Pain communication through body posture: The development and validation of a stimulus set

Denver pain authenticity stimulus set (D-PASS)

We introduce the Denver Pain Authenticity Stimulus Set (D-PASS), a free resource containing 315 videos of 105 unique individuals expressing authentic and posed pain. All expressers were recorded displaying one authentic (105; pain was elicited via a pressure algometer) and two posed (210) expressions of pain (one posed expression recorded before [posed-unrehearsed] and one recorded after [posed-rehearsed] the authentic pain expression). In addition to authentic and posed pain videos, the database includes an accompanying codebook including metrics assessed at the expresser and video levels (e.g., Facial Action Coding System metrics for each video controlling for neutral images of the expresser), expressers' pain threshold and pain tolerance values, averaged pain detection performance by naïve perceivers who viewed the videos (e.g., accuracy, response bias), neutral images of each expresser, and face characteristic rating data for neutral images of each expresser (e.g., attractiveness, trustworthiness). The stimuli and accompanying codebook can be accessed for academic research purposes from https://digitalcommons.du.edu/lsdl_dpass/1/ . The relatively large number of stimuli allow for consideration of expresser-level variability in analyses and enable more advanced statistical approaches (e.g., signal detection analyses). Furthermore, the large number of Black (n = 41) and White (n = 56) expressers permits investigations into the role of race in pain expression, perception, and authenticity detection. Finally, the accompanying codebook may provide pilot data for novel investigations in the intergroup or pain sciences.

Development, refinement, and validation of an equine musculoskeletal pain scale

Musculoskeletal disease is a common cause of chronic pain that is often overlooked and inadequately treated, impacting the quality of life of humans and horses alike. Lameness due to musculoskeletal pain is prevalent in horses, but the perception of pain by owners is low compared with veterinary diagnosis. Therefore, this study aims to establish and validate a pain scale for chronic equine orthopaedic pain that is user-friendly for horse owners and veterinarians to facilitate the identification and monitoring of pain in horses. The newly developed musculoskeletal pain scale (MPS) was applied to 154 horses (mean age 20 ± 6.4 years SD) housed at an equine sanctuary, of which 128 (83%) suffered from chronic orthopaedic disease. To complete the MPS, the horses were observed and videotaped from a distance while at rest in their box or enclosure. In addition, they received a complete clinical and orthopaedic exam. The need for veterinary intervention to address pain (assessed and executed by the sanctuary independent from this study) was used as a longitudinal health outcome to determine the MPS's predictive validity. To determine the interrater agreement, the MPS was scored for a randomly selected subset of 30 horses by six additional blinded raters, three equine veterinary practitioners, and three experienced equestrians. An iterative process was used to refine the tool based on improvements in the MPS's correlation with lameness evaluated at the walk and trot, predictive validity for longitudinal health outcomes, and interrater agreement. The intraclass correlation improved from 0.77 of the original MPS to 0.88 of the refined version (95% confidence interval: 0.8-0.94). The refined MPS correlated significantly with lameness at the walk (r = 0.44, p = 0.001) and trot (r = 0.5, p < 0.0001). The refined MPS significantly differed between horses that needed veterinary intervention (mean MPS = 8.6) and those that did not (mean MPS = 5.0, p = 0.0007). In summary, the MPS showed good interrater repeatability between expert and lay scorers, significant correlation with lameness at the walk and trot, and good predictive validity for longitudinal health outcomes, confirming its ability to identify horses with orthopaedic health problems.

A scoping review and index of body stimuli in psychological science

Naturalistic body stimuli are necessary for understanding many aspects of human psychology, yet there are no centralized databases of body stimuli. Furthermore, there are a high number of independently developed stimulus sets lacking in standardization and reproducibility potential, and a general lack of organization, contributing to issues of both replicability and generalizability in body-related research. We conducted a comprehensive scoping review to index and explore existing naturalistic whole-body stimuli. Our research questions were as follows: (1) What sets of naturalistic human whole-body stimuli are present in the literature? And (2) On what factors (e.g., demographics, emotion expression) do these stimuli vary? To be included, stimulus sets had to (1) include human bodies as stimuli; (2) be photographs, videos, or other depictions of real human bodies (not computer generated, drawn, etc.); (3) include the whole body (defined as torso, arms, and legs); and (4) could include edited images, but still had to be recognizable as human bodies. We identified a relatively large number of existing stimulus sets (N = 79) which offered relative variability in terms of main manipulated factors and the degree of visual information included (i.e., inclusion of heads and/or faces). However, stimulus sets were demographically homogenous, skewed towards White, young adult, and female bodies. We identified significant issues in reporting and availability practices, posing a challenge to the generalizability, reliability, and reproducibility of body-related research. Accordingly, we urge researchers to adopt transparent and accessible practices and to take steps to diversify body stimuli.

