A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.

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.

Techniques are disclosed for measuring the corpus callosum volume of a fetus using magnetic resonance imaging. A scanogram of a fetus is acquired, and a detection area is determined using the corpus callosum position of the fetus in the scanogram. Magnetic resonance scanning is performed on the detection area to obtain a diffusion weighted image, with a gradient direction that is orthogonal or normal to an extending direction of fiber bundles of the corpus callosum. A fetal head image is cropped in the diffusion weighted image, and a predetermined threshold is applied to obtain an image including pixels having a brightness value that is greater than the threshold. Image processing is performed on the binarized image, with the largest region therein being identified as the corpus callosum, and the sum of voxel dimensions associated with the signal of the largest region being calculated as the corpus callosum volume.

The invention provides systems and methods for monitoring the wellbeing of a fetus by the non-invasive detection and analysis of fetal cardiac electrical activity data.

A system for monitoring fetal health data and mother health data comprises a belly-covering garment that is configured to at least partially cover a belly and to hold one or more sensor modules directly adjacent to the belly. One or more sensor modules disposed within the belly-covering garment. The one or more sensor modules comprise a pulse-oximeter sensor that gathers pulse oximetry data from the mother through contact with the belly. The one or more sensor modules also comprise an accelerometer sensor that gathers movement data from the mother. Additionally, the one or more sensor modules comprise a fetal sensor that gathers health data from a fetus within the belly.

A system for monitoring fetal wellbeing over time during pregnancy includes a sensor coupled to a pregnant woman; a processor communicatively coupled to the sensor; and a computer-readable medium having non-transitory, processor-executable instructions stored thereon. Execution of the instructions causes the processor to perform a method including: acquiring a signal from a sensor; processing the signal to identify and extract a parameter of interest from the signal; and analyzing the parameter of interest to determine a degree of fetal wellbeing. The parameter of interest may include one or more of: an average fetal heart rate, an average fetal heart rate variability, a fetal kick or movement count, an average placental oxygenation level, an average placental temperature, an average placental pH, an average amount of amniotic fluid, a fetal heart rate profile, a fetal heart rate variability profile, and a fetal movement profile.

The invention is a method for processing a phonocardiographic signal characterising fetal breathing movement (FBM), wherein in initial start point (SP) determination (S100) in frequency filtering (S110), bandpass-filtered signals of frequency subbands by first and second bandpass filters are generated from the phonocardiographic signal, and first identified SP of an FBM episode is determined in a frequency subband in SP search (S120), in episode discovering (S130) further SP is searched applying the SP search (S120) in episode search time period, and if found at smaller distance from identified SP than a clustering threshold, it is merged with identified SP, if found at larger distance from identified SP than the clustering threshold, an SP closest to identified SP is identified as second identified SP.

The invention is, furthermore, a system for processing a phonocardiographic signal characterising FBM. (FIG. 4A)

Systems, devices, and methods for performing trans-abdominal fetal oximetry and/or trans-abdominal fetal pulse oximetry using physiological characteristics and/or a calibration factor may receive a physiological characteristic of a pregnant mammal and determine one or more potential impact(s) of the physiological characteristic on a behavior of an optical signal projected into the abdomen of the pregnant mammal Then a calibration factor for the optical signal responsively to the impact. The calibration factor may then be used to calibrate a fetal detected electronic signal so that a level of fetal hemoglobin oxygen saturation may be determined.

The present invention is directed to a method for health monitoring using one or more sensors comprising first measuring (100) a body composition via one or more sensors. The measured body composition is then classified (102) into one of a plurality of categories. An at least one setting to be used for the health monitoring is adjusted (104) based on the classified body composition. Then, the health monitoring is performed (106) using the adjusted at least one health monitoring setting, wherein at least one of the sensors used to measure the body composition may also be used to perform the health monitoring.