The Cochleopalpebral reflex test is an electroacoustic transducer that emits a harmless sound stimulus that induces the cochlea palpebral reflex and the subsequent variation in the heart rate of the fetus that is detected as described in the prior paragraph. The Cochleopalpebral reflex test consists of a housing, a transducer, an amplifier, and a signal source. The transducer and amplifier are contained within the housing. The signal source is an externally generated electrical signal of a previously determined frequency. The previously determined frequency is in the audible range of humans. The electrical signal of a previously determined frequency is amplified by the amplifier and is converted into acoustic energy and introduced to the fetus through the transducer.

Methods and system are described for multi-parametric, non-invasive, and real-time assessment of blood perfusion and oxygenation in the fetal brain during labor and delivery of a fetus through a vaginal birth canal of a maternal pelvis, and include positioning a probe device in the maternal pelvis during active labor, transmitting and receiving a plurality of ultrasound (US) and photoacoustic (PA) signals between the probe device and fetal brain, displaying in real-time on an US machine communicatively coupled to the probe device one or more images of venous and arterial blood flow of respective blood vessels in the fetal brain, measuring oxygen saturation of the respective venous and arterial blood vessels based on data from the one or more images, and estimating the oxygen measurement in the fetal brain during active labor based on the measured oxygen saturation.

An electrode sheet is provided which can be flexibly adapted to the position where a signal is acquired. This electrode sheet 1, which is attached to a living body M and acquires a biological signal, is provided with a sheet-form biological signal acquisition unit 10 which is attached to a living body part where a biological signal is acquired, and a reference potential acquisition unit 20 which extends from the living body signal acquisition unit and which is attached to a living body part where a reference potential is acquired, wherein the reference potential acquisition unit 20 is provided with multiple electrodes 23 which are arranged at a prescribed interval along the direction of extension and each of which can attach to the living body part where the reference potential is acquired.

A seamless, smart fetal monitoring garment and methods of using thereof. The system includes a knitted or interwoven garment having a multiplicity of conductive textile electrodes for sensing maternal and fetal electrical vital signals. The maternal and fetal electrical vital signals are selected from a group including maternal heart rate, fetal heart rate and electromyogram (EMG) activities including uterine activities. The method includes wearing the garment, acquiring electrical mixed common, maternal and fetal vital signals from surface region of a pregnant woman, using the plurality of textile electrodes, optimally weighted summing-up the acquired signals, analyzing the summed-up signals to thereby extract the maternal signal and the fetal signal, including determining their heart rates, and including detecting health hazards and in some embodiments, including detecting a uterine contraction sequence suggesting the need to be hospitalized for birth giving.

Systems and methods for monitoring uterus contraction activity and progress of labor. The system of the subject invention can comprises (1) a plurality of sensors; (2) an amplifying/filtering means; (3) a computing means; and (4) a graphical user interface. Accurate clinical data, which can be extracted and provided to the user in real-time using the system of the invention, include without limitation, progress of labor, prediction and monitoring of preterm labor, and intrauterine pressure prediction. In a preferred embodiment, the system of the invention includes an intelligence means, such as a neural network system, to analyze and interpret clinical data for use in clinical diagnosis as well as delivery strategy.

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.

A system for treating livestock may include a ramp for containing dairy livestock and one or more mobile units configured to travel on the ramp, below the dairy livestock, and milk the dairy livestock. A mobile unit may be adapted to travel to a predefined location within a stall, and attach a milking equipment unit to the dairy livestock in the stall. A plurality of mobile units and a central management unit may be configured to dynamically cause at least some of the plurality of mobile units to each perform a portion of a treatment or task.

A risk stratification method for a patient in a disease state and specifically patients presenting a tumor, includes determining if the patient is a homozygote or heterozygote and further determining the allelic expression for the patient, CC, T/C, or C/T. For patients having the cytosine methylated, they have a T/C allelic expression and patients without a methylated cytosine have a C/T allelic expression. A patient with a TT allelic expression is classified as a highest risk patient, a patient with a T/C allelic expression is classified as a second highest risk patient, a patient with a C/T allelic expression is classified as a third highest risk patients and a patient with a CC allelic expression is classified as a lowest risk patient. The risk stratification method may further include identification of an abnormal expression or mutation/function of a gene product produced by CTCF biding site 6.

A computer-implemented method includes providing, by at least one computer processor, a plurality of signal channels, wherein the plurality of signal channels includes a plurality of electrical uterine monitoring signal channels and a plurality of acoustic uterine monitoring signal channels; determining, by the at least one computer processor, a plurality of channel weights, wherein each of the channel weights corresponds to a particular one of the signal channels; and generating, by the at least one computer processor, a combined uterine monitoring signal channel by calculating a weighted average of the signal channels based on the channel weight for each of the signal channels.

The present invention discloses a virtual reality embryo image providing system. More specifically, the present invention relates to a deep learning-based embryo image providing system which extracts facial features of an embryo from an ultrasound image on the basis of a deep learning technique, generates a 3D model corresponding to the ultrasound image reflecting the facial features, and provides a virtual reality image using the 3D model. According to an embodiment of the present invention, the figure of an embryo can be displayed three-dimensionally through an HMD or the like by setting a plurality of codewords reflecting the features of each body part for a 2D embryo image, and performing a learning procedure on the basis of the codewords according to a deep learning model to provide a 3D model generated by combining the body components that are most similar to the actual face of the embryo. Therefore, a differentiated and realistic embryo imaging service can be provided to a pregnant person.