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Related Experiment Video

Updated: Jun 17, 2026

Real-time Video Projection in an MRI for Characterization of Neural Correlates Associated with Mirror Therapy for Phantom Limb Pain
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Advancing Gait Analysis: Integrating Multimodal Neuroimaging and Extended Reality Technologies.

Vera Gramigna1, Arrigo Palumbo1, Giovanni Perri2

  • 1Department of Medical and Surgical Sciences, University "Magna Graecia", Viale Europa, 88100 Catanzaro, Italy.

Bioengineering (Basel, Switzerland)
|March 28, 2025
PubMed
Summary
This summary is machine-generated.

Advanced gait analysis combines neuroimaging and eXtended Reality (XR) for better diagnosis. This approach integrates brain activity monitoring and immersive simulations to improve understanding of human locomotion and patient outcomes.

Keywords:
biomedical applicationsextended realitygait analysismultimodal methodologies

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Area of Science:

  • Neuroscience and Biomedical Engineering
  • Focuses on the intersection of brain function, biomechanics, and advanced technology for human locomotion analysis.

Background:

  • Human gait analysis is crucial for diagnosing neuromuscular and orthopedic conditions.
  • Technological advancements enable innovative multimodal approaches combining neuroimaging and eXtended Reality (XR).

Purpose of the Study:

  • To review state-of-the-art solutions in advanced gait analysis integrating neuroimaging, XR, and sensor-based methods.
  • To explore the potential of these integrated technologies for understanding human locomotion and improving clinical applications.

Main Methods:

  • Integration of wearable neuroimaging (fNIRS, EEG) to monitor brain activity during walking.
  • Utilizing XR technologies (VR, AR, MR) for immersive gait analysis, simulation, and visualization.
  • Combining cerebral and biomechanical data for a comprehensive assessment of locomotion.

Main Results:

  • Advanced gait analysis offers real-time, high-resolution data and immersive visualization.
  • Provides enhanced understanding of brain-musculoskeletal coordination and neural mechanisms of motor control.
  • Highlights potential for improved clinical decision-making and personalized rehabilitation strategies.

Conclusions:

  • Multimodal neuroimaging and XR integration presents a transformative approach to gait analysis.
  • Challenges include data fusion, computational demands, and scalability.
  • Future research directions involve leveraging artificial intelligence for optimization and clinical translation.