Experimental Pain Picture System (EPPS): Development and Validation

Pain-related pictures are useful for studying how individuals respond to pain-related stimulation. Such pictures can occasionally be found in databases for affective pictures. However, a validated database specifically for pain-related pictures is not available yet. In 2 experiments (N = 185 and 103, respectively), we developed and validated the Experimental Pain Pictures System (EPPS). In both experiments, negative valence, arousal, and painfulness ratings were compared between neutral-, sad-, and pain-related pictures. The pain-related pictures represented both deep and superficial somatic pain. Across the 2 experiments, pain-related pictures were judged as more negative, arousing, and painful than neutral pictures and more painful than sad pictures. The final EPPS contains 50 pictures of different painful events considered moderately to highly painful by participants. The EPPS is a valuable tool for studying pain-related responses, as it gives researchers a choice among many validated pictures depicting different types of pain, increasing the comparability between studies. PERSPECTIVE: This article presents the validation of the experimental pain pictures system, which consists of a set of pain-related pictures. The experimental pain pictures system is composed of pictures depicting different types of pain. Participants rated all the pictures as being negative, arousing, and painful.

Development of a binary classifier model from extended facial codes toward video-based pain recognition in cancer patients

OBJECTIVES

The Automatic Pain Assessment (APA) relies on the exploitation of objective methods to evaluate the severity of pain and other pain-related characteristics. Facial expressions are the most investigated pain behavior features for APA. We constructed a binary classifier model for discriminating between the absence and presence of pain through video analysis.

METHODS

A brief interview lasting approximately two-minute was conducted with cancer patients, and video recordings were taken during the session. The Delaware Pain Database and UNBC-McMaster Shoulder Pain dataset were used for training. A set of 17 Action Units (AUs) was adopted. For each image, the OpenFace toolkit was used to extract the considered AUs. The collected data were grouped and split into train and test sets: 80 % of the data was used as a training set and the remaining 20 % as the validation set. For continuous estimation, the entire patient video with frame prediction values of 0 (no pain) or 1 (pain), was imported into an annotator (ELAN 6.4). The developed Neural Network classifier consists of two dense layers. The first layer contains 17 nodes associated with the facial AUs extracted by OpenFace for each image. The output layer is a classification label of "pain" (1) or "no pain" (0).

RESULTS

The classifier obtained an accuracy of ∼94 % after about 400 training epochs. The Area Under the ROC curve (AUROC) value was approximately 0.98.

CONCLUSIONS

This study demonstrated that the use of a binary classifier model developed from selected AUs can be an effective tool for evaluating cancer pain. The implementation of an APA classifier can be useful for detecting potential pain fluctuations. In the context of APA research, further investigations are necessary to refine the process and particularly to combine this data with multi-parameter analyses such as speech analysis, text analysis, and data obtained from physiological parameters.

Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts. The purpose of this article is to discuss the state of the art of research and perspectives on APA applications in both research and clinical scenarios. Principles of AI functioning will be addressed. For narrative purposes, AI-based methods are grouped into behavioral-based approaches and neurophysiology-based pain detection methods. Since pain is generally accompanied by spontaneous facial behaviors, several approaches for APA are based on image classification and feature extraction. Language features through natural language strategies, body postures, and respiratory-derived elements are other investigated behavioral-based approaches. Neurophysiology-based pain detection is obtained through electroencephalography, electromyography, electrodermal activity, and other biosignals. Recent approaches involve multimode strategies by combining behaviors with neurophysiological findings. Concerning methods, early studies were conducted by machine learning algorithms such as support vector machine, decision tree, and random forest classifiers. More recently, artificial neural networks such as convolutional and recurrent neural network algorithms are implemented, even in combination. Collaboration programs involving clinicians and computer scientists must be aimed at structuring and processing robust datasets that can be used in various settings, from acute to different chronic pain conditions. Finally, it is crucial to apply the concepts of explainability and ethics when examining AI applications for pain research and management.

Going Deeper than Tracking: A Survey of Computer-Vision Based Recognition of Animal Pain and Emotions

Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go ‘deeper’ than tracking, and address automated recognition of animals’ internal states such as emotions and pain with the aim of improving animal welfare, making this a timely moment for a systematization of the field. This paper provides a comprehensive survey of computer vision-based research on recognition of pain and emotional states in animals, addressing both facial and bodily behavior analysis. We summarize the efforts that have been presented so far within this topic—classifying them across different dimensions, highlight challenges and research gaps, and provide best practice recommendations for advancing the field, and some future directions for research.

Attentional Biases Towards Body Expressions of Pain in Men and Women

This study investigated whether there are gender differences in attention to bodily expressions of pain and core emotions. Three experiments are reported using the attentional dot probe task. Images of men and women displaying bodily expressions, including pain, were presented. The task was used to determine whether participants' attention was drawn towards or away from target expressions. Inconsistent evidence was found for an attentional bias towards body expressions, including pain. While biases were affected by gender, patterns varied across the Experiments. Experiment 1, which had a presentation duration of 500 ms, found a relative bias towards the location of male body expressions compared to female expressions. Experiments 2 and 3 varied stimulus exposure times by including both shorter and longer duration conditions (e.g., 100 vs. 500 vs. 1250 ms). In these experiments, a bias towards pain was confirmed. Gender differences were also found, especially in the longer presentation conditions. Expressive body postures captured the attention of women for longer compared to men. These results are discussed in light of their implications for why there are gender differences in attention to pain, and what impact this has on pain behaviour. PERSPECTIVE: We show that men and women might differ in how they direct their attention towards bodily expressions, including pain. These results have relevance to understanding how carers might attend to the pain of others, as well as highlighting the wider role that social-contextual factors have in pain.

Gender differences in attention to pain body postures in a social context: a novel use of the bodies in the crowd task

Pain signals the presence of potential harm, captures attention, and can inhibit performance on concurrent tasks. What is less well known, however, is whether such attentional capture also occurs in a wider social context, such as when observing people in pain. To explore this possibility, we adopted a novel social-cue detection methodology: the bodies-in-the-crowd task. Two experiments are reported that consider whether nonverbal cues of pain, happiness, and anger as expressed through body postures would capture and hold attention. Both experiments recruited 40 (20 male and 20 female) pain-free individuals. Overall, results show that pain postures do not capture attention any more than happiness or anger postures, but disengagement from pain postures was significantly slower across both studies. Gender differences were also found, and were more likely to be found when crowds comprised both men and women. Male pain postures were more likely to capture attention. However, female observers had faster target detection speed, and were quicker to disengage from distractors. They also showed slower disengagement from female expressions overall. Male observers showed no variation based on target or distractor gender. Implications and potential directions for future research are discussed.

The role of observer's fear of pain and health anxiety in empathy for pain: an experimental study

Introduction

Empathy for pain is influenced by several factors, including observer beliefs. This study aimed to test the associations between empathy for pain, fear of pain and health anxiety.

Methods

A total of 182 participants rated their levels of empathy towards 16 images (8 female and 8 male) of individuals in pain and provided measures of fear of pain, health anxiety as well as age, sex and the presence of current pain.

Findings

Both fear of pain and health anxiety were positively associated with empathy for pain, but in the regression model, only fear of pain was a significant positive predictor of overall empathy for pain and its three subscales: affective distress, vicarious pain and empathic concern. The presence of pain also predicted overall empathy for pain, affective distress and vicarious pain.Observer's sex and age were not significant. The pattern of results remained the same when we repeated the analysis separately for images with males and females.

Conclusion

The results suggest that more fearful observers, and those in current pain themselves, have higher levels of empathy for pain. Future research should examine the mechanisms underlying this relationship and how fear of pain may influence empathic behaviours towards people in pain.

[From external assessment of pain to automated multimodal measurement of pain intensity : Narrative review of state of research and clinical perspectives]

BACKGROUND

In patients with limited communication skills, the use of conventional scales or external assessment is only possible to a limited extent or not at all. Multimodal pain recognition based on artificial intelligence (AI) algorithms could be a solution.

OBJECTIVE

Overview of the methods of automated multimodal pain measurement and their recognition rates that were calculated with AI algorithms.

METHODS

In April 2018, 101 studies on automated pain recognition were found in the Web of Science database to illustrate the current state of research. A selective literature review with special consideration of recognition rates of automated multimodal pain measurement yielded 14 studies, which are the focus of this review.

RESULTS

The variance in recognition rates was 52.9-55.0% (pain threshold) and 66.8-85.7%; in nine studies the recognition rate was ≥80% (pain tolerance), while one study reported recognition rates of 79.3% (pain threshold) and 90.9% (pain tolerance).

CONCLUSION

Pain is generally recorded multimodally, based on external observation scales. With regard to automated pain recognition and on the basis of the 14 selected studies, there is to date no conclusive evidence that multimodal automated pain recognition is superior to unimodal pain recognition. In the clinical context, multimodal pain recognition could be advantageous, because this approach is more flexible. In the case of one modality not being available, e.g., electrodermal activity in hand burns, the algorithm could use other modalities (video) and thus compensate for missing information.

