Article
Chemistry, Analytical
Laura Gutierrez-Martin, Elena Romero-Perales, Clara Sainz de Baranda Andujar, Manuel F. Canabal-Benito, Gema Esther Rodriguez-Ramos, Rafael Toro-Flores, Susana Lopez-Ongil, Celia Lopez-Ongil
Summary: Affective computing through physiological signals monitoring is a hot topic in both scientific literature and industry. Wearable devices for health and wellness tracking are being developed, as well as applications for early detection and emotion classification. However, there are still unexplored biological elements that could provide additional information.
Article
Computer Science, Artificial Intelligence
Garima Sharma, Abhinav Dhall, Jianfei Cai
Summary: This paper focuses on group-level affect analysis on videos and proposes an audio-visual perceived group affect dataset. The dataset consists of 4,183 group videos collected from YouTube and is manually annotated for three group affect classes. Experimental results show the effectiveness of facial, holistic, and speech features for group-level affect analysis.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Review
Computer Science, Artificial Intelligence
K. Ezzameli, H. Mahersia
Summary: The omnipresence of numerous information sources in our daily life provides new options for emotion recognition in various domains. Multimodal machine learning, due to the diversity of data, poses challenges for computer scientists. The progress of emotion recognition in each modality, common strategies, the role of deep learning, the concept of multimodality, methods of information fusion, and commonly used datasets can help us understand and compare different approaches.
INFORMATION FUSION
(2023)
Review
Computer Science, Artificial Intelligence
Sicheng Zhao, Xingxu Yao, Jufeng Yang, Guoli Jia, Guiguang Ding, Tat-Seng Chua, Bjorn W. Schuller, Kurt Keutzer
Summary: This survey comprehensively reviews the development of affective image content analysis (AICA) in the past two decades, focusing on the state-of-the-art methods and addressing three main challenges. It provides an overview of emotion representation models, available datasets, and compares representative approaches in emotion feature extraction, learning methods, and AICA-based applications. The survey also discusses future research directions and challenges in the field.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Multidisciplinary Sciences
Martin Gjoreski, Ivana Kiprijanovska, Simon Stankoski, Ifigeneia Mavridou, M. John Broulidakis, Hristijan Gjoreski, Charles Nduka
Summary: This study used a novel wearable surface electromyography to investigate the affective states induced by different videos. The results showed that subjective valence, subjective arousal, and objective valence measured through sEMG varied significantly depending on the video content.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Analytical
Chiara Filippini, Adolfo Di Crosta, Rocco Palumbo, David Perpetuini, Daniela Cardone, Irene Ceccato, Alberto Di Domenico, Arcangelo Merla
Summary: This study presents an automated emotion recognition model based on easily accessible physiological signals and deep learning approaches. The model achieved a classification accuracy of 70% in identifying four emotional states, outperforming traditional machine learning algorithms. The proposed model has potential applications in affective computing field.
Article
Engineering, Electrical & Electronic
Dongrui Wu, Bao-Liang Lu, Bin Hu, Zhigang Zeng
Summary: A brain-computer interface (BCI) allows direct communication between a user and a computer through the central nervous system. An affective BCI (aBCI) monitors and regulates the emotional state of the brain, which has various applications in human cognition, communication, decision-making, and health. This tutorial provides a comprehensive and up-to-date guide on aBCIs, covering basic concepts, components of a closed-loop aBCI system, representative applications, and challenges and opportunities in aBCI research and applications.
PROCEEDINGS OF THE IEEE
(2023)
Article
Computer Science, Artificial Intelligence
Panagiotis Tzirakis, Jiaxin Chen, Stefanos Zafeiriou, Bjorn Schuller
Summary: This paper proposes an emotion recognition system that utilizes raw text, audio, and visual information, achieving state-of-the-art results in text, visual, and multimodal domains through the use of Deep Neural Networks and other techniques.
INFORMATION FUSION
(2021)
Article
Computer Science, Artificial Intelligence
Akshi Kumar, Kapil Sharma, Aditi Sharma
Summary: The intersection of people, data and intelligent machines has a significant impact on the productivity, efficiency and operations of a smart industry. Internet-of-things offers great potential for workplace gains through quantified self and computer vision strategies. Recognizing and regulating human emotion is crucial for people analytics as it plays an important role in workplace productivity.
