Human Performance Enhancement

Our mobile EEG systems enable accelerated learning across a variety of environments including improved training, sports performance and education.

Overview

The ‘mental game’ of sports, performance, and learning reaches new levels through EEG-based brain mapping techniques. By understanding the biological differences between expert and novice cognitive states during performance, teachers can teach better and students can learn faster.

Whereas as traditional coaching and expert observation assessments identify mistakes when they are made, EEG-based measures provide insights as to why they occurred.

Adaptive Peak Performance Trainer (APPT)

  • Accelerates novice skill learning by a factor of 2.3x
  • Assesses localized EEG Alpha & Theta, HR+HRV
  • Developed and validated on +300 subject database
  • Integrated into Cubic’s virtual marksmanship trainer
  • Predicts deadly force decision making errors

Cognitive skills assessment during robot assisted surgery

EEG-based cognitive assessment of surgeons may aid in defining levels of expertise performing complex surgical tasks once competence is achieved. The B-Alert cognitive state metrics may be used as an adjunct to the traditional methods for skill assessment during RAS.

Learn More

Accelerating Training Using Interactive Neuro- Educational Technologies: Applications to Archery, Golf and Rifle Marksmanship. Berka, C, et al. (2010).  Int. J. Sports Soc. 1.
Zen and the Art of Genius. Adee, S. (2012, February 4). New Scientist, (213), 32–35.
Characterizing the Psychophysiological Profile of Expert and Novice Marksmen. Pojman, N., Behneman, A., Kintz, N., Johnson, R., Chung, G., Nagashima, S., … Berka, C. (2009). Presented at the 13th International Conference on Human-Computer Interaction, San Diego, CA.
Neurotechnology to Accelerate Learning: During Marksmanship Training. Behneman, A., Berka, C., Stevens, R., Vila, B., Tan, V., Galloway, T., … Raphael, G.(2012). IEEE Pulse, 3(1), 60–63.
Cognitive Skills Assessment During Robot-Assisted Surgery: Separating Wheat from Chaff. Guru,K., Tarkesh Esfahani, E., Raza, S., Bhat, R., Wang, K., Hammond, Y., …Chowriappa, A. (2014). BJU International, 115, 166–174.
Characterizing the Expertise and Proficiency of Surgeons Using EEG-based Metrics. Korszen, S., Sharif, M. A., Shafiei, S., Berka, C., Esfahani, E. T., & Guru, K. (n.d.). Poster.
Modeling Temporal Sequences of Cognitive State Changes Based on a Combination of EEG-Engagement, EEG-Workload, and Heart Rate Metrics. Stikic, M., Berka, C., Levendowski, D. J., Rubio, R. F., Tan, V., Korszen, S., …Wurzer, D. (2014).  Frontiers in Neuroscience, 8.
Identifying Psychophysiological Indices of Expert Vs. Novice Performance in Deadly Force Judgment and Decision Making. Johnson, R. R., Stone, B. T., Miranda, C. M., Vila, B., James, L., James, S. M., …Berka, C. (2014). Frontiers in Human Neuroscience, 8.  
Assessing a learning process with functional ANOVA estimators of EEG power spectral densities. Gutiérrez,D., & Ramírez Moreno, M. A. (2015).  Cognitive Neurodynamics, 10, 175–183.
Curriculum for Accelerated Learning Through Mindfulness (CALM) Skinner, A., Fidopiastis, C., Pascarelle, S., & Reichel, H. (2018).
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