An extended emotion-eliciting film clips set (EGEFILM): assessment of emotion ratings for 104 film clips in a Turkish sample.

The primary aim of this study was to test emotion-elicitation levels of widely used film clips in a Turkish sample and to expand existing databases by adding several new film clips with the capacity to elicit a wide range of emotions, including a rarely studied emotion category, i.e., calmness. For this purpose, we conducted a comprehensive review of prior studies and collected a large number of new suggestions from a Turkish sample to select film clips for eight emotion categories: amusement, tenderness, calmness, anger, sadness, disgust, fear, and neutrality. Furthermore, we aimed to assess emotion-eliciting levels of short video clips, mostly taken by amateur video footage. In total, 104 film clips were tested online by rating several affective dimensions. Self-reported emotional experience was assessed in terms of intensity, discreteness, valence, and arousal. It was found that at least one of the existing film clips, most of the new film clips, and the short video clips were successful at eliciting medium to high levels of target emotions. However, we also observed overlaps between certain emotions (e.g., tenderness-sadness, anger-sadness-disgust, or fear-anxiety). The current results are mostly in line with previous databases, suggesting that film clips are efficient at eliciting a wide range of emotions where cultural background might play a role in the elicitation of certain emotions (e.g., amusement, anger, etc.). We hope that this extended emotion-eliciting film clips set (EGEFILM) will provide a rich resource for future emotion research both in Turkey and the international area.

Comparative Assessment of Physiological Responses to Emotional Elicitation by Auditory and Visual Stimuli.

The study of emotions through the analysis of the induced physiological responses gained increasing interest in the past decades. Emotion-related studies usually employ films or video clips, but these stimuli do not give the possibility to properly separate and assess the emotional content provided by sight or hearing in terms of physiological responses. In this study we have devised an experimental protocol to elicit emotions by using, separately and jointly, pictures and sounds from the widely used International Affective Pictures System and International Affective Digital Sounds databases. We processed galvanic skin response, electrocardiogram, blood volume pulse, pupillary signal and electroencephalogram from 21 subjects to extract both autonomic and central nervous system indices to assess physiological responses in relation to three types of stimulation: auditory, visual, and auditory/visual. Results show a higher galvanic skin response to sounds compared to images. Electrocardiogram and blood volume pulse show different trends between auditory and visual stimuli. The electroencephalographic signal reveals a greater attention paid by the subjects when listening to sounds compared to watching images. In conclusion, these results suggest that emotional responses increase during auditory stimulation at both central and peripheral levels, demonstrating the importance of sounds for emotion recognition experiments and also opening the possibility toward the extension of auditory stimuli in other fields of psychophysiology. Clinical and Translational Impact Statement- These findings corroborate auditory stimuli's importance in eliciting emotions, supporting their use in studying affective responses, e.g., mood disorder diagnosis, human-machine interaction, and emotional perception in pathology.

Indirect Identification of Perinatal Psychosocial Risks from Natural Language.

During the perinatal period, psychosocial health risks, including depression and intimate partner violence, are associated with serious adverse health outcomes for birth parents and children. To appropriately intervene, healthcare professionals must first identify those at risk, yet stigma often prevents people from directly disclosing the information needed to prompt an assessment. In this research we use short diary entries to indirectly elicit information that could indicate psychosocial risks, then examine patterns that emerge in the language of those at risk. We find that diary entries exhibit consistent themes, extracted using topic modeling, and emotional perspective, drawn from dictionary-informed sentiment features. Using these features, we use regularized regression to predict screening measures for depression and psychological aggression by an intimate partner. Journal text entries quantified through topic models and sentiment features show promise for depression prediction, corresponding with self-reported screening measures almost as well as closed-form questions. Text-based features are less useful in predicting intimate partner violence, but topic models generate themes that align with known risk correlates. The indirect features uncovered in this research could aid in the detection and analysis of stigmatized risks.

A novel multi-modal depression detection approach based on mobile crowd sensing and task-based mechanisms.

