Method Article

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

DOI:

10.3791/68588

October 10th, 2025

In This Article

Summary

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This study explores the effects of a configurable soft pneumatic robot on enhancing whole-brain network topology post-stroke. Graph theory analysis indicates significant improvements in clustering coefficient, path length, and global efficiency. Findings highlight the potential of programmable robotic protocols to modulate neuroplasticity and optimize functional recovery in stroke rehabilitation.

Abstract

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Functional restoration of the cerebral cortex relies on activity-dependent neuroplasticity following stroke. However, optimizing robotic rehabilitation for hand recovery remains a significant challenge. This proof-of-concept study investigates the feasibility of a configurable soft pneumatic robot in modulating the brain network among ten participants with hand motor impairments after stroke. The programmable robotic intervention was administered in a randomized sequence for resting-state assessment, slow-mode, and fast-mode robotic therapy by adjusting working mode, action time, and interaction duration. Functional near-infrared spectroscopy (fNIRS) was employed to measure cortical activity and functional connectivity. Additionally, graph theory metrics, including clustering coefficient, average path length, small-world index, global efficiency, degree centrality, and eigenvector centrality, were derived from fNIRS-based functional connectivity matrices. The results demonstrated that robotic intervention significantly improved clustering coefficient (P = 0.034), average path length (P = 0.007), and global efficiency (P = 0.001). While small-world index, degree centrality, and eigenvector centrality showed an increasing trend, these differences did not reach statistical significance. Moreover, fast-mode therapy induced more substantial changes in clustering coefficient compared to slow-mode therapy, suggesting a potentially stronger effect on neural reorganization. These findings preliminarily support the use of soft robotics with adjustable paradigms to enhance brain network connectivity and facilitate neuroplasticity following stroke. The observed improvements in global efficiency and small-world properties indicate that robotic therapy optimizes cortical organization, promoting functional recovery. Further studies with larger sample sizes and personalized intervention protocols are needed to confirm these results and explore their long-term effects.

Introduction

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Stroke remains a leading cause of mortality and long-term disability for adults worldwide1. Among its debilitating sequelae, hand motor impairments significantly compromise essential daily activities and functional independence, thereby diminishing social participation and life quality in stroke survivors2,3. While physical medicine and rehabilitation are critical for motor recovery, conventional therapeutic approaches often yield inconsistent outcomes due to the complexity and interindividual variability of post-stroke neural reorganization4.

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Protocol

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This study was approved by the Ethics Committee of the Tongji Hospital, Wuhan, China. All research protocols adhered to the principles outlined in the Declaration of Helsinki. Written informed consent was obtained from all participants before their inclusion in the study. The equipment and software used are listed in the Table of Materials.

1. Participants

  1. Consider the following inclusion criteria:
    1. Age between 18 and 75 years.
    2. First-ever ischemic or hemorrhagic stroke confirmed by CT or MRI.
    3. Medically stable condition.
    4. Sign informed consent in person ....

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Results

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A total of 10 individuals with stroke were enrolled in the study and underwent resting-state assessment, slow-mode robotic therapy, and fast-mode robotic therapy in a randomized order. The results demonstrated the feasibility of individualizing neuroplasticity modulation by programming the robotic protocol and calculating graph theory metrics of the brain network. During soft robotic therapy, simultaneous fNIRS assessment enabled the acquisition of both brain activation and functional connectivity data.

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Discussion

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This study investigated the neuroplastic effects of a configurable soft pneumatic robot on brain network dynamics in individuals with stroke using fNIRS-based graph theory analysis. The findings suggest that soft robotic therapy effectively modulates the topological organization of distributed brain networks, with participants demonstrating high compliance. Specifically, significant changes were observed in clustering coefficient, average path length, and global efficiency. While the small-world index, degree centrality,.......

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Acknowledgements

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This work was supported by Hubei Provincial Major Science and Technology Special Project (No. 2023BCA002), Interdisciplinary Research Support Program of Huazhong University of Science and Technology (No. 2024JCYJ067), Natural Science Foundation of Hubei Province, China (No. 2024AFB043), and Research Fund of Tongji Hospital (No. 2024B24).

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
106-channel fNIRS deviceWuhan Znion Technology Co., LTDBS-2000Program implementation
FInger joint rehabilitation systemNanjing Reseader Medical Technology Co., LTD.RSD RS3Rehabilitation intervention
R softwareR FoundationVersion 4.2.1Statistic analysis
SPSS softwareIBMVersion 22.0Statistic analysis

References

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  1. He, Q., et al. Global, regional, and national burden of stroke, 1990-2021: A systematic analysis for global burden of disease 2021. Stroke. 55 (12), 2815-2824 (2024).
  2. Houwink, A., Nijland, R. H., Geurts, A. C., Kwakkel, G.

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Tags

Brain Network ModulationStroke RecoveryFunctional Near Infrared SpectroscopyClustering CoefficientGlobal EfficiencyRobotic TherapyNeuroplasticity Enhancement

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