mCardia: A Context-Aware ECG Collection System for Ambulatory Arrhythmia Screening

Abstract

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.

Software Architecture Patterns for Extending Sensing Capabilities and Data Formatting in Mobile Sensing

“…CAMS has been used in the design and implementation of several mHealth applications targeting mental health [ 28 ], CVDs [ 29 ], and diabetes [ 30 ]. From an application and UI point-of-view, these applications are quite different both in terms of technical design and in data collection and management, which hence demonstrate the flexibility and extensibility of CAMS for mobile and wearable sensing for a broad range of applications.…”

“…The ‘Sampling Package’ and ‘Data Transformer’ design patterns have been derived from, and used in, the CAMS software architecture and help to achieve the non-functional software architecture goal of being highly extensible. CAMS has been evolving over eight major releases, and has been used in the design and implementation of several released mHealth applications targeting mental health [ 28 ], cardiovascular disease (CVDs) [ 29 ], and diabetes [ 30 ]. These applications are very different in their design and requirements for mobile sensing, and hence testifies to the wide applicability of CAMS for different types of applications.…”

CACHET-CADB: A Contextualized Ambulatory Electrocardiography Arrhythmia Dataset

“…We used the mCardia system (28) for the data collection. It uses a single-channel chest-mounted wireless ECG Holter [the Movisens ECGMove4 ( 29)] and a mobile application for data collection (Figure 1).…”

“…In Denmark, the study was exempted for ethical approval by the Danish Research Ethical Committee because the ECG recordings were only collected for technical purposes, and not to be used in a clinical setting (File # H-19071015). In India, the data collection was done with Mahatma Gandhi University of Medical Sciences and Technology (MGUMST), Jaipur, and the process complies with MGUMST's human participant's guideline the mCardia mobile application for collection of patient-reported data (28).…”

Mapping the Journeys of Atrial Fibrillation Patients and Citizens Using Wearable Devices for Remote Cardiac Monitoring

“…Nowadays, there are several 'smart' wearable and portable devices including smartwatches and patch electrodes that can remotely monitor heart rate and rhythm using sensors, and automatically diagnose AF in its nascent stages using different algorithms (Egan et al, 2022). These include commercially available devices such as Apple Watch, Fitbit, Zio patch, etc., which have received regulatory approval for their widespread use in different health systems, as well as customised systems such as KardiaMobile (Kumar et al, 2022). Such devices along with their concomitant software applications allow users to observe their heart rate and rhythm in real time, which can empower them in making informed decisions.…”