Depression has become a global concern, and COVID-19 also has caused a big surge in its incidence. Broadly, there are two primary methods of detecting depression: Task-based and Mobile Crowd Sensing (MCS) based methods. These two approaches, when integrated, can complement each other. This paper proposes a novel approach for depression detection that combines real-time MCS and task-based mechanisms. We aim to design an end-to-end machine learning pipeline, which involves multimodal data collection, feature extraction, feature selection, fusion, and classification to distinguish between depressed and non-depressed subjects. For this purpose, we created a real-world dataset of depressed and non-depressed subjects. We experimented with: various features from multi-modalities, feature selection techniques, fused features, and machine learning classifiers such as Logistic Regression, Support Vector Machines (SVM), etc. for classification. Our findings suggest that combining features from multiple modalities perform better than any single data modality, and the best classification accuracy is achieved when features from all three data modalities are fused. Feature selection method based on Pearson's correlation coefficients improved the accuracy in comparison with other methods. Also, SVM yielded the best accuracy of 86%. Our proposed approach was also applied on benchmarking dataset, and results demonstrated that the multimodal approach is advantageous in performance with state-of-the-art depression recognition techniques.

DynAMoS: The Dynamic Affective Movie Clip Database for Subjectivity Analysis.

In this paper, we describe the design, collection, and validation of a new video database that includes holistic and dynamic emotion ratings from 83 participants watching 22 affective movie clips. In contrast to previous work in Affective Computing, which pursued a single "ground truth" label for the affective content of each moment of each video (e.g., by averaging the ratings of 2 to 7 trained participants), we embrace the subjectivity inherent to emotional experiences and provide the full distribution of all participants' ratings (with an average of 76.7 raters per video). We argue that this choice represents a paradigm shift with the potential to unlock new research directions, generate new hypotheses, and inspire novel methods in the Affective Computing community. We also describe several interdisciplinary use cases for the database: to provide dynamic norms for emotion elicitation studies (e.g., in psychology, medicine, and neuroscience), to train and test affective content analysis algorithms (e.g., for dynamic emotion recognition, video summarization, and movie recommendation), and to study subjectivity in emotional reactions (e.g., to identify moments of emotional ambiguity or ambivalence within movies, identify predictors of subjectivity, and develop personalized affective content analysis algorithms). The database is made freely available to researchers for noncommercial use at https://dynamos.mgb.org.

Emotion elicitation during music listening: Subjective self-reports, facial expression, and autonomic reactivity.

The use of music as emotional stimuli in experimental studies has grown in recent years. However, prior studies have mainly focused on self-reports and central measures, with a few works exploring the time course of psychophysiological correlates. Moreover, most of the previous research has been carried out either from the dimensional or categorical model but not combining both approaches to emotions. This study aimed to investigate subjective and physiological correlates of emotion elicitation through music, following the three-dimensional and the discrete emotion model. A sample of 50 healthy volunteers (25 women) took part in this experiment by listening to 42 film music excerpts (14 pleasant, 14 unpleasant, 14 neutral) presented during 8 s, while peripheral measures were continuously recorded. After music offset, affective dimensions (valence, energy arousal, and tension arousal) as well as discrete emotions (happiness, sadness, tenderness, fear, and anger) were collected using a 9-point scale. Results showed an effect of the music category on subjective and psychophysiological measures. In peripheral physiology, greater electrodermal activity, heart rate acceleration, and zygomatic responses, besides lower corrugator amplitude, were observed for pleasant excerpts in comparison to neutral and unpleasant music, from 2 s after stimulus onset until the end of its duration. Overall, our results add evidence for the efficacy of standardized film music excerpts to evoke powerful emotions in laboratory settings; thus, opening a path to explore interventions based on music in pathologies with underlying emotion deregulatory processes.

The physiological signature of sadness: A comparison between text, film and virtual reality.

