Dynamical biomarkers in teams and other multiagent systems

Gaurav Patil, Patrick Nalepka, Andrew Novak, Fabrizia Auletta, Gert-Jan Pepping, Job Fransen, Rachel W. Kallen, Michael J. Richardson

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)
27 Downloads (Pure)

Abstract

Effective team behavior in high-performance environments such as in sport and the military requires individual team members to efficiently perceive the unfolding task events, predict the actions and action intents of the other team members, and plan and execute their own actions to simultaneously accomplish individual and collective goals. To enhance team performance through effective cooperation, it is crucial to measure the situation awareness and dynamics of each team member and how they collectively impact the team's functioning. Further, to be practically useful for real-life settings, such measures must be easily obtainable from existing sensors. This paper presents several methodologies that can be used on positional and movement acceleration data of team members to quantify and/or predict team performance, assess situation awareness, and to help identify task-relevant information to support individual decision-making. Given the limited reporting of these methods within military cohorts, these methodologies are described using examples from team sports and teams training in virtual environments, with discussion as to how they can be applied to real-world military teams.
Original languageEnglish
Pages (from-to)9-13
Number of pages5
JournalJournal of Science and Medicine in Sport
Volume26
Issue number1
DOIs
Publication statusPublished - Jun 2023

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