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Current evidence and clinical applications of robotic gait training devices for motor function recovery post-stroke are increasingly available. Although existing research demonstrates that robotic gait training can improve patients' gait and balance, there remains a lack of in-depth investigation into its specific mechanisms of action concerning central nervous system (CNS) reorganization - notably, changes in activity within the motor cortex and associated neural networks. The intrinsic changes within the CNS have received insufficient attention, limiting a comprehensive and profound understanding of the rehabilitation outcomes. Therefore, this study aims to elucidate the potential mechanisms underlying robotic gait training-induced neuroplasticity by integrating functional near-infrared spectroscopy (fNIRS) technology with multi-dimensional lower limb motor function assessment tools (such as FAC, BBS, AMEDA, 10MWT, 6MWT, TUGT). It will systematically investigate the effects of robotic gait training on both the central nervous system and lower limb motor function in stroke patients. Furthermore, the study will compare the differences in functional recovery efficacy between robotic gait training and conventional rehabilitation therapies.
In this study, participants will be randomly allocated into two groups: the Welwalk training group and the conventional rehabilitation therapy group.
Welwalk Training Group: Each session will consist of 30 minutes of Welwalk robot-assisted training, followed by 15 minutes of gait training and 15 minutes of supplementary exercises.Control Group (Conventional Rehabilitation Therapy): Each session will consist of 45 minutes of gait training and 15 minutes of supplementary exercises.The intervention period will span 3 weeks, with sessions administered six times per week. Each session will last 1 hour.
Clinical assessments will be conducted by certified healthcare professionals at four time points: at baseline (prior to the commencement of formal training), and after the 1st week, 2nd week, and 3rd week of treatment.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| welwalk training | Experimental | Daily physiotherapy training using the welwalk lower limb walking training robot |
|
| conventional physical therapy | Active Comparator | Daily training using traditional physiotherapy such as core training, gait training, etc. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| welwalk training | Device | welwalk training group 30 min of welwalk robot-assisted training + 15 min of walking training + 15 min of other training per session.The intervention lasted a total of 3 weeks, 6 sessions/week, 1 hour/session. |
| Measure | Description | Time Frame |
|---|---|---|
| The Functional Ambulation Categories (FAC) | FAC is a functional walking test that evaluates ambulation ability. This 6-point scale assesses ambulation status by determining how much human support the patient requires when walking, regardless of whether or not they use a personal assistive device.The FAC uses a six-point scale from 0 to 5, where a higher score indicates better performance. | Before intervention (Week 0); After the First week of intervention (Week 1); After the Second week of intervention (Week 2); After the Third week of intervention (Week 3); |
| Measure | Description | Time Frame |
|---|---|---|
| functional near - infrared spectroscopy (fNIRS) | Using fNIRS technology to observe brain activation and brain network changes during the walking period in participants. | Before intervention (Week 0); After the First week of intervention (Week 1); After the Second week of intervention (Week 2); After the Third week of intervention (Week 3) |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Ming Kang, master of science | Contact | +8615830039916 | km04514@rjh.com.cn |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Shanghai Ruijin Hospital, affiliated to Shanghai Jiao Tong University, School of medicine, | Shanghai | Shanghai Municipality | 200025 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33675076 | Result | Zhang B, Li D, Liu Y, Wang J, Xiao Q. Virtual reality for limb motor function, balance, gait, cognition and daily function of stroke patients: A systematic review and meta-analysis. J Adv Nurs. 2021 Aug;77(8):3255-3273. doi: 10.1111/jan.14800. Epub 2021 Mar 6. | |
| 40341197 | Result | Wang C, Zhang Q, Hou S, Guo D, Han X, Huo W, Zhang Y. Split-belt treadmill training improves gait symmetry and lower limb function in patients with stroke. Sci Rep. 2025 May 8;15(1):16123. doi: 10.1038/s41598-025-98322-3. |
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We will share the demographic information and baseline clinical data of all participants.
Starting 6 months after publication
Authorized professional researchers, including but not limited to researchers engaged in neuroscience research who have obtained data access permission from their affiliated institutions, and clinical doctors from other medical institutions that have a cooperative relationship with this study and have signed data confidentiality agreements.
They can access the detailed clinical medical histories of the participants, including past disease histories and treatment process records; neurological function assessment scale data; as well as imaging data collected during the study, such as brain magnetic resonance imaging (MRI) results. However, sensitive information related to participants' privacy, such as names, ID numbers, and contact information, will be strictly anonymized to ensure that such information cannot be obtained.
They can contact the corresponding author or the first author via email.
