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Articles 1 - 13 of 13
Full-Text Articles in Computer Engineering
How Degrees Of Freedom Affects Sense Of Agency, Akima Connelly, Jungsu Pak, Tian Lan, Uri Maoz
How Degrees Of Freedom Affects Sense Of Agency, Akima Connelly, Jungsu Pak, Tian Lan, Uri Maoz
Student Scholar Symposium Abstracts and Posters
Can the rubber-hand illusion be extended to a moving robotic arm in different degrees of freedom (DOF), inducing sense of ownership & agency over the arm? We hypothesize that DOF closer to what humans possess will result in a stronger sense of ownership and agency.
Comparing Record Linkage Software Programs And Algorithms Using Real-World Data., Alan F. Karr, Matthew T. Taylor, Suzanne L. West, Soko Setoguchi, Tzuyung D. Kou, Tobias Gerhard, Daniel B. Horton
Comparing Record Linkage Software Programs And Algorithms Using Real-World Data., Alan F. Karr, Matthew T. Taylor, Suzanne L. West, Soko Setoguchi, Tzuyung D. Kou, Tobias Gerhard, Daniel B. Horton
Student Papers, Posters & Projects
Linkage of medical databases, including insurer claims and electronic health records (EHRs), is increasingly common. However, few studies have investigated the behavior and output of linkage software. To determine how linkage quality is affected by different algorithms, blocking variables, methods for string matching and weight determination, and decision rules, we compared the performance of 4 nonproprietary linkage software packages linking patient identifiers from noninteroperable inpatient and outpatient EHRs. We linked datasets using first and last name, gender, and date of birth (DOB). We evaluated DOB and year of birth (YOB) as blocking variables and used exact and inexact matching methods. …
A Low-Cost Soft Robotic Hand Exoskeleton For Use In Therapy Of Limited Hand–Motor Function, Grant Rudd, Liam Daly, Vukica Jovanovic, Filip Cukov
A Low-Cost Soft Robotic Hand Exoskeleton For Use In Therapy Of Limited Hand–Motor Function, Grant Rudd, Liam Daly, Vukica Jovanovic, Filip Cukov
Engineering Technology Faculty Publications
We present the design and validation of a low-cost, customizable and 3D-printed anthropomorphic soft robotic hand exoskeleton for rehabilitation of hand injuries using remotely administered physical therapy regimens. The design builds upon previous work done on cable actuated exoskeleton designs by implementing the same kinematic functionality, but with the focus shifted to ease of assembly and cost effectiveness as to allow patients and physicians to manufacture and assemble the hardware necessary to implement treatment. The exoskeleton was constructed solely from 3D-printed and widely available of-the-shelf components. Control of the actuators was realized using an Arduino microcontroller, with a custom-designed shield …
Non-Parametric Combination Analysis Of Multiple Data Types Enables Detection Of Novel Regulatory Mechanisms In T Cells Of Multiple Sclerosis Patients., Sunjay Jude Fernandes, Hiromasa Morikawa, Ewoud Ewing, Sabrina Ruhrmann, Rubin Narayan Joshi, Vincenzo Lagani, Nestoras Karathanasis, Mohsen Khademi, Nuria Planell, Angelika Schmidt, Ioannis Tsamardinos, Tomas Olsson, Fredrik Piehl, Ingrid Kockum, Maja Jagodic, Jesper Tegnér, David Gomez-Cabrero
Non-Parametric Combination Analysis Of Multiple Data Types Enables Detection Of Novel Regulatory Mechanisms In T Cells Of Multiple Sclerosis Patients., Sunjay Jude Fernandes, Hiromasa Morikawa, Ewoud Ewing, Sabrina Ruhrmann, Rubin Narayan Joshi, Vincenzo Lagani, Nestoras Karathanasis, Mohsen Khademi, Nuria Planell, Angelika Schmidt, Ioannis Tsamardinos, Tomas Olsson, Fredrik Piehl, Ingrid Kockum, Maja Jagodic, Jesper Tegnér, David Gomez-Cabrero
Computational Medicine Center Faculty Papers
Multiple Sclerosis (MS) is an autoimmune disease of the central nervous system with prominent neurodegenerative components. The triggering and progression of MS is associated with transcriptional and epigenetic alterations in several tissues, including peripheral blood. The combined influence of transcriptional and epigenetic changes associated with MS has not been assessed in the same individuals. Here we generated paired transcriptomic (RNA-seq) and DNA methylation (Illumina 450 K array) profiles of CD4+ and CD8+ T cells (CD4, CD8), using clinically accessible blood from healthy donors and MS patients in the initial relapsing-remitting and subsequent secondary-progressive stage. By integrating the output of a …
Recent Trends, Current Research In Cyberpsychology: A Literature Review, Amarjit Kumar Singh, Pawan Kumar Singh
Recent Trends, Current Research In Cyberpsychology: A Literature Review, Amarjit Kumar Singh, Pawan Kumar Singh
Library Philosophy and Practice (e-journal)
Cyberpsychology refers to the study of the mind and behavior in the context of interactions with technology. It is an emerging branch, which has focused on the psychological aspects connected to the increasing presence and usages of technology in modern lives. This paper traces recent advancement and trends of Cyberpsychology is an emerging domain of knowledge and goes on the give a literature review of the same. An analysis of the recent research and literature covering 300 most relevant research papers from the period of 2012 to 15, August 2019 was conducted to determine and shape the research pattern based …
Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin
Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin
Honors Projects
A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …
Using Big Data Analytics To Improve Hiv Medical Care Utilisation In South Carolina: A Study Protocol, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Mohammad Rifat Haider, Xiaoming Li
