BACKGROUND: Electrocardiogram (ECG) telemonitoring is one of the most promising applications of medical telemetry. However, previous approaches to ECG telemonitoring have largely relied on public databases of ECG results. MATERIALS AND METHODS: In this article we propose a smart ECG system called Pit-a-Pat, which extracts features from ECG signals and detects arrhythmia. It is designed to run on an Android™ (Google, Mountain View, CA) device, without requiring modifications to other software. RESULTS: We implemented the Pit-a-Pat system using a commercial ECG device, and the experimental results demonstrate the effectiveness and accuracy of Pit-a-Pat for monitoring the ECG signal and analyzing the cardiac activity of a mobile patient. CONCLUSIONS: The proposed system allows monitoring of cardiac activity with automatic analysis, thereby providing a convenient, inexpensive, and ubiquitous adjunct to personal healthcare.
BACKGROUND: Electrocardiogram (ECG) telemonitoring is one of the most promising applications of medical telemetry. However, previous approaches to ECG telemonitoring have largely relied on public databases of ECG results. MATERIALS AND METHODS: In this article we propose a smart ECG system called Pit-a-Pat, which extracts features from ECG signals and detects arrhythmia. It is designed to run on an Android™ (Google, Mountain View, CA) device, without requiring modifications to other software. RESULTS: We implemented the Pit-a-Pat system using a commercial ECG device, and the experimental results demonstrate the effectiveness and accuracy of Pit-a-Pat for monitoring the ECG signal and analyzing the cardiac activity of a mobile patient. CONCLUSIONS: The proposed system allows monitoring of cardiac activity with automatic analysis, thereby providing a convenient, inexpensive, and ubiquitous adjunct to personal healthcare.
Entities:
Keywords:
decision tree; electrocardiogram monitoring; heartbeat classification; personal healthcare; random forests; telemedicine
Authors: Jasjit S Suri; Mrinalini Bhagawati; Sudip Paul; Athanasios D Protogerou; Petros P Sfikakis; George D Kitas; Narendra N Khanna; Zoltan Ruzsa; Aditya M Sharma; Sanjay Saxena; Gavino Faa; John R Laird; Amer M Johri; Manudeep K Kalra; Kosmas I Paraskevas; Luca Saba Journal: Diagnostics (Basel) Date: 2022-03-16