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| ID | Term |
|---|---|
| D020521 | Stroke |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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| ID | Term |
|---|---|
| D026741 | Physical Therapy Modalities |
| ID | Term |
|---|---|
| D013812 | Therapeutics |
| D012046 | Rehabilitation |
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| physical therapy | Other | 45 min of walking training + 15 min of other training per session. The intervention lasted a total of 3 weeks, 6 sessions/week, 1 hour/session. |
|
| 10 Meter Walk Test(10WMT) |
assessing the participants' walking ability. Less time spent by patients indicates better walking ability. |
| Before intervention (Week 0); After the First week of intervention (Week 1); After the Second week of intervention (Week 2); After the Third week of intervention (Week 3) |
| Timed Up and Go Test (TUGT) | Assessment of motor function of the unaffeected and affected steering sides | Before intervention (Week 0); After the First week of intervention (Week 1); After the Second week of intervention (Week 2); After the Third week of intervention (Week 3) |
| 6minute walking test(6MWT) | Assessment of cardiorespiratory endurance in participants | Before intervention (Week 0); After the First week of intervention (Week 1); After the Second week of intervention (Week 2); After the Third week of intervention (Week 3) |
| Berg Balance Scale (BBS) | Assessment of the participant's ability to balance. The BBS is scored on a scale of 0 to 56; higher scores reflect better balance function. | Before intervention (Week 0); After the First week of intervention (Week 1); After the Second week of intervention (Week 2); After the Third week of intervention (Week 3) |
| Modified Barthel Index,MBI | Assessment of the subject's ability to perform daily living tasks.The MBI is scored on a scale of 0 to 100; higher scores reflect better ADL. | Before intervention (Week 0); After the First week of intervention (Week 1); After the Second week of intervention (Week 2); After the Third week of intervention (Week 3) |
| 39973293 | Result | Sheng Y, Han J. Biomechanical characteristics and neuromuscular action control mechanism of single-dual-task walking-conversion training in stroke patients. J Back Musculoskelet Rehabil. 2025 May;38(3):576-592. doi: 10.1177/10538127241308215. Epub 2025 Feb 12. |
| 32506008 | Result | Caliandro P, Molteni F, Simbolotti C, Guanziroli E, Iacovelli C, Reale G, Giovannini S, Padua L. Exoskeleton-assisted gait in chronic stroke: An EMG and functional near-infrared spectroscopy study of muscle activation patterns and prefrontal cortex activity. Clin Neurophysiol. 2020 Aug;131(8):1775-1781. doi: 10.1016/j.clinph.2020.04.158. Epub 2020 May 18. |
| 40533805 | Result | Li X, Zhang H, Zhang W, Wu J, Dai L, Long N, Jin T, Gu L, Chen J. Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study. J Neuroeng Rehabil. 2025 Jun 18;22(1):136. doi: 10.1186/s12984-025-01656-2. |
| 22165907 | Result | Belda-Lois JM, Mena-del Horno S, Bermejo-Bosch I, Moreno JC, Pons JL, Farina D, Iosa M, Molinari M, Tamburella F, Ramos A, Caria A, Solis-Escalante T, Brunner C, Rea M. Rehabilitation of gait after stroke: a review towards a top-down approach. J Neuroeng Rehabil. 2011 Dec 13;8:66. doi: 10.1186/1743-0003-8-66. |
| 40319228 | Result | Fan T, Zheng P, Zhang X, Gong Z, Shi Y, Wei M, Zhou J, He L, Li S, Zeng Q, Lu P, Zhao Y, Zou J, Chen R, Peng Z, Xu C, Cao P, Huang G. Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke. BMC Neurol. 2025 May 3;25(1):193. doi: 10.1186/s12883-025-04203-7. |
| 38647534 | Result | Chen S, Zhang W, Wang D, Chen Z. How robot-assisted gait training affects gait ability, balance and kinematic parameters after stroke: a systematic review and meta-analysis. Eur J Phys Rehabil Med. 2024 Jun;60(3):400-411. doi: 10.23736/S1973-9087.24.08354-0. Epub 2024 Apr 22. |
| 40140968 | Result | Hao QH, Qiu MM, Wang J, Tu Y, Lv ZH, Zhu TM. The effect of lower limb rehabilitation robot on lower limb -motor function in stroke patients: a systematic review and meta-analysis. Syst Rev. 2025 Mar 26;14(1):70. doi: 10.1186/s13643-025-02759-6. |
| 37490379 | Result | Zhang S, Fan L, Ye J, Chen G, Fu C, Leng Y. An Intelligent Rehabilitation Assessment Method for Stroke Patients Based on Lower Limb Exoskeleton Robot. IEEE Trans Neural Syst Rehabil Eng. 2023;31:3106-3117. doi: 10.1109/TNSRE.2023.3298670. Epub 2023 Aug 2. |
| 19629252 | Result | Hesse S, Mehrholz J, Werner C. Robot-assisted upper and lower limb rehabilitation after stroke: walking and arm/hand function. Dtsch Arztebl Int. 2008 May;105(18):330-6. doi: 10.3238/arztebl.2008.0330. Epub 2008 May 2. |
| 39871991 | Result | Xu S, Zhu S, Li M, Zhang T, Wang Q, Sui Y, Shen Y, Chaojie K, Zhuang R, Guo C, Wang T, Zhu L. Altered cortical activation patterns in post-stroke patients during walking with two-channel functional electrical stimulation: a functional near-infrared spectroscopy observational study. Front Neurol. 2025 Jan 13;15:1449667. doi: 10.3389/fneur.2024.1449667. eCollection 2024. |
| 33526065 | Result | Rodriguez-Fernandez A, Lobo-Prat J, Font-Llagunes JM. Systematic review on wearable lower-limb exoskeletons for gait training in neuromuscular impairments. J Neuroeng Rehabil. 2021 Feb 1;18(1):22. doi: 10.1186/s12984-021-00815-5. |
| 33069609 | Result | Scrivener K, Dorsch S, McCluskey A, Schurr K, Graham PL, Cao Z, Shepherd R, Tyson S. Bobath therapy is inferior to task-specific training and not superior to other interventions in improving lower limb activities after stroke: a systematic review. J Physiother. 2020 Oct;66(4):225-235. doi: 10.1016/j.jphys.2020.09.008. Epub 2020 Oct 14. |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |