What is MALUM Terminus

Malum Terminus - Injury
MALUM has proven valuable predicting injuries in soldiers and athletes.

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
  • Dynamic injury prediction models (initially focused on lower limb musculoskeletal injuries)
  • Accessibility to tracked data: Athletics and Military


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:

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


Two Ways to Engage

Applied Research

The MALUM simulation platform serves as an open environment for researchers to import injury data and models into the human simulation. MALUM can ingest data from individuals, teams, and units to predict likelihood of injury. MALUM is also compatible with other applications, such as working with the virtual human, Santos, and the Cognitive Assessment Tool Set, or CATS.

TRL 4-6
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  • Malum Terminus Technologies, Incorporated (MTTI) holds exclusive commercial license to the intellectual property enabling the MALUM capabilities.  As a spinout of the University of Iowa Technology Institute, MTTI is building upon the MALUM foundation to deliver both Health & Human Performance and Safety & Security solutions. MTTI's product portfolio ranges from AI solutions for the U.S. Department of Defense to keeping schools, stores, hospitals and communities safer by pairing the power of AI with existing surveillance systems through MTTI's brand Intellisee (www.intellisee.com).  
  • Contact MTTI CEO Scott Keplinger at s.keplinger@intellisee.com or Jill Mast at jill@thinkdenovo.com for inquiries.


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