Autonomic Nervous System Monitoring - Heart Rate Variability (original) (raw)
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Physiological modeling for technical, clinical and research applications
Frontiers in bioscience (Scholar edition), 2010
Various and disparate technical disciplines have identified a growing need for tools to predict human thermal and thermoregulatory responses to environmental heating and cooling and other thermal challenges such as anesthesia and non-ionizing radiation. In this contribution, a dynamic simulation model is presented and used to predict human thermophysiological and perceptual responses for different applications and situations. The multi-segmental, multi-layered mathematical model predicts body temperatures, thermoregulatory responses, and components of the environmental heat exchange in cold, moderate, as well as hot stress conditions. The incorporated comfort model uses physiological states of the human body to predict thermal sensation responses to steady state and transient conditions. Different validation studies involving climate-chamber physiological and thermal comfort experiments, exposures to uncontrolled outdoor weather conditions, extreme climatic and radiation asymmetry s...
Preventing Heat Injuries by Predicting Individualized Human Core Temperature
2015
: Heat injury is a problem for the Armed Forces, especially during deployment to localities with very hot and humid climates. Early warning of a rising core body temperature (TC) can help prevent heat injuries. To this end, we developed an algorithm that, given a series of past TC measurements obtained using an ingestible temperature pill, accumulates evidence of a rising TC over time and provides ahead-of-time warning of an impending, dangerously elevated TC. Using data from a cohort of six Soldiers involved in field exercises whose TC exceeded 38.5C, we assessed the performance of the warning algorithm. The algorithm predicted rises in TC with a clinically useful lead time ( 18 min) and reasonable sensitivity and specificity ( 87). However, because ingestible temperature pills are impractical for monitoring a large number of Warfighters during prolonged operations, we developed a mathematical model that uses non-invasive measurements of physiological variables, such as activity (A...
Journal of thermal biology, 2017
Physiological models provide useful summaries of complex interrelated regulatory functions. These can often be reduced to simple input requirements and simple predictions for pragmatic applications. This paper demonstrates this modeling efficiency by tracing the development of one such simple model, the Heat Strain Decision Aid (HSDA), originally developed to address Army needs. The HSDA, which derives from the Givoni-Goldman equilibrium body core temperature prediction model, uses 16 inputs from four elements: individual characteristics, physical activity, clothing biophysics, and environmental conditions. These inputs are used to mathematically predict core temperature (Tc) rise over time and can estimate water turnover from sweat loss. Based on a history of military applications such as derivation of training and mission planning tools, we conclude that the HSDA model is a robust integration of physiological rules that can guide a variety of useful predictions. The HSDA model is ...
Human core temperature prediction for heat-injury prevention
IEEE journal of biomedical and health informatics, 2014
Previously, our group developed auto-regressive (AR) models to predict human core temperature and help prevent hyperthermia (temperature > 39 oC). However, the models often yielded delayed predictions, limiting their application as a real-time warning system. To mitigate this problem, here we combined AR-model point estimates with statistically derived prediction intervals (PIs) and assessed the performance of three new alert algorithms [AR model plus PI, median filter of AR model plus PI decisions, and an adaptation of the sequential probability ratio test (SPRT)]. Using field-study data from 22 Soldiers, including five subjects who experienced hyperthermia, we assessed the alert algorithms for AR-model prediction windows from 15-30 min. Cross-validation simulations showed that, as the prediction windows increased, improvements in the algorithms' effective prediction horizons were offset by deteriorating accuracy, with a 20-min window providing a reasonable compromise. Model...
2018
In order to evaluate health risks under severe thermal environments, we are developing a new human thermophysiological model, which can predict not only body temperature but also blood pressure (BP) and blood flow rate (BFR). In the present study, we developed a submodel (thermal network model) to simulate body temperature, and carried out subjective experiments under different ambient temperatures to collect reference data. The experiments indicated that human thermoregulatory ability in cold environments is weaker than that in hot environments. The experiments also showed that BFRs of limbs compose only small portions of total BFR but increase greatly with ambient temperature. On the other hand, our thermal network model could reproduce the trend of tympanic temperature and mean skin temperature. In addition, some numerical simulations showed that the BFRs of limbs are important for thermoregulation even if their portions are small, and besides, heat transfer along vessels is also...