The Pain Assessment in Impaired Cognition scale (PAIC15): A multidisciplinary and international approach to develop and test a meta-tool for pain assessment in impaired cognition, especially dementia

BACKGROUND

Over the last decades, a considerable number of observational scales have been developed to assess pain in persons with dementia. The time seems ripe now to build on the knowledge and expertize implemented in these scales to form an improved, "best-of" meta-tool. The EU-COST initiative "Pain in impaired cognition, especially dementia" aimed to do this by selecting items out of existing observational scales and critically re-assessing their suitability to detect pain in dementia. This paper reports on the final phase of this collaborative task.

METHODS

Items from existing observational pain scales were tested for "frequency of occurrence (item difficulty)," "reliability" and "validity." This psychometric testing was carried out in eight countries, in different healthcare settings, and included clinical as well as experimental pain conditions.

RESULTS

Across all studies, 587 persons with dementia, 27 individuals with intellectual disability, 12 Huntington's disease patients and 59 cognitively healthy controls were observed during rest and movement situations or while receiving experimental pressure pain, respectively. The psychometric outcomes for each item across the different studies were evaluated within an international and multidisciplinary team of experts and led a final selection of 15 items (5x facial expressions, 5x body movements, 5x vocalizations).

CONCLUSIONS

The final list of 15 observational items have demonstrated psychometric quality and clinical usefulness both in their former scales and in the present international evaluation; accordingly, they qualified twice to form a new internationally agreed-on meta-tool for Pain Assessment in Impaired Cognition, the PAIC-15 scale.

SIGNIFICANCE

Using a meta-tool approach by building on previous observational pain assessment scales and putting the items of these scales through rigorous empirical testing (using experimental as well as clinical pain studies in several European countries), we were able to identify the best items for pain assessment in individuals with impaired cognition. These selected items form the novel PAIC15 scale (pain assessment in impaired cognition, 15 items).

Feeling Hurt: Revisiting the Relationship Between Social and Physical Pain

Pain overlap theory has generated decades of controversy and still receives considerable research attention. A major advance has been the revelation that social and physical pain activate similar neural regions, providing suggestive evidence of a “piggybacked” alarm system that coevolved to detect social exclusion. Recent developments, however, have brought neural evidence for pain overlap into question. We analyze these developments from a social psychological perspective and identify the need for a reformulated approach. To meet this need, we provide a framework that a priori predicts generalized overlap and specific divergence across a range of biopsychosocial domains. The framework points to a functional pattern for similarities and differences, which can be utilized to generate testable hypotheses so that the field can move forward. To demonstrate the utility and promise of the framework, we identify key hypotheses relating to attention, motivation, and responses to pain, and review research relevant to these hypotheses.

Interpersonal problem behavior and low back pain

OBJECTIVE

The theory of interpersonal problem behaviour (IPB) provides a more fundamental framework for understanding the psychosocial aspects of pain. The present study focused on the IPB, based on the Interpersonal Problem Circumplex (IPC), in persons with low back pain and its association with pain, psychological characteristics, and health care utilisation.

METHODS

In a cross-sectional design, individuals with back pain (N = 88) and healthy control persons who matched by age, gender, and educational level (N = 88) were compared with regard to IPB. Furthermore, back pain patients classified by their IPB (N = 24 low, N = 48 moderate, N = 16 high) were compared regarding pain, depression, catastrophising, and health care utilisation.

RESULTS

In comparison to the healthy reference sample, a significant difference in the interpersonal problems of the low back pain group, with a tendency towards being overly 'introverted', 'exploitable', and 'subassertive', was revealed. In the back pain group, participants with elevated IPB showed significantly higher levels of pain intensity, functional disability, depression, catastrophising, and health care utilisation than participants with IPB in the normal range.

CONCLUSION

Application of the Interpersonal Circumplex Model can help to characterize a subgroup of persons with low back pain. Increased general interpersonal problems are associated with elevated burden in pain-related, psychological, and health care-related variables. Future research should focus on the treatment opportunities for this subgroup, as well as on the influence of interpersonal problems during the course of back pain.

Accurate empathy of romantic partners increases pain ratings but promotes recovery

Background

Perceived empathy is a commonly used strategy to cope with pain and is crucial for maintaining intimacy in dyadic relationships.

