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Authors: Boris R. M. Kingma 1 ; Wim H. Saris 1 ; Arjan J. H. Frijns 2 ; Anton A. van Steenhoven 2 and Wouter D. van Marken Lichtenbelt 1

Affiliations: 1 NUTRIM School for Nutrition and Toxicology and Metabolism of Maastricht Universitary, Netherlands ; 2 Eindhoven University of Technology, Netherlands

ISBN: 978-989-8425-32-4

Keyword(s): Thermoregulation, Neural pathway simulation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Complex Artificial Neural Network Based Systems and Dynamics ; Computational Intelligence ; Enterprise Information Systems ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neuro-Fuzzy Systems ; Neuroinformatics and Bioinformatics ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: In humans skin blood flow (SBF) plays a major role in body heat loss. Therefore the accuracy of models of human thermoregulation depends for a great deal on their ability to predict skin blood flow. Most SBF-models use body temperatures directly for calculation of skin perfusion. However, humans do not sense temperature directly, yet the information is coded into neuron fire rates. The aim of this study was to investigate whether SBF can be adequately modelled through simulation of temperature sensitive neurons and neuro-physiological pathways of excitation and inhibition. Methods: In this study a mathematical model for SBF was developed based on physiological knowledge on neural thermo-sensitivity and neural pathways. The model was fitted on human experimental data. Mean squared residuals (MSR) were estimated through k-fold cross-validation. Results: The model adequately explains the variance of the measurements (r2=0.91). Furthermore the averaged MSR is close to the natural variatio n in the measurements (AMSR=0.087 vs. r2=01.080) indicating a small bias. Conclusion: In this study we developed a model for skin perfusion based on physiological evidence on thermo-reception and neural pathways. Given the highly explained variance this study shows that a neuro-physiological approach is applicable for modelling skin blood flow in thermoregulation. (More)

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Paper citation in several formats:
Kingma, B.; Saris, W.; Frijns, A.; van Steenhoven, A. and van Marken Lichtenbelt, W. (2010). MODELING SKIN BLOOD FLOW - A Neuro-physiological Approach.In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 156-162. DOI: 10.5220/0003059001560162

author={Boris R. M. Kingma. and Wim H. Saris. and Arjan J. H. Frijns. and Anton A. van Steenhoven. and Wouter D. van Marken Lichtenbelt.},
title={MODELING SKIN BLOOD FLOW - A Neuro-physiological Approach},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},


JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
TI - MODELING SKIN BLOOD FLOW - A Neuro-physiological Approach
SN - 978-989-8425-32-4
AU - Kingma, B.
AU - Saris, W.
AU - Frijns, A.
AU - van Steenhoven, A.
AU - van Marken Lichtenbelt, W.
PY - 2010
SP - 156
EP - 162
DO - 10.5220/0003059001560162

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