Technical Evaluation Report - Nato

T-8
In the rest of the session, and also on the other days, various examples of the development and
application of models were presented:
• Montain et al. [25] showed how modelling (USARIEM models on water requirement) can
reduce the number of evaluation tests needed;
• Danielsson [28] showed an elegant study of the use of an improved Wind Chill Index (WCI)
model in the prediction of the risk of skin freezing, adding the previously absent effects of
solar radiation, humid skin and habituation to cold to the old WCI model approach and
thereby improving the quality of the risk prediction (in the discussion a comment was made
that the assumption that CIVD (Cold Induced Vaso-Dilation) is always present could result in
an underestimation of risk);
• Camenzind and den Hartog [5] predicted application ranges of sleeping bags, using a simple
model based on the principles of that developed by Farnworth, using material measurements
for top and bottom sides; -Holmér and Nilsson [6] presented an empirical model that can be
used to predict loss of clothing insulation due to wind and movement, taking clothing air
permeability into account; and finally Mäntysaari et al. presented data that can be used to
model sweat accumulation in clothing during interval exercise in the cold, demonstrating that
the type of work/rest cycle has a strong influence on sweat accumulation giving the advantage
to short work/rest cycles as sweat peaks are smaller then.
Monitoring and Thermal Limits
In the second part of this session, Markou et al. [29] (presented by Dr. Diamantopoulos) discussed the
evaluation of a heat stress index to be used by the Hellenic air force. So far they worked with the
‘discomfort index’. The authors discussed that application of WBGT and more recently of the FITS:
the ‘Fighter Pilot Index of Thermal Stress’. They see clear improvements by the implementation of
FITS, but also conclude that this index needs some adjustment to the specific situation of the Hellenic
forces.
Pandolf and Moran [30] presented two strain indices, one for the heat (the Physiological (heat) Strain
Index, PSI) and one for the cold (Cold Strain Index, CSI). These are not predictive indices, but indices
that integrate a number of physiological responses in a single index value. For heat this is a weighted
sum of the heart rate and of the core temperature response, both expressed as fractions of the
difference between resting and maximal values. For the cold, this is a weighted response of the change
of body skin and core temperatures from ‘resting’ values again expressed as fraction of the difference
between resting and limit values. Hence the latter is an alternative way of expressing body heat deficit
relative to set limit values. The indices, especially the PSI have been tested on a number of datasets,
and they have been shown to discriminate well between stress conditions. In the discussion, the
problem of individual differences was mentioned: during heavy work, a fit person would reach heat
exhaustion at a higher PSI (both high core temperature and high heart rate) than an unfit person (high
heart rate at still low core temperature). Hence the meaning of a certain PSI value is different for
different individuals. The authors (also of [31, 32]) suggested that, for instance where the PSI is used
for personal heat stress monitoring, it should be individually calibrated.
An application of PSI in personal monitoring systems was demonstrated by Hoyt et al. [32] (presented
by Obusek), where PSI was used to integrate heart rate and body core data (as measured using a radio
pill). These data were then transmitted to a base station, allowing the commanders to monitor the
physiological status of the individual soldiers. This promising technique is in development to improve
reliability and to reduce intelligibility of the radio signals by unfriendly forces.
Moran et al. [31] discussed a possible integration of the PSI with a new climatic index: the ESI
(Environmental Stress Index). They showed the deduction of a new ESI index producing highly
similar values as the WBGT index, but based on more commonly measured climate parameters
(temperature, relative humidity, solar radiant flux) than those for the widely used Wet Bulb Globe
Index. Despite not including the wind speed in the new index they observed a high correlation