Computer Mediated Automatic Detection of Pain-Related Behavior: Prospect, Progress, Perils

Pain is often characterized as a fundamentally subjective phenomenon; however, all pain assessment reduces the experience to observables, with strengths and limitations. Most evidence about pain derives from observations of pain-related behavior. There has been considerable progress in articulating the properties of behavioral indices of pain; especially, but not exclusively those based on facial expression. An abundant literature shows that a limited subset of facial actions, with homologs in several non-human species, encode pain intensity across the lifespan. Unfortunately, acquiring such measures remains prohibitively impractical in many settings because it requires trained human observers and is laborious. The advent of the field of affective computing, which applies computer vision and machine learning (CVML) techniques to the recognition of behavior, raised the prospect that advanced technology might overcome some of the constraints limiting behavioral pain assessment in clinical and research settings. Studies have shown that it is indeed possible, through CVML, to develop systems that track facial expressions of pain. There has since been an explosion of research testing models for automated pain assessment. More recently, researchers have explored the feasibility of multimodal measurement of pain-related behaviors. Commercial products that purport to enable automatic, real-time measurement of pain expression have also appeared. Though progress has been made, this field remains in its infancy and there is risk of overpromising on what can be delivered. Insufficient adherence to conventional principles for developing valid measures and drawing appropriate generalizations to identifiable populations could lead to scientifically dubious and clinically risky claims. There is a particular need for the development of databases containing samples from various settings in which pain may or may not occur, meticulously annotated according to standards that would permit sharing, subject to international privacy standards. Researchers and users need to be sensitive to the limitations of the technology (for e.g., the potential reification of biases that are irrelevant to the assessment of pain) and its potentially problematic social implications.

Indicators of Health-Related Quality of Life in Cats With Degenerative Joint Disease: Systematic Review and Proposal of a Conceptual Framework

Objectives: The assessment of health-related quality of life (HRQoL) is becoming increasingly important in companion animals. This study describes a systematic review and development of a proposed conceptual framework to assess HRQoL in cats with osteoarthritis (OA).Methods: The conceptual framework was developed according to published guidelines. A comprehensive search of the CAB Direct, Scopus, PubMed, and Web of Science databases was carried out for publications in English from inception to November 12, 2019. Search words used were “cat”, “feline”, “chronic pain”, “pain”, and “quality of life”. Publications were selected if they were full-text and peer-reviewed, based on primary data, and identified or measured behavioral symptoms of chronic musculoskeletal pain in cats. A systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A data extraction form was developed from categories identified in the literature review and piloted on a small number of studies to ascertain the appropriateness for relevant data extraction. Categories were then finalized, and key domains were identified. The domains were then synthesized to develop a conceptual framework.Results: A total of 454 studies were identified, of which 14 met the eligibility criteria and were included in the meta-synthesis. All 14 were assessed to be of good quality. Seven domains related to HRQoL in cats with OA were thematically identified from the data: mobility, physical appearance, energy and vitality, mood, pain expression, sociability, and physical and mental wellbeing. The three main HRQoL domains were pain expression, mobility, and physical and mental wellbeing, which impacted all the others. Pain and mobility impacted all six other domains, with increased pain and decreased mobility negatively impacting physical appearance, energy and vitality, mood, sociability, and physical and mental wellbeing.Conclusions and Relevance: This is the first study to develop an evidence-based conceptual framework for the assessment of HRQoL in cats with OA. The proposed conceptual framework suggests that effective management of chronic pain in cats may improve their overall HRQoL.

Natural human postural oscillations enhance the empathic response to a facial pain expression in a virtual character

Virtual reality platforms producing interactive and highly realistic characters are being used more and more as a research tool in social and affective neuroscience to better capture both the dynamics of emotion communication and the unintentional and automatic nature of emotional processes. While idle motion (i.e., non-communicative movements) is commonly used to create behavioural realism, its use to enhance the perception of emotion expressed by a virtual character is critically lacking. This study examined the influence of naturalistic (i.e., based on human motion capture) idle motion on two aspects (the perception of other’s pain and affective reaction) of an empathic response towards pain expressed by a virtual character. In two experiments, 32 and 34 healthy young adults were presented video clips of a virtual character displaying a facial expression of pain while its body was either static (still condition) or animated with natural postural oscillations (idle condition). The participants in Experiment 1 rated the facial pain expression of the virtual human as more intense, and those in Experiment 2 reported being more touched by its pain expression in the idle condition compared to the still condition, indicating a greater empathic response towards the virtual human’s pain in the presence of natural postural oscillations. These findings are discussed in relation to the models of empathy and biological motion processing. Future investigations will help determine to what extent such naturalistic idle motion could be a key ingredient in enhancing the anthropomorphism of a virtual human and making its emotion appear more genuine.

