What is MALUM Terminus

MALUM Terminus is an artificial intelligence engine that analyzes data input and sensor input to predict injuries. MALUM pairs with the virtual avatar Santos – technology developed by Iowa Technology Institute's Virtual Soldier Research Program – to take in various physical, physiological, and biomechanical parameters. Using data from other commercially available human monitoring systems, MALUM can identify the likelihood of injury risk when put in various high-intensity tasks.

Applications

MALUM can be used to promote safety and injury avoidance among soldiers, athletes, and many others.

• MALUM has been used to predict musculoskeletal injuries in warfighters, which can cost millions of lost duty days and are among the leading medical problems eroding military readiness.
• For the Office of Naval Research, Science and Technology, MALUM was used to enhance warfighter performance by maximizing the training load and providing customized strength and conditioning interventions for the individual warfighter.
• Using data from the University of Iowa Athletics Department for basketball and soccer, MALUM was used to track athletes with various sensors, historical data, medical records, and performance records. An artificial intelligence program was developed to learn from the data, identify causality of injury, and predict future injuries.
• One simulation of actual data from a University of Iowa female athletic team revealed injuries for specific players occurred when sleep, stress, and a specific amount of player load occurred. These quantified parameters indicated a specific ACL injury.
• While developed as an injury prediction tool, it has multiple other capabilities. MALUM is the analytic engine in software being developed to capture human motion from a video camera to detect potential safety risks ranging from weapons to slip and fall hazards.

Major Capabilities

• Predicting human musculoskeletal injuries
• Human motion prediction models are now mature
• Integrating simulation models for large data
• AI deep learning models incorporated to classify motion and predict injuries
• Predictive models that can adapt to missing data
• Dynamic injury prediction models (initially focused on lower limb musculoskeletal injuries)
• Accessibility to tracked data: Athletics and Military

Partners

MALUM is the result of experts in a number of fields. Partner in disciplines across the University of Iowa campus and off have contributed. A selection of University of Iowa collaborators include:

• College of Engineering
• College of Education
• Department of Athletics
• Department of Health and Human Physiology

In addition, MALUM has been commercialized by Intellisee, a division of Malum Terminus Technologies, Incorporated (MTTI).

Two Ways to Engage