Using Big Data Analytics To Improve Hiv Medical Care Utilisation In South Carolina: A Study Protocol, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Mohammad Rifat Haider, Xiaoming Li
Faculty Publications
Introduction Linkage and retention in HIV medical care remains problematic in the USA. Extensive health utilisation data collection through electronic health records (EHR) and claims data represent new opportunities for scientific discovery. Big data science (BDS) is a powerful tool for investigating HIV care utilisation patterns. The South Carolina (SC) office of Revenue and Fiscal Affairs (RFA) data warehouse captures individual-level longitudinal health utilisation data for persons living with HIV (PLWH). The data warehouse includes EHR, claims and data from private institutions, housing, prisons, mental health, Medicare, Medicaid, State Health Plan and the department of health and human services. The …
Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead
Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead
Engineering Faculty Articles and Research
Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing ASD, exploring its genetic underpinnings, and designing effective interventions. This paper provides a comprehensive review of 45 papers utilizing supervised machine learning in ASD, including algorithms for classification and text analysis. The goal of the paper is to identify and describe supervised machine learning trends in ASD literature as …
Two-Stage Bagging Pruning For Reducing The Ensemble Size And Improving The Classification Performance, Hua Zhang, Yujie Song, Bo Jiang, Bi Chen, Guogen Shan
Two-Stage Bagging Pruning For Reducing The Ensemble Size And Improving The Classification Performance, Hua Zhang, Yujie Song, Bo Jiang, Bi Chen, Guogen Shan
Environmental & Occupational Health Faculty Publications
Ensemble methods, such as the traditional bagging algorithm, can usually improve the performance of a single classifier. However, they usually require large storage space as well as relatively time-consuming predictions. Many approaches were developed to reduce the ensemble size and improve the classification performance by pruning the traditional bagging algorithms. In this article, we proposed a two-stage strategy to prune the traditional bagging algorithm by combining two simple approaches: accuracy-based pruning (AP) and distance-based pruning (DP). These two methods, as well as their two combinations, “AP+DP” and “DP+AP” as the two-stage pruning strategy, were all examined. Comparing with the single …
Shaping The Future Of Trusted Digital Identity: The Idef Registry With Health Information Use Cases, Noreen Y. Whysel
Shaping The Future Of Trusted Digital Identity: The Idef Registry With Health Information Use Cases, Noreen Y. Whysel
Publications and Research
No abstract provided.
Real-Time Classification Of Multivariate Olfaction Data Using Spiking Neural Networks, Arnup Vanarse, Adam Osseiran, Alexander Rassau, Therese O'Sullivan, Jonny Lo, Amanda Devine
Real-Time Classification Of Multivariate Olfaction Data Using Spiking Neural Networks, Arnup Vanarse, Adam Osseiran, Alexander Rassau, Therese O'Sullivan, Jonny Lo, Amanda Devine
Research outputs 2014 to 2021
Recent studies in bioinspired artificial olfaction, especially those detailing the application of spike-based neuromorphic methods, have led to promising developments towards overcoming the limitations of traditional approaches, such as complexity in handling multivariate data, computational and power requirements, poor accuracy, and substantial delay for processing and classification of odors. Rank-order-based olfactory systems provide an interesting approach for detection of target gases by encoding multi-variate data generated by artificial olfactory systems into temporal signatures. However, the utilization of traditional pattern-matching methods and unpredictable shuffling of spikes in the rank-order impedes the performance of the system. In this paper, we present an …
A Hardware-Deployable Neuromorphic Solution For Encoding And Classification Of Electronic Nose Data, Anup Vanarse, Alexander Rassau, Peter Van Der Made
A Hardware-Deployable Neuromorphic Solution For Encoding And Classification Of Electronic Nose Data, Anup Vanarse, Alexander Rassau, Peter Van Der Made
Research outputs 2014 to 2021
In several application domains, electronic nose systems employing conventional data processing approaches incur substantial power and computational costs and limitations, such as significant latency and poor accuracy for classification. Recent developments in spike-based bio-inspired approaches have delivered solutions for the highly accurate classification of multivariate sensor data with minimized computational and power requirements. Although these methods have addressed issues related to efficient data processing and classification accuracy, other areas, such as reducing the processing latency to support real-time application and deploying spike-based solutions on supported hardware, have yet to be studied in detail. Through this investigation, we proposed a spiking …
Emerging Roles Of Virtual Patients In The Age Of Ai, C. Donald Combs, P. Ford Combs
Emerging Roles Of Virtual Patients In The Age Of Ai, C. Donald Combs, P. Ford Combs
Computational Modeling & Simulation Engineering Faculty Publications
Today's web-enabled and virtual approach to medical education is different from the 20th century's Flexner-dominated approach. Now, lectures get less emphasis and more emphasis is placed on learning via early clinical exposure, standardized patients, and other simulations. This article reviews literature on virtual patients (VPs) and their underlying virtual reality technology, examines VPs' potential through the example of psychiatric intake teaching, and identifies promises and perils posed by VP use in medical education.