College - Author 1
College of Engineering
Department - Author 1
Electrical Engineering Department
Degree Name - Author 1
BS in Electrical Engineering
College - Author 2
College of Engineering
Department - Author 2
Electrical Engineering Department
Degree - Author 2
BS in Electrical Engineering
College - Author 3
College of Engineering
Department - Author 3
Electrical Engineering Department
Degree - Author 3
BS in Electrical Engineering
College - Author 4
College of Engineering
Department - Author 4
Electrical Engineering Department
Degree - Author 4
BS in Electrical Engineering
Date
6-2020
Primary Advisor
Helen Xiao-Hua Yu, College of Engineering, Electrical Engineering Department
Abstract/Summary
This project introduces a new form of biometric identification with an ECG signal with the use of machine learning concepts. The ECG signal makes a good candidate for identification because of its unique characteristics that make it easy to distinguish individuals from one another. A patient who has previously had ECG scans stored in a database before, can be verified using this program. This project has the capability of identifying a person or verifying a person solely using their ECG signal. Utilizing this biometric identification, hospitals would be able to add to the reliability of their identification process. Additionally, companies could invest in this project if they wanted to increase its security to protect confidential information with a better verification process.
URL: https://digitalcommons.calpoly.edu/eesp/486