Raw fetal PCG dataset contaminated with Mother’s PCG
Year: 2025
Type: data-paper
Abstract: This article presents a dataset of raw fetal phonocardiogram (fPCG) signals that naturally include contamination from maternal heart sounds. Recordings were conducted with eight pregnant participants, most of whom were at 36 weeks or later gestation, and one participant at 32 weeks. The data were collected in the Biomedical Instrumentation and Signal Processing Laboratory at Independent University, Bangladesh, using a simple non-invasive device: a stethoscope coupled with a microphone. At the same time, Doppler ultrasound and a pulse oximeter were used to obtain reference values of the fetal and maternal heart rates. For the second recording batch, the oxygen saturation of the mother was also measured. Each participant contributed either two or three one-minute sessions, with 10-second breaks between sessions. Three patients were included in the first batch (two sessions each) and five in the second batch (three sessions each). File names were given systematically to indicate the batch, patient, and session (for example, B1_P1_S1). The audio was first stored in AAC format and later converted to MATLAB (.mat) and CSV (.csv) formats. The CSV files also contain anonymized demographic details, as well as notes on stethoscope placement. The dataset is intended for use in studies of fetal heart activity where signal overlap, background noise, and variability in stethoscope placement are real challenges. It is openly available through the Mendeley Data repository in standard formats. Researchers in biomedical signal processing, fetal monitoring, and related fields can use these data to test algorithms for heart sound separation, denoising, and other advanced processing tasks.
Source: Data in Brief
Authors: Tasfia Hasan Faiza, Muhammad Sajid Hossain, Samara Islam, Nazmus Sakib, Tasnuva Faruk, Md. Kafiul Islam
Institution: Independent University, Bangladesh
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,220
OpenAlex ID: W4414517933