We have developed a novel method to measure human cardiac pulse at a distance. It is based on the information contained in the thermal signal emitted from major superficial vessels. This signal is acquired through a highly sensitive thermal imaging system. Temperature on the vessel is modulated by pulsative blood flow. To compute the frequency of modulation (pulse), we extract a line-based region along the vessel. Then, we apply fast Fourier transform (FFT) to individual points along this line of interest to capitalize on the pulse's thermal propagation effect. Finally, we use an adaptive estimation function on the average FFT outcome to quantify the pulse. We have carried out experiments on a data set of 34 subjects and compared the pulse computed from our thermal signal analysis method to concomitant ground-truth measurements obtained through a standard contact sensor (piezo-electric transducer). The performance of the new method ranges from 88.52% to 90.33% depending on the clarity of the vessel's thermal imprint. To the best of our knowledge, it is the first time that cardiac pulse has been measured several feet away from a subject with passive means.

We have developed a high-definition thermal-imaging technique that can detect attempted deceit by recording the thermal patterns from people's faces. This technique has an accuracy comparable to that of polygraph examination by experts and has potential for application in remote and rapid security screening, without the need for skilled staff or physical contact.

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.

In the present study we quantify stress by measuring transient perspiratory responses on the perinasal area through thermal imaging. These responses prove to be sympathetically driven and hence, a likely indicator of stress processes in the brain. Armed with the unobtrusive measurement methodology we developed, we were able to monitor stress responses in the context of surgical training, the quintessence of human dexterity. We show that in dexterous tasking under critical conditions, novices attempt to perform a task's step equally fast with experienced individuals. We further show that while fast behavior in experienced individuals is afforded by skill, fast behavior in novices is likely instigated by high stress levels, at the expense of accuracy. Humans avoid adjusting speed to skill and rather grow their skill to a predetermined speed level, likely defined by neurophysiological latency.

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