A mobile full-time daily system for fetal monitoring

The article describes a mobile hardware and software system designed for daily monitoring of the state of fetal and maternal cardiovascular systems. The assessment is carried out by means of recording and further online analysis of acoustic data, obtained from the abdominal surface of a pregnant woman’s body. The components and operating principles of the hardware and software system designed are described. The results of experimental studies aimed at assessing the applicability of a method of acoustic data analysis implemented in the system developed are shown. The results obtained have been compared with the results obtained using cardiotocography

Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

Monitoring fetal heart rate (FHR) variability plays a fundamental role in fetal state assessment. Reliable FHR signal can be obtained from an invasive direct fetal electrocardiogram (FECG), but this is limited to labour. Alternative abdominal (indirect) FECG signals can be recorded during pregnancy and labour. Quality, however, is much lower and the maternal heart and uterine contractions provide sources of interference. Here, we present ten twenty-minute pregnancy signals and 12 five-minute labour signals. Abdominal FECG and reference direct FECG were recorded simultaneously during labour. Reference pregnancy signal data came from an automated detector and were corrected by clinical experts. The resulting dataset exhibits a large variety of interferences and clinically significant FHR patterns. We thus provide the scientific community with access to bioelectrical fetal heart activity signals that may enable the development of new methods for FECG signals analysis, and may ultimately advance the use and accuracy of abdominal electrocardiography methods.Web of Science71art. no. 20

Non Invasive Foetal Monitoring with a Combined ECG - PCG System

Although modern ultrasound provides remarkable images and biophysical measures, the technology is expensive and the observations are only available over a short time. Longer term monitoring is achieved in a clinical setting using ultrasonic Doppler cardiotocography (CTG) but this has a number of limitations. Some pathologies and some anomalies of cardiac functioning are not detectable with CTG. Moreover, although frequent and/or long-term foetal heart rate (FHR) monitoring is recommended, mainly in high risk pregnancies, there is a lack of established evidence for safe ultrasound irradiation exposure to the foetus for extended periods (Ang et al., 2006). Finally, high quality ultrasound devices are too expensive and not approved for home care use. In fact, there is a remarkable mismatch between ability to examine a foetus in a clinical setting, and the almost complete absence of technology that permits longer term monitoring of a foetus at home. Therefore, in the last years, many efforts (Hany et al., 1989; Jimenez et al., 1999; Kovacs et al., 2000; Mittra et al., 2008; Moghavvemi et al., 2003; Nagal, 1986; Ruffo et al., 2010; Talbert et al., 1986; Varady et al., 2003) have been attempted by the scientific community to find a suitable alternative

Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals

In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate (FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing. Despite the availability of several approaches to analyze the variability of FHR signals (namely the FHRV), there are still shadows hindering a comprehensive understanding of how linear and nonlinear dynamics are involved in the control of the fetal heart rhythm. In this study, we propose a straightforward processing and modeling route for a deeper understanding of the relationships between the characteristics of the FHR signal. A multiparametric modeling and investigation of the factors influencing the FHR accelerations, chosen as major indicator of fetal wellbeing, is carried out by means of linear and nonlinear techniques, blockwise dimension reduction, and artificial neural networks. The obtained results show that linear features are more influential compared to nonlinear ones in the modeling of HRV in healthy fetuses. In addition, the results suggest that the investigation of nonlinear dynamics and the use of predictive tools in the field of FHRV should be undertaken carefully and limited to defined pregnancy periods and FHR mean values to provide interpretable and reliable information to clinicians and researchers

Antepartum Fetal Monitoring through a Wearable System and a Mobile Application

Prenatal monitoring of Fetal Heart Rate (FHR) is crucial for the prevention of fetal pathologies and unfavorable deliveries. However, the most commonly used Cardiotocographic exam can be performed only in hospital-like structures and requires the supervision of expert personnel. For this reason, a wearable system able to continuously monitor FHR would be a noticeable step towards a personalized and remote pregnancy care. Thanks to textile electrodes, miniaturized electronics, and smart devices like smartphones and tablets, we developed a wearable integrated system for everyday fetal monitoring during the last weeks of pregnancy. Pregnant women at home can use it without the need for any external support by clinicians. The transmission of FHR to a specialized medical center allows its remote analysis, exploiting advanced algorithms running on high-performance hardware able to obtain the best classification of the fetal condition. The system has been tested on a limited set of pregnant women whose fetal electrocardiogram recordings were acquired and classified, yielding an overall score for both accuracy and sensitivity over 90%. This novel approach can open a new perspective on the continuous monitoring of fetus development by enhancing the performance of regular examinations, making treatments really personalized, and reducing hospitalization or ambulatory visits. Keywords: tele-monitoring; wearable devices; fetal heart rate; telemedicin

Extraction of digital cardiotocographic signals from digital cardiotocographic images: Robustness of eCTG procedure

none6noA recently developed software application, eCTG, extracts cardiotocographic (CTG) signals from digital CTG images, possibly obtained by scanning paper CTG reports. The aim of this study was to evaluate eCTG robustness across varying image formats, resolution and screw. Using 552 digital CTG signals from the “CTU-UHB Intrapartum Cardiotocography Database” of Physionet, seven sets of digital CTG images were created, differing in format (.TIFF, .PNG and .JPEG), resolution(96 dpi, 300 dpi and 600 dpi) and screw (0.0◦, 0.5◦, and 1.0◦). All created images were submitted to eCTG for CTG signals extraction. Quality of extracted signals was statistically evaluated based 1) on signal morphology, by computation of the correlation coefficient (ρ) and of the mean signal error percent (MSE%), and 2) on signal clinical content, by assessment of 18 standard CTG variables.For all sets of images, ρ was high (ρ ≥ 0.81) and MSE% was small (MSE% ≤ 2%). However, significant changes occurred in median values of four, four and five standard CTG variables in image sets with 96 dpi resolution, 0.5◦ screw and 1.0◦ screw, respectively. In conclusion, for an optimal eCTG performance, digital images should be saved in lossless formats, have a resolution of at least 300 dpi and not be affected by screw.openSbrollini A.; Brini L.; Di Tillo M.; Marcantoni I.; Morettini M.; Burattini L.Sbrollini, A.; Brini, L.; Di Tillo, M.; Marcantoni, I.; Morettini, M.; Burattini, L