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60 results for “emotion expression”
EEG Data for Emotive Response to Robot Facial Expressions
<p>This dataset consists of EEG recorded during visual human-robot interaction from 10 healthy participants to investigate the emotive response in EEG to different robot facial expressions. Participants observed four different facial expressions (angry, happy, sad and surprised along with neutral expression) displayed by the social robot Miko on its digital screen. EEG was recorded from 16 unipolar channels in frontal, central, temporal, parietal, and occipital locations . During each trial, an emotion stimulus was displayed for approximately 4s followed by 4s break during which the Miko robot displayed neutral expression and blinked regularly. Emotions were displayed in random order. Total of 240 EEG trials were recorded from each participant with 60 trials per emotion. The dataset provides raw minimally filtered EEG along with cleaned EEG with artefacts removal using ICA with sampling frequency of 128 Hz, and corresponding stimulus onset markers. Please refer to README file for further details and example code.</p> <p><em>Please cite the original publication:</em></p> <p>M. Wairagkar et al., "Emotive Response to a Hybrid-Face Robot and Translation to Consumer Social Robots," <em>IEEE Internet of Things Journal</em>, DOI: <a href="https://doi.org/10.1109/JIOT.2021.3097592">10.1109/JIOT.2021.3097592</a>.</p> <p><em>Preprint: </em></p> <p>M. Wairagkar et al., "Emotive Response to a Hybrid-Face Robot and Translation to Consumer Social Robots," <a href="https://arxiv.org/abs/2012.04511">arXiv:2012.04511</a></p>
Identification of emotional facial expressions in a lab and over the internet
<p>This dataset includes the data used for the analyses presented in the paper published (under the same title as this dataset) in the journal Psychology, Journal of the Higher School of Economics. </p> <p>Abstract of the publication:</p> <p>Collecting data over the internet is an approach that allows researchers to vastly expand the possible sample sizes of their studies, and enables the study of populations that may otherwise be difficult to access. However, to ensure that data collected over the internet is of the same level of quality as data collected in a lab, the comparability of internet-collected data with lab-collected data must first be assessed for individual areas of research and experimental approaches. To answer the question of whether internet data collection is suitable for experiments involving facial expressions, we conducted a deliberately difficult facial emotion-identification experiment where participants completed the same task either under supervision in our lab, or at an unsupervised location over the internet. Stimuli consisted of sad faces that participants were asked to identify as resembling either anger, fear, or disgust. Regardless of belonging to either the group tested in the lab or over the internet, participants showed highly similar response distributions, while differences between the groups were non-significant and of very low magnitude. We can therefore conclude from our findings that internet data collection is a viable method for experiments requiring the identification of emotional facial expressions, being able to produce similar results to those which can be obtained in a lab.</p>
Data and supplementary material in support of article "Can robots express facial emotions dominantly enough for use in dementia care?"
<p>Data and supplementary material in support of article "Vlachos, E. and Tan, Z. H. (2020). Can robots express facial emotions dominantly enough for use in dementia care?, <em>International Psychogeriatrics</em>, Cambridge University Press". </p> <p>Our objective is to evaluate the recognition, and denomination of the six basic emotional facial expressions as displayed by a social robot to persons with dementia, and to compare it with the results from the evaluation of static photographs of humans from the Paul Ekman database in order to investigate the differences in recognition rates among the two stimuli.</p>
IFEED: Interactive Facial Expression and Emotion Detection Dataset
<p>Interactive Facial Expression and Emotion Detection (IFEED) is an annotated dataset that can be used to train, validate, and test Deep Learning models for facial expression and emotion recognition. It contains pre-filtered and analysed images of the interactions between the six main characters of the Friends television series, obtained from the video recordings of the Multimodal EmotionLines Dataset (MELD).</p> <p>The images were obtained by decomposing the videos into multiple frames and extracting the facial expression of the correctly identified characters. A team composed of 14 researchers manually verified and annotated the processed data into several classes: Angry, Sad, Happy, Fearful, Disgusted, Surprised and Neutral.</p> <p>IFEED can be valuable for the development of intelligent facial expression recognition solutions and emotion detection software, enabling binary or multi-class classification, or even anomaly detection or clustering tasks. The images with ambiguous or very subtle facial expressions can be repurposed for adversarial learning. The dataset can be combined with additional data recordings to create more complete and extensive datasets and improve the generalization of robust deep learning models.</p>
Multi-view emotional expressions dataset
<p>Multi-view emotional expressions dataset (MEED) using 2D pose estimation.</p>
Dataset for "Using Adaptive Immersive Environments to Stimulate Emotional Expression and Connection in Dementia Care: Insights from User Perspectives towards SENSE-GARDEN"
<p>This dataset contains all qualitative interview data recorded from early stage research on an adaptive, immersive, multi-sensory intervention that is being developed for people living with dementia (SENSE-GARDEN). 52 semi-structured interviews were conducted with people living with mild cognitive impairment, informal caregivers, and professional caregivers across Belgium, Norway, Portugal, and Romania. The aim of these interviews was to collect initial user responses towards SENSE-GARDEN. </p> <p>The pdf file "Registration Sheet and Interview Questions" lists the questions that were asked during the interviews. The excel file "Interview Data with Thematic Analysis" contains all raw interview data with ideas, notes, and codes made during thematic analysis. The first three sheets in the file correspond to the user type (Person with mild cognitive impairment/Informal Caregiver/Professional Caregiver). The fourth sheet, "Overall themes", gives an overview of each theme, subtheme, and relevant quotes belonging to these themes. </p> <p>This research was conducted as part of a larger project. The SENSE-GARDEN project (AAL/Call2016/054-b/2017, implementation period June 2017 - May 2020) is funded by AAL Programme, co-funded by the European Commission and National Funding Authorities of Norway, Belgium, Romania, and Portugal. </p>