Studies focused on the ubiquitous emotion of sadness demonstrate substantial variability in physiological responses during sadness elicitation, with no consensus regarding the physiological pattern of sadness. Variability in findings could be attributed to (a) the use of different induction techniques across studies or (b) the existence of subtypes of sadness with distinct physiological activation patterns. Typically, studies have used text and film to elicit sadness. However, virtual reality (VR) confers advantages over more traditional methods by allowing individuals a subjective sense of "being there" or presence. We compared participants' physiological responses to the same narrative presented via VR, Film and Story (n = 20 each) and collected their subjective responses to the stimuli. Results confirmed that participants in all conditions experienced the discrete emotion of sadness. Moreover, participants in the VR condition experienced the highest degree of presence. Regarding psychophysiological responses, participants in the VR condition had the lowest degree of baseline-adjusted parasympathetic activation in comparison to participants in the Film condition. Furthermore, while participants in the VR group showed diminished baseline-adjusted respiration rate and parasympathetic activation with an increase in presence, the opposite pattern was true for participants in the other conditions. The data suggest that the VR condition may elicit an activating pattern of sadness; whereas Film and Story conditions may elicit a deactivating pattern of sadness. Our results have implications for research using the discrete model of emotion, highlighting that different emotion elicitation techniques may result in differing expressions of what is considered a unitary emotion.

Quantifying multidimensional control mechanisms of cardiovascular dynamics during multiple concurrent stressors.

Heartbeat regulation is achieved through different routes originating from central autonomic network sources, as well as peripheral control mechanisms. While previous studies successfully characterized cardiovascular regulatory mechanisms during a single stressor, to the best of our knowledge, a combination of multiple concurrent elicitations leading to the activation of different autonomic regulatory routes has not been investigated yet. Therefore, in this study, we propose a novel modeling framework for the quantification of heartbeat regulatory mechanisms driven by different neural routes. The framework is evaluated using two heartbeat datasets gathered from healthy subjects undergoing physical and mental stressors, as well as their concurrent administration. Experimental results indicate that more than 70% of the heartbeat regulatory dynamics is driven by the physical stressor when combining physical and cognitive/emotional stressors. The proposed framework provides quantitative insights and novel perspectives for neural activity on cardiac control dynamics, likely highlighting new biomarkers in the psychophysiology and physiopathology fields. A Matlab implementation of the proposed tool is available online.

Comparison of response to Chinese and Western videos of mental-health-related emotions in a representative Chinese sample.

BACKGROUND: Emotion plays an important role in mental health. Studying the relationship between emotion and mental health requires effective emotion-eliciting materials. Most standardized emotional stimuli, however, were based on Western contents and have not been validated in other cultures. The present study compared the emotional response to standard Western videos with videos of Chinese contents in a large representative Chinese sample. The effects of content source (film vs. real-life) and delivery medium (online vs. offline), as well as the effects of demographic factors were investigated. Participants' depression level was assessed to test the potential use of the videos in mental health research. METHODS: Top-ranked videos of basic emotions commonly implicated in mental health (happiness, sadness, anger, and fear) were chosen from a widely used Western video database. Twelve corresponding Chinese videos (film or real-life) were selected, with three clips for each emotion. In addition, three Chinese videos of the emotion "awe" were included because of the growing research attention to its role in promoting mental health. A large representative sample were recruited (N = 348) either online or offline and each participant viewed and rated his/her emotional reaction to all videos. RESULTS: All Chinese and Western videos effectively elicited target emotions. The intensity of emotional response was generally higher for Chinese videos than for Western videos. Film and real-life videos provided mixed results in terms of the intensity of elicited emotions. There was a small difference in the delivery medium in which one video watched online were rated more intense than being watched in the laboratory. Older adults were more emotional reactive than young people in general, but the latter showed more differentiated response to Chinese versus Western videos. People with higher education levels responded less to happy videos. Finally, emotional reactivity of anger and awe were negatively related to depression level, which was partially consistent with the emotional-context-insensitivity (ECI) hypothesis of depression. CONCLUSIONS: The results suggest that both Western and Chinese videos could reliably elicit emotion in Chinese people, but videos with local contents were generally more effective. The set of videos can be a useful tool for studying emotion and mental health in the Chinese cultural context.

Selection and validation of emotional videos: Dataset of professional and amateur videos that elicit basic emotions.

