Electrical and Computer Engineering Commons^™

Behavior, Switching Losses, And Efficiency Enhancement Potentials Of 1200 V Sic Power Devices For Hard-Switched Power Converters, Ali Mahmoud Salman Al-Bayati, Mohammad Abdul Matin

Electrical and Computer Engineering: Faculty Scholarship

Semiconductor power devices are the major constituents of any power conversion system. These systems are faced by many circumscriptions due to the operating constraints of silicon (Si) based semiconductors under certain conditions. The emergence and persistence evolution of wide bandgap technology pledge to transcend the restrictions imposed by Si based semiconductors. This paper presents a thorough experimental study and assessment of the performance of three power devices: 1200 V SiC cascode, 1200 V SiC MOSFET, and 1200 V Si IGBT under the same hardware setup. The study aims to capture the major attributes for each power device toward determining their …

Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor

Electrical and Computer Engineering: Faculty Scholarship

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …

A Pilot Study On Facial Expression Recognition Ability Of Autistic Children Using Ryan, A Rear-Projected Humanoid Robot, Farzaneh Askari, Huanghao Feng, Timothy D. Sweeny, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Rear-projected robots use computer graphics technology to create facial animations and project them on a mask to show the robot’s facial cues and expressions. These types of robots are becoming commercially available, though more research is required to understand how they can be effectively used as a socially assistive robotic agent. This paper presents the results of a pilot study on comparing the facial expression recognition abilities of children with Autism Spectrum Disorder (ASD) with typically developing (TD) children using a rear-projected humanoid robot called Ryan. Six children with ASD and six TD children participated in this research, where Ryan …

How Children With Autism Spectrum Disorder Recognize Facial Expressions Displayed By A Rear-Projection Humanoid Robot, Farzaneh Askari, Huanghao Feng, Anibal Gutierrez, Timothy Sweeny, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Background: Children with Autism Spectrum Disorder (ASD) experience reduced ability to perceive crucial nonverbal communication cues such as eye gaze, gestures, and facial expressions. Recent studies suggest that social robots can be used as effective tools to improve communication and social skills in children with ASD. One explanation has been put forward by several studies that children with ASD feel more contented and motivated in systemized and predictable environment, like interacting with robots.

Objectives: There have been few research studies evaluating how children with ASD perceive facial expression in humanoid robots but no research evaluating facial expression perception …

Human Behavior Recognition Ssing Brain Lfp Signal In The Presence Of The Stimulation Pulse, Hosein M. Golshan, Adam O. Hebb, Sara J. Hanrahan, Joshua Nedrud, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Design and Methodology

This study concentrates on human behavior classification task using local field potential (LFP) signals recorded from three subjects with Parkinson’s disease (PD). Existing approaches mainly employ the LFP signals acquired under the stimulation/off condition. In practical situations, however, it is necessary to design a classification method capable of recognizing different human activities under the stimulation/on condition, where the classification task is more complicated due to the artifacts imposed by the high amplitude stimulation pulse (~1-3volts). We utilize the time-frequency representation of the acquired LFPs in the Beta frequency range (~10-30Hz) to develop a feature space based on …

Behavior Classification Using Multi-Site Lfp And Ecog Signals, Adam O. Hebb, Hosein M. Golshan, Sara J. Hanrahan, Joshua Nedrud, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Abstract-Deep Brain Stimulation (DBS) is an effective therapy that alleviates the motor signs of Parkinson’s disease (PD). Existing DBS is open loop, providing a time invariant stimulation pulse train that may generate cognitive, speech, and balance side effects. A closed-loop DBS system that utilizes appropriate physiological control variables may improve therapeutic results, reduce stimulation side effects, and extend battery life of pulse generators. Furthermore, by customizing DBS to a patient’s behavioral goal, side effects of stimulation may arise only when they are non-detrimental to the patient’s current goals. Therefore, classification of human behavior using physiological signals is an …

Using Robots As Therapeutic Agents To Teach Children With Autism Recognize Facial Expression, Seyedmohammad Mavadati, Huanghao Feng, Peyten B. Sanger, S. Silver, Anibal Gutierrez, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Background: Recognizing and mimicking facial expressions are important cues for building great rapport and relationship in human-human communication. Individuals with Autism Spectrum Disorder (ASD) have often deficits in recognizing and mimicking social cues, such as facial expressions. In the last decade several studies have shown that individuals with ASD have superior engagement toward objects and particularly robots (i.e. humanoid and non-humanoid). However, majority of the studies have focused on investigating robot’s appearances and the engineering design concepts and very few research have been done on the effectiveness of robots in therapeutic and treatment applications. In fact, the critical question that …

Children-Robot Interaction: Eye Gaze Analysis Of Children With Autism During Social Interactions, Seyedmohammad Mavadati, Huanghao Feng, S. Silver, Anibal Gutierrez, Mohammad H. Mahoor

Electrical and Computer Engineering: Graduate Student Scholarship

Background:

Typical developing individuals utilize the direction of eye gaze and eye fixation/shifting as crucial elements to transmit socially relevant information (e.g. like, dislike) to others. Individuals with Autism Spectrum Disorder (ASD), deviant pattern of mutual eye gaze is a noticeable feature that may be one of the earliest (detectable) demonstrations of impaired social skills that would lead to other deficits in ASD Individuals (e.g. delaying development of social cognition and affective construal processes). This can significantly affect the quality of human’s social interactions. Recent studies reveal that children with ASD have superior engagement to the robot-based interaction, and it …