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Background: Uterine activity (UA) monitoring is an essential element of pregnancy management. The gold-standard intrauterine pressure catheter (IUPC) is invasive and requires ruptured membranes, while the standard-of-care, external tocodynamometry (TOCO)'s accuracy is hampered by obesity, maternal movements, and belt positioning. There is an urgent need to develop telehealth tools enabling patients to remotely access care. Here, we describe and demonstrate a novel algorithm enabling remote, non-invasive detection and monitoring of UA by analyzing the modulation of the maternal electrocardiographic and phonocardiographic signals. The algorithm was designed and implemented as part of a wireless, FDA-cleared device designed for remote pregnancy monitoring. Two separate prospective, comparative, open-label, multi-center studies were conducted to test this algorithm. Methods: In the intrapartum study, 41 laboring women were simultaneously monitored with IUPC and the remote pregnancy monitoring device. Ten patients were also monitored with TOCO. In the antepartum study, 147 pregnant women were simultaneously monitored with TOCO and the remote pregnancy monitoring device. Results: In the intrapartum study, the remote pregnancy monitoring device and TOCO had sensitivities of 89.8 and 38.5%, respectively, and false discovery rates (FDRs) of 8.6 and 1.9%, respectively. In the antepartum study, a direct comparison of the remote pregnancy monitoring device to TOCO yielded a sensitivity of 94% and FDR of 31.1%. This high FDR is likely related to the low sensitivity of TOCO. Conclusion: UA monitoring via the new algorithm embedded in the remote pregnancy monitoring device is accurate and reliable and more precise than TOCO standard of care. Together with the previously reported remote fetal heart rate monitoring capabilities, this novel method for UA detection expands the remote pregnancy monitoring device's capabilities to include surveillance, such as non-stress tests, greatly benefiting women and providers seeking telehealth solutions for pregnancy care.

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BACKGROUND: The serial fetal monitoring recommended for women with high-risk pregnancies places a substantial burden on the patient, often disproportionately affecting underprivileged and rural populations. A telehealth solution that can empower pregnant women to obtain recommended fetal surveillance from the comfort of their own home has the potential to promote health equity and improve outcomes. We have previously validated a novel, wireless pregnancy monitor that can remotely capture fetal and maternal heart rates. However, such a device must also detect uterine contractions if it is to be used to robustly conduct remote nonstress tests. OBJECTIVE: This study aimed to describe and validate a novel algorithm that uses biopotential and acoustic signals to noninvasively detect uterine contractions via a wireless pregnancy monitor. STUDY DESIGN: A prospective, open-label, 2-center study evaluated simultaneous detection of uterine contractions by the wireless pregnancy monitor and an intrauterine pressure catheter in women carrying singleton pregnancies at ≥32 0/7 weeks' gestation who were in the first stage of labor (ClinicalTrials.gov Identifier: NCT03889405). The study consisted of a training phase and a validation phase. Simultaneous recordings from each device were passively acquired for 30 to 60 minutes. In a subset of the monitoring sessions in the validation phase, tocodynamometry was also deployed. Three maternal-fetal medicine specialists, blinded to the data source, identified and marked contractions in all modalities. The positive agreement and false-positive rates of both the wireless monitor and tocodynamometry were calculated and compared with that of the intrauterine pressure catheter. RESULTS: A total of 118 participants were included, 40 in the training phase and 78 in the validation phase (of which 39 of 78 participants were monitored simultaneously by all 3 devices) at a mean gestational age of 38.6 weeks. In the training phase, the positive agreement for the wireless monitor was 88.4% (1440 of 1692 contractions), with a false-positive rate of 15.3% (260/1700). In the validation phase, using the refined and finalized algorithm, the positive agreement for the wireless pregnancy monitor was 84.8% (2722/3210), with a false-positive rate of 24.8% (897/3619). For the subgroup who were monitored only with the wireless monitor and intrauterine pressure catheter, the positive agreement was 89.0% (1191/1338), with a similar false-positive rate of 25.4% (406/1597). For the subgroup monitored by all 3 devices, the positive agreement for the wireless monitor was significantly better than for tocodynamometry (P<.0001), whereas the false-positive rate was significantly higher (P<.0001). Unlike tocodynamometry, whose positive agreement was significantly reduced in the group with obesity compared with the group with normal weight (P=.024), the positive agreement of the wireless monitor did not vary across the body mass index groups. CONCLUSION: This novel method to noninvasively monitor uterine activity, via a wireless pregnancy monitoring device designed for self-administration at home, was more accurate than the commonly used tocodynamometry and unaffected by body mass index. Together with the previously reported remote fetal heart rate monitoring capabilities, this added ability to detect uterine contractions has created a complete telehealth solution for remote administration of nonstress tests.

