Core temperature (Tc) is an excellent indicator of heat strain status. A computer model, Initial Capability Decision Aid (ICDA), was developed from existing models and algorithms to predict Tc and other physiological parameters in real-time from non-invasively measured inputs of heart rate (HR) and environment parameters together with the person's clothing and anthropometrics. The model was validated with laboratory studies. Tc prediction errors were small (0.11∼0.31ºC). Predictions of sweat rate and physiological strain index also agreed well (p>0.05) with measured values.


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    Title :

    Real-time Non-invasive Heat Strain Prediction Model


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    Digital Human Modeling for Design and Engineering Symposium ; 2008



    Publication date :

    2008-06-17




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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