We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

HospiMedica

Download Mobile App
Recent News AI Critical Care Surgical Techniques Patient Care Health IT Point of Care Business Focus

Continuous Fetal Monitor Could Prevent Millions of Stillbirths

By HospiMedica International staff writers
Posted on 21 Aug 2019
Print article
A new study indicates that commercially available inertial sensors could potentially extract fetal heart rate (FHR) continuously and noninvasively.

Under development at the Stevens Institute of Technology (Hoboken, NJ, USA) and New York University (NYU, USA), the new FHR monitor is based on seismo-cardiogram (SCG) and gyro-cardiogram (GCG) recordings collected from inertial sensors that are currently used to re-orient displayed images on a smartphone when it is rotated to a horizontal or vertical position. The monitor is based on a setup that picked up signals from inertial sensors placed at three points on the mother’s abdomen, and then extracts FHR from a fused cepstrum of recordings from all the sensors.

The novel monitor was evaluated with experiments on ten pregnant women under supine, seated, and standing positions, with the results compared to simultaneously recorded fetal cardiotocography (fCTG) readings, which are based on Doppler ultrasound. When matching the two modalities, the reliability was found to be quite comparable, with the supine position showing the highest correlation. A further advantage is that the monitor measures fetal movements without the mother’s active participation. The researchers claim that being able to assess both FHR and movement at the same time could help rule out fetal distress. The study was published on July 24, 2019, in IEEE Sensors Journal.

“Almost one-third of stillbirths occur in the absence of complicating factors; our device could let a pregnant woman know if her fetus is compromised and she needs to go to the doctor,” said senior author Negar Tavassolian, PhD, of the Stevens Institute of Technology. “Wearable inertial sensors could potentially be used to extract FHR outside the clinic, with accuracy and reliability metrics comparable to other modalities, such as fCTG. Our monitors are also completely passive, so there's no health concern.”

A normal FHR usually ranges from 120 to 160 beats per minute (bpm) in the in-utero period. It is measurable sonographically from around six weeks and the normal range varies during gestation, increasing to around 170 bpm at 10 weeks and decreasing from then to around 130 bpm at term.

Related Links:
Stevens Institute of Technology
New York University

Gold Member
Disposable Protective Suit For Medical Use
Disposable Protective Suit For Medical Use
Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
Silver Member
Wireless Mobile ECG Recorder
NR-1207-3/NR-1207-E
New
Illuminator
Trimline Basic

Print article

Channels

Critical Care

view channel
Image: The new risk assessment tool determines patient-specific risks of developing unfavorable outcomes with heart failure (Photo courtesy of 123RF)

Powerful AI Risk Assessment Tool Predicts Outcomes in Heart Failure Patients

Heart failure is a serious condition where the heart cannot pump sufficient blood to meet the body's needs, leading to symptoms like fatigue, weakness, and swelling in the legs and feet, and it can ultimately... Read more

Surgical Techniques

view channel
Image: The multi-sensing device can be implanted into blood vessels to help physicians deliver timely treatment (Photo courtesy of IIT)

Miniaturized Implantable Multi-Sensors Device to Monitor Vessels Health

Researchers have embarked on a project to develop a multi-sensing device that can be implanted into blood vessels like peripheral veins or arteries to monitor a range of bodily parameters and overall health status.... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The Quantra Hemostasis System has received US FDA special 510(k) clearance for use with its Quantra QStat Cartridge (Photo courtesy of HemoSonics)

Critical Bleeding Management System to Help Hospitals Further Standardize Viscoelastic Testing

Surgical procedures are often accompanied by significant blood loss and the subsequent high likelihood of the need for allogeneic blood transfusions. These transfusions, while critical, are linked to various... Read more