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Final Program


Final Congress Guide

Clinical Sciences/Health Conditions

200 Section - Real-Time Multimodal Biofeedback for Enhancing Robotic Assisted Gait Training in Children with Cerebral Palsy: A Preliminary Study

Tuesday, May 19, 2026
6:00 PM - 7:30 PM PT
Objectives : Cerebral Palsy (CP) impairs movement and coordination. Robotic Assisted Gait Training (RAGT) promotes neuroplasticity, but its effectiveness depends on active patient participation. Monitoring psychophysical and motivational factors allows for personalized treatment. As part of the "AID2GAIT" project, this study evaluates a pediatric case during RAGT, monitoring physiological parameters and cortical activity to assess engagement.
 

Design: A pediatric patient underwent 12 Lokomat® sessions (30 min, 3/week) at the Padre Pio Foundation. Data were acquired at T0, T1, and T2. Clinical outcomes included WeeFIM and GMFM-88 scales. Physiological monitoring involved heart rate variability (Garmin Vivosmart 5) and facial infrared thermography (FLIR A400). Cortical activity (oxy/deoxyhaemoglobin) was measured via fNIRS in frontal and motor regions. Exoskeleton kinematic data (hip/knee) were analyzed using wavelet transform to estimate the patient's active contribution, allowing real-time parameter adjustments by the therapist.

Results: WeeFIM scores showed significant mobility improvements. GMFM-88 total net improvement was 11.6%. HRV increased by 7.5%, indicating higher engagement. Facial temperature decreased (nose -2.4%, nostrils -31.2%, corrugator -12.1%), suggesting reduced fatigue and increased well-being. Mechanical parameters showed a 22.1% increase in wavelet power, reflecting greater active contribution . fNIRS confirmed increased brain activity.

Conclusion: RAGT combined with multimodal biofeedback demonstrated satisfactory clinical and psychophysical benefits. This preliminary study establishes a basis for larger cohorts and the development of machine-learning models to predict patient engagement and optimize personalized robotic therapy.
This work was supported by the European Union - Next Generation EU, Mission 4, Component 1, CUP D53D23021770001, Project Name: AID2GAIT.