Physical Sciences and Mathematics Commons^™

Classifying Emotions With Eeg And Peripheral Physiological Data Using 1d Convolutional Long Short-Term Memory Neural Network, Rupal Agarwal

USF Tampa Graduate Theses and Dissertations

Recognizing emotions is very important while building robust and interactive Affective Brain-Computer Interfaces as it allows the machines to have some degree of emotional intelligence with the help of which they can understand the changing emotional state of users. In the past, emotions have been recognized via unimodal data such as electroencephalography (EEG) signals, speech, facial expressions or peripheral physiological signals. However, emotions are complex as they are a combination of human behavior, thinking and feeling. Therefore, as compared to unimodal methods, multi-modal techniques, recognize emotions with more reliability. This thesis aims to recognize and classify human emotions into high/low …

Emotion Recognition Using Deep Convolutional Neural Network With Large Scale Physiological Data, Astha Sharma

USF Tampa Graduate Theses and Dissertations

Classification of emotions plays a very important role in affective computing and has real-world applications in fields as diverse as entertainment, medical, defense, retail, and education. These applications include video games, virtual reality, pain recognition, lie detection, classification of Autistic Spectrum Disorder (ASD), analysis of stress levels, and determining attention levels. This vast range of applications motivated us to study automatic emotion recognition which can be done by using facial expression, speech, and physiological data.

A person’s physiological signals such are heart rate, and blood pressure are deeply linked with their emotional states and can be used to identify a …

Automatic Multimodal Assessment Of Neonatal Pain, Ghada Zamzmi

USF Tampa Graduate Theses and Dissertations

For several decades, pediatricians used to believe that neonates do not feel pain. The American Academy of Pediatrics (AAP) recognized neonates' sense of pain in 1987. Since then, there have been many studies reporting a strong association between repeated pain exposure (under-treatment) and alterations in brain structure and function. This association has led to the increased use of anesthetic medications. However, recent studies found that the excessive use of analgesic medications (over-treatment) can cause many side effects. The current standard for assessing neonatal pain is discontinuous and suffers from inter-observer variations, which can lead to over- or under-treatment. Therefore, it …