2013 Annual Research Symposium Abstract Book

2013 annual volume of abstracts for science research projects conducted by students at Trinity College

Big data analytics in intensive care units: challenges and applicability in an Argentinian hospital

In a typical intensive care unit of a healthcare facilities, many sensors are connected to patients to measure high frequency physiological data. Currently, measurements are registered from time to time, possibly every hour. With this data lost, we are losing many opportunities to discover new patterns in vital signs that could lead to earlier detection of pathologies. The early detection of pathologies gives physicians the ability to plan and begin treatments sooner or potentially stop the progression of a condition, possibly reducing mortality and costs. The data generated by medical equipment are a Big Data problem with near real-time restrictions for processing medical algorithms designed to predict pathologies. This type of system is known as realtime big data analytics systems. This paper analyses if proposed system architectures can be applied in the Francisco Lopez Lima Hospital (FLLH), an Argentinian hospital with relatively high financial constraints. Taking into account this limitation, we describe a possible architectural approach for the FLLH, a mix of a local computing system at FLLH and a public cloud computing platform. We believe this work may be useful to promote the research and development of such systems in intensive care units of hospitals with similar characteristics to the FLLH.Facultad de Informátic

Big data analytics in intensive care units: challenges and applicability in an Argentinian hospital

In a typical intensive care unit of a healthcare facilities, many sensors are connected to patients to measure high frequency physiological data. Currently, measurements are registered from time to time, possibly every hour. With this data lost, we are losing many opportunities to discover new patterns in vital signs that could lead to earlier detection of pathologies. The early detection of pathologies gives physicians the ability to plan and begin treatments sooner or potentially stop the progression of a condition, possibly reducing mortality and costs. The data generated by medical equipment are a Big Data problem with near real-time restrictions for processing medical algorithms designed to predict pathologies. This type of system is known as realtime big data analytics systems. This paper analyses if proposed system architectures can be applied in the Francisco Lopez Lima Hospital (FLLH), an Argentinian hospital with relatively high financial constraints. Taking into account this limitation, we describe a possible architectural approach for the FLLH, a mix of a local computing system at FLLH and a public cloud computing platform. We believe this work may be useful to promote the research and development of such systems in intensive care units of hospitals with similar characteristics to the FLLH.Facultad de Informátic

Wireless impact sensing headband - W.I.S.H.

The prevalence of undiagnosed head injuries in the athletic world, and their associated health risks, is too great to ignore. This is especially true in non-helmeted sports where the availability of impact monitoring technologies is few and far between. In this paper, we discuss our wireless impact sensing headband technology that aids in the awareness and detection of potential concussions, from inception through design completion. Through the use of a custom-built validation system capable of simulating impact collisions, along with a series of experiments and revisions, our team was able to build a device that can sense and transmit data throughout the majority of the impact range of standard concussions. This system has the potential to help millions of athletes around the world be much better prepared in the event of a potentially life-threatening head impact. However, while our system is able to accurately detect and transmit impact data in real time, we found that additions such as the ability to sample at a much higher rate than experimented with, a more ergonomic design, and a lightweight, durable enclosure would be needed in order for our product to be a viable mass-market competitor. Although the product is not ready for the mass market as of today, it will be a vital part to larger systems used for predictive analytics and more innovative and robust athletic game strategy

The Impact of Trauma on Young Children/The Effect of Animal-Assisted Intervention on Young Children with Trauma

The purpose of this study is to determine the impact of trauma on the development of young children. This study will define trauma and its symptoms, determine the effect of trauma on the brain and critical development, and identify strategies and interventions. The purpose of this study is to identify the effects of Animal-Assisted Intervention (AAI) on young children with trauma. This study will define AAI and determine if animals are an appropriate therapy for young children

Participative Urban Health and Healthy Aging in the Age of AI

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2022, held in Paris, France, in June 2022. The 15 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 33 submissions. They cover topics such as design, development, deployment, and evaluation of AI for health, smart urban environments, assistive technologies, chronic disease management, and coaching and health telematics systems

Public Perceptions of Facebook’s Libra Digital Currency Initiative: Text Mining on Twitter

Large corporations in the financial and technology sectors are increasingly interested in digital currencies, and central bank digital currencies are being actively researched around the globe. In this study, we analyzed the public discourse conducted through the social media platform Twitter concerning Facebook’s Libra digital currency initiative. Text mining of tweets posted during the one-month period around the official announcement of the digital currency project revealed that the majority of the public have a neutral sentiment toward the proposed digital currency. However, those with positive attitudes outnumbered those perceiving the digital currency initiative as negative, and the negative sentiment mainly stemmed from anger and anxiety. Through topical modeling analysis using latent Dirichlet allocation, we identified eight themes in the public discourse related to Facebook Libra. The study provides an early exploratory assessment of factors facilitating and hindering user adoption of one of the most important practical applications of blockchain technology

INVESTIGATING DIFFUSION TENSOR IMAGING CORRELATES OF COGNITIVE IMPAIRMENT IN IDIOPATHIC NORMAL PRESSURE HYDROCEPHALUS AND ALZHEIMER\u27S DISEASE

Modest expansion of the human brain cerebrospinal fluid (CSF)-filled ventricles is normal with aging, and because of this, it can be difficult for physicians to accurately diagnose and treat enlarged ventricles (ventriculomegaly), called hydrocephalus1 (fluid or water in the brain) Ventriculomegaly occurs due to an obstruction (such as a blood clot or tumor), or a change in CSF absorption2. Primary hydrocephalus, also called idiopathic normal pressure hydrocephalus (iNPH), is non-obstructive and may be comorbid with other neurodegenerative diseases such as Alzheimer’s disease (AD) or frontotemporal dementia (FTD). Clinically, it can be difficult to tell whether the pathophysiological changes leading to cognitive impairment also led to the ventriculomegaly, as may occur in AD, versus whether the hydrocephalus itself is driving cognitive and motor impairment, i.e. iNPH. The goal of this thesis project is to investigate the relationship between iNPH and AD in order to better understand how they may contribute to each other, and to help clinicians distinguish between them. To do this, we compared cognitive performance and white matter integrity between patients with “pure” iNPH, “pure” Alzheimer’s disease (AD), and co-morbid iNPH + AD. Our results demonstrated that there are specific periventricular structures in the brain that are associated with cognitive impairment in AD versus iNPH. We conclude that the distribution pattern of AD vs. iNPH may be a valid tool to distinguish between these disorders, and may form the basis for subsequent studies that can further explicate the link between these often-overlapping etiologies

The Internet of Things Will Thrive by 2025

This report is the latest research report in a sustained effort throughout 2014 by the Pew Research Center Internet Project to mark the 25th anniversary of the creation of the World Wide Web by Sir Tim Berners-LeeThis current report is an analysis of opinions about the likely expansion of the Internet of Things (sometimes called the Cloud of Things), a catchall phrase for the array of devices, appliances, vehicles, wearable material, and sensor-laden parts of the environment that connect to each other and feed data back and forth. It covers the over 1,600 responses that were offered specifically about our question about where the Internet of Things would stand by the year 2025. The report is the next in a series of eight Pew Research and Elon University analyses to be issued this year in which experts will share their expectations about the future of such things as privacy, cybersecurity, and net neutrality. It includes some of the best and most provocative of the predictions survey respondents made when specifically asked to share their views about the evolution of embedded and wearable computing and the Internet of Things