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Dive into the research topics where Thomas W. Hubbard is active.

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Featured researches published by Thomas W. Hubbard.


Pediatric Dermatology | 2010

A randomized, double-blind study comparing the efficacy of selenium sulfide shampoo 1% and ciclopirox shampoo 1% as adjunctive treatments for tinea capitis in children.

Catherine Chen; Laine H. Koch; James E. Dice; Kimberly K. Dempsey; Alan B. Moskowitz; Myra Barnes-Eley; Thomas W. Hubbard; Judith V. Williams

Abstract:  Our objective was to compare the efficacy of selenium sulfide shampoo 1% and ciclopirox shampoo 1% as adjunctive treatments for tinea capitis in children. Forty children aged 1–11 years with clinically diagnosed tinea capitis were randomized to receive selenium sulfide shampoo 1% or ciclopirox shampoo 1% twice a week as adjuncts to an 8‐week course of ultramicronized griseofulvin dosed at 10–12 mg/kg/day. At weeks 2, 4, and 8, subjects returned to the clinic for evaluation and scalp cultures. Subjects then returned for follow‐up visits 4 weeks after completing treatment. Overall, by 8 weeks, 30 of 33 (90.9%) treated children demonstrated mycological cure. Selenium sulfide shampoo 1% and ciclopirox shampoo 1% were equally effective as adjunctive treatments for tinea capitis in children in our study.


international symposium on mixed and augmented reality | 2004

Augmented standardized patients now virtually a reality

Frederic D. McKenzie; Hector M. Garcia; Reynel J. Castelino; Thomas W. Hubbard; John A. Ullian; Gayle A. Gliva

Standardized patients (SPs), individuals who realistically portray patients, are widely used in medical education to teach and assess communication skills, eliciting a history, performing a physical exam, and other important clinical skills. One limitation is that each SP can only portray a limited set of physical symptoms. Finding SPs with the abnormalities students need to encounter is typically not feasible. This project augments the SP by permitting the learner to hear abnormal heart and lung sounds in a normal SP.


Human Factors | 2017

Running Memory for Clinical Handoffs: A Look at Active and Passive Processing:

Brittany L. Anderson-Montoya; Mark W. Scerbo; Dana E. Ramirez; Thomas W. Hubbard

Objective: The goal of the present study was to examine the effects of domain-relevant expertise on running memory and the ability to process handoffs of information. In addition, the role of active or passive processing was examined. Background: Currently, there is little research that addresses how individuals with different levels of expertise process information in running memory when the information is needed to perform a real-world task. Method: Three groups of participants differing in their level of clinical expertise (novice, intermediate, and expert) performed an abstract running memory span task and two tasks resembling real-world activities, a clinical handoff task and an air traffic control (ATC) handoff task. For all tasks, list length and the amount of information to be recalled were manipulated. Results: Regarding processing strategy, all participants used passive processing for the running memory span and ATC tasks. The novices also used passive processing for the clinical task. The experts, however, appeared to use more active processing, and the intermediates fell in between. Conclusion: Overall, the results indicated that individuals with clinical expertise and a developed mental model rely more on active processing of incoming information for the clinical task while individuals with little or no knowledge rely on passive processing. Application: The results have implications about how training should be developed to aid less experienced personnel identify what information should be included in a handoff and what should not.


Simulation in healthcare : journal of the Society for Simulation in Healthcare | 2013

Board 322 - Research Abstract Validation of an ECG-Based Stethoscope Tracking Technology (Submission #1247)

Andrew Cross; Nahom Kidane; Edgar Miles Leviste; Thomas W. Hubbard; Frederic D. McKenzie

