Unique Presentation Identifier:
P43
Program Type
Undergraduate
Faculty Advisor
Dr. Carl Greco
Document Type
Poster
Location
Face-to-face
Start Date
29-4-2025 11:30 AM
Abstract
This project seeks to advance the work of previous researchers in the field of cardiac arrhythmia detection [1]. By leveraging existing wearable technology, a system which is capable of real time heart rate monitoring, timely alerts and electrocardiograph data acquisition was designed. In addition, a python script capable of identifying potential pathological patterns present in EKG recordings was designed. Future endeavors may include integrating these two systems
For real time heart rate monitoring and timely alerts, a Galaxy watch FE is used. Using Android studio integrated development environment, a wearable app was developed to notify a user when their heart rate is irregular. Using heart rate and interbeat interval values given from the watch, the program determines the standard deviation of time between beats and notifies the user when it passes beyond a specific threshold. The alert sent to the user will advise them to check their EKG using a mobile EKG device.
A python script was also written such that the algorithm can later be implemented into a mobile device. The python script was written to identify specific pathologies based on identified patterns in EKG recordings. This is done by delineating P, R, and T waves and assigning them an index in the recording. Once this is done the properties of the waves can be used to identify a wide range of patterns that may suggest presence of harmful arrythmias.
References
[1] Genesis Garay and Arath Sanchez. Ambulatory Electrocardiogram Monitoring Device. Arkansas Tech University Student Research Grant Final Report, 2024.
Recommended Citation
Grisham, Samuel G., "Ambulatory EKG Project" (2025). ATU Student Research Symposium. 30.
https://orc.library.atu.edu/atu_rs/2025/2025/30
Ambulatory EKG Project
Face-to-face
This project seeks to advance the work of previous researchers in the field of cardiac arrhythmia detection [1]. By leveraging existing wearable technology, a system which is capable of real time heart rate monitoring, timely alerts and electrocardiograph data acquisition was designed. In addition, a python script capable of identifying potential pathological patterns present in EKG recordings was designed. Future endeavors may include integrating these two systems
For real time heart rate monitoring and timely alerts, a Galaxy watch FE is used. Using Android studio integrated development environment, a wearable app was developed to notify a user when their heart rate is irregular. Using heart rate and interbeat interval values given from the watch, the program determines the standard deviation of time between beats and notifies the user when it passes beyond a specific threshold. The alert sent to the user will advise them to check their EKG using a mobile EKG device.
A python script was also written such that the algorithm can later be implemented into a mobile device. The python script was written to identify specific pathologies based on identified patterns in EKG recordings. This is done by delineating P, R, and T waves and assigning them an index in the recording. Once this is done the properties of the waves can be used to identify a wide range of patterns that may suggest presence of harmful arrythmias.
References
[1] Genesis Garay and Arath Sanchez. Ambulatory Electrocardiogram Monitoring Device. Arkansas Tech University Student Research Grant Final Report, 2024.