A Novel Machine Learning Approach to Classify and Detect Atrial Fibrillation Using Optimized Implantable Electrocardiogram Sensor

Seyed Jamaleddin Mostafavi Yazdi,Jong-Ha Lee,Chang-Sik Son,Hee-Joon Park

doi:10.1109/access.2021.3123367

Abstract

There are some constraints such as external electrodes, a failure to capture most paroxysmal atrial fibrillation (AFib), low power transfer efficiency (PTE) for 24/7 charging technology, a short period of monitoring, and automatic detection of AFib in conventional electrocardiogram (ECG) sensors. To overcome these constraints, an implantable ECG sensor with a 2-coil inductive link with maximum power transfer efficiency (PTE) is designed to continuously monitor patients and efficiently detect AFib using global covering rule discovery and the minimum description length (MDL) algorithm. Among different combinations of ECG coils, the square spiral-square spiral coil demonstrates the maximum PTE, 56.23%, at the resonant frequency of 13.56 MHz and it is used in the implantable ECG sensor. The QRS complex from ECG signals of twenty-nine AFib patients is detected using different operation methods (DOM). The MDL algorithm is used to group 12 features of heart rate variability (HRV) parameters. The global covering rule discovery is proposed as a novel classification technique of AFib in ECG data. The average classification accuracy was 96.67 ± 7.03, and then the average recall, precision, F1-measures, and an average number of generated rules were 97.08 ± 6.23, 97.08 ± 6.23, 96.57 ± 7.23, and 7.9 ± 0.32, respectively. We found that the NN50, pNN50, and LF parameters can distinguish the AFib patient better than a healthy one. Among these parameters, pNN50 showed that it is greater than 34.75 in 41.38% of patients. The optimized implantable ECG sensor with a maximum PTE of 56.23% along with novel AFib detection and classification methods is suitable for its implementation in future implantable ECG sensors.

Highlights

Arrhythmia is defined as the abnormal rhythm of heartbeat
We showed that the proposed method had significantly better discriminatory power than these benchmark methods
We have demonstrated that the power transfer efficiency (PTE) of the square spiral coils was greater than the circular ones at the resonant frequency of 13.56 MHz which is consistent with other research [74]

Summary

Introduction

Arrhythmia is defined as the abnormal rhythm of heartbeat. Atrial fibrillation (AFib) is a type of an arrhythmia that can cause heart problems such as stroke and heart stop. Cardiovascular disease is the leading cause of death in the United States [1]. South Korean patients with AFib are four times as great as the general population at high risk of death [2]. A Holter monitor, which uses electrodes, is utilized to record the heart’s rhythm and performance between 24 to 72 hours and the data can be printed whenever the cardiologist needs the data. A cardiologist requests a Holter monitor when a person suddenly faints or has an irregular heartbeat [3]. Conventional Holter monitoring devices have few leads and difficulty to catch AFib [4]. An implantable ECG sensor is required to continuously monitor patients and efficiently detect AFib in ECG data

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