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Affective computing

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Full-Text Articles in Physical Sciences and Mathematics

Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray Aug 2022

Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray

Electrical & Computer Engineering Theses & Dissertations

Affective computing is an exciting and transformative field that is gaining in popularity among psychologists, statisticians, and computer scientists. The ability of a machine to infer human emotion and mood, i.e. affective states, has the potential to greatly improve human-machine interaction in our increasingly digital world. In this work, an ensemble model methodology for detecting human emotions across multiple subjects is outlined. The Continuously Annotated Signals of Emotion (CASE) dataset, which is a dataset of physiological signals labeled with discrete emotions from video stimuli as well as subject-reported continuous emotions, arousal and valence, from the circumplex model, is used for …

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Multi-Modality Affective Computing Model Based On Personality And Memory Mechanism, Sijin Zhou, Dicheng Chen, Geng Tu, Dazhi Jiang Apr 2022

Multi-Modality Affective Computing Model Based On Personality And Memory Mechanism, Sijin Zhou, Dicheng Chen, Geng Tu, Dazhi Jiang

Journal of System Simulation

Abstract: With the development of affective computing, the correlation of memory, individuation and emotion is more and more important. Focus on the machine emotion shortcomings in the perception, understanding and expression, an emotion computing model integrating the emotion perception, understanding and expression is proposed. The model is a memory-oriented deep network perception model that accepts multiple modal inputs (visual, auditory, lexical) and applies a fuzzy emotion integration decision to realize the understanding of uncertain emotions. The simulation experiments prove that the model has a good performance in all kinds of multimodal affective computing.

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Volitional Control Of Lower-Limb Prosthesis With Vision-Assisted Environmental Awareness, S M Shafiul Hasan Mar 2022

Volitional Control Of Lower-Limb Prosthesis With Vision-Assisted Environmental Awareness, S M Shafiul Hasan

FIU Electronic Theses and Dissertations

Early and reliable prediction of user’s intention to change locomotion mode or speed is critical for a smooth and natural lower limb prosthesis. Meanwhile, incorporation of explicit environmental feedback can facilitate context aware intelligent prosthesis which allows seamless operation in a variety of gait demands. This dissertation introduces environmental awareness through computer vision and enables early and accurate prediction of intention to start, stop or change speeds while walking. Electromyography (EMG), Electroencephalography (EEG), Inertial Measurement Unit (IMU), and Ground Reaction Force (GRF) sensors were used to predict intention to start, stop or increase walking speed. Furthermore, it was investigated whether …

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Stressed Or Just Running? Differentiation Of Mental Stress And Physical Activityby Using Machine Learning, Yekta Sai̇d Can Jan 2022

Stressed Or Just Running? Differentiation Of Mental Stress And Physical Activityby Using Machine Learning, Yekta Sai̇d Can

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, modern people have excessive stress in their daily lives. With the advances in physiological sensors and wearable technology, people?s physiological status can be tracked, and stress levels can be recognized for providing beneficial services. Smartwatches and smartbands constitute the majority of wearable devices. Although they have an excellent potential for physiological stress recognition, some crucial issues need to be addressed, such as the resemblance of physiological reaction to stress and physical activity, artifacts caused by movements and low data quality. This paper focused on examining and differentiating physiological responses to both stressors and physical activity. Physiological data are collected …

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Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh Jan 2022

Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Artificial intelligence (AI) enables continuous monitoring of patients’ health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals’ decisions for themselves, we focus on family members’ rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members’ decision making on behalf of their parents. We find …

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Paralleled Dynamic Crowd Emotion Contagion Algorithm, Xiang Nan, Mingmin Zhang, Lingyun Zhu Aug 2020

Paralleled Dynamic Crowd Emotion Contagion Algorithm, Xiang Nan, Mingmin Zhang, Lingyun Zhu

Journal of System Simulation

Abstract: As the positions of crowd usually change dynamically, then computing the contagion process becomes a challenge. There current algorithms were too time consuming to be adopted as they needed to calculate the reactions between every two objects. In order to solve this problem, a social force based contagion computing algorithm with GPU acceleration was provided. Individuals’ affection fields were projected onto two dimensional mesh grid and represented by the nine-box diary; The social force reactions between individual and nearest neighbors were computed to get the moving position; The contagion results from nearest neighbors were calculated. All of these steps …

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Pedestrian Dynamic Aggregation Simulation Model With Emotional Affection, Xiang Nan, Lingyun Zhu, Mingmin Zhang Aug 2020

Pedestrian Dynamic Aggregation Simulation Model With Emotional Affection, Xiang Nan, Lingyun Zhu, Mingmin Zhang

Journal of System Simulation

Abstract: In order to improve the fidelity of dynamic aggregation process of virtual pedestrian, the relationship between gathering process and emotion contagion were simulated by integrating individual emotional interaction into crowd model. Individuals within the crowd firstly chose moving target and produced aggregation according to their expectation. The gathering process propagated the influences of target through the emotional interaction of individuals. The propagated influences affected individuals' expectation which made further efforts on crowd aggregation. Social force for simulating moving individuals and heat conduction theory were adopted by the model to simulate the emotional contagion of the crowd. Experimental results show …

