TY - JOUR
T1 - Dynamical biomarkers in teams and other multiagent systems
AU - Patil, Gaurav
AU - Nalepka, Patrick
AU - Novak, Andrew
AU - Auletta, Fabrizia
AU - Pepping, Gert-Jan
AU - Fransen, Job
AU - Kallen, Rachel W.
AU - Richardson, Michael J.
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/6
Y1 - 2023/6
N2 - 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.
AB - 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.
KW - Perceptual-motor behaviors
KW - Quantitative methods
KW - Situation awareness
KW - Team coordination
KW - Team sports
KW - Military Personnel
KW - Awareness
KW - Humans
KW - Patient Care Team
KW - Team Sports
KW - Sports
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=woscharlessturt_pure&SrcAuth=WosAPI&KeyUT=WOS:001028557500001&DestLinkType=FullRecord&DestApp=WOS
UR - http://www.scopus.com/inward/record.url?scp=85158874999&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85158874999&partnerID=8YFLogxK
U2 - 10.1016/j.jsams.2023.04.004
DO - 10.1016/j.jsams.2023.04.004
M3 - Review article
C2 - 37150726
SN - 1878-1861
VL - 26
SP - 9
EP - 13
JO - Journal of Science and Medicine in Sport
JF - Journal of Science and Medicine in Sport
IS - 1
ER -