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Related Experiment Video

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Biomechanical Analysis Methods to Assess Professional Badminton Players' Lunge Performance
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Interpretable Biomechanical Feature Selection for VR Exercise Assessment Using SHAP and LDA.

Urszula Czajkowska1, Magdalena Żuk1, Michał Popek1

  • 1Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370 Wrocław, Poland.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
Summary

Virtual reality (VR) rehabilitation can objectively assess human movement quality using biomechanical features. Simplified sensor setups offer reliable insights for interpretable VR systems in clinics and homes.

Keywords:
SHapley additive explanations (SHAP)biomechanicshuman movement quality assessment (HMQA)linear discriminant analysis (LDA)motion analysisvirtual reality (VR)

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Area of Science:

  • Biomechanics
  • Rehabilitation Engineering
  • Virtual Reality

Background:

  • Virtual reality (VR) offers interactive rehabilitation but lacks objective human movement quality assessment (HMQA).
  • Identifying key biomechanical features for accurate HMQA in VR is crucial for effective rehabilitation.

Purpose of the Study:

  • To identify biomechanical features distinguishing correct from incorrect lateral lunges.
  • To determine the minimum sensors for reliable VR motion analysis, prioritizing interpretability.

Main Methods:

  • Thirty-two healthy adults performed lateral lunges recorded with a 7-sensor HTC Vive Tracker system.
  • Linear Discriminant Analysis (LDA) and SHapley Additive exPlanations (SHAP) analyzed joint angles, velocities, accelerations, and sensor distances.
  • Physiotherapist video observation classified repetitions for ground truth.

Main Results:

  • Angular features (e.g., hip flexion, knee rotation acceleration) showed higher LDA performance (F1=0.89) than distance features (F1=0.78).
  • SHAP and LDA analyses agreed on key features, including sensor-to-body spatial relations.
  • Fewer sensors can provide reliable diagnostic information, with angular features being more stable.

Conclusions:

  • Objective HMQA in VR is feasible using selected biomechanical features.
  • Simplified sensor configurations can achieve reliable and interpretable motion analysis.
  • This supports the development of accessible VR rehabilitation systems for diverse settings.