This article describes the process of selecting a collection of professional and amateur videos that elicit five basic emotions (i.e., happiness, fear, disgust, anger, and sadness) and validating these videos in three groups of participants (i.e., Chinese from China, Chinese from Malaysia, and Bumiputera from Malaysia). In the video selection phase, professional videos, which were Western movie trailers, were selected from IMDb (Internet Movie Database) and amateur videos were selected from YouTube. The researchers selected videos that display five basic emotions, identified the time frames with the strongest display of emotion, and rated the emotional intensity of each video on a 5-point Likert scale. After the initial stage of selection, two other researchers performed an emotion recognition task by watching the videos without audio to ensure that the emotions can be elicited without understanding the language. This data was used to refine the final selection of 20 professional videos and 20 amateur videos. In the video validation phase, 30 participants were asked to identify and rate the intensity of emotion felt. This article includes a description of the video selection method, a detailed list of the videos selected, and participants' responses and ratings of emotional intensity for the 40 videos.

Adaptive Non-Immersive VR Environment for Eliciting Fear of Cockroaches: A Physiology-Driven Approach Combined with 3D-TV Exposure.

Non-immersive VR environments are related to the least interactive application of VR techniques, such that interaction with the VR environment can occur commonly by 3D-TV without full immersion into the environment. This study presents how 3D-TV exposure combined with physiology recording can elicit fear of cockroaches among individuals with different levels of fear. Thirty-six participants, set apart into three fear groups (low vs. moderate vs. high), were exposed to VR environment with cockroaches for 4 minutes while recording and using cardiac activity as input to the VR environment. Results revealed significant effects on self-report measures and heart rate between different fear groups. Moreover, participants with higher levels of fear were more likely to trigger cockroaches into the scenario due to their cardiac acceleration. Overall results suggest that our physiology-driven VR environment is valid for fear elicitation while having potential use in therapeutic domain.

Los entornos de RV no inmersivos se constituyen en la aplicación de menor interactividad en relación con las técnicas de realidad virtual, de modo que la interacción con el entorno de realidad virtual puede ocurrir de forma común en televisores 3D (TV-3D), sin que exista una inmersión total en el entorno. Este estudio presenta cómo la exposición a la TV-3D, combinada con el registro fisiológico, puede inducir temor a las cucarachas en personas con diferentes niveles de miedo. Treinta y seis participantes, divididos en tres grupos según su nivel de miedo a las cucarachas, fueron expuestos a un entorno de realidad virtual con cucarachas, durante 4 minutos, mientras se registraba su actividad cardíaca, que fue usada como entrada para el entorno de realidad virtual. Los resultados revelaron efectos significativos en las medidas tomadas por autorreporte y en la frecuencia cardíaca de diferentes grupos temerosos a las cucarachas. Además, los participantes más temerosos son más propensos a desencadenar la aparición de cucarachas en el entorno de realidad virtual, debido a su aceleración cardíaca. Los resultados generales sugieren que nuestro entorno de RV es válido para inducir miedo a las cucarachas, con un potencial uso en el dominio terapéutico.

Emotion Elicitation Under Audiovisual Stimuli Reception: Should Artificial Intelligence Consider the Gender Perspective?

Identification of emotions triggered by different sourced stimuli can be applied to automatic systems that help, relieve or protect vulnerable groups of population. The selection of the best stimuli allows to train these artificial intelligence-based systems in a more efficient and precise manner in order to discern different risky situations, characterized either by panic or fear emotions, in a clear and accurate way. The presented research study has produced a dataset of audiovisual stimuli (UC3M4Safety database) that triggers a complete range of emotions, with a high level of agreement and with a discrete emotional categorization, as well as quantitative categorization in the Pleasure-Arousal-Dominance Affective space. This database is adequate for the machine learning algorithms contained in these automatic systems. Furthermore, this work analyses the effects of gender in the emotion elicitation under audiovisual stimuli, which can help to better design the final solution. Particularly, the focus is set on emotional responses to audiovisual stimuli reproducing situations experienced by women, such as gender-based violence. A statistical study of gender differences in emotional response was carried out on 1332 participants (811 women and 521 men). The average responses per video is around 84 (SD = 22). Data analysis was carried out with RStudio®.