IMAGE AND VISION COMPUTING
(2022)
Review
Computer Science, Artificial Intelligence
Haiwei Ma, Svetlana Yarosh
Summary: Affective computing has made significant technical advancements in bridging the gap between human affect and computational technology. However, the theoretical underpinnings of affective computing are often overlooked. This paper provides a comprehensive conceptual analysis of the literature, proposing the function-component-representation framework to understand essential theoretical questions in affective computing. The findings reveal preferences for affect detection, behavioral component, and categorical representation, as well as observed coupling between certain conceptions. The FCR framework not only organizes theoretical perspectives systematically and quantitatively but also serves as a blueprint for conceptualizing affective computing projects and identifying new possibilities.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Michael Braun, Florian Weber, Florian Alt
Summary: Affective technology has the potential to improve road safety by regulating driver emotions, but faces various technological and methodological challenges in practice. The review aims to provide comprehensive knowledge for interested researchers, offer focused guidance for practitioners, and identify opportunities for enhancing emotional interaction in the car for road safety.
ACM COMPUTING SURVEYS
(2021)
Review
Computer Science, Artificial Intelligence
Renan Vinicius Aranha, Cleber Gimenez Correa, Fatima L. S. Nunes
Summary: The study focuses on the impact of Affective Computing in promoting user engagement in computer applications, with a systematic literature review of available articles discussing emotion recognition techniques and challenges to be overcome in the field.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Yazhou Zhang, Jinglin Wang, Yaochen Liu, Lu Rong, Qian Zheng, Dawei Song, Prayag Tiwari, Jing Qin
Summary: Sarcasm, sentiment, and emotion are closely related in the research of artificial intelligence and affective computing. This paper proposes a multimodal multitask learning model (M2Seq2Seq) to address the challenges of context dependency, multimodal fusion, and multitask interaction. The model incorporates encoder-decoder architecture and attention mechanisms to capture contextual dependency and multimodal interactions. Experimental results demonstrate the effectiveness of M2Seq2Seq over state-of-the-art baselines.
INFORMATION FUSION
(2023)
Review
Chemistry, Multidisciplinary
Panagiotis Koromilas, Theodoros Giannakopoulos
Summary: This work provides a review of state of the art in multimodal speech emotion recognition methodologies, presenting a new descriptive categorization and summarizing basic feature representation methods for each modality. The aggregated evaluation results are also presented. Furthermore, the future challenges related to validation procedures, representation learning, and method robustness are analyzed in depth.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Cybernetics
Jingjing Liu, Zhiyong Wang, Wei Nie, Jia Zeng, Bingrui Zhou, Jingxin Deng, Huiping Li, Qiong Xu, Xiu Xu, Honghai Liu
Summary: Autism Spectrum Disorders (ASD) are a healthcare challenge due to their increasing prevalence rates and burden on families and society. This paper addresses the problem of automatic recognition of emotional states in ASD children. The proposed method combines facial expressions and body poses to achieve better recognition results compared to methods using only facial information.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Article
Allergy
Sharon Ruth Davis, Dorian Peters, Rafael Alejandro Calvo, Susan M. Sawyer, Juliet M. Foster, Lorraine D. Smith
Summary: The pilot study showed that young people with asthma were highly satisfied with the content and usability of the "Kiss myAsthma" app, making it easier for them to discuss asthma with their doctors and feel confident in managing their condition. After six weeks, there was a significant improvement in asthma quality of life, with participants actively tracking symptoms and utilizing tools for intrinsic motivation.
Article
Computer Science, Software Engineering
Yifan Wang, Kiran Ijaz, Dong Yuan, Rafael A. Calvo
SOFTWARE-PRACTICE & EXPERIENCE
(2020)
Article
Public, Environmental & Occupational Health
Melissa Aji, Nick Glozier, Delwyn Bartlett, Dorian Peters, Rafael A. Calvo, Yizhong Zheng, Ronald Grunstein, Christopher Gordon
Summary: The study showed that using a mobile app to deliver SRT to individuals with insomnia is feasible, highly engaging, well accepted, and potentially efficacious. Results indicated significant improvements in sleep measures and daytime symptoms in the short term.
TRANSLATIONAL BEHAVIORAL MEDICINE
(2021)
Article
Psychiatry
Isabella Choi, Nicholas Ho, Richard Morris, Samuel B. Harvey, Rafael A. Calvo, Nicholas Glozier
Summary: This study evaluated the impact of communicating personal mental health risk profiles on psychological distress, and found that providing such risk profiles did not lead to unacceptable worsening of distress.
