Sensor-based Assessment Technologies

Sensor-based Assessment Technologies

Sense and assess with purpose

Aptima’s Sensor-based Assessment Technologies (SAT) capability leverages signals from the brain and body to inform performance-optimizing solutions that accelerate learning and optimize human-machine teams to transform the work of the future.

As humans engage in various activities, such as work, play, and daily routines, our brains, bodies, and the actions we take offer valuable clues about our activities and the level of proficiency we exhibit in them. Aptima’s expertise lies in utilizing advanced data analytics to identify patterns and extract key features that facilitate the translation from raw data into meaningful insights.

SAT leverages a wide range of multimodal data, including:

  1. Neuroimaging devices such as electroencephalography [EEG] and functional near-infrared spectroscopy [fNIRS]
  2. Physiological monitors such as heart rate and respiratory monitors
  3. Physical sensors such as electromyography [EMG] and inertial measurement unit [IMU]
  4. Computerized software including software for interpersonal communication (email, text) and cognitive task performance

These data are processed and analyzed using sophisticated algorithms and machine learning techniques and trained and tested against ground truth, to output cognitive or physiological state estimates, movement predictions, and team skill assessments.

With SAT, data-derived insights provide objective feedback about individual internal conditions and abilities that would otherwise go unnoticed. As a result, individuals, supervisors, and even computerized co-workers (systems-as-teammates, automated assistants) can make informed adjustments to enhance safety and efficiency.


With their slim form factors and advanced data analytics, innovative fNIRS and EEG device designs enable comfortable and reliable near-real-time cognitive monitoring to inform interventions (e.g., during detrimental workload states), even in noisy environments.

Reduction of
Physical Exertion

With data from lower leg sensors, algorithms monitor ongoing ambulatory movement, and quickly and accurately predict the future ankle joint dynamics that drive a motorized exoskeleton to move with or ahead of the Warfighter.

Team Behavior Measurement

Multimodal data, such as email and interpersonal interactions, populate graph-based visualizations to show how team members interact, share information, and evolve over time, as well as factor into assessments of team skills, including coordination and resilience.