Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive PerformanceThe U.S. military’s concerns about the individual combat service member’s ability to avoid performance degradation, in conjunction with the need to maintain both mental and physical capabilities in highly stressful situations, have led to and interest in developing methods by which commanders can monitor the status of the combat service members in the field. This report examines appropriate biological markers, monitoring technologies currently available and in need of development, and appropriate algorithms to interpret the data obtained in order to provide information for command decisions relative to the physiological “readiness” of each combat service member. More specifically, this report also provides responses to questions posed by the military relative to monitoring the metabolic regulation during prolonged, exhaustive efforts, where nutrition/hydration and repair mechanisms may be mismatched to intakes and rest, or where specific metabolic derangements are present. |
Contents
EXECUTIVE SUMMARY | 1 |
STATISTICAL | 37 |
MONITORING OVERALL PHYSICAL STATUS TO PREDICT | 53 |
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accelerometers actigraphy algorithms amino acids analysis Appl Physiol assessment associated Aviat biochemical biomarkers blood body odors body temperature bone resorption brain changes chemical energy Clin clinical cognitive performance cold combat service members concentrations core temperature cortisol currently cytokines decreased dehydration devices disease effects energy expenditure environment environmental evaluation exercise exposure factors flight fluid Friedl glucose heart rate heat stress hormones human hydration status hyponatremia IGF-I immune increased indicators individual insulin-like growth factor laboratory lactate levels loss markers measures mechanical Medicine metabolic Metabolic Monitoring methods models Monitoring Technologies mood muscle fatigue muscle protein noninvasive normal NS NS NS Nutrition operational osmolality osteoblasts oxygen parameters percent physical activity plasma potential predict Sawka Sci Sports Exerc sensors skeletal muscle sleep deprivation specific stress fractures studies sweat tasks tion tryptophan turnover types U.S. Army urinary urine validated variability