Facial expression as a potential measure of both intent and emotion

From masks to muscles: Mapping facial structure of Nycticebus

Facial musculature in mammals underlies mastication and nonverbal communicative facial displays. Our understanding of primate facial expression comes primarily from haplorrhines (monkeys and apes), while our understanding of strepsirrhine (lemurs and lorises) facial expression remains incomplete. We examined the facial muscles of six specimens from three Nycticebus species (Nycticebus coucang, Nycticebus javanicus, and Nycticebus menagensis) using traditional dissection methodology and novel three-dimensional facial scanning to produce a detailed facial muscle map, and compared these results to another nocturnal strepsirrhine genus, the greater bushbaby (Otolemur spp.). We observed 19 muscles with no differences among Nycticebus specimens. A total of 17 muscles were observed in both Nycticebus and Otolemur, with little difference in attachment and function but some difference in directionality of movement. In the oral region, we note the presence of the depressor anguli oris, which has been reported in other primate species but is absent in Otolemur. The remaining muscle is a previously undescribed constrictor nasalis muscle located on the lateral nasal alar region, likely responsible for constriction of the nares. We propose this newly described muscle may relate to vomeronasal organ functioning and the importance of the use of nasal musculature in olfactory communication. We discuss how this combined methodology enabled imaging of small complex muscles. We further discuss how the facial anatomy of Nycticebus spp. relates to their unique physiology and behavioral ecology.

Witness for resolution: post-conflict quadratic affiliation in semi-free ranging pigs

In social mammals, post-conflict resolution can involve the reunion of former opponents (reconciliation), spontaneous/solicited post-conflict affiliation of a third party with either opponent (triadic contacts), and affiliation between other individuals (hereafter bystanders; quadratic contacts). Quadratic contacts-possibly informing complex cognitive abilities-have been neglected in post-conflict studies. We investigated quadratic affiliation in semi-free ranging pigs Sus scrofa, at the ethical farm Parva-Domus (Cavagnolo, Italy). Kinship was known. We collected behavioral data on adult pigs (n = 104) via video recordings (43 h) followed by video analyses. Affiliative and anxiety behaviors between bystanders were collected under post-conflict (PC; following a conflict between non-bystanders) and matched-control (MC; no conflict) conditions. Quadratic affiliation was present in pigs, as bystanders affiliated more in PC than MC, and such affiliation was followed by a decrease in the anxiety behaviors of both the interacting bystanders. Thus, quadratic contacts may be partly aimed at reducing one's own anxiety (intrinsic regulation). Quadratic affiliation was highest between closely related bystanders, which suggests that such affiliation may be most effective when close kin is involved. Quadratic affiliation was lowest after reconciliation and spontaneous triadic contacts. This suggests that direct peacemaking between opponents and spontaneous triadic contacts with close kin may most likely replace quadratic affiliation. Hence, pigs can be influenced by the negative events that affect other pigs-but not themselves-and their response may be modulated by social factors. Such non-random quadratic affiliation may point toward the presence of elements of social appraisal abilities in pigs.

Finding biomarkers of experience in animals

At a time when there is a growing public interest in animal welfare, it is critical to have objective means to assess the way that an animal experiences a situation. Objectivity is critical to ensure appropriate animal welfare outcomes. Existing behavioural, physiological, and neurobiological indicators that are used to assess animal welfare can verify the absence of extremely negative outcomes. But welfare is more than an absence of negative outcomes and an appropriate indicator should reflect the full spectrum of experience of an animal, from negative to positive. In this review, we draw from the knowledge of human biomedical science to propose a list of candidate biological markers (biomarkers) that should reflect the experiential state of non-human animals. The proposed biomarkers can be classified on their main function as endocrine, oxidative stress, non-coding molecular, and thermobiological markers. We also discuss practical challenges that must be addressed before any of these biomarkers can become useful to assess the experience of an animal in real-life.

Deep learning strategies with CReToNeXt-YOLOv5 for advanced pig face emotion detection

This study underscores the paramount importance of facial expressions in pigs, serving as a sophisticated mode of communication to gauge their emotions, physical well-being, and intentions. Given the inherent challenges in deciphering such expressions due to pigs' rudimentary facial muscle structure, we introduced an avant-garde pig facial expression recognition model named CReToNeXt-YOLOv5. The proposed model encompasses several refinements tailored for heightened accuracy and adeptness in detection. Primarily, the transition from the CIOU to the EIOU loss function optimized the training dynamics, leading to precision-driven regression outcomes. Furthermore, the incorporation of the Coordinate Attention mechanism accentuated the model's sensitivity to intricate expression features. A significant innovation was the integration of the CReToNeXt module, fortifying the model's prowess in discerning nuanced expressions. Efficacy trials revealed that CReToNeXt-YOLOv5 clinched a mean average precision (mAP) of 89.4%, marking a substantial enhancement by 6.7% relative to the foundational YOLOv5. Crucially, this advancement holds profound implications for animal welfare monitoring and research, as our findings underscore the model's capacity to revolutionize the accuracy of pig facial expression recognition, paving the way for more humane and informed livestock management practices.

Visual perception of emotion cues in dogs: a critical review of methodologies

Comparative studies of human-dog cognition have grown exponentially since the 2000's, but the focus on how dogs look at us (as well as other dogs) as social partners is a more recent phenomenon despite its importance to human-dog interactions. Here, we briefly summarise the current state of research in visual perception of emotion cues in dogs and why this area is important; we then critically review its most commonly used methods, by discussing conceptual and methodological challenges and associated limitations in depth; finally, we suggest some possible solutions and recommend best practice for future research. Typically, most studies in this field have concentrated on facial emotional cues, with full body information rarely considered. There are many challenges in the way studies are conceptually designed (e.g., use of non-naturalistic stimuli) and the way researchers incorporate biases (e.g., anthropomorphism) into experimental designs, which may lead to problematic conclusions. However, technological and scientific advances offer the opportunity to gather much more valid, objective, and systematic data in this rapidly expanding field of study. Solving conceptual and methodological challenges in the field of emotion perception research in dogs will not only be beneficial in improving research in dog-human interactions, but also within the comparative psychology area, in which dogs are an important model species to study evolutionary processes.

Domestic pigs (Sus scrofa) engage in non-random post-conflict affiliation with third parties: cognitive and functional implications

In social mammals, conflict resolution involves the reunion of former opponents (aggressor and victim) after an aggressive event (reconciliation) or post-conflict triadic contacts with a third party, started by either opponent (solicited-TSC) or spontaneously offered by the third party (unsolicited-TUC). These post-conflict strategies can serve different functions, including consolation (specifically when TUCs reduce the victim's anxiety). We investigated the possible presence and modulating factors of such strategies on semi-free ranging pigs (Sus scrofa; N = 104), housed at the ethical farm Parva Domus (Cavagnolo, Italy). Kinship was known. Reconciliation was present and mainly occurred between weakly related pigs to possibly improve tolerant cohabitation. Triadic contacts (all present except aggressor TSCs) mostly occurred between close kin. TSCs enacted by victims reduced neither their post-conflict anxiety behaviors nor further attacks by the previous aggressor, possibly because TSCs remained largely unreciprocated. TUCs towards aggressors did not reduce aggressor post-conflict anxiety but limited aggression redirection towards third parties. TUCs towards the victim reduced the victim but not the third-party's anxiety. However, TUCs may also provide inclusive fitness benefits to third parties by benefiting close kin. In sum, pigs engaged in non-random solicited/unsolicited triadic contacts, which suggests that pigs might possess socio-emotional regulation abilities to change their own or others' experience and elements of social appraisal, necessary to detect the emotional arousal of relevant others and (in case of TUCs) take the agency to restore homeostasis.

Positive Welfare Indicators in Dairy Animals

Nowadays, there is growing interest in positive animal welfare not only from the view of scientists but also from that of society. The consumer demands more sustainable livestock production, and animal welfare is an essential part of sustainability, so there is interest in incorporating positive welfare indicators into welfare assessment schemes and legislation. The aim of this review is to cite all the positive welfare indicators that have been proposed for dairy animals in theory or practice. In total, twenty-four indicators were retrieved. The most promising are exploration, access to pasture, comfort and resting, feeding, and behavioral synchronicity. Qualitative behavioral assessment (QBA), social affiliative behaviors, play, maternal care, ear postures, vocalizations, visible eye white, nasal temperature, anticipation, cognitive bias, laterality, and oxytocin have been also studied in dairy ruminants. QBA is the indicator that is most often used for the on-farm welfare assessment. Among all dairy animals, studies have been performed mostly on cattle, followed by sheep and goats, and finally buffaloes. The research on camel welfare is limited. Therefore, there is a need for further research and official assessment protocols for buffaloes and especially camels.

Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning

Advances in neural networks have garnered growing interest in applications of machine vision in livestock management, but simpler landmark-based approaches suitable for small, early stage exploratory studies still represent a critical stepping stone towards these more sophisticated analyses. While such approaches are well-validated for calibrated images, the practical limitations of such imaging systems restrict their applicability in working farm environments. The aim of this study was to validate novel algorithmic approaches to improving the reliability of scale-free image biometrics acquired from uncalibrated images of minimally restrained livestock. Using a database of 551 facial images acquired from 108 dairy cows, we demonstrate that, using a simple geometric projection-based approach to metric extraction, a priori knowledge may be leveraged to produce more intuitive and reliable morphometric measurements than conventional informationally complete Euclidean distance matrix analysis. Where uncontrolled variations in image annotation, camera position, and animal pose could not be fully controlled through the design of morphometrics, we further demonstrate how modern unsupervised machine learning tools may be used to leverage the systematic error structures created by such lurking variables in order to generate bias correction terms that may subsequently be used to improve the reliability of downstream statistical analyses and dimension reduction.

Expressive Interaction Design Using Facial Muscles as Controllers

Here we describe a proof-of-concept case study focusing on the design and development of a novel computer interface that uses facial muscles to control interactivity within a virtual environment. We have developed a system comprised of skin-mounted electrodes that detect underlying muscle activity through electromyography. The signals from the electrodes are filtered and smoothed, then used as input data to an application that displays a virtual environment with a 3D animated avatar. The user’s expressions control the facial movements of the avatar, thus conveying user emotions through real-time animation of a representative face in a virtual scenario. To achieve this, we collaborated with our Public and Patient Involvement focus group to discuss concepts and design appropriate interactions, while simultaneously developing a prototype system. Programmers and 3D artists worked together to create a system whereby individual user facial muscles are connected to 3D animated models of the same muscle features represented in an avatar, providing the user with an option to receive visual and numerical feedback on the extent of their muscle control. Using the prototype system, people can communicate facial expressions virtually with each other, without the need for a camera. This research is part of an on-going project to develop a facial muscle rehabilitation system that can be optimized to help patients with conditions such as hypomimia.

The Application of 3D Landmark-Based Geometric Morphometrics towards Refinement of the Piglet Grimace Scale

Proper methods of assessment to objectively identify pain are essential for welfare improvements of piglets undergoing surgical castration on commercial farms. The Piglet Grimace Scale (PGS) is used to identify changes in facial expressions caused by acute pain in piglets undergoing tail docking and castration. However, subjective scoring methods are a concern for the validation of the PGS. The objectives of this study were to evaluate and refine the PGS through 3D landmark geometric morphometrics. Male piglets (n = 88) were randomly allocated to one of two treatments: castration and sham-castration. Piglet facial images were taken at four time points (before treatment, immediately post-treatment, 1 h post-treatment, and 4 h post-treatment) using a photogrammetry rig. Images were scored by four raters using five facial action units (FAUs): orbital tightening, ear position, temporal tension, lip contraction, and nose bulge/cheek tension. Three-dimensional facial models were generated and landmarked denoting 3 FAUs (orbital tightening, lip contraction, and nose bulge/cheek tension). Results suggest that orbital tightening and ear position may be reliable FAUs for the PGS. However, neither the PGS nor 3D landmark-based geometric morphometrics were able (both p > 0.10) to reliably identify facial indicators of pain in piglets undergoing castration.

Novel Method for Three-Dimensional Facial Expression Recognition Using Self-Normalizing Neural Networks and Mobile Devices

Introduction To date, most ways to perform facial expression recognition rely on two-dimensional images, advanced approaches with three-dimensional data exist. These however demand stationary apparatuses and thus lack portability and possibilities to scale deployment. As human emotions, intent and even diseases may condense in distinct facial expressions or changes therein, the need for a portable yet capable solution is signified. Due to the superior informative value of three-dimensional data on facial morphology and because certain syndromes find expression in specific facial dysmorphisms, a solution should allow portable acquisition of true three-dimensional facial scans in real time. In this study we present a novel solution for the three-dimensional acquisition of facial geometry data and the recognition of facial expressions from it. The new technology presented here only requires the use of a smartphone or tablet with an integrated TrueDepth camera and enables real-time acquisition of the geometry and its categorization into distinct facial expressions. Material and Methods Our approach consisted of two parts: First, training data was acquired by asking a collective of 226 medical students to adopt defined facial expressions while their current facial morphology was captured by our specially developed app running on iPads, placed in front of the students. In total, the list of the facial expressions to be shown by the participants consisted of "disappointed", "stressed", "happy", "sad" and "surprised". Second, the data were used to train a self-normalizing neural network. A set of all factors describing the current facial expression at a time is referred to as "snapshot". Results In total, over half a million snapshots were recorded in the study. Ultimately, the network achieved an overall accuracy of 80.54% after 400 epochs of training. In test, an overall accuracy of 81.15% was determined. Recall values differed by the category of a snapshot and ranged from 74.79% for "stressed" to 87.61% for "happy". Precision showed similar results, whereas "sad" achieved the lowest value at 77.48% and "surprised" the highest at 86.87%. Conclusions With the present work it can be demonstrated that respectable results can be achieved even when using data sets with some challenges. Through various measures, already incorporated into an optimized version of our app, it is to be expected that the training results can be significantly improved and made more precise in the future. Currently a follow-up study with the new version of our app that encompasses the suggested alterations and adaptions, is being conducted. We aim to build a large and open database of facial scans not only for facial expression recognition but to perform disease recognition and to monitor diseases' treatment progresses.

CalliFACS: The common marmoset Facial Action Coding System

Facial expressions are subtle cues, central for communication and conveying emotions in mammals. Traditionally, facial expressions have been classified as a whole (e.g. happy, angry, bared-teeth), due to automatic face processing in the human brain, i.e., humans categorise emotions globally, but are not aware of subtle or isolated cues such as an eyebrow raise. Moreover, the same facial configuration (e.g. lip corners pulled backwards exposing teeth) can convey widely different information depending on the species (e.g. humans: happiness; chimpanzees: fear). The Facial Action Coding System (FACS) is considered the gold standard for investigating human facial behaviour and avoids subjective interpretations of meaning by objectively measuring independent movements linked to facial muscles, called Action Units (AUs). Following a similar methodology, we developed the CalliFACS for the common marmoset. First, we determined the facial muscular plan of the common marmoset by examining dissections from the literature. Second, we recorded common marmosets in a variety of contexts (e.g. grooming, feeding, play, human interaction, veterinary procedures), and selected clips from online databases (e.g. YouTube) to identify their facial movements. Individual facial movements were classified according to appearance changes produced by the corresponding underlying musculature. A diverse repertoire of 33 facial movements was identified in the common marmoset (15 Action Units, 15 Action Descriptors and 3 Ear Action Descriptors). Although we observed a reduced range of facial movement when compared to the HumanFACS, the common marmoset's range of facial movements was larger than predicted according to their socio-ecology and facial morphology, which indicates their importance for social interactions. CalliFACS is a scientific tool to measure facial movements, and thus, allows us to better understand the common marmoset's expressions and communication. As common marmosets have become increasingly popular laboratory animal models, from neuroscience to cognition, CalliFACS can be used as an important tool to evaluate their welfare, particularly in captivity.

Systematic review of animal-based indicators to measure thermal, social, and immune-related stress in pigs

The intense nature of pig production has increased the animals’ exposure to stressful conditions, which may be detrimental to their welfare and productivity. Some of the most common sources of stress in pigs are extreme thermal conditions (thermal stress), density and mixing during housing (social stress), or exposure to pathogens and other microorganisms that may challenge their immune system (immune-related stress). The stress response can be monitored based on the animals’ coping mechanisms, as a result of specific environmental, social, and health conditions. These animal-based indicators may support decision making to maintain animal welfare and productivity. The present study aimed to systematically review animal-based indicators of social, thermal, and immune-related stresses in farmed pigs, and the methods used to monitor them. Peer-reviewed scientific literature related to pig production was collected using three online search engines: ScienceDirect, Scopus, and PubMed. The manuscripts selected were grouped based on the indicators measured during the study. According to our results, body temperature measured with a rectal thermometer was the most commonly utilized method for the evaluation of thermal stress in pigs (87.62%), as described in 144 studies. Of the 197 studies that evaluated social stress, aggressive behavior was the most frequently-used indicator (81.81%). Of the 535 publications examined regarding immune-related stress, cytokine concentration in blood samples was the most widely used indicator (80.1%). Information about the methods used to measure animal-based indicators is discussed in terms of validity, reliability, and feasibility. Additionally, the introduction and wide spreading of alternative, less invasive methods with which to measure animal-based indicators, such as cortisol in saliva, skin temperature and respiratory rate via infrared thermography, and various animal welfare threats via vocalization analysis are highlighted. The information reviewed was used to discuss the feasible and most reliable methods with which to monitor the impact of relevant stressors commonly presented by intense production systems on the welfare of farmed pigs.

Affective State Recognition in Livestock—Artificial Intelligence Approaches

Simple Summary

Emotions or affective states recognition in farm animals is an underexplored research domain. Despite significant advances in animal welfare research, animal affective state computing through the development and application of devices and platforms that can not only recognize but interpret and process the emotions, are in a nascent stage. The analysis and measurement of unique behavioural, physical, and biological characteristics offered by biometric sensor technologies and the affiliated complex and large data sets, opens the pathway for novel and realistic identification of individual animals amongst a herd or a flock. By capitalizing on the immense potential of biometric sensors, artificial intelligence enabled big data methods offer substantial advancement of animal welfare standards and meet the urgent needs of caretakers to respond effectively to maintain the wellbeing of their animals.

Abstract

Farm animals, numbering over 70 billion worldwide, are increasingly managed in large-scale, intensive farms. With both public awareness and scientific evidence growing that farm animals experience suffering, as well as affective states such as fear, frustration and distress, there is an urgent need to develop efficient and accurate methods for monitoring their welfare. At present, there are not scientifically validated ‘benchmarks’ for quantifying transient emotional (affective) states in farm animals, and no established measures of good welfare, only indicators of poor welfare, such as injury, pain and fear. Conventional approaches to monitoring livestock welfare are time-consuming, interrupt farming processes and involve subjective judgments. Biometric sensor data enabled by artificial intelligence is an emerging smart solution to unobtrusively monitoring livestock, but its potential for quantifying affective states and ground-breaking solutions in their application are yet to be realized. This review provides innovative methods for collecting big data on farm animal emotions, which can be used to train artificial intelligence models to classify, quantify and predict affective states in individual pigs and cows. Extending this to the group level, social network analysis can be applied to model emotional dynamics and contagion among animals. Finally, ‘digital twins’ of animals capable of simulating and predicting their affective states and behaviour in real time are a near-term possibility.

Current Advances in Assessment of Dog's Emotions, Facial Expressions, and Their Use for Clinical Recognition of Pain

Animals' facial expressions are involuntary responses that serve to communicate the emotions that individuals feel. Due to their close co-existence with humans, broad attention has been given to identifying these expressions in certain species, especially dogs. This review aims to analyze and discuss the advances in identifying the facial expressions of domestic dogs and their clinical utility in recognizing pain as a method to improve daily practice and, in an accessible and effective way, assess the health outcome of dogs. This study focuses on aspects related to the anatomy and physiology of facial expressions in dogs, their emotions, and evaluations of their eyebrows, eyes, lips, and ear positions as changes that reflect pain or nociception. In this regard, research has found that dogs have anatomical configurations that allow them to generate changes in their expressions that similar canids-wolves, for example-cannot produce. Additionally, dogs can perceive emotions similar to those of their human tutors due to close human-animal interaction. This phenomenon-called "emotional contagion"-is triggered precisely by the dog's capacity to identify their owners' gestures and then react by emitting responses with either similar or opposed expressions that correspond to positive or negative stimuli, respectively. In conclusion, facial expressions are essential to maintaining social interaction between dogs and other species, as in their bond with humans. Moreover, this provides valuable information on emotions and the perception of pain, so in dogs, they can serve as valuable elements for recognizing and evaluating pain in clinical settings.

Once bitten, twice shy: Aggressive and defeated pigs begin agonistic encounters with more negative emotions

Aggression between unfamiliar commercial pigs is common and likely invokes strong emotions in contestants. Furthermore, contest outcomes affect subsequent aggressive behaviour, suggesting a potential lasting influence on affective state. Here we used a combination of qualitative and quantitative methods to assess the emotional expression of pigs in agonistic encounters. We investigated how recent victory or defeat influences emotions expressed in a subsequent contest, and the role of aggressiveness as a personality trait in emotional expression. We observed the pre-escalation contest behaviour (second contest; age 13 wks) in animals of different aggressiveness (categorised using two resident intruder tests as Agg+ or Agg-, age 9 wks), which had recently won or lost a contest (first contest; 10 wks). We measured gaze direction and ear position. Observers watched video clips of the initial 30 s of the second contest and evaluated the emotional expression of 57 pigs (25 contest 1 winners, 32 contest 1 losers) using qualitative behavioural assessment (QBA) with a fixed list of 20 descriptive terms. QBA identified three principal components (PCs), accounting for 68% of the variation: PC1 (agitated/tense to relaxed/content), PC2 (fearful/aimless to confident/enjoying) and PC3 (listless/ indifferent). Agg- pigs and males showed a more positive emotionality (PC2). PC1 and PC3 were unaffected by first contest outcome and aggressiveness. Agg+ pigs were more likely to hold their ears back (X2 =7.8, p = 0.005) during the early contest period. Differences in attention were detected in the contest outcome × aggressiveness interaction (χ24.3, p = 0.04), whereby approaching the opponent was influenced by winning and losing in the Agg- pigs only. QBA and gaze behaviour reveal differences in emotional valence between pigs of different aggressiveness: less aggressive pigs may be more susceptible to the emotional impact of victory and defeat but overall, more aggressive pigs express more negative emotionality at the start of agonistic encounters.

Happy Cow or Thinking Pig? WUR Wolf—Facial Coding Platform for Measuring Emotions in Farm Animals

Emotions play an indicative and informative role in the investigation of farm animal behaviors. Systems that respond and can measure emotions provide a natural user interface in enabling the digitalization of animal welfare platforms. The faces of farm animals can be one of the richest channels for expressing emotions. WUR Wolf (Wageningen University & Research: Wolf Mascot), a real-time facial recognition platform that can automatically code the emotions of farm animals, is presented in this study. The developed Python-based algorithms detect and track the facial features of cows and pigs, analyze the appearance, ear postures, and eye white regions, and correlate these with the mental/emotional states of the farm animals. The system is trained on a dataset of facial features of images of farm animals collected in over six farms and has been optimized to operate with an average accuracy of 85%. From these, the emotional states of animals in real time are determined. The software detects 13 facial actions and an inferred nine emotional states, including whether the animal is aggressive, calm, or neutral. A real-time emotion recognition system based on YoloV3, a Faster YoloV4-based facial detection platform and an ensemble Convolutional Neural Networks (RCNN) is presented. Detecting facial features of farm animals simultaneously in real time enables many new interfaces for automated decision-making tools for livestock farmers. Emotion sensing offers a vast potential for improving animal welfare and animal–human interactions.

Evaluating the accuracy of facial expressions as emotion indicators across contexts in dogs

Facial expressions potentially serve as indicators of animal emotions if they are consistently present across situations that (likely) elicit the same emotional state. In a previous study, we used the Dog Facial Action Coding System (DogFACS) to identify facial expressions in dogs associated with conditions presumably eliciting positive anticipation (expectation of a food reward) and frustration (prevention of access to the food). Our first aim here was to identify facial expressions of positive anticipation and frustration in dogs that are context-independent (and thus have potential as emotion indicators) and to distinguish them from expressions that are reward-specific (and thus might relate to a motivational state associated with the expected reward). Therefore, we tested a new sample of 28 dogs with a similar set-up designed to induce positive anticipation (positive condition) and frustration (negative condition) in two reward contexts: food and toys. The previous results were replicated: Ears adductor was associated with the positive condition and Ears flattener, Blink, Lips part, Jaw drop, and Nose lick with the negative condition. Four additional facial actions were also more common in the negative condition. All actions except the Upper lip raiser were independent of reward type. Our second aim was to assess basic measures of diagnostic accuracy for the potential emotion indicators. Ears flattener and Ears downward had relatively high sensitivity but low specificity, whereas the opposite was the case for the other negative correlates. Ears adductor had excellent specificity but low sensitivity. If the identified facial expressions were to be used individually as diagnostic indicators, none would allow consistent correct classifications of the associated emotion. Diagnostic accuracy measures are an essential feature for validity assessments of potential indicators of animal emotion.

'Puppy Dog Eyes' Are Associated With Eye Movements, Not Communication

The inner brow raiser is a muscle movement that increases the size of the orbital cavity, leading to the appearance of so-called 'puppy dog eyes'. In domestic dogs, this expression was suggested to be enhanced by artificial selection and to play an important role in the dog-human relationship. Production of the inner brow raiser has been shown to be sensitive to the attentive stance of a human, suggesting a possible communicative function. However, it has not yet been examined whether it is sensitive to human presence. In the current study, we aimed to test whether the inner brow raiser differs depending on the presence or absence of an observer. We used two versions of a paradigm in an equivalent experimental setting in which dogs were trained to expect a reward; however, the presence/absence of a person in the test apparatus was varied. In the social context, a human facing the dog delivered the reward; in the non-social context, reward delivery was automatized. If the inner brow raiser has a communicative function and dogs adjust its expression to an audience, we expect it to be shown more frequently in the social context (when facing a person in the apparatus) than in the non-social context (when facing the apparatus without a person inside). The frequency of the inner brow raiser differed between the two contexts, but contrary to the prediction, it was shown more frequently in the non-social context. We further demonstrate that the inner brow raiser is strongly associated with eye movements and occurs independently in only 6% of cases. This result challenges the hypothesis that the inner brow raiser has a communicative function in dog-human interactions and suggests a lower-level explanation for its production, namely an association with eye movements.

Measuring Farm Animal Emotions-Sensor-Based Approaches

Understanding animal emotions is a key to unlocking methods for improving animal welfare. Currently there are no ‘benchmarks’ or any scientific assessments available for measuring and quantifying the emotional responses of farm animals. Using sensors to collect biometric data as a means of measuring animal emotions is a topic of growing interest in agricultural technology. Here we reviewed several aspects of the use of sensor-based approaches in monitoring animal emotions, beginning with an introduction on animal emotions. Then we reviewed some of the available technological systems for analyzing animal emotions. These systems include a variety of sensors, the algorithms used to process biometric data taken from these sensors, facial expression, and sound analysis. We conclude that a single emotional expression measurement based on either the facial feature of animals or the physiological functions cannot show accurately the farm animal’s emotional changes, and hence compound expression recognition measurement is required. We propose some novel ways to combine sensor technologies through sensor fusion into efficient systems for monitoring and measuring the animals’ compound expression of emotions. Finally, we explore future perspectives in the field, including challenges and opportunities.

Extending the MaqFACS to measure facial movement in Japanese macaques (Macaca fuscata) reveals a wide repertoire potential

Facial expressions are complex and subtle signals, central for communication and emotion in social mammals. Traditionally, facial expressions have been classified as a whole, disregarding small but relevant differences in displays. Even with the same morphological configuration different information can be conveyed depending on the species. Due to a hardwired processing of faces in the human brain, humans are quick to attribute emotion, but have difficulty in registering facial movement units. The well-known human FACS (Facial Action Coding System) is the gold standard for objectively measuring facial expressions, and can be adapted through anatomical investigation and functional homologies for cross-species systematic comparisons. Here we aimed at developing a FACS for Japanese macaques, following established FACS methodology: first, we considered the species' muscular facial plan; second, we ascertained functional homologies with other primate species; and finally, we categorised each independent facial movement into Action Units (AUs). Due to similarities in the rhesus and Japanese macaques' facial musculature, the MaqFACS (previously developed for rhesus macaques) was used as a basis to extend the FACS tool to Japanese macaques, while highlighting the morphological and appearance changes differences between the two species. We documented 19 AUs, 15 Action Descriptors (ADs) and 3 Ear Action Units (EAUs) in Japanese macaques, with all movements of MaqFACS found in Japanese macaques. New movements were also observed, indicating a slightly larger repertoire than in rhesus or Barbary macaques. Our work reported here of the MaqFACS extension for Japanese macaques, when used together with the MaqFACS, comprises a valuable objective tool for the systematic and standardised analysis of facial expressions in Japanese macaques. The MaqFACS extension for Japanese macaques will now allow the investigation of the evolution of communication and emotion in primates, as well as contribute to improving the welfare of individuals, particularly in captivity and laboratory settings.

The Application of Geometric Morphometrics to Explore Potential Impacts of Anthropocentric Selection on Animals' Ability to Communicate via the Face: The Domestic Cat as a Case Study

During their domestication via artificial selection, humans have substantially modified the morphology and thus visual appearance of non-human animals. While research highlights the negative impact of these modifications on physical functioning, little is known about their impact on behavior and signaling, either toward humans or conspecifics. Changes in the appearance of the face, such as those associated with, but not limited to, facial expressions, form an important part of non-verbal communication. In companion animals, the face is one of their most visually diverse features (due to human-driven selection), which may impact the visual clarity of expressions and other forms of signaling. Using the domestic cat as our model, we applied a new analytical technique in order to understand the impact of breed variation on relative positioning of facial landmarks, chosen specifically for their association with the production of various facial movements, and the expression of affect. We then assessed the extent to which facial appearances known to be associated with a specific underlying state (i.e., pain, assessed via a validated, facial pain score), could be reliably detected in a morphologically diverse population. Substantial baseline variation in landmarks was identified at both the cephalic (e.g., brachycephalic, dolichocephalic, mesocephalic) as well as breed levels. While differences in facial pain scores could successfully differentiate between "pain" and "no pain" in the facial appearance of domestic shorthaired cats (DSH), these differences were no longer detectable when assessed within a larger more morphologically diverse population, after corrections for multiple testing were applied. There was also considerable overlap between pain scores in the DSH "pain" population and the neutral faces of other breeds. Additionally, for several paedomorphic breeds, their neutral face shapes produced scores indicative of greater pain, compared to most other breeds, including the DSH cats actually in pain. Our findings highlight the degree to which anthropocentric selection might disrupt the communicative content of animals' faces, in this case the domestic cat. These results also suggest a potential human preference for features extending beyond the infantile, to include negatively-valenced facial forms such as pain.

Can Tail and Ear Postures Be Suitable to Capture the Affective State of Growing Pigs?

The present study examined whether tail and ear postures in fattening pigs (n = 228) housed in different environments could be suitable for assessing their affective state. In doing so, it investigated the appearance of curled-up, hanging, raised, tucked-under or wagging tails, respectively, ears directed forward, backward, mixed, and laterally. The environments included a barren and two enriched habitats that offered straw-bedded pens and soil-based rooting areas for the pigs. The tail and ear postures were analyzed using the scan sampling method. At the end of fattening, the pigs in the barren environment showed significantly fewer curled-up tails than those in the enriched environment. The barren-housed pigs showed also more raised, respectively, wagging tails than the enriched-housed pigs. Particularly at the end of fattening, there were no differences concerning the ears directed forward between the two environments and significantly fewer ears directed laterally were observed in the barren than in the enriched environment. Primarily, the curled-up tails could be suitable for indicating the affective state of the fattening pigs whereas the other tail, respectively, ear postures seemed to be less suitable to represent their affective state.

Moving Beyond the Absence of Pain and Distress: Focusing on Positive Animal Welfare

For many years, researchers, veterinarians, animal ethics committees, and regulators have focused on minimizing pain and distress as a primary goal of refinement when working with animals in science. More recent publications as well as a shift in animal ethics and public opinion have emphasized promotion of positive affective states, culminating in the concept of positive animal welfare. Robust measures are required to know when positive animal welfare states are occurring, and a number of measures are proposed and discussed. Regardless of whether there are newer methods available that focus exclusively on measuring positive affective states, consistent consideration of research animal behavioral programs, refinement, and adopting periodic stand-alone animal welfare assessments for all species involved will help to push the care and practices of research animals towards an increased focus on positive animal welfare.

Transforming the Adaptation Physiology of Farm Animals through Sensors

Simple Summary

Strategy for the protection and welfare of farm animals, and the sustainable animal production is dependent on the thorough understanding of the adaptation physiology. Real-time, continuous, and precise measurement of the multi-dimensions and complex intricacies of adaptive capacity of farm animals namely the mental, behavioral, and physiological states are possible only through the sensor-based approaches. This paper critically reviews the latest sensor technologies as assessment tools for the adaptation physiology of farm animals and explores their advantages over traditional measurement methods. Digital innovation, diagnostics, genetic testing, biosensors, and wearable animal devices are important tools that enable the development of decision support farming platforms and provides the path for predicting diseases in livestock. Sensor fusion data from a multitude of biochemical, emotional, and physiological functions of the farm animals not only helps to identify the most productive animal but also allows farmers to predict which individual animal may have greater resilience to common diseases. Insights into the cost of adoption of sensor technologies on farms including computing capacity, human resources in training, and the sensor hardware are being discussed.

Abstract

Despite recent scientific advancements, there is a gap in the use of technology to measure signals, behaviors, and processes of adaptation physiology of farm animals. Sensors present exciting opportunities for sustained, real-time, non-intrusive measurement of farm animal behavioral, mental, and physiological parameters with the integration of nanotechnology and instrumentation. This paper critically reviews the sensing technology and sensor data-based models used to explore biological systems such as animal behavior, energy metabolism, epidemiology, immunity, health, and animal reproduction. The use of sensor technology to assess physiological parameters can provide tremendous benefits and tools to overcome and minimize production losses while making positive contributions to animal welfare. Of course, sensor technology is not free from challenges; these devices are at times highly sensitive and prone to damage from dirt, dust, sunlight, color, fur, feathers, and environmental forces. Rural farmers unfamiliar with the technologies must be convinced and taught to use sensor-based technologies in farming and livestock management. While there is no doubt that demand will grow for non-invasive sensor-based technologies that require minimum contact with animals and can provide remote access to data, their true success lies in the acceptance of these technologies by the livestock industry.

Turning Heads: The Effects of Face View and Eye Gaze Direction on the Perceived Attractiveness of Expressive Faces

We investigated whether the perceived attractiveness of expressive faces was influenced by head turn and eye gaze towards or away from the observer. In all experiments, happy faces were consistently rated as more attractive than angry faces. A head turn towards the observer, whereby a full-face view was shown, was associated with relatively higher attractiveness ratings when gaze direction was aligned with face view (Experiment 1). However, preference for full-face views of happy faces was not affected by gaze shifts towards or away from the observer (Experiment 2a). In Experiment 3, the relative duration of each face view (front-facing or averted at 15°) during a head turn away or towards the observer was manipulated. There was benefit on attractiveness ratings for happy faces shown for a longer duration from the front view, regardless of the direction of head turn. Our findings support previous studies indicating a preference for positive expressions on attractiveness judgements, which is further enhanced by the front views of faces, whether presented during a head turn or shown statically. In sum, our findings imply a complex interaction between cues of social attention, indicated by the view of the face shown, and reward on attractiveness judgements of unfamiliar faces.

Challenges in the comparative study of empathy and related phenomena in animals

The aim of this review is to discuss recent arguments and findings in the comparative study of empathy. Based on a multidisciplinary approach including psychology and ethology, we review the non-human animal literature concerning theoretical frameworks, methodology, and research outcomes. One specific objective is to highlight discrepancies between theory and empirical findings, and to discuss ambiguities present in current data and their interpretation. In particular, we focus on emotional contagion and its experimental investigation, and on consolation and targeted helping as measures for sympathy. Additionally, we address the feasibility of comparing across species with behavioural data alone. One main conclusion of our review is that animal research on empathy still faces the challenge of closing the gap between theoretical concepts and empirical evidence. To advance our knowledge, we propose to focus more on the emotional basis of empathy, rather than on possibly ambiguous behavioural indicators, and we provide suggestions to overcome the limitations of previous research .

Where are we heading? Challenges in evidence-based severity assessment

Evidence-based severity assessment in laboratory animals is, apart from the ethical responsibility, imperative to generate reproducible, standardized and valid data. However, the path towards a valid study design determining the degree of pain, distress and suffering experienced by the animal is lined with pitfalls and obstacles as we will elucidate in this review. Furthermore, we will ponder on the genesis of a holistic concept relying on multifactorial composite scales. These have to combine robust and reliable parameters to measure the multidimensional aspects that define the severity of animal experiments, generating a basis for the substantiation of the refinement principle.

Infrared thermography of agonistic behaviour in pigs

Infrared thermography (IRT) or thermal imaging is increasingly being used as a non-invasive method to gain information on animals' physiological and emotional state. IRT has the potential to serve as a non-invasive quantitative assessment method but few studies have examined its utility in predicting welfare-relevant outcomes of dynamic scenarios relevant to commercial farming. This study used 1284 thermal images taken from 46 pigs in a controlled test environment while they engaged in an agonistic encounter (dyadic contest) at 13 wk. of age. Images were taken of the complete body from a dorsal perspective. A pilot study indicated that a rectangular thermal window on the back region was the most suitable and reliable area for obtaining temperature data in this situation. From this thermal window, the average, minimum and maximum temperature, standard deviation and coefficient of variation (CV) were obtained. These were analysed in relation to contest phase (from non-contact assessment, through escalated fighting to retreat), fight occurrence, contest duration, contest outcome (winner/loser status) and changes in blood glucose, blood lactate, and skin injuries. Variables showed a strong change in response to the moment of contest resolution (retreat of the loser); temperatures reduced sharply and CV increased, but did not differ between winners and losers. Contests that included a fight showed lower temperatures. Contest duration, body weight and sex only had minor influences on the temperatures. As the drop in temperature at contest resolution was irrespective of contest intensity, and the pattern was similar in winners and losers, this data potentially reflects vasoconstriction as a result of psychological stress rather than solely a physiological change. The study shows that peripheral temperature, as recorded by IRT, responds to the intensity and phases of a contest and may allow new insight into the physiological and welfare outcomes of aggressive behaviour.