Developing AI enabled sensors and decision support for military operators in the field

被引:2
作者
Russell, Brian K. [1 ,2 ]
McGeown, Josh [4 ]
Beard, Bettina L. [3 ]
机构
[1] Auckland Univ Technol, Sports Performance Inst New Zealand, Auckland, New Zealand
[2] Ambient Cognit Ltd, Auckland, New Zealand
[3] NASA Ames Res Ctr, Moffett Field, CA USA
[4] Matai Med Res Inst Inc, Gisborne, New Zealand
关键词
Remote physiological monitoring; Cognition performance; Artificial Intelligence; Decision Support; PERFORMANCE; HEALTH; CLASSIFIER;
D O I
10.1016/j.jsams.2023.03.001
中图分类号
G8 [体育];
学科分类号
04 ; 0403 ;
摘要
Wearable sensors enable down range data collection of physiological and cognitive performance of the warfighter. However, autonomous teams may find the sensor data impractical to interpret and hence influence real-time decisions without the support of subject matter experts. Decision support tools can reduce the burden of interpreting physiological data in the field and incorporate a systems perspective where noisy field data can contain useful additional signals. We present amethodology of how artificial intelligence can be used for modeling human performance with decision-making to achieve actionable decision support. We provide a framework for systems design and advancing from the laboratory to real world environments. The result is a validated measure of down-range human performance with a low burden of operation. (c) 2023 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:S40 / S45
页数:6
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