MALUM Terminus

Malum Terminus injury prediction
Malum Terminus software can predict the likelihood of injuries based on a data input.

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.


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
  • Injury prediction models are limited to musculoskeletal injuries of the lower limbs
  • Accessibility to tracked data: Athletics and Military

A model of collaboration

MALUM is the result of experts in a number of fields. In addition to Santos and the Virtual Soldier Research program, partners in the areas of physiology and athletics all contributed to this technology.

Commercial partners

Intellisee, a division of MALUM Terminus Technologies


Prof. Karim Abdel-Malek, director of ITI and the Virtual Soldier Research Program


Landon Evans, director of sports science at University of Iowa