TY - JOUR

T1 - mCardia

T2 - A Context-Aware ECG Collection System for Ambulatory Arrhythmia Screening

AU - Kumar, Devender

AU - Maharjan, Raju

AU - Maxhuni, Alban

AU - Dominguez, Helena

AU - Frølich, Anne

AU - Bardram, Jakob E.

N1 - Publisher Copyright: © 2022 Association for Computing Machinery.

PY - 2022

Y1 - 2022

N2 - This article presents the design, technical implementation, and feasibility evaluation of mCardia-a context-aware, mobile electrocardiogram (ECG) collection system for longitudinal arrhythmia screening under free-living conditions. Along with ECG, mCardia also records active and passive contextual data, including patient-reported symptoms and physical activity. This contextual data can provide a more accurate understanding of what happens before, during, and after an arrhythmia event, thereby providing additional information in the diagnosis of arrhythmia. By using a plugin-based architecture for ECG and contextual sensing, mCardia is device-agnostic and can integrate with various wireless ECG devices and supports cross-platform deployment. We deployed the mCardia system in a feasibility study involving 24 patients who used the system over a two-week period. During the study, we observed high patient acceptance and compliance with a satisfactory yield of collected ECG and contextual data. The results demonstrate the high usability and feasibility of mCardia for longitudinal ambulatory monitoring under free-living conditions. The article also reports from two clinical cases, which demonstrate how a cardiologist can utilize the collected contextual data to improve the accuracy of arrhythmia analysis. Finally, the article discusses the lessons learned and the challenges found in the mCardia design and the feasibility study.

AB - This article presents the design, technical implementation, and feasibility evaluation of mCardia-a context-aware, mobile electrocardiogram (ECG) collection system for longitudinal arrhythmia screening under free-living conditions. Along with ECG, mCardia also records active and passive contextual data, including patient-reported symptoms and physical activity. This contextual data can provide a more accurate understanding of what happens before, during, and after an arrhythmia event, thereby providing additional information in the diagnosis of arrhythmia. By using a plugin-based architecture for ECG and contextual sensing, mCardia is device-agnostic and can integrate with various wireless ECG devices and supports cross-platform deployment. We deployed the mCardia system in a feasibility study involving 24 patients who used the system over a two-week period. During the study, we observed high patient acceptance and compliance with a satisfactory yield of collected ECG and contextual data. The results demonstrate the high usability and feasibility of mCardia for longitudinal ambulatory monitoring under free-living conditions. The article also reports from two clinical cases, which demonstrate how a cardiologist can utilize the collected contextual data to improve the accuracy of arrhythmia analysis. Finally, the article discusses the lessons learned and the challenges found in the mCardia design and the feasibility study.

KW - Arrhythmia

KW - arrhythmia screening

KW - cardiovascular

KW - context aware ECG

KW - electrocardiogram (ECG)

KW - holter monitoring

KW - mHealth

KW - mobile health

KW - mobile sensing

U2 - 10.1145/3494581

DO - 10.1145/3494581

M3 - Journal article

AN - SCOPUS:85126818655

VL - 3

JO - ACM Transactions on Computing for Healthcare

JF - ACM Transactions on Computing for Healthcare

SN - 2691-1957

IS - 2

M1 - 20

ER -