Introduction/Background The ECG-based stethoscope tracking technology described in this abstract aims to improve the process of obtaining abnormal cardiac auscultation findings when using a standardized patient to train medical and health profession students in the acquisition of that skill. Since SPs are typically healthy individuals with normal findings, the number and range of conditions that students can be exposed to is limited without the use of one of many technology applications meant to enhance cardiac auscultation in clinical simulation.1 Real time tracking of a stethoscope head using ECG signals would allow for the development of a teaching stethoscope that provides the standardized patient and the learner a more realistic, reproducible and flexible experience compared to currently available technology. Methods In a previous study, a modified stethoscope head with two electrodes was used to pick up ECG signals at the four cardiac auscultation sites (and at various angle orientations from vertical position) on two male subjects in the seated position. The method correctly identified the cardiac auscultation sites with 95 percent accuracy, irrespective of angle variation. This study was conducted to extend the validity of the ECG-based stethoscope tracking technology to a larger subject pool, assess classification accuracy of the technology on subjects in a supine vs. seated position and determine if subject characteristics (gender and body mass index) influence classification accuracy. Data collection for this study was achieved using the Welch-Allyn Meditron stethoscope to record ECG signals from the four cardiac auscultation areas of 35 individual participants. Five 10-second runs were recorded with the subject supine and seated up-right. Electrode gel was used to decrease motion artifacts from the signals.2 The signals that were obtained were then preprocessed and filtered. Noises and artifacts from breathing, body movements and power line interference were filtered using low pass and high pass filters. After the collected ECG signals had been processed and filtered a Pan-Tompkins algorithm3 was used to identify characteristics of QRS complexes. Amplitude and time interval features (e.g. RQamp and RQ) were then extracted and the Results from the algorithm predicted cardiac auscultation sites of the collected signals. Results The algorithm classified the cardiac auscultation areas with the stethoscope head placed at the four target sites. Based on features extracted from each QRS wave, a 10-fold cross validation of a Random Forest classifier was conducted. The classifier accuracy for subjects in the supine position was 89.3 ± 6.80, in the seated upright position was 89.12 ± 5.07, and combined was 85.73 ± 6.18 at the 95 percent confidence level. Paired and two sample t-tests revealed no significant difference in auscultation area classification from ECG signals collected from supine and seated, among males and females, and among normal and overweight/obese (Body Mass Index> 25) subjects. Conclusion The result of 86% accuracy for the combined data set was obtained in classifying the four different auscultation areas. The statistical comparative tests showed that the ECG-based stethoscope tracking technology can be extended to a larger subject pool and function reliably irrespective of subject’s body position, gender or body mass index. The classification Results can be further improved by performing an online classification that makes predictions based on a sequence of QRS waves from the incoming ECG signal increasing cardiac auscultation area classification accuracy. Advances in this technology hope to produce a versatile stethoscope that allows for a more realistic experience for learners when acquiring the skills necessary for cardiac auscultation using standardized patients. References 1. Ward J, Wattier B: Technology for Enhancing Chest Auscultation in Clinical Simulation. Respir Care 2011;56(6):834-845. 2. Cömert A, Honkala M, Hyttinen J: Effect of pressure and padding on motion artifact of textile electrodes. Biomed Eng Online 2013;12(1):26. 3. Pan J, Tompkins W: A real-time QRS detection algorithm. IEEE Trans Biomed Eng 1985;32(3):230-236. Disclosures Research could result in a future product that would be marketed by Cardionics. Inc. with which this author has a patent licensure and royalty agreement.


Archive | 2013

Automated intelligent mentoring system (aims)

Geoffrey T. Miller; Thomas W. Hubbard; Johnny Joe Garcia; Justin Maestri


Archive | 2005

System, method and medium for simulating normal and abnormal medical conditions

Frederic D. McKenzie; Hector M. Garcia; Reynel J. Castelino; Thomas W. Hubbard; John A. Ullian; Gayle Gliva-McConvey; Robert J. Alpino


Archive | 2009

Method and apparatus for chronic disease control

Thomas W. Hubbard; Eric Gyuricsko; Marta Satin-Smith; Mark W. Scerbo; Hector M. Garcia; Frederic D. McKenzie


Archive | 2006

Subject actuated system and method for simulating normal and abnormal medical conditions

Thomas W. Hubbard; Frederic D. McKenzie; Hector M. Garcia; John A. Ullian; Gayle Gliva-McConvey; Bo Sun


Studies in health technology and informatics | 2007

Medical student evaluation using augmented standardized patients: new development and results.

Bo Sun; Frederic D. McKenzie; Hector M. Garcia; Thomas W. Hubbard; John A. Ullian; Gayle A. Gliva


Academic Medicine | 2001

The Interdisciplinary Generalist Curriculum Project at Eastern Virginia Medical School.

Christine Matson; John A. Ullian; Thomas W. Hubbard

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John A. Ullian

Eastern Virginia Medical School

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Reynel J. Castelino

Eastern Virginia Medical School

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Gayle A. Gliva

Eastern Virginia Medical School

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Robert J. Alpino

Eastern Virginia Medical School

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Alan B. Moskowitz

Boston Children's Hospital

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Bo Sun

Old Dominion University

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