A technology for detecting fetal movement. In one example an electrocardiogram (ECG) dataset can be obtained where the ECG dataset contains fetal heart rate (FHR) values acquired from a pregnant subject, and the ECG dataset is for a segment of time during which an FHR is monitored using an ECG monitor. An FHR baseline can be calculated for the FHR values in the ECG dataset, and the ECG dataset can be analyzed to identify an accelerated FHR value that exceeds the FHR baseline that is followed in time in the ECG dataset by a decelerated FHR value that is less than or equal to the FHR baseline. Identifying the accelerated FHR value followed in time in the ECG dataset by the decelerated FHR value in the ECG dataset may indicate a fetal movement.

The present invention relates to an ECG monitor device including a removable electrode pad and a monitor element configured for use with a single lead that receives and processes information associated with a plurality of leads.

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.

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.

An electrode sheet is flexibly adapted to the position where a signal is acquired. The electrode sheet is attached to a living body and acquires a biological signal, and is provided with a sheet-form biological signal acquisition unit, which is attached to a living body part where a biological signal is acquired. A reference potential acquisition unit extends from the living body signal acquisition unit and is attached to a living body part where a reference potential is acquired. The reference potential acquisition unit is provided with multiple electrodes, which are arranged at a prescribed interval along the direction of extension. Each of the electrodes can attach to the living body part where the reference potential is acquired.

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.

A method includes receiving acoustic inputs; generating signal channels from the acoustic inputs; pre-processing data in the signal channels; extracting S1-S2 peaks from the pre-processed data; removing artifacts and outliers from the S1-S2 peaks; generating S1-S2 signal channels based on the S1-S2 peaks in the pre-processed signal channels; selecting two or more of the S1-S2 signal channels; and combining the selected two or more S1-S2 signal channels to produce an acoustic uterine monitoring signal.

Systems and methods are provided for enhanced heart medical imaging operations, particularly as by incorporating use of artificial intelligence (AI) based fetal heart functional analysis and/or real-time and automatic ejection fraction (EF) measurement and analysis.

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.

Provided are a fetal electrocardiographic signal processing method and a fetal electrocardiographic signal processing device that can appropriately select a signal reliably including a fetal electrocardiographic component from a plurality of signals separated by independent component analysis with reference. The fetal electrocardiographic signal processing method according to the invention includes: a fetal feature display signal extraction step of separating separation signals for a plurality of channels from biological signals of the plurality of channels acquired from a pregnant mother, using independent component analysis with reference, and removing noise from the separation signal for each channel to extract a fetal feature display signal; and a maternal electrocardiographic signal removal step of removing the fetal feature display signal at a timing when an electrocardiographic signal of the mother is likely to appear from the fetal feature display signals to obtain fetal feature signals including a large number of fetal electrocardiographic signals.