A system, computer program product and method for facilitating concurrent monitoring of multiple obstetrics patients over a data network are proposed. Data conveying pregnancy progression information, including maternal and fetal vital sign information associated with the obstetrics patients, is received and processed to derive criticality levels for the obstetrics patients. As a first feature, notification data related to a particular obstetrics patient may be selectively transmitted to a medical expert based on different conditions including for example an associated criticality level exceeding a threshold and/or receipt of a consultation request. As a second feature, used together or separately from the first, a graphical user interface (GUI) may present a user with an ordered list of obstetrics patients dynamically adaptable based on the criticality levels. The GUI allows a user to select an obstetrics patient from the list and then adapts the GUI to present an expanded set of pregnancy progression information related to the selected obstetrics patient. Optionally, the GUI may also provide a tool allowing the user to cause a notification to be transmitted to a medical expert over the data network.

A system for achieving optimal sensor placement and enhanced signal quality for monitoring maternal and fetal activities is disclosed. The system includes a monitoring device and a computing unit. The monitoring device is configured for monitoring maternal and fetal activities and providing guidance to the user via the computing unit upon detecting a feature of interest. The monitoring device includes a plurality of sensors, a data acquisition and transmission unit, one or more reference electrodes, and a ground electrode. Based on personal data acquired using the computing unit, the system utilizes a statistical or machine learning model which incorporates one or more subsets of the personal data to determine the optimal sensor placement close to the fetal heart position. Following sensor placement, the monitoring device performs a signal quality assessment and selects the optimal sensors to ensure reliable information on maternal and fetal activities is obtained.

Described herein are methods for identifying a labor state in a pregnant female, including: receiving an input indicating a gestational age; acquiring a physiological signal; processing the physiological signal to extract a parameter of interest; and feeding the parameter of interest into a machine learning model. The machine learning model is configured to: determine a first labor probability based on the parameter of interest, determine a second labor probability based on the parameter of interest or a second parameter of interest and the gestational age, and classify the labor state of the pregnant female based on the first and second labor probability.

A device and method for deriving and displaying a time-averaged fetal heart rate signal in conjunction with microvariability information relating to variation in the beat-to-beat heart rate signal within the different time-averaging epochs or windows. Supplementary information is displayed, for example temporally aligned or registered with the time-average heart rate signal, which is indicative of variation information for the signal during averaging windows of the time-averaged signal.

A maternal and fetal monitoring device using multiple sensing units is disclosed. The maternal and fetal monitoring device comprises: a processor module and a plurality of sensor modules, wherein each said sensor module comprises: an inertial sensor, a temperature sensor and a first acoustic sensor. After being attached onto a maternal body, each said sensor module collects a body temperature signal, an inertia signal and a sound signal. Subsequently, the processor module determines a maternal body posture by analyzing the inertia signal, determines a maternal physical condition and a fetal physical condition by analyzing the inertial signal, the plurality of first sound signals and the second sound signal, and estimates physiological parameters of the maternal body and a fetus by analyzing the body temperature sensing signal, the plurality of first sound signals, and the second sound signals.

An ultrasound system includes: an ultrasound device having a two-dimensional array of ultrasound transducers; and a smartphone or tablet in operative communication with the ultrasound device. The ultrasound system is configured to: collect multiple sets of ultrasound data from multiple regions within the subject; detect fetal heartbeat signals and uterine contraction signals; monitor a fetal heartbeat signal among the fetal heartbeat signals by automatically steering an ultrasound beam to a first region among the multiple regions within the subject to collect first further ultrasound data from the first region based on a quality of the fetal heartbeat signal; and monitor a uterine contraction signal among the uterine contraction signals by automatically steering the ultrasound beam to a second region among the multiple regions within the subject to collect second further ultrasound data from the second region based on a quality of the uterine contraction signal.

In the present invention, a system and associated method is provided for monitoring fetal vital parameters. The system includes a base unit, a monitoring hub including a digital signal processor/controller and operably connected to the base unit by a single channel digital signal protocol cable, e.g., a USB cable, and a number of fetal monitoring sensors operably connected to the monitoring hub. The controller processes the signals from the sensors into a single USB protocol which can be sent along a single cable to the base unit. The USB cable allows power to be supplied to the hub in order to charge a battery used to operate the hub and the sensors connected to the hub when disconnected from the base unit to allow the patient using the hub to move freely about the base unit, with all sensor signals from the hub being wirelessly transmitted to the base unit.

There is provided a system and methods for quantitatively assessing fetal well-being based on observing fetal movement activity in an audio/visual data feed. The system includes a method that detects and quantifies fetal movements in an audio/visual data feed by audio/visual-processing motion estimation techniques. The system also includes a method that captures metrics relating to fetal movements sensed by the mother or other independent party, whereby termed “maternal perception”. The system further includes a method that cross validates the fetal movement detected by the system with fetal movement sensed by “maternal perception”. The system further includes a method that generates output to summarize fetal movement activity over a recorded time period. This output may be reviewed by a third party to assist in determining if further intervention is needed.

The present application relates to the technical field of medical monitoring. Specifically disclosed are a method for managing monitoring data, a probe assembly, and a system for managing monitoring data. The method for managing monitoring data based on the probe assembly comprises the following steps: establishing a communication connection with a first monitor; in response to a data roll-out instruction, receiving first monitoring data from the first monitor, and after the transmission of the first monitoring data is completed, breaking the communication connection with the first monitor; establishing a communication connection with a second monitor; and sending at least the first monitoring data to the second monitor, and cooperating with the second monitor to execute a monitoring task.

A sensor interface system for providing a connection between at least one sensor and a maternal-fetal monitor, wherein the interface system converts electrical muscle activity captured by the sensor(s) into uterine activity data signals for use by the maternal-fetal monitor. The sensor interface system of the invention preferably includes a conversion means for converting the signals from the sensor(s) into signals similar to those produced by a tocodynamometer.