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Toward Culturally Relevant Emotion Detection Using Physiological Signals, Khadija Zanna Mar 2020

Toward Culturally Relevant Emotion Detection Using Physiological Signals, Khadija Zanna

USF Tampa Graduate Theses and Dissertations

Research shows that emotional distress has a statistically significant impact on a student’s grade point average and intent to drop out of college. Because students of different races have varying college experiences, it is important to understand the emotional experiences of different racial groups to better support students’ needs and academic success. In this work, we explore several physiological responses to ten different emotional stimuli captured from 140 students. We employ unsupervised learning via the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and supervised learning via Random Forests and Support Vector machines to analyze clustering partitions and classification …

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A Review Of Emotion Sensing: Categorization Models And Algorithms, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria Jan 2020

A Review Of Emotion Sensing: Categorization Models And Algorithms, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria

Research Collection School Of Computing and Information Systems

Sentiment analysis consists in the identification of the sentiment polarity associated with a target object, such as a book, a movie or a phone. Sentiments reflect feelings and attitudes, while emotions provide a finer characterization of the sentiments involved. With the huge number of comments generated daily on the Internet, besides sentiment analysis, emotion identification has drawn keen interest from different researchers, businessmen and politicians for polling public opinions and attitudes. This paper reviews and discusses existing emotion categorization models for emotion analysis and proposes methods that enhance existing emotion research. We carried out emotion analysis by inviting experts from …

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Detecting Personal Intake Of Medicine From Twitter, Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah, Jing Jiang Jul 2018

Detecting Personal Intake Of Medicine From Twitter, Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah, Jing Jiang

Research Collection School Of Computing and Information Systems

Mining social media messages such as tweets, blogs, and Facebook posts for health and drug related information has received significant interest in pharmacovigilance research. Social media sites (e.g., Twitter), have been used for monitoring drug abuse, adverse reactions to drug usage, and analyzing expression of sentiments related to drugs. Most of these studies are based on aggregated results from a large population rather than specific sets of individuals. In order to conduct studies at an individual level or specific groups of people, identifying posts mentioning intake of medicine by the user is necessary. Toward this objective we develop a classifier …

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Feature Space Augmentation: Improving Prediction Accuracy Of Classical Problems In Cognitive Science And Computer Vison, Piyush Saxena Oct 2017

Feature Space Augmentation: Improving Prediction Accuracy Of Classical Problems In Cognitive Science And Computer Vison, Piyush Saxena

Dissertations (1934 -)

The prediction accuracy in many classical problems across multiple domains has seen a rise since computational tools such as multi-layer neural nets and complex machine learning algorithms have become widely accessible to the research community. In this research, we take a step back and examine the feature space in two problems from very different domains. We show that novel augmentation to the feature space yields higher performance. Emotion Recognition in Adults from a Control Group: The objective is to quantify the emotional state of an individual at any time using data collected by wearable sensors. We define emotional state as …

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Evaluating A Personal Stress Monitoring System, Sneha Gogineni May 2017

Evaluating A Personal Stress Monitoring System, Sneha Gogineni

Theses and Dissertations

Now-a-days, Life is generally much more stressful than in the past. "Stress" is the word that we use when we feel that we are overloaded mentally in our thoughts and wonder whether we can really cope with those placed upon us. Sometimes, stress gets us going and they are good for us but at other times, it could be the cause to undermine both our mental and physical health. The way we respond to a challenge can be considered as a kind of stress. Part of our response to a challenge is physiological and affects our own physical state. When …

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Computational Modeling Of Facial Response For Detecting Differential Traits In Autism Spectrum Disorders, Manar D. Samad Jul 2016

Computational Modeling Of Facial Response For Detecting Differential Traits In Autism Spectrum Disorders, Manar D. Samad

Electrical & Computer Engineering Theses & Dissertations

This dissertation proposes novel computational modeling and computer vision methods for the analysis and discovery of differential traits in subjects with Autism Spectrum Disorders (ASD) using video and three-dimensional (3D) images of face and facial expressions. ASD is a neurodevelopmental disorder that impairs an individual’s nonverbal communication skills. This work studies ASD from the pathophysiology of facial expressions which may manifest atypical responses in the face. State-of-the-art psychophysical studies mostly employ na¨ıve human raters to visually score atypical facial responses of individuals with ASD, which may be subjective, tedious, and error prone. A few quantitative studies use intrusive sensors on …

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A Facial Component-Based System For Emotion Classification, Elena Sönmez, Songül Albayrak Jan 2016

A Facial Component-Based System For Emotion Classification, Elena Sönmez, Songül Albayrak

Turkish Journal of Electrical Engineering and Computer Sciences

Smart environments with ubiquitous computers are the next generation of information technology, which requires improved human--computer interfaces. That is, the computer of the future must be aware of the people in its environment; it must know their identities and must understand their moods. Despite the great effort made in the past decades, the development of a system capable of automatic facial emotion recognition is still rather difficult. In this paper, we challenge the benchmark algorithm on emotion classification of the Extended Cohn-Kanade (CK$+)$ database, and we present a facial component-based system for emotion classification, which beats the given benchmark performance: …

