fNIRS Cognitive Sensors

Tracking cognitive state by measuring visible
and infrared light reflectance in cortical tissue

Our miniaturized fNIRS sensors, Pioneer™ and Explorer™, were developed and launched in partnership with PLUX, a biomedical engineering company based in Portugal. fNIRS sensors, typically applied on the forehead, measure visible and infrared light reflectance in cortical tissue to estimate blood oxygen saturation levels in the brain.

In this video, Dr. Bethany Bracken describes fNIRS sensors and how Charles River Analytics is using them in human state assessment projects.

“Historically, fNIRS sensors are clunky and cumbersome. We developed small and portable fNIRS sensors to enhance our human state assessment projects. Our fNIRS Explorer sensor comes with an adjustable, flexible headband that’s made of rubber, so it’s comfortable to wear for long periods of time. It’s also hermetically sealed, allowing it to be useful even in environments with sun, sand, and dust, letting wearers perform training activities both in and out of the lab.”

Dr. Bethany Bracken,
Principal Scientist at Charles River Analytics

Our solutions in action

Our sensors have been used in a variety of projects to automatically sense indicators of cognitive workload in trainees, resulting in the augmentation of performance observations and offering insight into factors underlying that performance.


Tracking cognitive workload for medical personnel
The MEDIC system uses our fNIRS sensors and Sherlock™ platform to sense cognitive workload indicators in medical personnel to analyze factors underlying medical outcomes. The system collects and processes information about brain activity and delivers estimates of cognitive workload during high fidelity training simulations.


Measuring pilot physiology during flight training
Our PHARAOH platform uses non-invasive fNIRS sensors to provide quantitative and objective information on pilots during simulated flights. This provides engineers with high-quality assessments and insight into the trainee experience so they can design new training systems that alleviate cognitive workload and maximize trainee success.


Measuring astronauts’cognitive workload
Our CAPT PICARD system uses fNIRS Pioneer sensors to assess astronaut workload and performance while testing and evaluating new NASA systems. During these assessments, our sensors successfully identified real-time physiological measures that contributed to high workloads. These early detections make future redesigns more feasible and less costly. CAPT PICARD is built on Sherlock™, our open and extensible software and hardware platform that provides a unified, end-to-end solution.

“An unobtrusive system that measures cognitive state is useful across multiple domains. For example, using such a system would enable lab-based experiments to be easier to conduct and make portable to real-world environments, or it could be used in training to assess the effectiveness of a curriculum or to tailor the curriculum to the needs of each student. It could also be used during testing and evaluation of new tools early in the design phase, which would streamline the development of intuitive tools.”

Dr. Bethany Bracken,
Principal Scientist at Charles River Analytics

Product capabilities

Our noninvasive, miniaturized fNIRS sensors track cognitive state by measuring visible and infrared light reflectance in cortical tissue. Our partnership with PLUX resulted in two miniaturized fNIRS sensors:

  • fNIRS Pioneer™ delivers all the necessary tools for single-channel fNIRS acquisitions in an affordable hardware kit
  • fNIRS Explorer™ is a wireless and ruggedized wearable that lets users acquire high-quality brain activation data, even out of the lab

Both the fNIRS Pioneer and fNIRS Explorer capture high-quality signals at a fraction of the cost of current systems and are available for purchase through PLUX or its resellers’ networks.

Watch as Charles River Analytics demonstrates our fNIRS wearables.

 Contact us to learn more about our fNIRS sensors and our other healthcare and training efforts. 

The development of this sensor is based upon work supported by the United States Army Medical Research and Materiel Command under Contract No(s). W81XWH-14-C-0018 and W81XWH-17-C-0205, and United States Air Force under Contract No. FA8650-14-C-6579. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Army Medical Research and Materiel Command or the United States Air Force.


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