Emotion Recognition in Immersive Virtual Reality: From Statistics to Affective Computing.

Emotions play a critical role in our daily lives, so the understanding and recognition of emotional responses is crucial for human research. Affective computing research has mostly used non-immersive two-dimensional (2D) images or videos to elicit emotional states. However, immersive virtual reality, which allows researchers to simulate environments in controlled laboratory conditions with high levels of sense of presence and interactivity, is becoming more popular in emotion research. Moreover, its synergy with implicit measurements and machine-learning techniques has the potential to impact transversely in many research areas, opening new opportunities for the scientific community. This paper presents a systematic review of the emotion recognition research undertaken with physiological and behavioural measures using head-mounted displays as elicitation devices. The results highlight the evolution of the field, give a clear perspective using aggregated analysis, reveal the current open issues and provide guidelines for future research.

Complex Scenes From the International Affective Picture System (IAPS).

Complex scenes from standardized stimuli databases such as the International Affective Picture System (IAPS) are organized dimensionally rather than discretely. Further, the potentially unique function of socially relevant scenes is often overlooked. This study sought to identify discrete categories of complex scenes from the IAPS and to explore if there were qualitative features that make the emotional content of some social scenes identifiable with higher levels of agreement. One hundred and three participants (53.4% female, mean age 24.4) judged 118 IAPS scenes as reflecting fear, happy, sad, or neutral. A second judgment study was conducted with a separate group of participants (N = 117; 79.2% female; mean age 30.41) to further characterize valid affective scenes across the full range of basic emotions. Sixty images received agreement on their emotional category from >70% of judges and were considered valid. IAPS identifier codes for these images are available for reference (along with the supplementary material from the second judgment study), organized by emotional and social content. An incidental observation was such that compared to nonsocial scenes, lower agreement rates were observed for social scenes across the board. Qualitative features of social scenes that were classified into emotional categories based on higher levels of agreement are discussed.

Toward Emotion Recognition From Physiological Signals in the Wild: Approaching the Methodological Issues in Real-Life Data Collection.

Emotion, mood, and stress recognition (EMSR) has been studied in laboratory settings for decades. In particular, physiological signals are widely used to detect and classify affective states in lab conditions. However, physiological reactions to emotional stimuli have been found to differ in laboratory and natural settings. Thanks to recent technological progress (e.g., in wearables) the creation of EMSR systems for a large number of consumers during their everyday activities is increasingly possible. Therefore, datasets created in the wild are needed to insure the validity and the exploitability of EMSR models for real-life applications. In this paper, we initially present common techniques used in laboratory settings to induce emotions for the purpose of physiological dataset creation. Next, advantages and challenges of data collection in the wild are discussed. To assess the applicability of existing datasets to real-life applications, we propose a set of categories to guide and compare at a glance different methodologies used by researchers to collect such data. For this purpose, we also introduce a visual tool called Graphical Assessment of Real-life Application-Focused Emotional Dataset (GARAFED). In the last part of the paper, we apply the proposed tool to compare existing physiological datasets for EMSR in the wild and to show possible improvements and future directions of research. We wish for this paper and GARAFED to be used as guidelines for researchers and developers who aim at collecting affect-related data for real-life EMSR-based applications.

Eliciting emotion ratings for a set of film clips: A preliminary archive for research in emotion.

Film clips are commonly used to elicit subjectively experienced emotional states for many research purposes, but film clips currently available in databases are out of date, include a limited set of emotions, and/or pertain to only one conceptualization of emotion. This work reports validation data from two studies aimed to elicit basic and complex emotions (amusement, anger, anxiety, compassion, contentment, disgust, fear, happiness/joy, irritation, neutrality, pride, relief, sadness, surprise), equally distributed according to valence (positive, negative) and intensity (high, low). Participants rated film clips according to the degree of experienced emotion, and for valence and arousal. Our findings initiate an iterative archive of film clips shown here to discretely elicit 11 different emotions. Although further validation of these film clips is needed, ratings provided here should assist researchers in selecting potential film clips to meet the aims of their work.

