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Friedrich-Alexander-Universität Lehrstuhl für Autonome Systeme und Mechatronik ASM
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  1. Friedrich-Alexander-Universität
  2. Technische Fakultät
  3. Department Elektrotechnik-Elektronik-Informationstechnik
Friedrich-Alexander-Universität Lehrstuhl für Autonome Systeme und Mechatronik ASM
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Applications of Biomechanical Simulations

In page navigation: Chair of Autonomous Systems and Mechatronics
  • Research
    • Components and Control
    • Interfaces and Interaction
    • Human-Machine-Centered Design Methods
    • Biomechanical Motion Analysis and Creation
      • Applications of Biomechanical Simulations
      • Biomechanical Assessment of Big Wave Surfing
      • Bridging the gap in ACL injury prevention with FAME: Field-based Athlete Motion Evaluation and simulation (FAME)
      • Digital Twin of the Musculoskeletal System
      • Fundamentals of Biomechanical Simulations
      • Individual Performance Prediction Using Musculoskeletal Modeling
      • Machine Learning for Personalisation of Biomechanical Movement Simulations (C01)
      • Personalization of Muscoskeletal Models
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Applications of Biomechanical Simulations

Project leader: Björn Eskofier
Project members: Marlies Nitschke, Eva Dorschky, Anne Koelewijn
Start date: 1. January 2017
End date: 31. December 2020
Funding source: adidas AG

 

Abstract

In this project, we investigate musculoskeletal modeling and simulation to analyze and understand human movement and performance. Our objective is to reconstruct human motion from measurement data for example for medical assessments or to predict human responses for virtual product development.

 

Reconstruction of Human Motion: Biomechanical analysis using wearable systems


Inertial sensor systems provide the possibility of cheap gait analysis in everyday life. One major challenge is to achieve a high quality gait analysis based on noisy sensor measurements. Moreover, inertial sensors can only quantify human joint kinematics and are not able to measure joint kinetics as performed in gait laboratories. Existing systems are based on an integration of the inertial sensor data for estimating human poses. This error-prone integration can be avoided using a computer simulation of a biomechanical model that tracks the measured sensor signals. Furthermore, such a model can give insight into joint kinetics, muscle control and other gait-related parameters such as stride length, stride time and ground-reaction force.

 

Synthesis of Human Motion: Predictive biomechanical simulation for design applications

Sports and medical products such as running shoes, bandages or prostheses should support and improve our movement. But, how to derive optimal design parameters? The conventional process of prototyping and testing is often time-consuming, expensive, hazardous or even not realizable. Our purpose is to avoid prototyping and testing by virtual product development to derive optimal design parameters. We investigate biomechanical simulation to predict the influence of design parameters on human movement and performance.

Lehrstuhl für Autonome Systeme und Mechatronik
Friedrich-Alexander-Universität Erlangen-Nürnberg

Paul-Gordan-Strasse 3/5
91052 Erlangen
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