Background: Stroke often leads to persistent gait impairments that significantly
reduce mobility and quality of life. Conventional rehabilitation has demonstrated
therapeutic value but is limited by insufficient personalization and low
patient engagement.
Objectives: This study aimed to evaluate the clinical effectiveness of a realtime
Kinect-based motion analysis and AI-driven virtual reality (VR) gait training
system for stroke rehabilitation.
Design: Randomized controlled trial with parallel-group assignment.
Methods: Thirty stroke patients were randomly assigned to a VR-based gait
training group (n=15) or a conventional physical therapy group (n=15) for 8
weeks. The VR system integrated Kinect-based markerless motion capture, a
14-layer artificial neural network for gait parameter prediction, and immersive
VR feedback to provide personalized gait retraining. Spatiotemporal gait
parameters—including gait velocity, step length, cadence, and step width—
were assessed before and after the intervention.
Results: The VR group demonstrated significantly greater improvements in gait
velocity (0.52 to 0.73 m/s, +40.4%), step length (78.3 to 95.7 cm, +22.2%), and
cadence (100.2 to 110.4 steps/min, +10.2%) than the control group, while step
width decreased (12.3 to 9.8 cm, −20.3%), indicating enhanced balance and
stability. The artificial neural network accurately predicted movement patterns
and supported adaptive training with real-time feedback.
Conclusion: The real-time VR gait rehabilitation system effectively enhanced
gait performance and motor coordination among stroke patients, outperforming
conventional physical therapy. The integration of Kinect-based motion
capture and AI-driven personalization provides a promising platform for scalable
and clinically meaningful stroke rehabilitation.

INTRODUCTION
SUBJECTS AND METHODS
    Subjects
    Intervention
    Outcome Measures
    Sample Size Determination
    Statistical Analysis
    Blinding
    Ethical Considerations
RESULTS
DISCUSSION
CONCLUSION
FUNDING
CONFLICTS OF INTEREST
AUTHOR CONTRIBUTIONS
REFERENCES

• Lichao Chen(Department of Traditional Chinese Medicine, Shandong College of Traditional Chinese Medicine, Shandong, China)
• Yuchen Liu(Department of Physical Therapy, Kyungwoon University, Gumi, Republic of Korea)
• Peizhe Ding(Department of Physical Therapy, Kyungwoon University, Gumi, Republic of Korea)
• Shaoxuan Liu(Department of Physical Therapy, Kyungwoon University, Gumi, Republic of Korea)
• Sohee Kim(Department of Physical Therapy, Kyungwoon University, Gumi, Republic of Korea)
• Yuemei Jin(Department of Physical Therapy, Kyungwoon University, Gumi, Republic of Korea)
• Miran Goo(Department of Physical Therapy, Kyungwoon University, Gumi, Republic of Korea)
• Wansuk Choi(Department of Physical Therapy, Kyungwoon University, Gumi, Republic of Korea) Corresponding author
• Dogyu Lee(Department of Rehabilitation Medicine, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea)
• Seoa Park(College of Nursing, Kyungwoon University, Gumi, Republic of Korea)