Children's physiological reactivity in emotion contexts and prosocial behavior.

INTRODUCTION: Building on prior evidence that prosocial behavior is related to the regulation of personal distress in difficult situations, and given that physiological regulation is a central contributor to effective emotion regulation, this investigation evaluated whether and how children's autonomic nervous system (ANS) reactivity during emotion challenges influenced later expressions of prosocial behavior. METHODS: The current study utilized a diverse sample of school-aged children (N = 169; 47.9% female; 47.3% Latinx) to evaluate relations between children's parasympathetic (i.e., respiratory sinus arrhythmia; RSA) and sympathetic (i.e., pre-ejection period; PEP) reactivity in response to each of three film-elicited emotion challenges (i.e., sadness, happiness, and fear) at age 7 and both observed and parent-reported prosocial behavior one year later. RESULTS: Children's parasympathetic reactivity to a film eliciting sadness evidenced a nonlinear relation with later prosocial sharing such that children who evidenced either RSA withdrawal or augmentation in response to the sad emotion challenge engaged in higher levels of prosocial behavior than children who evidenced relatively low or absent reactivity. Parasympathetic reactivity to films eliciting happiness or fear was not significantly related to later prosocial behavior. Likewise, children's sympathetic reactivity in response to the emotion challenges did not significantly predict later prosocial behavior. CONCLUSIONS: These findings provide preliminary support for a nonlinear association between children's parasympathetic emotion reactivity and later prosocial behavior, and suggest that children's ANS regulation in sad emotion contexts may be particularly important for understanding prosocial development.

LATEMO-E: A Film Database to Elicit Discrete Emotions and Evaluate Emotional Dimensions in Latin-Americans / LATEMO-E: Banco de Dados de Filmes para Suscitar Emoções e Avaliar Dimensões Emocionais para Latino-Americanos / LATEMO-E: Set de Fragmentos de Películas para Inducir Emociones y Evaluar Dimensiones Emocionales en Latinoamericanos

Abstract Introduction: Film clips are the most used stimuli to induce different emotional states. Objective: Identify, select, and evaluate a set of film clips according to dimensionality and discreteness of emotions. Film experts suggested 437 fragments, but only 70 met the criteria to be included in the LATEMO-E film-clip database. Study 1: The 70 film clips were tested for their ability to induce disgust, anger, fear, sadness, amusement, tenderness, and neutral (n = 147 participants; mean age = 20.64 years, SD ±2.21 years). Results: A total of 28 film clips presented adequate scores on intensity and discreteness. Study 2: A total of 28 selected film clips were assessed again in a new sample of 106 participants (mean age = 20.96 years, SD ±2.45 years). Results: Anger and amusement film clips were the most extreme in the valence and activation dimensions. Anger and fear film clips were the most extreme categories in the intensity, certainty, and control dimensions. Conclusions: These stimuli were useful for inducing emotional states that can be judged from both the dimensional perspective of emotions and the basic emotions perspective. Evoked emotions could be differentiated according to cognitive patterns of evaluation that guide behavior in response to emotional stimulation.

Resumo Introdução: os clipes são os estímulos mais utilizados para induzir diferentes estados emocionais. Objetivo: identificar, selecionar e avaliar um conjunto de clipes de filme de acordo com a discrição e dimensionalidade da emoção. 437 fragmentos foram sugeridos por especialistas em filmes, mas 70 atenderam aos criterios de inclusão em um banco de dados de filmes. Estudo 1: os 70 clipes foram testados em sua capacidade de induzir: nojo, raiva, medo, tristeza, diversão, ternura e neutro (N = 147 participantes; M = 20,64; DP ±2,21). Resultados: 28 clipes apresentaram escores adequados de intensidade e discrição. Estudo 2: 28 clipes selecionados foram reavaliados em uma nova amostra de 106 participantes (M = 20,96; DP ±2,45). Resultados: os clipes de raiva e diversão foram os mais extremos nas dimensões de valência e ativação. Clips de raiva e medo foram as categorias mais extremas nos indicadores de intensidade, certeza e controle. Conclusões: os estímulos foram úteis para induzir estados emocionais que podem ser julgados tanto pela perspectiva dimensional das emoções quanto pela perspectiva básica das emoções. Além disso, as emoções evocadas são diferenciadas de acordo com os padrões cognitivos de avaliação que guiam o comportamento em resposta à estimulação emocional.

