Medicine and Health Sciences Commons^™

Training In The Use Of Interpretive Services For Patients With Limited English Proficiency, Kristina Wooten

Symposium of Student Scholars

In clinical settings, there is a disconnect between health care professionals (HCPs) and patients with limited English proficiency (LEP). HCPs rely on ad hoc interpreters to communicate with patients with LEP (e.g. nurses using untrained friends and family or nursing students to interpret care information). Refusing to use or misusing professional interpreters and other interpretive services may lead patients with LEP to avoid seeking necessary care, misunderstand their diagnoses and treatment regimens, and fail to return for follow-up care. This increases the already existing health care disparity between patients who speak English and patients with LEP. Studies show that if …

Hipaachecker: A Web Based Application On Hipaa Technical Safeguards Assessment Of Android Mhealth Applications, Bilash Saha

Symposium of Student Scholars

Protecting personal health records is becoming increasingly important as more people use Mobile Health applications (mHealth apps) to improve their health outcomes. These mHealth apps enable consumers to monitor their health-related problems, store, manage, and share health records, medical conditions, treatment, and medication. With the increase of mHealth apps accessibility and usability, it is crucial to create, receive, maintain or transmit protected health information (PHI) on behalf of a covered entity or another business associate. The Health Insurance Portability and Accountability Act (HIPAA) provides guidelines to the app developers so that the apps must be compliant with required and addressable …

Interventions To Prevent Hospital Acquired Pressure Injuries, Astrid Geronimo

Symposium of Student Scholars

Background: Hospital acquired pressure injuries (HAPIs) are the most common preventable complication among critical care patients. This project is conducted to compare the effectiveness between the current implemented preventative measure versus the new measures that have data supporting their effectiveness. Brief Significance: Five articles were chosen that outlined the prevalence of hospital acquired pressure injuries in critical care patients and alternative interventions that have been effective in the prevention of HAPIs. These evidence-based interventions include: The application of multilayered foam dressing with hypo oxygenated fatty oils which would reduce sheer and provide support from the pressure of laying in the …

Voice Assistant For Improving Patient's Lives: The Implementation And Case Study, Anh Duong

Symposium of Student Scholars

Over the last few years, the adoption of voice assistants in IoT devices has experienced rapid growth as a result of advanced technology alongside the development of artificial intelligence. According to a survey conducted by Juniper Research, over 2.5 billion digital voice assistants were being used in devices around the world by the end of 2018. By 2023, the number is expected to triple to 8 billion. Voice assistants (VA) have integrated into and become a part of human’s modern life with the purpose of making things more accessible and easier to use, hence, improving the users’ living experience. VA …

Relation Between Emotions And Students’ Code Quality Using Iot, Lisero Mugula

Symposium of Student Scholars

Programming can be a mentally demanding exercise. The objective of this study is to explore the effects emotions have on a programmer’s quality of code. Programmers in the study are given a Rainfall Problem to solve as their emotional data is collected simultaneously. Emotional data is collected using EMOTIV’s neuroheadset. There are 6 emotions tracked in this study: engagement, excitement, focus, interest, relaxation, and stress. One control group is relaxed prior to beginning the programming problem. An EEG-powered relaxation device called Muse is used to accomplish this task. Coding quality is measured based on 6 parameters: average, sum, count, sentinel, …

Smart Voice Assistant For Diabetes Management With Non-Invasive Iot Software, Anh Duong

Symposium of Student Scholars

Over the last few decades, the rapid growth of the Internet of Things (IoT) technology has been exponentially expanding and positively impacting different aspects of life. Alongside the innovations and developments of artificial intelligence, smart voice assistant (SVA) was invented and is widely used on a daily basis—controlling home automation, performing tasks such as playing music, accessing and checking information—to make people’s lives easier. Furthermore, SVA has also been integrated into and is used in healthcare, especially personal assistance for elderly patients. In this study, we first explored and surveyed the usages and impacts of SVA in healthcare and particularly …

Pulmon-C: A Real-Time Monitoring Framework Of Pulmonary Function, Md Saiful Islam, Maria Valero, Shahriar Hossain

Symposium of Student Scholars

This project will develop PulMon-C, a real-time monitoring framework of pulmonary function to diagnose COVID-19 patients who are being self-quarantined at home. The tool will identify anomalies in breathe rate and predict pulmonary deterioration to raise alert for immediate actions. The uniqueness of the tool is using non-invasive sensors placed under-mattress that are able to communicate data about the respiratory signal. The customer segment of PulMon-C will be the diagnosed COVID-19 patients and healthcare providers. PulMon-C will assist with the remote monitoring of COVID-19 patients as an urgent need in the USA and will bring larger impact in delivering …

Impact Of Covid-19 On Health Disparities In The United States - A Preliminary Study, Alina Panjwani

Symposium of Student Scholars

Health disparities are the differences in health outcomes and health status among people belonging to different groups. This means that people with low socioeconomic status, old age, racial and ethnic minorities, who are often those with limited access to healthcare may often face a higher disease burden and experience worse health outcomes. The current pandemic of Coronavirus 2019 (COVID-19), caused by the novel coronavirus SARS-CoV-2, provides a painful reminder of why inequities harm all of us as the devastating impact of the pandemic is apparent. This paper examines the differences in and possible cause of the rates of COVID infections, …

A Study Of Covid Tweet: Text Mining And Sentiment Analysis., Tiffany Agiri

Symposium of Student Scholars

A Study of COVID Tweet: Text Mining and Sentiment Analysis.

Tiffany Agiri, BSIT

Advisor: Dr. Chi Zhang, Associate Professor of Information Technology

Abstract

How do the tweets of two polarizing news outlets differ regarding COVID-19, and what can we draw from this data? CNN and Fox News are the two opposing news sources whose tweets we used to conduct our research, with the objective to analyze the tweet most frequently discussed terms on Covid-19 using Natural Language Processing and learn what kind of sentiments the terms are conveying, in each news source’s tweets. Through the use of the Python library …

R-Lstm: Time Series Forecasting For Covid-19 Confirmed Cases With Lstm-Based Framework, Mohammad Masum

Symposium of Student Scholars

The coronavirus disease 2019 (COVID-19) caused a pandemic outbreak affecting 213 nations worldwide. Global policymakers are imposing many measures to slow and reduce the rapid growth of infections. On the other hand, the healthcare system is encountering significant challenges for a massive number of COVID-19 confirmed or suspected individuals seeking treatment. Therefore, estimating the number of confirmed cases is necessary to provide valuable insights into the growth of the outbreak and facilitate the policy-making process. In this study, we apply ARIMA models as well as LSTM-based recurrent neural networks to forecast the daily cumulative confirmed cases. The LSTM architecture generates …

An Investigation On Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset And Its Effectiveness, Md Jobair Hossain Faruk

Symposium of Student Scholars

Neurotechnology describes as one of the focal points of today’s research around the domain of Brain-Computer Interfaces (BCI). The primary attempts of BCI research are to decoding human speech from brain signals and controlling neuro-psychological patterns that would benefit people suffering from neurological disorders. In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches. First, we explore a decoding natural speech approach that is designed to decode human speech directly from the human brain onto a digital screen introduced by Facebook Reality Laband University of California San Francisco. Then, we study a recently …