ABSTRACT
Monitoring of fetal electrocardiogram (fECG) would provide useful information about fetal wellbeing as well as any abnormal development during pregnancy. Recent advances in flexible electronics and wearable technologies have enabled compact devices to acquire personal physiological signals in the home setting, including those of expectant mothers. However, the high noise level in the daily life renders long-entrenched challenges to extract fECG from the combined fetal/maternal ECG signal recorded in the abdominal area of the mother. Thus, an efficient fECG extraction scheme is a dire need. In this work, we intensively explored various extraction algorithms, including template subtraction (TS), independent component analysis (ICA), and extended Kalman filter (EKF) using the data from the PhysioNet 2013 Challenge. Furthermore, the modified data with Gaussian and motion noise added, mimicking a practical scenario, were utilized to examine the performance of algorithms. Finally, we combined different algorithms together, yielding promising results, with the best performance in the F1 score of 92.61% achieved by an algorithm combining ICA and TS. With the data modified by adding different types of noise, the combination of ICA-TS-ICA showed the highest F1 score of 85.4%. It should be noted that these combined approaches required higher computational complexity, including execution time and allocated memory compared with other methods. Owing to comprehensive examination through various evaluation metrics in different extraction algorithms, this study provides insights into the implementation and operation of state-of-the-art fetal and maternal monitoring systems in the era of mobile health.
ABSTRACT
BACKGROUND: Having mobile devices that provide patients with the ability to record and monitor the electrical activity of their heart enhances patient self-care and the early detection of irregular heartbeat (cardiac arrhythmia), yet few such devices exist in Vietnam. Challenges exist for introducing mobile electrocardiography (ECG) monitoring devices in Vietnam, including patient accessibility and affordability. A low-cost mobile ECG monitoring device designed and developed in Vietnam, which allows patients to easily measure their heart's electrical activity and navigate recordings, may be a solution. OBJECTIVE: The aim of this project is to assess the usability of the MD-Link system, a newly developed mobile handheld 1-lead ECG device, in detecting patients with irregular heartbeat. We will compare its outputs to the standard printed outputs of a 12-lead electrocardiogram generated by the Nihon Kohden Cardiofax S Electrocardiograph Model ECG-1250K. METHODS: We will conduct a cross-sectional study in two stages, including the measurement of ECG signals of patients using the MD-Link and the Nihon Kohden Cardiofax S and analysis of the selected standard outputs collected from the ECG recordings of the MD-Link and the Nihon Kohden Cardiofax S. The MD-Link consists of (1) a mobile device (eg, a smartphone); (2) a lead wire with 2 disposable electrodes; and (3) an easy-to-use mobile app interface enabling the upload and accurate display of ECG recordings to patients and their clinicians. Our research team, consisting of members from Dartmouth College; the Institute of Health, Population and Development; Hanoi University of Science and Technology; and physicians and nurses from Thanh Chan Clinic, will assist in carrying out this project. RESULTS: We will proceed with a publication plan that includes a project report and, ultimately, articles for peer-reviewed journals. We also hope to disseminate our work at relevant conferences to provide more coverage and exposure to the MD-Link mobile device. Recruitment and data collection were completed in January 2018. Data analysis started in February 2018 and is ongoing. Results are expected mid-2019. CONCLUSIONS: At the end of this project, we will have developed and tested the MD-Link, a low-cost mobile ECG monitoring device, with some supportive comparisons to standard ECG devices commonly used in heart clinics or hospitals in Vietnam. Our long-term goal is for the MD-Link to be easily accessible, affordable, and to fit into a patient's daily routine, thus improving the care and treatment of patients with cardiovascular diseases (CVDs). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/8762.
ABSTRACT
Electrocardiogram (ECG) monitoring of the fetus during pregnancy, before and during labor, can provide crucial information for the assessment of fetal well-being and development, as well as labor progress. An out-of-clinics fetal ECG monitoring system may pave the way for instant diagnosis, suggesting immediate intervention, which could help reduce the fetal mortality rate. In this paper, we present an unobtrusive fetal maternal ECG monitoring system which can operate in the home setting. The acquisition of the mother's abdominal ECG is done using the non-contact electrode approach. The extraction of the fetal ECG from the combined fetal/maternal ECG signal is investigated using both Fast Independent Component Analysis (FastICA) and RobustICA algorithms. An accelerometer is integrated for motion artifact detection which would help reduce interferences due to movement. The device also is connected to a cloud server, allowing doctors to access the data in real time.
ABSTRACT
Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlying molecular mechanisms. Zebrafish (Danio rerio) are an excellent model system for studying heart disease as they enable a forward genetic approach to tackle this unmet medical need. In recent years, our team has been employing electrocardiogram (ECG) as an efficient tool to study the zebrafish heart along with conventional approaches, such as immunohistochemistry, DNA and protein analyses. We have overcome various challenges in the small size and aquatic environment of zebrafish in order to obtain ECG signals with favorable signal-to-noise ratio (SNR), and high spatial and temporal resolution. In this paper, we highlight our recent efforts in zebrafish ECG acquisition with a cost-effective simplified microelectrode array (MEA) membrane providing multi-channel recording, a novel multi-chamber apparatus for simultaneous screening, and a LabVIEW program to facilitate recording and processing. We also demonstrate the use of machine learning-based programs to recognize specific ECG patterns, yielding promising results with our current limited amount of zebrafish data. Our solutions hold promise to carry out numerous studies of heart diseases, drug screening, stem cell-based therapy validation, and regenerative medicine.
