The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Military applications of soldier physiological monitoring
Open accessAbstract
Wearable physiological status monitoring is part of modern precision medicine that permits predictions about an individual's health and performance from their real-time physiological status (RT-PSM) instead of relying on population-based predictions informed by estimated human, mission, and environmental/ambient conditions. RT-PSM systems have useful military applications if they are soldier-acceptable and provide important actionable information. Most commercially available systems do not address relevant military needs, typically lack the validated algorithms that make real time computed information useful, and are not open architected to be integrated with the soldier technological ecology. Military RT-PSM development requires committed investments in iterative efforts involving physiologists, biomedical engineers, and the soldier users. Military operational applications include: (1) technological enhancement of performance by providing individual status information to optimize self-regulation, workload distribution, and enhanced team sensing/situational awareness; (2) detection of impending soldier failure from stress load (physical, psychological, and environmental); (3) earliest possible detection of threat agent exposure that includes the "human sensor"; (4) casualty detection, triage, and early clinical management; (5) optimization of individual health and fitness readiness habits; and (6) long term health risk-associated exposure monitoring and dosimetry. This paper is focused on the performance-related applications and considers near term predictions such as thermal-work limits, alertness and fitness for duty status, musculoskeletal fatigue limits, neuropsychological status, and mission-specific physiological status. Each new measurement capability has provided insights into soldier physiology and advances the cycle of invention, lab and field testing, new discovery and redesign.
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Mantua, J., Gravel, N., & Spencer, R. (2016) · Sensors · doi:10.3390/s16050646 · Cited by 314
Walking economy is predictably determined by speed, grade, and gravitational load.
Ludlow, L. W., & Weyand, P. G. (2017) · Journal of applied physiology · doi:10.1152/japplphysiol.00504.2017 · Cited by 47
Zong, C., & Jafari, R. (2015) · 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7320268 · Cited by 39
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Fernández-Caramés, T., & Fraga-Lamas, P. (2018) · Electronics · doi:10.3390/electronics7120405 · Cited by 359
Metadata
- Authors
- Friedl, K. E.
- Venue
- Journal of Science and Medicine in Sport
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 21
- Issue
- 11
- Pages
- 1147-1153
- ISSN
- 1440-2440 (ISSN-L)
- OpenAlex
- W2809580568
- Cited by
- 194
- References
- 3
- FWCI
- 47.54
- Type
- journal article
- Language
- en
- Open access
- hybrid
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