ArticleInternational journal of legal medicine2025
Validation of computational models simulating injury-related kinematics with muscle activation - obtaining data under general anaesthesia.
Article in International journal of legal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Reconstructing injury-related movements and reactions in forensic biomechanics (e.g. abusive head trauma, whiplash, or falls) requires biofidelic representations of the human body. Muscle tone and activity can be integrated into these computational human body models. However, obtaining high-quality data on passive joint behaviour, which is crucial for ensuring accurate simulation results, remains challenging. A challenge in volunteer experiments is the high kinematic variability affecting passive responses. This study investigates differences in gravity-induced knee flexion between anaesthetised and awake subjects, aiming to clarify how muscle tone influences passive behaviour. Knee flexion kinematics and vastus lateralis activity were measured in eleven patients scheduled for surgery. Three tests were performed while patients were awake, two following propofol sedation, and three after administering a muscle relaxant. In awake trials, median duration to reach 47° knee flexion was 404 ms, compared to 355 ms for anaesthetised and 349 ms for anaesthetised + relaxed. Significant differences were found between anaesthetised + relaxed (p = < 0.001) and between anaesthetised + relaxed versus anaesthetised (p = 0.004). Only 15% of awake trials showed no measurable muscular activity. The results indicate significant muscle tension that cannot be detected by EMG and cannot be suppressed in awake patients. This study explores the differences in gravity-induced knee flexion between anaesthetised and awake subjects, focusing on how muscle tone impacts passive responses amidst the challenges of high kinematic variability. This study offers reference data for future validation and shows how involuntary activity in non-anaesthetised subjects can enhance computational models for addressing scenarios like abusive head trauma or falls.
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