Facial Muscles Reactions to Other Person’s Facial Expressions of Pain

The aim of this study was to record facial electromiograms (EMG) while subjects were viewing facial expressions of different pain levels (no-pain, medium pain and very painful) and to find objective criteria for measuring pain expressed in human’s face. The study involved 18 students with age 21 years. The magnitude of the EMG response of m. corrugator supercilii depended on voluntary performed facial pain expression in the subjects. EMG responses of voluntary performed facial pain expressions to mirrored pain reactions were detected at two time span intervals: 200–300 ms after stimulation in m. zygomaticus major, and 400–500 ms after stimulation in m. corrugator supercilii. These differences disappear after 1300 ms. In the second time interval, differences in EMG responses of both muscle groups occur 1600 ms after stimulus presentation, but disappear differently: 3100 ms after stimulation in m. zygomaticus major and 4000 ms in m. corrugator supercilii. Constant responding with “medium pain” expression when recognizing faces of different pain expressions have an effect on the voluntary EMG responses of individual subjects. Images with emotional expression “no pain” reduce m. corrugator supercilii activity and increase m. zygomaticus major activity for those observers.

3D Facial Pain Expression for a Care Training Assistant Robot in an Elderly Care Education Environment

As the elderly population increases, the importance of the caregiver’s role in the quality of life of the elderly has increased. To achieve effective feedback in terms of care and nursing education, it is important to design a robot that can express emotions or feel pain like an actual human through visual-based feedback. This study proposes a care training assistant robot (CaTARo) system with 3D facial pain expression that simulates an elderly person for improving the skills of workers in elderly care. First, in order to develop an accurate and efficient system for elderly care training, this study introduces a fuzzy logic–based care training evaluation method that can calculate the pain level of a robot for giving the feedback. Elderly caregivers and trainees performed the range of motion exercise using the proposed CaTARo. We obtained quantitative data from CaTARo, and the pain level was calculated by combining four key parameters using the fuzzy logic method. Second, we developed a 3D facial avatar for use in CaTARo that is capable of expressing pain based on the UNBC-McMaster Pain Shoulder Archive, and we then generated four pain groups with respect to the pain level. To mimic the conditions for care training with actual humans, we designed the system to provide pain feedback based on the opinions of experts. The pain feedback was expressed in real time by using a projector and a 3D facial mask during care training. The results of the study confirmed the feasibility of utilizing a care training robot with pain expression for elderly care training, and it is concluded that the proposed approach may be used to improve caregiving and nursing skills upon further research.

The Good, the Bad, and the Clever: Faking Ability as a Socio-Emotional Ability?

Socio-emotional abilities have been proposed as an extension to models of intelligence, but earlier measurement approaches have either not fulfilled criteria of ability measurement or have covered only predominantly receptive abilities. We argue that faking ability—the ability to adjust responses on questionnaires to present oneself in a desired manner—is a socio-emotional ability that can broaden our understanding of these abilities and intelligence in general. To test this theory, we developed new instruments to measure the ability to fake bad (malingering) and administered them jointly with established tests of faking good ability in a general sample of n = 134. Participants also completed multiple tests of emotion perception along with tests of emotion expression posing, pain expression regulation, and working memory capacity. We found that individual differences in faking ability tests are best explained by a general factor that had a large correlation with receptive socio-emotional abilities and had a zero to medium-sized correlation with different productive socio-emotional abilities. All correlations were still small after controlling these effects for shared variance with general mental ability as indicated by tests of working memory capacity. We conclude that faking ability is indeed correlated meaningfully with other socio-emotional abilities and discuss the implications for intelligence research and applied ability assessment.