Imaging Facial Signs of Neurophysiological Responses

In the present paper, we introduce an integrated framework for detecting peripheral sympathetic responses through purely imaging means. The measurements are performed on three facial areas of sympathetic importance, that is, periorbital, supraorbital, and maxillary. To the best of our knowledge, thi...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2009-02, Vol.56 (2), p.477-484
Main Authors: Shastri, Dvijesh, Merla, Arcangelo, Tsiamyrtzis, Panagiotis, Pavlidis, Ioannis
Format: Article
Language:English
Subjects:
Area measurement
Blood flow
Face - innervation
Face - physiology
Facial physiology
Fluid flow measurement
Frequency measurement
galvanic skin response (GSR)
Galvanic Skin Response - physiology
Humans
Image analysis
Image Processing, Computer-Assisted - methods
Models, Neurological
Nervous System Physiological Phenomena
Performance evaluation
Peripheral Nervous System - physiology
Psychology
Signal Processing, Computer-Assisted
stress
Studies
Sweat glands
thermal imaging
Thermal variables measurement
Thermography
Wavelet analysis
wavelets
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Summary:In the present paper, we introduce an integrated framework for detecting peripheral sympathetic responses through purely imaging means. The measurements are performed on three facial areas of sympathetic importance, that is, periorbital, supraorbital, and maxillary. To the best of our knowledge, this is the first time that the sympathetic importance of the maxillary area is analyzed. Because the imaging measurements are thermal in nature and are composed of multiple components of variable frequency (i.e., blood flow, sweat gland activation, and breathing), we chose wavelets as the image analysis framework. The measurements also carry substantial noise due to imperfections in tissue tracking and segmentation. The image analysis is grounded on galvanic skin response (GSR) signals, which are still considered the golden standard in peripheral neurophysiological and psychophysiological studies. The experimental results show that monitoring of the facial channels yields similar detecting power to GSR's. However, detailed quantification of the responses, although feasible in GSR through appropriate modeling, is quite difficult in the facial channels for the moment. Further improvements in facial tissue tracking and segmentation are bound to overcome this limitation. This paper opens a new research area that leads to unobtrusive screening technologies in neurophysiology and psychophysiology.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2008.2003265