Dynamical biomarkers in teams and other multiagent systems.
- Publisher:
- ELSEVIER SCI LTD
- Publication Type:
- Journal Article
- Citation:
- J Sci Med Sport, 2023, 26 Suppl 1, pp. S9-S13
- Issue Date:
- 2023-06
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Patil, G | |
dc.contributor.author | Nalepka, P | |
dc.contributor.author |
Novak, A |
|
dc.contributor.author | Auletta, F | |
dc.contributor.author | Pepping, G-J | |
dc.contributor.author |
Fransen, J |
|
dc.contributor.author | Kallen, RW | |
dc.contributor.author | Richardson, MJ | |
dc.date.accessioned | 2023-11-07T02:53:48Z | |
dc.date.available | 2023-04-17 | |
dc.date.available | 2023-11-07T02:53:48Z | |
dc.date.issued | 2023-06 | |
dc.identifier.citation | J Sci Med Sport, 2023, 26 Suppl 1, pp. S9-S13 | |
dc.identifier.issn | 1440-2440 | |
dc.identifier.issn | 1878-1861 | |
dc.identifier.uri | http://hdl.handle.net/10453/173154 | |
dc.description.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. | |
dc.format | Print-Electronic | |
dc.language | eng | |
dc.publisher | ELSEVIER SCI LTD | |
dc.relation.ispartof | J Sci Med Sport | |
dc.relation.isbasedon | 10.1016/j.jsams.2023.04.004 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | 1106 Human Movement and Sports Sciences, 1116 Medical Physiology, 1117 Public Health and Health Services | |
dc.subject.classification | Sport Sciences | |
dc.subject.classification | 3202 Clinical sciences | |
dc.subject.classification | 4207 Sports science and exercise | |
dc.subject.classification | 5201 Applied and developmental psychology | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Awareness | |
dc.subject.mesh | Sports | |
dc.subject.mesh | Military Personnel | |
dc.subject.mesh | Team Sports | |
dc.subject.mesh | Patient Care Team | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Awareness | |
dc.subject.mesh | Sports | |
dc.subject.mesh | Military Personnel | |
dc.subject.mesh | Patient Care Team | |
dc.subject.mesh | Team Sports | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Awareness | |
dc.subject.mesh | Sports | |
dc.subject.mesh | Military Personnel | |
dc.subject.mesh | Team Sports | |
dc.subject.mesh | Patient Care Team | |
dc.title | Dynamical biomarkers in teams and other multiagent systems. | |
dc.type | Journal Article | |
utslib.citation.volume | 26 Suppl 1 | |
utslib.location.activity | Australia | |
utslib.for | 1106 Human Movement and Sports Sciences | |
utslib.for | 1116 Medical Physiology | |
utslib.for | 1117 Public Health and Health Services | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health | |
pubs.organisational-group | /University of Technology Sydney/Strength - CHSP - Health Services and Practice | |
pubs.organisational-group | /University of Technology Sydney/Strength - HPRC - Human Performance Research Centre | |
utslib.copyright.status | open_access | * |
dc.date.updated | 2023-11-07T02:53:46Z | |
pubs.publication-status | Published | |
pubs.volume | 26 Suppl 1 |
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.
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