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Anthropometry and diagnostic aware deep learning for exercise assessment.

Karla Miriam Reyes Leiva1, Pavla Nikelova1, Martin Cerny1

  • 1Faculty of Electrical Engineering and Computer Science, VSB Technical University of Ostrava, Ostrava, Czech Republic.

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Summary

A new AI framework, ADA (Anthropometry and Diagnostic Aware), accurately classifies squat and Romanian deadlift technique using sensor data and personal information. This enhances movement analysis for injury prevention and personalized training feedback.

Keywords:
anthropometrybiomechanicsdeeplearningexercise assessmentpersonalized AIrehabilitationwearable sensors

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Area of Science:

  • Biomechanics
  • Machine Learning
  • Wearable Technology

Background:

  • Correct technique in strength exercises like squats and Romanian deadlifts (RDLs) is crucial for both athletic performance and preventing injuries.
  • Movement quality assessment is essential for effective training and rehabilitation programs.

Purpose of the Study:

  • To introduce ADA (Anthropometry and Diagnostic Aware), a multimodal deep-learning framework for classifying movement quality and predicting injury risk.
  • To integrate Inertial Measurement Unit (IMU) kinematics with anthropometric and diagnostic features for enhanced analysis.

Main Methods:

  • Collected 17-sensor IMU data from 15 healthy subjects performing correct and incorrect squats and RDLs.
  • Utilized a CNN-LSTM network for kinematic sequences and a fully connected network for static features, fusing them with attention weighting.

Main Results:

  • The ADA framework achieved 94.8% accuracy in movement quality classification, an improvement from 86.5% using kinematics alone.
  • Binary risk prediction accuracy reached 97.8%, with personalized fine-tuning further boosting performance by 3-5%.

Conclusions:

  • Subject-specific static features significantly enhance movement quality classification and risk stratification.
  • The ADA framework supports the development of wearable-based personalized feedback systems for training and rehabilitation.