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Wearable Computing: Interface, Emotions And The Wearer's Culture, Robert Mccloud, Martha B. Lerski Jan 2015

Wearable Computing: Interface, Emotions And The Wearer's Culture, Robert Mccloud, Martha B. Lerski

School of Computer Science & Engineering Faculty Publications

Wearable computing offers an interesting subset for the mobile computing field. While Google Glass might not yet have found the mass audience it sought, other, simpler, wearable devices have made an impact. This paper presents results of a four-week long experiment in how subjects interact and emotionally respond to the Fitbit Flex. Users tracked daily totals of steps, distance traveled, minutes active, calories burned, and time slept. They also found their own personal uses for the Fitbit interface. Users were asked to be aware of and report their emotional reactions by keeping continuous, daily journals. A popular and relatively inexpensive …

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Multisensory Emotion Recognition With Speech And Facial Expression, Jacob P. Roeland Aug 2014

Multisensory Emotion Recognition With Speech And Facial Expression, Jacob P. Roeland

Honors Theses

Computers through both desktop and mobile devices are only becoming more important in our lives leading us to have more involved and longer interactions with them. Because of this our brains actually classify our involvement with them in a manner similar to our interactions with our fellow humans. This can lead to frustration and anxiety when our computers interrupt our work or pleasure with contextually inappropriate messages, much the same way it would if a friend or co-worker was pushy or rude. A way to solve this issue is to give our machines emotional intelligence, or the ability to recognize …

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Designing An Educational And Intelligent Human-Computer Interface For Older Adults, Drew W. Williams Apr 2014

Designing An Educational And Intelligent Human-Computer Interface For Older Adults, Drew W. Williams

Master's Theses (2009 -)

As computing devices continue to become more heavily integrated into our lives, proper design of human-computer interfaces becomes a more important topic of discussion. Efficient and useful human-computer interfaces need to take into account the abilities of the humans who will be using such interfaces, and adapt to difficulties that different users may face – such as the particular difficulties older users must face. However, various issues in the design of human-computer interfaces for older users yet exist: a wide variance of ability is displayed by older adults, which can be difficult to design for. Motions and notions found intuitive …

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Script-Based Story Matching For Cyberbullying Prevention, Jamie Macbeth, Hanna Adeyema, Henry Lieberman, Christopher Fry Apr 2013

Script-Based Story Matching For Cyberbullying Prevention, Jamie Macbeth, Hanna Adeyema, Henry Lieberman, Christopher Fry

Computer Science: Faculty Publications

While the Internet and social media help keep today’s youth better connected to their friends, family, and community, the same media are also the form of expression for an array of harmful social behaviors, such as cyberbullying and cyber-harassment. In this paper we present work in progress to develop intelligent interfaces to social media that use commonsense knowledge bases and automated narrative analyses of text communications between users to trigger selective interventions and prevent negative outcomes. While other approaches seek merely to classify the overall topic of the text, we try to match stories to finer-grained “scripts” that represent stereotypical …

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Heaven And Hell: Visions For Pervasive Adaptation, Ben Paechter, Jeremy Pitt, Nikola Serbedzijac, Katina Michael, Jennifer Willies, Ingi Helgason Jun 2011

Heaven And Hell: Visions For Pervasive Adaptation, Ben Paechter, Jeremy Pitt, Nikola Serbedzijac, Katina Michael, Jennifer Willies, Ingi Helgason

Professor Katina Michael

With everyday objects becoming increasingly smart and the “info-sphere” being enriched with nanosensors and networked to computationally-enabled devices and services, the way we interact with our environment has changed significantly, and will continue to change rapidly in the next few years. Being user-centric, novel systems will tune their behaviour to individuals, taking into account users’ personal characteristics and preferences. But having a pervasive adaptive environment that understands and supports us “behaving naturally” with all its tempting charm and usability, may also bring latent risks, as we seamlessly give up our privacy (and also personal control) to a pervasive world of …

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Adaptive Intelligent User Interfaces With Emotion Recognition, Fatma Nasoz Jan 2004

Adaptive Intelligent User Interfaces With Emotion Recognition, Fatma Nasoz

Electronic Theses and Dissertations

The focus of this dissertation is on creating Adaptive Intelligent User Interfaces to facilitate enhanced natural communication during the Human-Computer Interaction by recognizing users' affective states (i.e., emotions experienced by the users) and responding to those emotions by adapting to the current situation via an affective user model created for each user. Controlled experiments were designed and conducted in a laboratory environment and in a Virtual Reality environment to collect physiological data signals from participants experiencing specific emotions. Algorithms (k-Nearest Neighbor [KNN], Discriminant Function Analysis [DFA], Marquardt-Backpropagation [MBP], and Resilient Backpropagation [RBP]) were implemented to analyze the collected data signals …

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