Motion Capture and Force-Plate TestBed for Human Movement Analysis
SHORT SUMMARY
This TestBed is a human-centric DeepTech research infrastructure for high-precision motion analysis, combining a four-camera Qualisys Miqus M3 optical motion-capture system with two AMTI OPTIMA Biomechanics Measurement Series BMS400600 force plates. It supports synchronized measurement of kinematics and kinetics for quantitative analysis of gait, balance, jump, landing, rehabilitation exercises, sports performance and human-machine interaction tasks. In the CITADELS context, the TestBed enables creation and validation of datasets, benchmarking of AI models, evaluation of XR/HMI systems, and evidence-based assessment of human movement in healthcare, robotics and Industry 5.0-related applications. The setup is suitable for academic research, collaborative R&D, training, demonstration and experimental validation with external users.
HOSTING INSTITUTION AND PI INFO
| Name of Host Organization | University of Belgrade – Faculty of Sport and Physical Education |
| Department or Lab | Methodological Research Laboratory “Slobodan Jaric” |
| Name of Building | Faculty of Sport and Physical Education |
| Physical Address | Blagoja Parovica 156, 11030 Belgrade, Serbia |
| Website Links |
https://www.fsfv.bg.ac.rs
https://www.fsfv.bg.ac.rs/nauka/metodicko-istrazivacka-laboratorija |
| Institutional contact name | Dragan Mirkov |
| Institutional contact email | dragan.mirkov@fsfv.bg.ac.rs |
APPLICATION CASES
| Application case: | Short description: |
| AI-based movement assessment and dataset generation | Ground-truth capture of kinematics and kinetics for training and validating AI models for gait analysis, movement classification, quality scoring and rehabilitation analytics. |
| Sports performance and landing mechanics assessment | Measurement of jump, landing, balance and force production metrics for athlete evaluation, return-to-play studies and performance diagnostics. |
| XR/HMI and robotics human-centered validation | Objective evaluation of how users move, react and compensate while interacting with XR environments, wearable interfaces or robot-assisted task scenarios. |
POTENTIAL STAKEHOLDERS
Non-academic stakeholders
Industrial Partners, Startups, SMEs, Community, Other (Clinics, rehabilitation centers, sports clubs, health-tech companies, med-tech companies)
Academic stakeholders
Undergraduate students, PhD students, MSc students, Researchers, Other (Postdoctoral researchers, visiting researchers, interdisciplinary AI/XR/robotics labs)
Other types of stakeholders
Athletes, patients, clinicians, physiotherapists, coaches, ergonomists