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, 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.
Shastri
Dvijesh
D
Computational Physiology Laboratory, University of Houston, Houston, TX 77204-0101, USA.
Merla
Arcangelo
A
Tsiamyrtzis
Panagiotis
P
Pavlidis
Ioannis
I
D005145:Face / Q000294:innervation / Q000502:physiology*; D005712:Galvanic Skin Response / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008959:Models, Neurological; D009424:Nervous System Physiological Phenomena; D017933:Peripheral Nervous System / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013817:Thermography