In one embodiment of the disclosure, a method of monitoring a fetus in utero is disclosed that includes implanting a medical device into a patient's uterus, collecting fetal data using the medical device, and transmitting, e.g., wirelessly, the fetal data from the medical device to a receiver. In another embodiment, a medical monitoring system is disclosed that includes a first device that is implantable into a patient's uterus for collecting fetal data, and a second device that is configured and dimensioned for connection with the first device such that the fetal data is wirelessly communicable from the first device to the second device.

The disclosed apparatus, systems and methods relate to tracking abdominal orientation and activity for purposes of preventing or treating conditions of pregnancy or other types of medical conditions. In certain specific embodiments, the system, device, or method relates to identifying abdominal orientation risk values, calculating and updating a cumulative risk value, comparing the cumulative risk value to a threshold, and outputting a warning when the cumulative risk value crosses the threshold.

There are provided a maternal and fetal monitoring device and a display device for monitoring device including fetal heart rate acquisition means configured to acquire a fetal heart rate, labor pain intensity acquisition means configured to acquire a maternal labor pain intensity, fetal bioelectric signal acquisition means configured to acquire a fetal bioelectric signal, and display means capable of simultaneously displaying a cardiotocogram that displays the fetal heart rate and the labor pain intensity side by side on the same time axis over time as a graph and a fetal bioelectric signal diagram displaying the fetal bioelectric signal, and optimizing and displaying, together with the cardiotocogram, the fetal bioelectric signal diagram and the like closely related to these pieces of information.

A wearable sensor apparatus is disclosed that includes a flexible substrate adapted to be coupled with a skin surface of an expectant mother. A conductor is disposed on the flexible substrate. The conductor can include micron-scale invaginations. The conductor can be capable of repeatable variation in resistance when subject to a strain. Also disclosed is a system for monitoring the health of a fetus in utero that includes a wearable sensor apparatus. The wearable sensor apparatus is configured to output a signal responsive to an electrical input. The system includes a computing system with one or more hardware processors. The computing system is programmed to implement a signal processing module configured to access the output signal from the wearable strain gauge and generate an output indicative of health of the baby in utero. The output can be based in part on the received output signal and previously stored correlations between signal data from the wearable strain gauge and observations of the system or of the mother. A user interface module can be provided and can be configured to display an output indicative of health of the baby in utero.

A method of estimating fetal electrocardiogram (FECG) signals utilizes a plurality of ECG signals measured along the mother's abdomen. The method includes defining an MECG (ECG) dictionary of symbols and projecting the plurality of abdominal ECG signals onto the MECG dictionary to estimate MECG signals within each of the plurality of abdominal ECG signals. The estimated MECG signals are subtracted from the plurality of measured abdominal ECG signals to estimate FECG signals and the plurality of estimated FECG signals are combined to generate a representation of the FECG source signal.

Wearable fetal health monitoring device for determining a heath condition of a fetus based on biosignals of an expecting mother and the fetus is provided. The device includes a MEMS accelerometer that converts an acoustic wave sensed in an abdominal region into an abdominal acoustic signal. The device also includes a pulse oximeter generates a maternal photoplethysmogram (mPPG) value from a pulse sensed in the abdominal region. The device further includes a microcontroller configured to: generate a maternal phonocardiogram (mPCG) value from the abdominal acoustic signal; calculate a first maternal heart rate (mHR) value from the mPCG value; calculate a second mHR value from the mPPG value; compare the first mHR value with the second mHR value to identify a noise correction value; and apply the identified noise correction value to the mPCG value to extract a fetal phonocardiogram (fPCG) value.

The disclosure describes techniques for predicting maternal and/or fetal health outcomes based on maternal and/or fetal patient data. The patient data may include, for example, data regarding sensed biopotential signals such as maternal and/or fetal electrocardiography (ECG) signals, maternal and/or fetal electromyography (EMG) signals, and/or other biopotential signals. The patient data may further include maternal and/or fetal biometric data and/or health assessment data. The system determines, based on processing the patient data using a machine learning model trained with historical patient data for a plurality of patients, one or more predicted outcomes associated with the patient.

The present invention relates to a pregnancy monitoring system, the system comprising a fetal monitoring transducer (20) arranged to detect fetal medical condition information; and a control device (48) comprising a motion assessment unit (50) and a signal output unit (52); wherein the fetal monitoring transducer (20) is arranged to detect fetal movement indicative information, wherein the motion assessment unit (50) is arranged to process fetal movement grading information, in addition to the fetal movement indicative information, wherein the signal output unit (52) is arranged to simultaneously output a fetal condition signal, particularly a fetal heart rate signal, and an augmented fetal movement signal based on the fetal movement indicative information and the fetal movement grading information, wherein a characteristic property of the original fetal movement information is still present in the augmented fetal movement signal. The disclosure further relates to a corresponding pregnancy monitoring method.

A system for providing health services to a pregnant woman away from a medical facility is provided. The system may be configured to include first and second wearable devices to be worn by the pregnant woman. The first wearable device may be configured to collect a first set of health data of the pregnant woman and the second wearable device may be configured to collect a second set of health data of an unborn baby growing in the pregnant woman. Further, the system may be configured to include a mobile device configured to: communicate with the first and second wearable devices; collect the health data of the pregnant woman and her unborn baby; and communicate with a remote hospital personnel via one or more servers over a cloud-based network. The mobile device may be further configured to receive guidance or instructions from the remote hospital personnel in response to transmission of the health data of the pregnant woman and her unborn baby.

Devices and techniques for magnetic detection of myocardial forces are generally described. In some examples, cardiac tissue may be cultured such that the cardiac tissue adheres to a first post and a second post. In further examples, a magnetometer may detect a change in a magnetic field resulting from a deflection of the first post in a first direction from a first position to a second position. In some other examples a signal corresponding to the change in the magnetic field may be generated. In still other examples, frequencies of the signal outside of a first frequency range may be excluded to produce a filtered signal. In various examples, the first frequency range may include frequencies associated with beating of cardiac tissue. In still further examples, a force exerted by the cardiac tissue may be determined based at least in part on the filtered signal.