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BACKGROUND: Access to prenatal care can be challenging due to physician shortages and rural geography. The multiple prenatal visits performed to collect basic fetal measurements lead to significant patient burden as well. The standard of care tools for fetal monitoring, external fetal heart rate monitoring with cardiotocography, as used today, must be applied by a medical professional in a healthcare setting. Novel tools to enable a remote and self-administered fetal monitoring solution would significantly alleviate some of the current barriers to care. OBJECTIVE: To compare maternal and fetal heart rate monitoring data obtained by 'Invu system' (a wireless, wearable, self-administered, fixed-location device containing passive electrical and acoustic sensors) to cardiotocography, toward a true remote fetal monitoring solution. MATERIALS AND METHODS: A prospective, open-label, multicenter study evaluated concurrent use of Invu and cardiotocography in pregnant women, aged 18 to 50 years, with singleton pregnancies ≥32+0 weeks' gestation (NCT03504189). Simultaneous recording sessions from Invu and cardiotocography lasted for ≥30 minutes. Data from the 8 electrical sensors and 4 acoustic sensors in the Invu belt were acquired, digitized, and sent wirelessly for analysis by an algorithm on cloud-based servers. The algorithm validates the data, preprocesses the data to remove noise, detects heartbeats independently from the two data sources (electrical and acoustic), and fuses the detected heartbeat arrays to calculate fetal heart rate (FHR) and maternal heart rate (MHR). The primary performance endpoint was Invu FHR limit of agreement within ± 10 beats per minute (bpm) of FHR measured with cardiotocography. RESULTS: A total of 147 women were included in the study analysis. The mean (SD) maternal age was 31.8 ±6.9 years, and the mean gestational age was 37.7 ±2.3 weeks. There was a highly significant correlation between FHR measurements from Invu and cardiotocography (r = 0.92; P<0.0001). The 95% limits of agreement for the difference, the range within which most differences between the two measurements will lie, were -8.84 bpm to 8.24 bpm. Invu measurements of MHR were also very similar to cardiotocography and were highly significantly correlated (r = 0.97; P<0.0001). No adverse events were reported during the study. CONCLUSION: Although captured by very different methods, the FHR and MHR outputs wirelessly obtained by the Invu system through passive methods were very similar to those obtained by the current standard of care. The limits of agreement for FHR measured by Invu were within a clinically acceptable ± 8 bpm of cardiotocography FHR. The Invu device uses passive technology to allow for safe, non-invasive and convenient monitoring of patients in the clinic and remotely. Further work should investigate how remote perinatal monitoring could best address some of the recent challenges seen with prenatal care and maternal and fetal outcomes. CLINICAL TRIAL INFORMATION: Registration date: April 20, 2018; First participant enrollment: February 28, 2018; ClinicalTrials.gov registration NCT03504189; https://clinicaltrials.gov/ct2/show/NCT03504189.

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The present theoretical study examines the ability to estimate cardiac stroke volume (CSV) in patients with implanted cardiac pacemaker using parametric electrical impedance tomography (pEIT) in a 2D computerized model of the thorax. CSV is a direct indicator of the cardiac pumping efficiency. The commonly used methods for measuring CSV require the invasive procedure of right heart catheterization or use expensive imaging techniques (i.e., MRI). Hence, experience with these techniques for diagnosis and monitoring has been limited to hospitalized patients. In the present study, pEIT scheme was applied in a computerized 2D model of the human thorax with implanted cardiac device to determine the left ventricular (LV) volume at different cardiac cycle phases. The LV was simulated as a prolate ellipse with its axes' lengths as the reconstruction parameters while all other geometries and conductivity values remained constant. An optimization was carried out in order to ensure that the ellipse is the appropriate model for the LV at each cardiac cycle phase. LV volumes calculated by both the pEIT algorithm and the ellipsoid model are consistent. A high correlation (ρ = 0.99) between the true and reconstructed volumes was found. The SV calculation error was ∼1%. The results suggest that the LV volume can be estimated using the pEIT method in a 2D computerized model, and that the method has the potential to be used for monitoring patients with implanted cardiac pacemaker.

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