Materials and methods

This study used the cold pressor test to investigate how perceived empathy and relationship type interact with the subjective perception of pain and objective measures of recovery time, using heart rate as an index. One hundred and ninety participants were recruited, including 49 friend dyads and 46 romantic partner dyads. Perceived empathy was manipulated by adopting three levels as the experimental conditions: high, accurate, and low.

Results

In the subjective perception stage, the results showed a significant interaction of relationship type and empathy with pain reporting, indicating that romantic partners reported more pain than friends under the accurate empathy condition. There were no differences between the two groups in the high and low perceived empathy conditions. In the self-recovery stage, the results showed that romantic partners had less pain tolerance than friends in all three perceived empathy conditions. On the other hand, romantic partners recovered faster than friends under the accurate empathy condition, but not under the high and low perceived empathy conditions.

Conclusion

These results suggest that perceived accurate empathy is necessary for romantic relationships when coping with pain. The findings deepen our understanding of the mechanism of perceived empathy, and the ways in which it modulates psychological and physiological responses in a social context.

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.

Sex differences in the decoding of pain-related body postures

BACKGROUND

Pain can be detected through nonverbal cues, including facial expressions, vocalisations, and body posture. While there are sex differences in how emotional expressions are recognized, these differences have not always been found for pain. One reason for this inconsistency may be methodological, as pain studies tend not to be designed to investigate individual differences in expression recognition. Also, few studies consider sex differences outside facial expression.

METHODS

This study applied an image degradation method used to examine individual differences in emotion recognition, to investigate sex differences in the decoding of pain body postures. Forty participants (20 male) were presented with a series of body posture images depicting pain at differing levels of image degradation. Happiness, anger and sadness expressions were also included for comparison.

RESULTS

Results showed significant effects of image degradation, affect type, and actor sex. Females were rated as presenting more intense pain than males; this pattern was also found for fear, but not anger or happiness. The accuracy of pain intensity judgements was reduced as image clarity decreased. Male actors depicting pain were recognized with greater accuracy than female actors. Interestingly, similar patterns were found for anger and fear expressions.

CONCLUSIONS

We conclude that sex has a significant influence on pain decoding under certain conditions, and while there are similarities with the way pain and core emotions are decoded, this may depend on the type of emotion presented. This also suggests that sex-related effects in the recognition of pain expressions may include body postural cues.

SIGNIFICANCE

Observer's judgements of pain displayed through body postures are driven by the sex of the person in pain.

Observer influences on pain: an experimental series examining same-sex and opposite-sex friends, strangers, and romantic partners

Despite the well-documented sex and gender differences, little is known about the relative impact of male-female social interactions on pain. Three experiments were conducted to investigate whether the type of interpersonal relationship men and women have with an observer affects how they respond to experimental pain. Study 1 recruited friends and strangers, study 2 examined the effects of same- and opposite-sex friends, whereas study 3 investigated the differences between opposite-sex friends and opposite-sex romantic partners. One hundred forty-four dyads were recruited (48 in each study). One person from each dyad completed 2 pain tasks, whereas the other person observed in silence. Overall, the presence of another person resulted in an increase in pain threshold and tolerance on the cold-pressor task and algometer. The sex status of the dyads also had a role, but only within the friendship groups. In particular, male friends had the most pronounced effect on men's pain, increasing pain tolerance. We suggest that the presence of an observer, their sex, and the nature of the participant-observer relationship all influence how pain is reported. Further research should focus on dyadic relationships, and their influence on how men and women report and communicate pain in specific contexts.

The Automatic Detection of Chronic Pain-Related Expression: Requirements, Challenges and the Multimodal EmoPain Dataset

Pain-related emotions are a major barrier to effective self rehabilitation in chronic pain. Automated coaching systems capable of detecting these emotions are a potential solution. This paper lays the foundation for the development of such systems by making three contributions. First, through literature reviews, an overview of how pain is expressed in chronic pain and the motivation for detecting it in physical rehabilitation is provided. Second, a fully labelled multimodal dataset (named 'EmoPain') containing high resolution multiple-view face videos, head mounted and room audio signals, full body 3D motion capture and electromyographic signals from back muscles is supplied. Natural unconstrained pain related facial expressions and body movement behaviours were elicited from people with chronic pain carrying out physical exercises. Both instructed and non-instructed exercises were considered to reflect traditional scenarios of physiotherapist directed therapy and home-based self-directed therapy. Two sets of labels were assigned: level of pain from facial expressions annotated by eight raters and the occurrence of six pain-related body behaviours segmented by four experts. Third, through exploratory experiments grounded in the data, the factors and challenges in the automated recognition of such expressions and behaviour are described, the paper concludes by discussing potential avenues in the context of these findings also highlighting differences for the two exercise scenarios addressed.