Negative mood affects the expression of negative but not positive emotions in mice
<p><span><span><span><span><span><span><span><span><span><span><span>Whether, and to what extent animals experience emotions is crucial for understanding their decisions and behaviour, and underpins a range of scientific fields, including animal behaviour, neuroscience, evolutionary biology and animal welfare science. However, research has predominantly focussed on alleviating negative emotions in animals, with the expression of positive emotions left largely unexplored. Therefore, little is known about positive emotions in animals and how their expression is mediated. We used tail handling to induce negative mood in laboratory mice and found that whilst being more anxious and depressed increased their expression of a discrete negative emotion ('disappointment') meaning that they were less resilient to negative events, their capacity to express a discrete positive emotion ('elation') was unaffected relative to control mice. Therefore, we show not only that mice have discrete positive emotions, but that they do so regardless of their current mood state. Our findings are the first to suggest that the expression of discrete positive and negative emotions in animals are not equally affected by long-term mood state. Our results also demonstrate that repeated negative events can have a cumulative effect to reduce resilience in laboratory animals, which has significant implications for animal welfare.</span></span></span></span></span></span></span></span></span></span></span></p>
The Significance of Emotional Facial Expression in Understanding Tears: Threat, Sincerity, and Cluster A Personality
Open the record for dataset details and reuse information.
Emotions expressed by the police, their state supporters, and experienced by officers
<p>Rak Joanna, Emotions expressed by the police, their state supporters, and experienced by officers.</p> <p>This dataset was elaborated for the research project <em>Civil Disorder in Pandemic-ridden European Union</em>. The latter was financially supported by the National Science Centre, Poland [grant number 2021/43/B/HS5/00290].</p>
Emotions expressed by the police, their state supporters, and experienced by officers
<p>Rak Joanna, <span>Emotions expressed by the police, their state supporters, and experienced by officers.</span></p> <p>This dataset dwas elaborated for the research project <em>Civil Disorder in Pandemic-ridden European Union</em>. The latter was financially supported by the National Science Centre, Poland [grant number 2021/43/B/HS5/00290].</p>
Spontaneous mimicry of live facial expressions: A biological mechanism for emotional contagion
<p>Observation of live facial expressions typically elicits similar expressions (facial mimicry) accompanied by shared emotional experiences (emotional contagion). The model of embodied emotion proposes that emotional contagion and facial mimicry are functionally linked although the neural underpinnings are unknown. To address this knowledge gap we employed two-person (n = 20 dyads) functional near-infrared spectroscopy during live emotive face-processing while also measuring eye-tracking, facial classifications, and ratings of emotion. One partner, "Movie Watcher", was instructed to emote natural facial expressions while viewing evocative short movie clips. The other partner, "Face Watcher", viewed the Movie Watcher's face. Dyadic roles were alternated between partners. Task and rest blocks were implemented by timed epochs of clear and opaque glass that separated partners. Correlations of dyadic facial expressions (r = 0.41) and dyadic affect ratings (r = 0.66) were consistent with findings of both emotional contagion and facial mimicry. Neural correlates of emotional contagion based on covariates of partner ratings included right angular and supramarginal gyri. Neural correlates of mimicry associated with partner facial action units include core face recognition system. Thus, the proposed linkages between facial mimicry and emotional contagion represent separate components of face processing.</p>
Internet-based Emotional Awareness and Expression Therapy for Somatic Symptom Disorder
ClinicalTrials.gov study NCT04122846. IPD Sharing: NO. Countries: 1. Publications: 1.
Safety Study of AVP-923 in the Treatment of IEED (Involuntary Emotional Expression Disorder) Also Known as Pseudobulbar Affect (Episodes of Uncontrolled Crying and/or Laughter)
ClinicalTrials.gov study NCT00056524. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Trial of Emotion Regulation for Inappropriate Anger Expression
ClinicalTrials.gov study NCT03858296. IPD Sharing: NO. Countries: 1. Publications: 1.
Supportive-Expressive and Emotion-Focused Treatment for Depression
ClinicalTrials.gov study NCT04576182. IPD Sharing: NO. Countries: 1. Publications: 1.
Emotional Awareness and Expression Therapy (EAET) as a Novel Migraine Treatment
ClinicalTrials.gov study NCT05837650. IPD Sharing: NO. Countries: 1. Publications: 2.
Biobehavioral Effects of Emotional Expression in Cancer
ClinicalTrials.gov study NCT00505310. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Gene Expression Correlates of Post-Traumatic Stress Disorder (PTSD) Symptom Change After EFT (Emotional Freedom Techniques)
ClinicalTrials.gov study NCT01250431. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Emotional Awareness and Expression Therapy (EAET) for Migraine
ClinicalTrials.gov study NCT05755698. IPD Sharing: NO. Countries: 1. Publications: 2.
Internet-based Emotional Awareness and Expression Therapy for Somatic Symptom Disorder - A Randomized Controlled Trial
ClinicalTrials.gov study NCT04751825. IPD Sharing: Not stated. Countries: 1. Publications: 14.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.