Recognition of Emotional Facial Expressions and Alexithymia in Patients with Chronic Facial Pain

Objectives Alexithymia, conceived as difficulties to identify emotions, is said to be related with several pain syndromes. This study examined the recognition of facially expressed emotions and its relation to alexithymia in subjects with chronic facial pain. Methods A total of 62 subjects were recruited, with n=20 patients with chronic facial pain and n=42 healthy controls. All subjects were tested for the recognition of facially expressed emotions (Facially Expressed Emotion Labelling Test (FEEL test). The Toronto Alexithymia Scale (TAS-26) was used for the diagnosis of alexithymia. Results Patients with chronic facial pain performed worse than controls at the FEEL task (p<.001) and showed higher total TAS scores (p<.001). This indicates the presence of alexithymia and facial emotion recognition deficits in the facial pain group. Discussion It was concluded from the results that both the recognition of facially expressed emotions, and the ability to identify and describe one’s own feelings (TAS), are restricted in chronic orofacial pain patients. This relationship is particularly important in the treatment of chronic facial pain, indicating that it should become part of the treatment in addition to the therapeutic key issues, to influence the quality of life of the affected patients positively

Head movements and postures as pain behavior.

Pain assessment can benefit from observation of pain behaviors, such as guarding or facial expression, and observational pain scales are widely used in clinical practice with nonverbal patients. However, little is known about head movements and postures in the context of pain. In this regard, we analyze videos of three publically available datasets. The BioVid dataset was recorded with healthy participants subjected to painful heat stimuli. In the BP4D dataset, healthy participants performed a cold-pressor test and several other tasks (meant to elicit emotion). The UNBC dataset videos show shoulder pain patients during range-of-motion tests to their affected and unaffected limbs. In all videos, participants were sitting in an upright position. We studied head movements and postures that occurred during the painful and control trials by measuring head orientation from video over time, followed by analyzing posture and movement summary statistics and occurrence frequencies of typical postures and movements. We found significant differences between pain and control trials with analyses of variance and binomial tests. In BioVid and BP4D, pain was accompanied by head movements and postures that tend to be oriented downwards or towards the pain site. We also found differences in movement range and speed in all three datasets. The results suggest that head movements and postures should be considered for pain assessment and research. As additional pain indicators, they possibly might improve pain management whenever behavior is assessed, especially in nonverbal individuals such as infants or patients with dementia. However, in advance more research is needed to identify specific head movements and postures in pain patients

Head posture time series with corresponding video frames showing reaction to a painful heat stimulus from BioVid dataset (high temperature plateau lasting from second 0 to 3.5).

<p>The subject moves her head downwards and followed by a little upward movement, which is reflected by the increase and following decrease of the pitch angle.</p

Overview on analyzed datasets.

<p>In each dataset, the same subjects underwent painful trials and control trials. For the BioVid dataset, several videos were excluded from analyses, because participants left the camera’s field of view or visual review revealed obvious pose measurement errors. Abbreviations: M = mean, SD = standard deviation.</p

Specific head posture’s occurrence counts and significance test results.

<p>Each dataset was subdivided in 27 postures. The 8 postures that occurred most frequently among pain trials were considered for comparing the frequency of occurrences in pain and control trials with binomial tests. The figure illustrates the 8 postures per dataset and lists the occurrence frequencies in the trial categories. Significant differences are marked by asterisks.</p

Head movement clusters in the BioVid dataset with number of pain and control trials falling into the cluster.

<p>Clusters are illustrated by their mean movement. Significant differences (according to the conduced binomial tests) are marked by asterisks.</p

Egocentric rotation angles describing orientation of the head in degrees (DEG).

<p>Pitch quantifies down- or upward head orientation, yaw quantifies left or right head turn, and roll quantifies right or left head tilt.</p

Head movement: Summary statistics of angular velocities (in DEG/s).

<p>Pitch, yaw, and roll velocity of each trial video sequence were summarized by their respective mean value and mean of magnitude. For each dataset (BioVid, UNBC, and BP4D) and statistic (columns) we report mean and standard deviation, M (SD), of pain and control trials as well as the <i>p</i>-value of the respective analysis of variance (rows). Significant differences are highlighted in bold.</p

Presentation of picture blocks.

<p>Presentation of picture blocks.</p