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Informatics Research Seminar: Wearable Device Data Access – Attitudes, Barriers and Possible Solutions

September 4 @ 4:00 pm - 5:00 pm EDT

Speaker: Ayesha Aslam, MD
Presented from UNC-CH

Broadcast Link: Seminar (There is content, click play button on the bottom left)

At Duke, all seminars live or broadcast will be held in Hock Auditorium from 4-5 pm.


Wearable Device Data Access – Attitudes, Barriers and Possible Solutions

The Global smart wearable device market is growing at a tremendous pace. For Healthcare providers, this means significant improvements in data accuracy, remote patient monitoring and convenience in provision of services. Access to the data collected through these devices can revolutionize dynamics in Medical Research. These devices are not only powerful resources for continually updating medical data from billions of individuals, but also allow the correlation of measured health parameters with other user demographic data.

Despite the promise of endless possibilities, there are some major barriers in accessing wearable device data. Many consumers are not willing to share their personal device data for a variety of reasons.  A qualitative coding of consumers survey responses was done to explore and quantify major barriers in wearables data sharing. This discussion will include analysis of consumers attitudes that lead to their decline in sharing wearables data as well as recommendations and possible ways to address these concerns.


Ayesha Aslam, MD is a Professional science Masters student in Biomedical and Health Informatics at UNC-Chapel Hill. Her work, as a digital Health intern at RTI included qualitative review of the survey data collected from wearable devices by consumers and devising recommendations to improve personal health data sharing by the consumers.

Dr. Aslam is ECFMG certified and has over 8 years of clinical experience working in both the public and private sectors in Pakistan.  She aspires to contribute her expertise as a physician informaticist to improve healthcare and develop clinical decision tools for the providers to make the best informed decisions.


An Analysis Of Heart Rate Variability (HRV) Using Kubios

With the innovation of new technologies, biofeedback received from biological data such as heart rate in wearable devices has proved to be an effective way of measuring well being. In this presentation we review software available to analyze heart rate variability data. We narrow down the top three softwares for HRV (Heart Rate Variability) analysis and found Kubios as the most popular and validated HRV analysis software. Using Kubios we analyzed the heart rate variability data that was generated.


Tanzila Zaman is a Master’s Student at University of North Carolina-Chapel Hill studying Biomedical and Health Informatics. She has recently completed her internship working on assessing “Heart Rate Variability (HRV) using open-source softwares” with the Digital Health Informatics Program at RTI International. Prior to starting this program, she worked in various domains in healthcare including working with a Clinical Trials Program at Duke University Health System, managing and facilitating a multispecialty clinic, and helping establish a free-clinic. She has various publications in reputed journals, and has held multiple leadership roles. She is currently working at UNC Health Care, and is graduating in Fall 2019. After completing this program, Tanzila hopes to work in a research setting.


Defining Wearable Technologies for Optimal Use: Considerations and Recommendations

The last decade has seen increased investment in digital health solutions, with roughly $8.2 billion in investments recorded in 2018, and $8.4 billion projected for 2019.  Much of the focus for this investment has been around the development of wearable technologies due to their broad applicability in health care, clinical research and personal health education. Consumer wearable technologies represent the subset of wearable technologies that are marketed directly to every-day consumers as having the ability to promote self-education about personal health through quantifiable self-monitoring actions outside of traditional health assessments made by medical professionals. Despite the great economic and intellectual fervor surrounding consumer wearable technologies, there exists equal debate as to their clinical efficacy for use in clinical and research settings as these devices are now being marketed with claims of synonymy with validated medical devices. Claims that consumer wearable technologies can be used in the same way that clinical grade wearable technologies can be used are potentially deleterious to health given that many consumer wearable technologies remain medically unsubstantiated and subject to variation in clinical measurement. Overall, there currently exists no reliable mechanism for identifying and using validated wearable technologies. In this project, an attempt is made to design a base framework for the characterization and summarization of wearable technologies according to essential device qualities. Additionally, recommendations are offered for ideal selection of wearable technologies given three defined usage contexts.


Blondell P. Glover is a Master’s Student at University of North Carolina-Chapel Hill studying Biomedical and Health Informatics with a concentration in Public Health Informatics. She recently completed an internship working with the Digital Health and Clinical Informatics (DHCI) Group at RTI International on a project defining wearable technologies optimally for usage in both clinical and personal contexts. She currently works in clinical research for the University of North Carolina at Chapel Hill in the Division of Pulmonary and Clinical Care Medicine overseeing the administration of clinical trials for pulmonary hypertension. She is graduating in Fall 2019, after which she plans to enroll in a doctoral program in a subspecialty of public health.


September 4
4:00 pm - 5:00 pm
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