Sensors-Enabled Human State Monitoring System for Tactical Settings

There is potential great value in turning physiological and behavioral data into actionable information in tactical environments. However, the design of an appropriate system in terms of measurement accuracy, wearing comfort and technical feasibility, for instance for forces training in realistic co...

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Bibliographic Details
Main Authors: Salvan, Laura, Marois, Alexandre, Kopf, Maelle, Gagnon, Jean-Francois
Format: Conference Proceeding
Language:English
Subjects:
Artificial Intelligence
Biomonitoring
Collaboration
Data visualization
Force measurement
Human factors
Measurement
Real-time systems
Situation Management
Situation Visualization
Training
Turning
Wearable
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Summary:There is potential great value in turning physiological and behavioral data into actionable information in tactical environments. However, the design of an appropriate system in terms of measurement accuracy, wearing comfort and technical feasibility, for instance for forces training in realistic conditions, therefore requires addressing multiple scientific and technical challenges. The current paper focuses on work realized to address four challenges identified in recent efforts in the development of an integrated wearable system. These four challenges pertain to: 1) Data management; 2) Wearable sensors; 3) Algorithms and models; and 4) Human factors considerations. Components were developed and integrated to tackle each of the four challenges and the integrated system was tested on participants during field trials. The system referred to "Readiness Evaluation: QUantified INdividuals" (REQUIN), offers a dashboard to visualize in real time the various metrics collected and calculated by the system, including metrics derived from wearable sensors and models. Results of the field trials are discussed in regard with the four challenges addressed in the paper and recommendations for further research are presented, including using alternative sensing technologies for blood oxygenation measures and improving the models' specificity. This study represents a critical step in the integration of real-time sensing technologies for applications involving collective situation management and control.
ISSN:2379-1675
DOI:10.1109/CogSIMA54611.2022.9903277