Autonomous sensory meridian response (ASMR) is a sensory phenomenon commonly characterized by pleasant tingling sensations arising from the back of the head and accompanied by feelings of relaxation and calmness. Although research has found ASMR to have a distinct physiological pattern with increased skin conductance levels and reduced heart rate, the specific tingles felt in ASMR have not received much investigation. The aim of the present study was to investigate the physiology and characteristics of ASMR further by examining whether experiencing ASMR is visible from the pupil of the eye. A total of 91 participants were recruited and assigned to three different groups based on their experience of ASMR (ASMR vs. non-ASMR vs. unsure). Participants were instructed to watch a control video and an ASMR video and to report any tingling sensations by pressing down a button on the keyboard. Pupil diameter was measured over the duration of both videos using a tower-mounted eye tracker. Data was analyzed on a general level, averaging pupil diameter over each video, as well as on a more specific level, comparing pupil diameter during reported episodes of tingling sensations to pupil diameter outside of those episodes. On the general level, results revealed no significant differences between the groups. On the specific level, however, the tingling sensations experienced in ASMR were found to cause statistically significant increases in pupil diameter, demonstrating that they have a physiological basis. The results of the study further reinforce the credibility of ASMR and suggest that the tingles felt in ASMR are at the very core of the experience itself.

There is a long history of interest in looking behavior during human interaction. With the advance of (wearable) video-based eye trackers, it has become possible to measure gaze during many different interactions. We outline the different types of eye-tracking setups that currently exist to investigate gaze during interaction. The setups differ mainly with regard to the nature of the eye-tracking signal (head- or world-centered) and the freedom of movement allowed for the participants. These features place constraints on the research questions that can be answered about human interaction. We end with a decision tree to help researchers judge the appropriateness of specific setups.

Eye contact is essential for human interactions. We investigated whether humans are able to avoid eye contact while navigating crowds. At a science festival, we fitted 62 participants with a wearable eye tracker and instructed them to walk a route. Half of the participants were further instructed to avoid eye contact. We report that humans can flexibly allocate their gaze while navigating crowds and avoid eye contact primarily by orienting their head and eyes towards the floor. We discuss implications for crowd navigation and gaze behavior. In addition, we address a number of issues encountered in such field studies with regard to data quality, control of the environment, and participant adherence to instructions. We stress that methodological innovation and scientific progress are strongly interrelated.

Looking at the mouth region is thought to be a useful strategy for speech-perception tasks. The tendency to look at the eyes versus the mouth of another person during speech processing has thus far mainly been studied using screen-based paradigms. In this study, we estimated the eye-mouth-index (EMI) of 38 adult participants in a live setting. Participants were seated across the table from an experimenter, who read sentences out loud for the participant to remember in both a familiar (English) and unfamiliar (Finnish) language. No statistically significant difference in the EMI between the familiar and the unfamiliar languages was observed. Total relative looking time at the mouth also did not predict the number of correctly identified sentences. Instead, we found that the EMI was higher during an instruction phase than during the speech-processing task. Moreover, we observed high intra-individual correlations in the EMI across the languages and different phases of the experiment. We conclude that there are stable individual differences in looking at the eyes versus the mouth of another person. Furthermore, this behavior appears to be flexible and dependent on the requirements of the situation (speech processing or not).

Computer-vision-based gaze estimation refers to techniques that estimate gaze direction directly from video recordings of the eyes or face without the need for an eye tracker. Although many such methods exist, their validation is often found in the technical literature (e.g., computer science conference papers). We aimed to (1) identify which computer-vision-based gaze estimation methods are usable by the average researcher in fields such as psychology or education, and (2) evaluate these methods. We searched for methods that do not require calibration and have clear documentation. Two toolkits, OpenFace and OpenGaze, were found to fulfill these criteria. First, we present an experiment where adult participants fixated on nine stimulus points on a computer screen. We filmed their face with a camera and processed the recorded videos with OpenFace and OpenGaze. We conclude that OpenGaze is accurate and precise enough to be used in screen-based experiments with stimuli separated by at least 11 degrees of gaze angle. OpenFace was not sufficiently accurate for such situations but can potentially be used in sparser environments. We then examined whether OpenFace could be used with horizontally separated stimuli in a sparse environment with infant participants. We compared dwell measures based on OpenFace estimates to the same measures based on manual coding. We conclude that OpenFace gaze estimates may potentially be used with measures such as relative total dwell time to sparse, horizontally separated areas of interest, but should not be used to draw conclusions about measures such as dwell duration.