is particularly important for improving abnormal gait in stroke patients. Wearable exoskeleton-assisted training can improve patients’ walking function in a short period of time, and can also assist the coordinated movement of muscles around the pelvis, hip, knee, and ankle joints, control the walking trajectory of the lower limbs, and improve walking ability in patients with stroke.
OBJECTIVE: To explore the improvement of abnormal gait in stroke patients by a wearable exoskeleton with posture feedback, and to explore the rehabilitation mechanism.
METHODS: A total of 52 patients in the recovery period of stroke admitted to the Affiliated Hospital of Jining Medical College from January 2023 to January 2024 were included in this study and randomly divided into an experimental group (n=26) and a control group (n=26) using a random number table method. Based on conventional rehabilitation training, the patients in the experimental group participated in training using a wearable exoskeleton with posture feedback (15 minutes per day, 6 times per week), while those in the control group were given conventional gait therapy (15 minutes per day, 6 times per week). Training in each group lasted for 4 weeks. Before and after training, the lower limb motor function scores, gait parameters (step length, step speed, step width) and gait symmetry were compared between the two groups, and the brain functional connectivity values of the prefrontal motor area, the primary motor cortex and the sensorimotor area were detected using portable near-infrared spectroscopy.
RESULTS AND CONCLUSION: After training, lower limb motor function scores, gait parameters and gait symmetry were significantly improved in the two groups (P < 0. 05).  Meanwhile, the experimental group was superior to the control group in terms of gait parameters and gait symmetry (P < 0.05). Brain functional connectivity values of the right sensorimotor area-left prefrontal motor area and right sensorimotor area-right prefrontal motor area were significantly increased in the two groups after training (P < 0.05). The functional connectivity values of the left sensorimotor area-right primary motor cortex and left sensorimotor area-left primary motor cortex in the experimental group were increased after training (P < 0.05). Compared with the control group, the functional connectivity values of the left sensorimotor area-right primary motor cortex and left sensorimotor area-left primary motor cortex were increased in the experimental group after training (P < 0.05). To conclude, based on conventional rehabilitation training, a wearable exoskeleton with posture feedback can not only effectively improve the abnormal gait of stroke patients, but also activate the functional sensorimotor areas of the brain associated with abnormal gait. 

中国组织工程研究杂志出版内容重点:组织构建;骨细胞;软骨细胞;细胞培养;成纤维细胞;血管内皮细胞;骨质疏松;组织工程

Key words: functional near-infrared spectroscopy, posture feedback training, wearable exoskeleton, stroke, rehabilitation training, engineered materials

CLC Number: