Action Coding Research Articles

Determinan Pending Claim Badan Penyelenggara Jaminan Sosial Kesehatan di Rumah Sakit

Pending claims are a problem that still often occurs in Indonesia, where many hospitals face obstacles in the BPJS Kesehatan claim process. This problem can have a significant impact on the quality of health services. This study aims to analyze the factors that cause BPJS Kesehatan pending claims in hospitals. The method used is literature review by searching for articles through the Google Scholar database in the last five years. The study follows PRISMA guidelines and uses the PICO framework to determine inclusion and exclusion criteria. The keywords used in the search involve the operator's boolean: "Factor" AND "Pending Claim" OR "Return" AND "BPJS" OR "JKN". From the search results, 20 articles were found that were worthy of systematic review. The results of the review showed that 17 articles identified internal factors as the main cause of pending claims, especially the incompleteness of supporting documents such as laboratory results, ECG, and chronological letters. In addition, 19 articles revealed external factors as the main cause, namely lack of thoroughness and responsibility in carrying out tasks, such as data input errors, incompleteness in filling out medical resumes, and inaccuracies in diagnostic or action codes. Internal and external factors influence each other, so the right solutions are needed for every aspect, including improving the quality of documentation, improving the e-claim information system, and developing human resource competencies through training.

Examining Mammalian facial behavior using Facial Action Coding Systems (FACS) and combinatorics.

There has been an increased interest in standardized approaches to coding facial movement in mammals. Such approaches include Facial Action Coding Systems (FACS), where individuals are trained to identify discrete facial muscle movements that combine to create a facial configuration. Some studies have utilized FACS to analyze facial signaling, recording the quantity of morphologically distinct facial signals a species can generate. However, it is unclear whether these numbers represent the total number of facial muscle movement combinations (which we refer to as facial configurations) that each species is capable of producing. If unobserved combinations of facial muscle movements are communicative in nature, it is crucial to identify them, as this information is important for testing research hypotheses related to the evolution of complex communication among mammals. Our study aimed to assess how well the existing literature represents the potential range of facial signals in two previously studied species: chimpanzees (Pan troglodytes) and domesticated cats (Felis silvestris catus). We adhered to the coding guidelines outlined in the FACS manuals, which are based on the anatomical constraints and capabilities of each mammal's face, to create our comprehensive list of all potential facial configurations. Using this approach, we found that chimpanzees and domesticated cats may be capable of producing thousands of facial configurations, many of which have not yet been documented in the existing research literature. It is plausible that some of these facial configurations are communicative and could be discovered with further research and video recording. In addition to our findings having significant implications for future research on the communicative complexity of mammals, it can also assist researchers in evaluating FACS coding accuracy.

GorillaFACS: The Facial Action Coding System for the Gorilla spp.

The Facial Action Coding System (FACS) is an objective observation tool for measuring human facial behaviour. It avoids subjective attributions of meaning by objectively measuring independent movements linked to facial muscles, called Action Units (AUs). FACS has been adapted to 11 other taxa, including most apes, macaques and domestic animals, but not yet gorillas. To carry out cross species studies of facial expressions within and beyond apes, gorillas need to be included in such studies. Hence, we developed the GorillaFACS for the Gorilla spp. We followed similar methodology as previous FACS: First, we examined the facial muscular plan of the gorilla. Second, we analysed gorilla videos in a wide variety of contexts to identify their spontaneous facial movements. Third, we classified the individual facial movements according to appearance changes produced by the corresponding underlying musculature. A diverse repertoire of 42 facial movements was identified in the gorilla, including 28 AUs and 14 Action Descriptors, with several new movements not identified in the HumanFACS. Although some of the movements in gorillas differ from humans, the total number of AUs is comparable to the HumanFACS (32 AUs). Importantly, the gorilla's range of facial movements was larger than expected, suggesting a more relevant role in social interactions than what was previously assumed. GorillaFACS is a scientific tool to measure facial movements, and thus, will allow us to better understand the gorilla's expressions and communication. Furthermore, GorillaFACS has the potential be used as an important tool to evaluate this species welfare, particularly in settings of close proximity to humans.

Facial Biosignals Time–Series Dataset (FBioT): A Visual–Temporal Facial Expression Recognition (VT-FER) Approach

Visual biosignals can be used to analyze human behavioral activities and serve as a primary resource for Facial Expression Recognition (FER). FER computational systems face significant challenges, arising from both spatial and temporal effects. Spatial challenges include deformations or occlusions of facial geometry, while temporal challenges involve discontinuities in motion observation due to high variability in poses and dynamic conditions such as rotation and translation. To enhance the analytical precision and validation reliability of FER systems, several datasets have been proposed. However, most of these datasets focus primarily on spatial characteristics, rely on static images, or consist of short videos captured in highly controlled environments. These constraints significantly reduce the applicability of such systems in real-world scenarios. This paper proposes the Facial Biosignals Time–Series Dataset (FBioT), a novel dataset providing temporal descriptors and features extracted from common videos recorded in uncontrolled environments. To automate dataset construction, we propose Visual–Temporal Facial Expression Recognition (VT-FER), a method that stabilizes temporal effects using normalized measurements based on the principles of the Facial Action Coding System (FACS) and generates signature patterns of expression movements for correlation with real-world temporal events. To demonstrate feasibility, we applied the method to create a pilot version of the FBioT dataset. This pilot resulted in approximately 10,000 s of public videos captured under real-world facial motion conditions, from which we extracted 22 direct and virtual metrics representing facial muscle deformations. During this process, we preliminarily labeled and qualified 3046 temporal events representing two emotion classes. As a proof of concept, these emotion classes were used as input for training neural networks, with results summarized in this paper and available in an open-source online repository.

No need to execute: Omitted responses still yield response-response binding effects.

In the literature on human action control, the binding and retrieval of responses are assumed to shape the coordination of more complex actions. Specifically, the consecutive execution of two responses is assumed to result in their integration into cognitive representations (so-called event files) and can be retrieved from that upon later response repetition, thereby influencing behavior. Against the background of ideomotor theory and more recent theorizing in the binding and retrieval in action control framework (Frings et al., 2020), we investigated whether response execution is necessary for binding and retrieval of responses. We manipulated whether the retrieving response (Experiment 1), as well as the to-be-bound response (Experiment 2), is executed or omitted. The results showed that responses do not need to be executed to retrieve other responses or to be bound to other responses. Apparently, activating the cognitive representation of a response sufficed for this response to trigger event file binding and retrieval. Our results are the first to show that response-response binding is not dependent on executing responses. Together, the results support the core assumptions of ideomotor theory and the binding and retrieval in action control framework, namely a common coding of action and perception. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Facial expression analysis in children with autism spectrum disorder using a refined Human-Robot-Game platform for active learning

ABSTRACT The use of serious video games and robotics in children's education and therapy is rapidly increasing. Innovative Human-Robot-Game (HRG) platforms are particularly promising for assessing learning and behaviour in children with autism spectrum disorder (ASD), who often face challenges with attention, communication, and socialisation. Research shows that when children with ASD engage with social robots connected to interactive educational games, their learning, attention, and communication skills improve. This study aims to monitor the psychosocial and cognitive progress of children with ASD using an HRG platform, refining it as a tool for active learning. The article focuses on enhancing the facial recognition metrics of the HRG platform, which is identified as LOLY-MIDI and designed to measure attention and emotions in children while playing serious video games with the assistance of a social robot. Using a mixed-methods experimental approach strategy, reviewing previous studies, and employing tools like OpenFace and the Facial Action Coding System (FACS) for facial recognition, the research achieved greater precision in designing these metrics, providing accurate measurements of attention and emotional responses. The findings offer valuable insights for psychology and education professionals in assessing the socio-educational progress of children with ASD.

Tool Representations in Human Visual Cortex.

Tools such as pens, forks, and scissors play an important role in many daily-life activities, an importance underscored by the presence in visual cortex of a set of tool-selective brain regions. This review synthesizes decades of neuroimaging research that investigated the representational spaces in the visual ventral stream for objects, such as tools, that are specifically characterized by action-related properties. Overall, results reveal a dissociation between representational spaces in ventral and lateral occipito-temporal cortex (OTC). While lateral OTC encodes both visual (shape) and action-related properties of objects, distinguishing between objects acting as end-effectors (e.g., tools, hands) versus similar noneffector manipulable objects (e.g., a glass), ventral OTC primarily represents objects' visual features such as their surface properties (e.g., material and texture). These areas act in concert with regions outside of OTC to support object interaction and tool use. The parallel investigation of the dimensions underlying object representations in artificial neural networks reveals both the possibilities and the difficulties in capturing the action-related dimensions that distinguish tools from other objects. Although artificial neural networks offer promise as models of visual cortex computations, challenges persist in replicating the action-related dimensions that go beyond mere visual features. Taken together, we propose that regions in OTC support the representation of tools based on a behaviorally relevant action code and suggest future paths to generate a computational model of this object space.

Neurobiology and Anatomy of Facial Expressions in Great Apes: Application of the AnimalFACS and Its Possible Association with the Animal's Affective State.

The Facial Action Coding System (FACS) is an anatomically based system to study facial expression in humans. Currently, it is recognized that nonhuman animals, particularly nonhuman primates, have an extensive facial ethogram that changes according to the context and affective state. The facial expression of great apes, the closest species to humans, has been studied using the ChimpFACS and OrangFACS as reliable tools to code facial expressions. However, although the FACS does not infer animal emotions, making additional evaluations and associating the facial changes with other parameters could contribute to understanding the facial expressions of nonhuman primates during positive or negative emotions. The present review aims to discuss the neural correlates and anatomical components of emotional facial expression in great apes. It will focus on the use of Facial Action Coding Systems (FACSs) and the movements of the facial muscles (AUs) of chimpanzees, orangutans, and gorillas and their possible association with the affective state of great apes.

Stress recognition identifying relevant facial action units through explainable artificial intelligence and machine learning

Background and objective: Facial cues and expressions constitute a component of bodily responses that provide useful information about one’s stress levels. According to the Facial Action Coding System, they can be modelled consistently in terms of fundamental facial muscle movements, called facial Action Units (AUs). This article investigates automatic acute stress recognition based on AUs using conventional Machine and Deep Learning techniques. Methods: We created a new experimental dataset containing 58 participants performing 4 experimental phases and 11 stress and non-stress tasks in which the proposed system performs automatic facial AUs recognition. A computational feature selection method was employed to select a robust relevant AU combinations subset, which integrated with conventional Machine Learning and Deep Learning methods using the Layer-Wise Relevance Propagation algorithm to assess and model the implication of AUs under acute stress conditions. Ordinal modelling was used following the pairwise transformation to establish a common reference based on the personalized values of each participant. Results: The results indicate that, under acute stress conditions, participants’ faces presented significantly more AUs and with greater intensity compared to neutral conditions. The most relevant combination of AUs to each stress type was computationally identified, ranked and selected. The mean yielded classification accuracy of stress condition versus neutral achieved across all experimental tasks was greater than 93%. Conclusions: There are specific combinations of AUs that are relevant to the stress conditions of each experimental phase leading in each case to better neutral and stress separability.

Analisis Semiotika Feminisme Radikal dalam Film Poor Things

The issue of feminism has been a topic of intense and in-depth discussion in various circles, involving a variety of perspectives in academic, social, and cultural studies. Social dynamics that occur such as social class injustice based on gender, oppression of women, sexism, patriarchal ideology that defines women as objects of sexuality and so on make this issue raised in any media, one of which is film. In this study, researchers are interested in analyzing the film Poor Things directed by Yorgos Lanthimos from a script by Tony McNamara which highlights women having freedom over their bodies, the setting of this film was taken in the Victorian era where at that time women were considered a second class that functioned to satisfy male sexual urges. This research aims to explain the meaning of the semiotic code of radical feminism in Poor Things directed by Yorgos Lanthimos from a script by Tony McNamara which highlights women having freedom over their bodies. The method used in this research is a qualitative approach with John Fiske's semiotic analysis based on codes that are divided into three levels, namely the level of reality, representation and ideology. The results show the values of radical feminism at the level of reality through the codes of appearance, makeup, costumes, speech, environment and behavior. At the representation level, the values of feminism are shown through the codes of camera, character, action, conflict and dialog. At the ideological level, radical feminism found in the movie Poor Things is included in patriarchal ideology. In the movie Poor Things, the level of ideology displayed is patriarchy where women are considered as a second class that functions to satisfy men's sexual urges.

Playful programming, Social Resilience, and Persistent Actions as Drivers of Preservice Early Childhood Teachers’ Engagement in Computer Science

In this qualitative study, preservice early childhood education teachers created block-based code to control robots and used the robots in field experience at local preschools. The study is grounded in a conceptual framework that weaves together playful programing and resilience, interlocking concepts that can explain sustained engagement during times of challenge. We investigated how and why preservice early childhood teachers exhibit resilience during collaborative programing. We analyzed their debugging processes, reflections, and interviews using a phenomenological lens. We conducted open and axial coding and analysis of discourse and actions during debugging episodes. Results suggest that teachers exhibited resilience due to the following three reasons: through playful coding, preservice early childhood teachers (a) learned that computer science is approachable and fun, (b) engaged in adaptive attribution, and (c) engaged in joint celebration when they observed each other’s successes during collaborative tinkering. These findings provide potential insights for teacher learning of computing but also for novices learning to program.

Prototype Facial Response to Cute Stimuli: Expression and Recognition.

Cute, kindchenschema stimuli can evoke a suite of cognitive, physiological, and behavioral tendencies thought to promote caregiving. This research investigated facial expression elements associated with this response to cuteness and assessed the recognizability of an expression combining these elements. In Studies 1 and 2, participants at a community outreach event (Study 1, n = 19) and undergraduate students (Study 2, n = 103) showed spontaneous facial displays while watching videos/photos of baby humans and animals. These were Facial Action Coding System (FACS)-coded, revealing characteristic and statistically distinctive action unit elements of facial expression responses to cuteness. In six follow-up online studies (combined N = 962), including replications with Syrian refugees (n = 103) and Chinese samples (n = 222), a "cuteness prototype" expression combining all elements identified across Studies 1 and 2 (i.e., oblique brows, chin raise, lip tightening, and Duchenne smile) was commonly interpreted as a response to cuteness. These findings add to a growing literature about caregiving-focused motivational states and associated emotion/affect.

Knowledge over Time of Action Codes for Perceived Objects: An Exploratory Study on Developmental Children.

Over the past 20 years, there has been a growing interest in the processing of tool objects, and in the spatial S-R correspondence effects obtained with pictures of manipulable objects. Beyond the original affordance activation account, a location coding account has been proposed for such behavioral effects, which states that the location of the visually salient portion of an object speeds up spatially aligned motor responses and slows down misaligned ones. Furthermore, an additional action coding account has been proposed, according to which it is the direction of the action of the perceived object (e.g., "pouring tea leftward" when the spout of a teapot is leftward-oriented) that biases motor performance. We investigated this action coding account of S-R correspondence effects by comparing the reaction time (RT) performance of two groups: younger (6 to 9 years old) and older (10 to 13 years old) children. We assumed that knowledge of tool objects and the activation of action codes from object perception is proportional to age. Therefore, a larger correspondence effect was hypothesized for the older relative to the younger children's group. Consistently, a 34 ms correspondence effect was observed in the older children relative to the younger ones (18 ms). The results support the view that action direction is a constitutive feature of tool objects, which is subject to experience, and thus, to increasing knowledge over time.

Vicarious facilitation of facial responses to pain: Does the others' expression need to be painful?

Prior exposure to others' facial expressions of pain can lead to a facilitation of pain responses, including its corresponding response channel, namely facial responses to pain. It has been questioned, however, whether this vicarious pain facilitation occurs only when observing others' pain or whether the observation of other negative expressions can trigger similar facilitation of facial responses to pain. The study aimed to test this, by comparing the impact of viewing others' facial expressions of pain versus another negative expression (sadness) and two control expressions (neutral, happiness) on facial responses to pain. Participants (N = 56; 31 females), watched short video clips of computer-generated facial expressions (pain, sadness, neutral & happiness) before they received painful and non-painful heat stimuli. Facial responses were analysed using the Facial Action Coding System. In addition, subjective and autonomic responses were assessed. The prior exposure to others' expressions of pain and sadness versus neutral did not lead to significantly increased facial responses to pain. Likewise, subjective and autonomic pain responses were not facilitated. However, viewing others' expressions of happiness, consistently reduced facial as well as subjective and autonomic responses to pain compared to others' negative or neutral expressions. This dampening effect was not observed for non-painful heat. Facial and other pain responses were most strongly affected by prior exposure to others' facial expressions of happiness, which led to a pain-dampening effect. In contrast, the evidence for vicarious facilitation of pain was rather weak in the present study, with no evidence of pain-specificity. Facial responses to pain - along with subjective and autonomic responses - are reduced when observing others' expressions of happiness, demonstrating pain modulation by positive affective social signals, which may also transfer to clinical contexts.

Acquisition and Analysis of Facial Electromyographic Signals for Emotion Recognition.

The objective of the article is to recognize users' emotions by classifying facial electromyographic (EMG) signals. A biomedical signal amplifier, equipped with eight active electrodes positioned in accordance with the Facial Action Coding System, was used to record the EMG signals. These signals were registered during a procedure where users acted out various emotions: joy, sadness, surprise, disgust, anger, fear, and neutral. Recordings were made for 16 users. The mean power of the EMG signals formed the feature set. We utilized these features to train and evaluate various classifiers. In the subject-dependent model, the average classification accuracies were 96.3% for KNN, 94.9% for SVM with a linear kernel, 94.6% for SVM with a cubic kernel, and 93.8% for LDA. In the subject-independent model, the classification results varied depending on the tested user, ranging from 91.4% to 48.6% for the KNN classifier, with an average accuracy of 67.5%. The SVM with a cubic kernel performed slightly worse, achieving an average accuracy of 59.1%, followed by the SVM with a linear kernel at 53.9%, and the LDA classifier at 41.2%. Additionally, the study identified the most effective electrodes for distinguishing between pairs of emotions.

Representation of “Sapa Nandur Ngundhuh” in the Wayang Performance of Cupu Manik Astagina by Ki Enthus Susmono

Wayang kulit not only functions as entertainment, but is also a vehicle for conveying philosophical messages. As in the Cupu Manik Astagina puppet play, there is a philosophical message in the form of "sapa nandur ngundhuh" or whoever plants will reap. Therefore, this study aims to explore the philosophical message of "sapa nandur ngundhuh" in the Cupu Manik Astagina puppet play by Ki Enthus Susmono by representing it so that the message can be conveyed. This qualitative research uses Stuart Hall's representation theory through Roland Barthes' semiotic analysis model, namely symbolic code and action code. The data source is a video of a shadow puppet performance entitled "Pakeliran Solid Wayang Kulit Lakon Cupu Manik Astagina by Ki Enthus Susmono" on YouTube Aa Studio. The listening-note taking technique is used to collect data in the form of words and utterances obtained from ginem and janturan in the story. It is known through the symbol code and action code. The results showed that the concept of "sapa nandur ngundhuh" in the Cupu Manik Astagina puppet play does not only apply to the karma themselves, but can affect other people, including their descendants. In the story of Dewi Windradi, her actions have consequences not only for herself, but also her three children. This research also highlights how karma can be prevented from continuing to reap through some tirakat practices. Such as fasting (ngrowot), meditation and asceticism (tapa brata) which aim to cleanse themselves of past sins and minimize negative karma in the future.

Beyond the Rhetoric of Revanchism Towards the Metropolitan Core: An Analysis of Symbolic Representations of Milan From Its Peripheries

Socio-political research has shown that in metropolitan peripheries, populist parties have gained significant support. This is because these parties capitalise on a widespread feeling of exclusion, leading to a revanchist social representation of affluent metropolitan centres. This article contributes to the debate on metropolitan dynamics by exploring the social representations of the centre–periphery relationship, showing how symbolic representations play a role in shaping codes of action and revanchism alone is insufficient to understand the core–periphery relationship. Four suburbs with similar socioeconomic characteristics in the functional urban area of Milan were selected. Milan is the most important Italian metropolis, and it has a relevant socio-political fracture. Semi-structured interviews were carried out to analyse the cultural meanings of living on the periphery among local leaders. The metropolitan centre is perceived as necessary, evoking ‘efficient’ representations; however, these peripheral contexts are meaningful places of belonging. This article shows that an analysis of the dynamics at work at the metropolitan level should consider peripheral contexts.

Being facially expressive is socially advantageous

Individuals vary in how they move their faces in everyday social interactions. In a first large-scale study, we measured variation in dynamic facial behaviour during social interaction and examined dyadic outcomes and impression formation. In Study 1, we recorded semi-structured video calls with 52 participants interacting with a confederate across various everyday contexts. Video clips were rated by 176 independent participants. In Study 2, we examined video calls of 1315 participants engaging in unstructured video-call interactions. Facial expressivity indices were extracted using automated Facial Action Coding Scheme analysis and measures of personality and partner impressions were obtained by self-report. Facial expressivity varied considerably across participants, but little across contexts, social partners or time. In Study 1, more facially expressive participants were more well-liked, agreeable, and successful at negotiating (if also more agreeable). Participants who were more facially competent, readable, and perceived as readable were also more well-liked. In Study 2, we replicated the findings that facial expressivity was associated with agreeableness and liking by their social partner, and additionally found it to be associated with extraversion and neuroticism. Findings suggest that facial behaviour is a stable individual difference that proffers social advantages, pointing towards an affiliative, adaptive function.

BALANCING SENSORY STIMULATION/DEPRIVATION FROM THE ENVIRONMENT IN HEALTH-FORMING TECHNOLOGIES

The Medicine of the near future will develop not only along the path of improving diagnostics, treatment, rehabilitation, but also through the development of technologies for the formation (promotion) of health, human enhancement, and work productivity. It is clear that, due to their highly specialized multimodal sensory sensitivity, living systems are flexibly and plastically remodeling, changing structure and function in a completely physiological manner. Therefore, an attempt was made to conceptually and experimentally test the possibility of balancing sensory stimulation and sensory deprivation in their close dependence on the circadian sleep-wake cycle. A group of examined individuals practiced a mandatory evening walk in the park area for 40-60 minutes for 15 days and sensory deprivation by turning off artificial lighting, television, computer, gadgets and any other sensory signaling streams in the evening, starting from 8:00 pm and until going to bed (10:00 pm). The Facial Action Coding System (FACS) was applied to classify, qualitatively and quantitatively evaluate the facial psychomotor reactions of a person in the dynamics of his emotional state and by this tool indirectly reflects the balance of the activating and rewarding systems. The results obtained suggest that after a 15-day course of “Balancing Sensory Stimulation/Deprivation” the examined individuals maintain a positive emotional state during virtual immersion in a safe environment in the morning after a night’s sleep compared to baseline measurements. It is strategically important to optimize labor, work, educational activities, prevent overload and fatigue, it is necessary to ensure the formation of a balance of circadian sensory stimulation and deprivation in combination with activities that improve the architecture and quality of sleep.

Consistent movement of viewers' facial keypoints while watching emotionally evocative videos.

Neuropsychological research aims to unravel how diverse individuals' brains exhibit similar functionality when exposed to the same stimuli. The evocation of consistent responses when different subjects watch the same emotionally evocative stimulus has been observed through modalities like fMRI, EEG, physiological signals and facial expressions. We refer to the quantification of these shared consistent signals across subjects at each time instant across the temporal dimension as Consistent Response Measurement (CRM). CRM is widely explored through fMRI, occasionally with EEG, physiological signals and facial expressions using metrics like Inter-Subject Correlation (ISC). However, fMRI tools are expensive and constrained, while EEG and physiological signals are prone to facial artifacts and environmental conditions (such as temperature, humidity, and health condition of subjects). In this research, facial expression videos are used as a cost-effective and flexible alternative for CRM, minimally affected by external conditions. By employing computer vision-based automated facial keypoint tracking, a new metric similar to ISC, called the Average t-statistic, is introduced. Unlike existing facial expression-based methodologies that measure CRM of secondary indicators like inferred emotions, keypoint, and ICA-based features, the Average t-statistic is closely associated with the direct measurement of consistent facial muscle movement using the Facial Action Coding System (FACS). This is evidenced in DISFA dataset where the time-series of Average t-statistic has a high correlation (R2 = 0.78) with a metric called AU consistency, which directly measures facial muscle movement through FACS coding of video frames. The simplicity of recording facial expressions with the automated Average t-statistic expands the applications of CRM such as measuring engagement in online learning, customer interactions, etc., and diagnosing outliers in healthcare conditions like stroke, autism, depression, etc. To promote further research, we have made the code repository publicly available.