EARLY INTERVENTION IN PSYCHIATRY
(2021)
Review
Health Care Sciences & Services
Melissa Aji, Christopher Gordon, Elizabeth Stratton, Rafael A. Calvo, Delwyn Bartlett, Ronald Grunstein, Nick Glozier
Summary: This systematic review examined evidence for the design engineering and clinical implementation and evaluation of mHealth apps for sleep disturbance. Most apps delivered cognitive behavioral therapy for insomnia and half of them adopted user-centered design or multidisciplinary teams in their design approach.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Environmental Sciences
Rebecca M. Jedwab, Alison M. Hutchinson, Elizabeth Manias, Rafael A. Calvo, Naomi Dobroff, Nicholas Glozier, Bernice Redley
Summary: Nurses have concerns about the implementation of EMR, such as well-being and burnout, but also show high job satisfaction and intention to stay. Focus group interviews revealed nurses' expectations and concerns about EMR, including potential impact on nurse-patient relationships.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Editorial Material
Medicine, General & Internal
Stephen Cave, Jess Whittlestone, Rune Nyrup, Sean O. HEigeartaigh, Rafael A. Calvo
BMJ-BRITISH MEDICAL JOURNAL
(2021)
Review
Health Care Sciences & Services
Elizabeth Stratton, Amit Lampit, Isabella Choi, Hanna Malmberg Gavelin, Melissa Aji, Jennifer Taylor, Rafael A. Calvo, Samuel B. Harvey, Nick Glozier
Summary: This article presents a review and meta-analysis of eHealth interventions for anxiety, depression, and stress in the workplace. The findings suggest that eHealth interventions have a small positive impact on reducing mental health symptoms in employees. However, there is no evidence of improvement in the effectiveness of these interventions over the past decade.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
Health Care Sciences & Services
Alina-Irina Serban, Eyal Soreq, Payam Barnaghi, Sarah Daniels, Rafael A. Calvo, David J. Sharp
Summary: The COVID-19 pandemic has affected the home behaviors of people living with dementia, with social isolation being a significant factor. A study conducted in the UK monitored the home activities of 31 individuals with dementia using remote home monitoring technology, revealing a decreased amount of time spent outside during lockdowns.
NPJ DIGITAL MEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
Muhammad Johan Alibasa, Rizka W. Purwanto, Kalina Yacef, Nick Glozier, Rafael A. Calvo
Summary: Digital technology has complex effects on behaviors, moods, and wellbeing. This study investigates the relationship between lifestyle aspects and digital technology usage patterns using the mobile app MindGauge and productivity tool RescueTime. The findings suggest that frequent task-switching is associated with negative moods, while lifestyle factors such as sleep quality and physical activity are significantly related to positive moods. A mood detection model combining digital footprints and lifestyle contexts achieved an accuracy of 87%. The research provides evidence for understanding the impact of technology on wellbeing.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Federico Julien Tiersen, Rafael Alejandro Calvo
Summary: Consuming social and micro-targeted digital content excessively can lead to unhealthy smartphone use, while products exploiting user vulnerabilities are causing detrimental impacts. The Holdable device, utilizing biofeedback, helps users stay mindful through tactile feedback and visualization, showing potential positive impacts on cognitive and behavioral metrics in addressing problematic smartphone use.
HUMAN-COMPUTER INTERACTION: INTERACTION TECHNIQUES AND NOVEL APPLICATIONS, HCII 2021, PT II
(2021)
Article
Psychology, Multidisciplinary
Maria Mikheeva, Sascha Schneider, Maik Beege, Guenter Daniel Rey
Summary: This study investigated the impact of decorative pictures on online statistical learning, finding that positive pictures can reduce cognitive load or enhance learning performance, depending on their positions in the learning materials.
HUMAN BEHAVIOR AND EMERGING TECHNOLOGIES
(2021)
Article
Geriatrics & Gerontology
Federico Tiersen, Philippa Batey, Matthew J. C. Harrison, Lenny Naar, Alina-Irina Serban, Sarah J. C. Daniels, Rafael A. Calvo
Summary: This study explores the needs of people living with dementia, their caregivers, clinicians, and health and social care service providers towards smart home systems. Participatory design methods helped triangulate stakeholder perspectives for more patient-centered interventions, leading to the development of remote monitoring systems in public health pathways.
Article
Psychology, Multidisciplinary
Emma L. Bradshaw, Richard M. Ryan, Michael Noetel, Alexander K. Saeri, Peter Slattery, Emily Grundy, Rafael Calvo
Summary: Data safety assurance is a key factor influencing people's intentions to use contact tracing technology, while perceptions of government legitimacy and political affiliation also relate to intended application uptake.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Psychology, Experimental
Maik Beege, Steve Nebel, Sascha Schneider, Gunter Daniel Rey
Summary: Text-based learning media are widely used in education, with designers able to support learners through visual cues. This study found that signaling in text design can enhance transfer performance, regardless of text font, while induced extraneous cognitive load can impact metacognitive accuracy and effort invested. Interaction effects were observed in testing time, ease of learning, and navigation.
COGNITIVE PROCESSING
(2021)