DETECTION AND MONITORING OF STUDENT ATHLETES’ COGNITIVE STATE AND PERFORMANCE

Cognitive State

A portable, high-fidelity approach to assessing performance readiness.

Performance, whether in the classroom, in the boardroom or on the field, hinges upon one’s physical and mental well-being. With the advent of portable brain-monitoring devices and wearable technologies, it is now possible to gain insights into the physical, emotional and cognitive factors affecting a person’s performance, onsite and in real time. This project represents a novel synthesis of wearable technologies, standardized neurocognitive tasks and machine learning models to automatically detect an individual’s cognitive, emotional and physical state. Specifically, the team leveraged Dr. Meltem Izzetoglu’s functional near-infrared spectroscopy (fNIRs) wearable device to assess cognitive activity, a wireless wristband to monitor heart rate and electrodermal activity for stress and a force plate to monitor balance and postural stability.

The primary motivation behind this collaborative, multiyear project is to determine whether it’s possible to positively influence a student-athlete’s mental wellness and thereby boost their overall performance. During the first phase of the project, the team designed both multimodal data collection—tracking cognitive, motor and emotional biomarkers—and multidomain data analysis processes to assess athletes’ cognitive capacities during various activities: validated resting, attention, memory, vigilance and motor tasks. Three interventions—caffeine intake, meditation and no action (control)—were assessed for their potential to positively affect performance, with coffee having the greatest impact.

Having validated the data collection and analysis portions, during the first phase of the project, the team will explore how age, gender and physical fitness status (athletes vs. nonathletes) impact cognitive performance and physiological metrics. The team is ultimately striving to obtain objective, science-based measures of an individual’s cognitive and emotional state, as opposed to the current practice of subjective self-reports of behavioral outcomes. The advances in wireless and wearable technologies means that this objective data can now be collected in or on the field, in real time and under different stress states. This, in turn, enables routine monitoring of performance state and the ability to establish an individual’s cognitive, emotional and behavioral baseline. Routine monitoring will enable early detection of any deviation (declined, enhanced) from an individual’s baseline, allowing for timely and targeted interventions. Finally, the team believes that its multimodal platform can be used for the initial diagnosis and monitoring of concussion, leveraging the validated cognitive, emotional and motor tasks to provide more objective determination for when it’s safe for an athlete to return to the field of play.

RESEARCHERS

Principal Investigators
Meltem Izzetoglu, PhD
Associate Professor, Electrical and Computer Engineering
Director, Biomedical Signals, Systems and Analysis Lab

Xun Jiao, PhD
Assistant Professor, Electrical and Computer Engineering

Students
Michael Sommeling ’22 CpE, ’23 MSCpE

Partners
Joanie Milhous, Head Coach, Villanova Field Hockey
Kevin Miller, Associate Athletic Director/Director of Sports Performance, Villanova Athletics
Mark Jupina, PhD, Assistant Professor, Electrical and Computer Engineering
Shadi Malaeb, MD, St. Christopher’s Hospital for Children
Patricia Shewokis, PhD, Drexel University College of Nursing and Health Professions


 

PROJECT DETAILS

  • Portable, fully integrated monitoring system, powered by machine learning, makes it possible to measure performance anywhere, anytime—from athletes on the field to workers in high-risk environments.
  • Establishing an athlete’s baseline levels for cognitive, emotional and physical state and monitoring these metrics throughout the season can provide “a window into that individual’s brain.”
  • The relative influence of coffee vs. meditation will be explored more fully in Phase 2. Preliminary results indicate that coffee significantly improved neural efficiency in memory tasks and had the strongest impact on vigilance. Meditation, on the other hand, did significantly improve the effects of resting among participants.
  • Cognitive and emotional state are critical to success in everyday life, and such technology may soon become widespread.

Michael Sommeling, “Detection and Monitoring of Cognitive State with Functional Near-Infrared Spectroscopy (fNIRS)” MS Thesis, May 2023, Advisor: Meltem Izzetoglu

Sommeling M, Izzetoglu, M. “Automatic classification of attentional processing during Stroop task and meditation using fNIRS features” fNIRS Conference, Oct 2022, Boston MA.

Izzetoglu, M., Shewokis, P. A., Tsai, K., Dantoin, P., Sparango, K., & Min, K. (2020). Short-Term Effects of Meditation on Sustained Attention as Measured by fNIRS. Brain Sciences, 10(9), 608. (Villanova Engineering senior design group)

  • Mozel AE, Izzetoglu M, Master CL, Leber AB, Grady M, Vernau, BT, Folk C. “A Multimodal Investigation of Attention in Pediatric Concussion,” Annual Meeting of the International Neuropsychological Society, Feb 2023, San Diego, CA
  • Izzetoglu M, Jiao X, Park S. “Understanding Driving Behavior Using fNIRS and Machine Learning” In International Conference on Transportation and Development, 2021.

Project Leads

Meltem Izzetoglu, PhD

Meltem Izzetoglu, PhD
Associate Professor, Electrical and Computer Engineering
Director, Biomedical Signals, Systems and Analysis Lab
meltem.izzetoglu@villanova.edu

Xun Jiao, PhD

Xun Jiao, PhD
Assistant Professor, Electrical and Computer Engineering
xjiao@villanova.edu