NSF Award
1726424
This Major Research Instrumentation (MRI) award will support the acquisition of a motion capture/analysis system (MCAS) for leading-edge research and education on complex body movement analysis in medicine, sports and occupational safety. The instrumentation will bolster interdisciplinary research and support SIU graduate programs in Engineering and Applied Health. An essential tool for research in dynamics, controls, and biomechanics, it will be an important regional resource, serving the Southwestern Illinois and Eastern Missouri. The MCAS will be integrated into SIU's undergraduate research programs and will be a core research and educational platform for SIU and institutions in the St. Louis metropolitan area.<br/><br/>The MCAS provides a comprehensive platform for data collection, analysis, and modeling of the forces exerted by different muscle groups and that are being applied to ankle, knee, and hip joints. These data are critical to research projects on preventing musculoskeletal disorders and determining injury mechanisms and ways to minimize the risk of injury. The MCAS will enable complex body movement analysis, forming the basis for improved modeling and simulation and leading to improved physical therapy and training programs. For example, the instrumentation will enable researchers to analyze kinematic gait patterns, measure muscle activation patterns, and collect kinetic data, which will be combined with the kinematic data to calculate the load being applied to the ankle, knee, and hip joints and develop enhanced models for biomechanical gait analysis. The instrumentation, along with surface electromyography, will also be used to collect and analyze data on body movement and muscle activation of surgeons performing minimally invasive surgery. The instrumentation will enable the detection of muscle fatigue and the time-to-fatigue in vulnerable muscle groups-- to advance fundamental fatigue analysis research and determine the impact of muscle fatigue on surgical performance. Such real-time feedback on time-to-fatigue will provide crucial information to surgeons, enhancing their surgical performance and reducing harmful errors. Coupled with the breadth of expertise of the research team-- in engineering, modeling, obesity and exercise physiology-- the acquisition of this MCAS will provide a key resource for advancing fundamental research on complex body movement analysis and potential interventions to enhance human performance and reduce injury.