Resumen Introducción: los fragmentos de películas están entre los estímulos más usados para inducir distintos estados emocionales. Objetivo: identificar, seleccionar y evaluar un set de fragmentos de películas según la discreción y la dimensionalidad de la emoción. Expertos en cine sugirieron 437 fragmentos, pero solo 70 fueron identificados como aquellos que cumplieron con los criterios de inclusión en un set de fragmentos de películas. Estudio 1: los 70 fragmentos fueron evaluados en su capacidad para inducir: asco, ira, miedo, tristeza, diversión, ternura y neutro (N = 147 participantes; M = 20.64; DE ±2.21). Resultados: 28 fragmentos presentaron puntuaciones adecuadas en intensidad y discreción. Estudio 2: los 28 fragmentos fueron reevaluados en una nueva muestra de 106 participantes (M = 20.96, DE ±2.45). Resultados: los fragmentos de ira y diversión fueron los más extremos en las dimensiones valencia y activación. Ira y miedo fueron las categorías más extremas en los indicadores intensidad, certeza y control. Conclusiones: los estímulos resultaron útiles para inducir estados emocionales que pueden ser juzgados desde la perspectiva dimensional de las emociones, así como desde el enfoque de las emociones básicas. Además, las emociones provocadas se diferencian en función de patrones cognitivos de evaluación que guían la conducta en respuesta al estímulo emocional.

Evaluating and Validating Emotion Elicitation Using English and Arabic Movie Clips on a Saudi Sample.

With the advancement of technology in both hardware and software, estimating human affective states has become possible. Currently, movie clips are used as they are a widely-accepted method of eliciting emotions in a replicable way. However, cultural differences might influence the effectiveness of some video clips to elicit the target emotions. In this paper, we describe several sensors and techniques to measure, validate and investigate the relationship between cultural acceptance and eliciting universal expressions of affect using movie clips. For emotion elicitation, a standardised list of English language clips, as well as an initial set of Arabic video clips are used for comparison. For validation, bio-signal devices to measure physiological and behavioural responses associated with emotional stimuli are used. Physiological and behavioural responses are measured from 29 subjects of Arabic background while watching the selected clips. For the six emotions' classification, a multiclass SVM (six-class) classifier using the physiological and behavioural measures as input results in a higher recognition rate for elicited emotions from Arabic video clips (avg. 60%) compared to the English video clips (avg. 52%). These results might reflect that using video clips from the subjects' culture is more likely to elicit the target emotions. Besides measuring the physiological and behavioural responses, an online survey was carried out to evaluate the effectiveness of the selected video clips in eliciting the target emotions. The online survey, having on average 220 respondents for each clip, supported the findings.

A standardised database of Chinese emotional film clips.

Film clips are widely used in emotion research due to their relatively high ecological validity. Although researchers have established various film clip sets for different cultures, the few that exist related to Chinese culture do not adequately address positive emotions. The main purposes of the present study were to establish a standardised database of Chinese emotional film clips that could elicit more categories of reported positive emotions compared to the existing databases and to expand the available film clips that can be used as neutral materials. Two experiments were conducted to construct the database. In experiment 1, 111 film clips were selected from more than one thousand Chinese movies for preliminary screening. After 315 participants viewed and evaluated these film clips, 39 excerpts were selected for further validation. In experiment 2, 147 participants watched and rated these 39 film clips, as well as another 8 excerpts chosen from the existing databases, to compare their validity. Eventually, 22 film excerpts that successfully evoked three positive emotions (joy, amusement, and tenderness), four negative emotions (moral disgust, anger, fear, and sadness), and neutrality formed the standardised database of Chinese emotional film clips.