Date of Award

6-15-2017

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2017.

Departments

Electrical Engineering; Computer Engineering

First Advisor

Daniel W. Lewis

Second Advisor

Sarah Kate Wilson

Abstract

According to official estimates, cardiovascular disease will become the leading cause of death in the developing world by 2020 [1]. This makes regular screening and early detection a priority for these regions. At present, such screening relies on stationary electrocardiogram (ECG) machines, but this technology has several drawbacks. Most machines are costly, stationary, and require a physician onsite to collect and interpret the data; as a result many isolated rural communities lack access to basic heart disease screening. In order to better meet the screening needs of these populations, we propose a twopart solution involving a simplified, inexpensive ECG device that will utilize cellular networks prevalent throughout the world. This first part will require little or no medical training to use, and will send an encoded heartbeat waveform via SMS message to a central server. The second part of the system we propose involves a software backend to manage and display the data to doctors working remotely. Doctors will be able to view a patient’s waveform and recommend additional screening if necessary. This was done with the goal of making the system more feasible as a mass-screening tool, and in part to highlight the potential for incorporating “big data” methods into the screening process.

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