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

The Effect of Lost Data on the IoT Platform on the Formation of Fetal Heart Rate Graphs for Remote Diagnostic Purposes

FHR is the fetal heart rate from bpm recording detected by doppler, FHR monitoring is very important to monitor fetal health to avoid fetal distress or fetal death, FHR provides more in-depth information about how the baby is doing compared to traditional monitoring of the baby. IoT media is a medium for monitoring remote sensor values ​​using internet connections, but there are several obstacles, namely there are doubts about the data displayed by IoT media, namely the risk of missing or unsent data, this will be very dangerous if the data that is should be monitored by doctors as a reference for medical diagnosis and treatment is lost or not displayed on the IoT, because if there is missing data it will cause inaccurate diagnosis or health treatment decisions by doctors. The aim of this study to analyze the effect of lost data on the formation of the Fetal Heart Rate graph on the IoT platform as a medium for remote diagnosis. In addition, FHR data can be saved for further diagnosis by a doctor if needed. This study uses an ESP32 microcontroller which will also be used to send data to IoT (Thinger.io). The independent variable used in this study is FHR data before it is uploaded to the IoT, and the dependent variable is FHR data when it is uploaded to the IoT. The greatest data loss is at the farthest distance of 30 meters with a value of 62.47%. Based on the research that has been done, this study has the advantage that the results obtained from Doppler are close to the BPM value in humans. And also this research has developments that can be done in the future such as adding storage to the website that is used for monitoring, and placing the right position on Doppler so that the results are more stable

Wireless Fetal Heart Rate Monitoring in Inpatient Full-Term Pregnant Women: Testing Functionality and Acceptability

We tested functionality and acceptability of a wireless fetal monitoring prototype technology in pregnant women in an inpatient labor unit in the United States. Women with full-term singleton pregnancies and no evidence of active labor were asked to wear the prototype technology for 30 minutes. We assessed functionality by evaluating the ability to successfully monitor the fetal heartbeat for 30 minutes, transmit this data to Cloud storage and view the data on a web portal. Three obstetricians also rated fetal cardiotocographs on ease of readability. We assessed acceptability by administering closed and open-ended questions on perceived utility and likeability to pregnant women and clinicians interacting with the prototype technology. Thirty-two women were enrolled, 28 of whom (87.5%) successfully completed 30 minutes of fetal monitoring including transmission of cardiotocographs to the web portal. Four sessions though completed, were not successfully uploaded to the Cloud storage. Six non-study clinicians interacted with the prototype technology. The primary technical problem observed was a delay in data transmission between the prototype and the web portal, which ranged from 2 to 209 minutes. Delays were ascribed to Wi-Fi connectivity problems. Recorded cardiotocographs received a mean score of 4.2/5 (± 1.0) on ease of readability with an interclass correlation of 0.81(95%CI 0.45, 0.96). Both pregnant women and clinicians found the prototype technology likable (81.3% and 66.7% respectively), useful (96.9% and 66.7% respectively), and would either use it again or recommend its use to another pregnant woman (77.4% and 66.7% respectively). In this pilot study we found that this wireless fetal monitoring prototype technology has potential for use in a United States inpatient setting but would benefit from some technology changes. We found it to be acceptable to both pregnant women and clinicians. Further research is needed to assess feasibility of using this technology in busy inpatient settings

The Design and Implementation of Intelligent Labor Contraction Monitoring System based on Wearable Internet of Things

In current clinical practice, pregnant women who have entered 37 weeks cannot correctly judge whether they are in labor based on their subjective feelings. Wrong judgment of labor contraction can lead to adverse pregnancy outcomes and endanger the safety of mothers and babies. It will also increase the healthcare pressure in the hospital and the healthcare efficiency is reduced. Therefore, it is very meaningful to be able to design a system for monitoring labor contraction based on objective data to assist pregnant women who have entered 37 weeks in deciding the suitable time to go to hospital. For the above requirements, this thesis designs and implements an intelligent labor contraction monitoring system based on wearable Internet of Things. The system combines the Internet of Things technology, wearable technology and machine learning technology to collect contraction data through wearable sensing device. It uses the Long Short-Term Memory (LSTM) neural network to classify and identify the collected contraction data and realize real-time processing. It improves the accuracy of model recognition to 93.75%. And the recognition results are fed back to the WeChat applet so that pregnant women can view them in real time. The prototype of the wearable sensing device has been integrated by 3D printing and the proof-of-concept system has been demonstrated. Pregnant women can use this system to detect the contraction status and view the contractions in real time through the WeChat applet results. They can judge whether it is suitable for labor, and this system assists in making decisions about the best time to go to hospital

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

Information Technology and Childbirth Education

Information Technology and Childbirth Educatio

Speaking Their Language: Integrating Social Media into Childbirth Education Practice

With the advancement of modern technology, the internet has become a standard platform for many forms of communication and education. The majority of pregnant females fall into the cohort known as Millenials and have experienced technology since early in life. Millenials consider technology as part of their everyday life and use it for personal interaction or a source of information. The established comfort with the use of technology combined with busy lifestyles, multiple commitments, transportation costs or logistics, childcare, or a desire for privacy, support the use of perinatal online learning. This article examines options that childbirth educators may consider for integrating social media or other forms of technology into their repertoire