Transformer-based Explainable AI for Biomechanical Prediction Analysis: Optimized Kinematics and Kinetics Predicition (MSc Thesis, Guided Research)

17.11.2025, Biete ...

This project aims to analyze the contribution of different input features to biomechanical prediction models based on wearable sensor data. The focus lies on applying and evaluating explainable AI (XAI) techniques to a transformer-based architecture. By integrating post-hoc interpretability methods with a state-of-the-art transformer model, the project aims to systematically quantify the impact of individual sensor features on the prediction of lower-body kinematics and kinetics.

Please refer to the attached PDF for additional information.

Kontakt: daniel.homm@tum.de

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