This invention provides a fully automatic method and a system for detecting and classifying cardiac arrhythmias from a surface ECG record. The method defines four relevant parameters whose values are extracted from said ECG record. Clinically relevant conclusions are assigned to various combinations of the obtained values of said parameters. The method can be employed for detecting fetal QRS complexes from abdomen ECG of a pregnant woman.

An improved fetal ST monitoring system and method is provided using an ECG monitoring system collecting a plurality of T/QRS segments of a fetus, and a data analysis computer system connected to the ECG monitoring system calculating from the plurality of T/QRS segments.

An apparatus for measuring biopotential signals comprises a plurality of electrodes embedded or affixed to a wearable worn about the torso of a pregnant subject, enabling the non-invasive acquisition of electrocardiographic signals and the extraction of separate fetal and maternal electrocardiographic signals therefrom. The wearable is stretchable or adjustable to accommodate any maternal body habitus and can advantageously employ dry physiologic electrodes to eliminate the step of skin preparation and provide longer-term monitoring that is also both more convenient and more comfortable.

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.

Methods and systems for evaluating the electrical activity of the heart to identify novel ECG patterns closely linked to the subsequent development of serious heart rhythm disturbances and fatal cardiac events. Two approaches are describe, for example a model-based analysis and space-time analysis, which are used to study the dynamical and geometrical properties of the ECG data. In the first a model is derived using a modified Matching Pursuit (MMP) algorithm. Various metrics and subspaces are extracted to characterize the risk for serious heart rhythm disturbances, sudden cardiac death, other modes of death, and all-cause mortality linked to different electrical abnormalities of the heart. In the second method, space-time domain is divided into a number of regions (e.g., 12 regions), the density of the ECG signal is computed in each region and input to a learning algorithm to associate them with these events.

A living body state estimation apparatus acquires information indicating a state of a living body. The living body state estimation apparatus is configured to include an electrocardiogram signal acquisition unit which acquires an electrocardiogram signal of the living body and an information acquisition unit which acquires a parameter as the information, the parameter specifying a predetermined function indicating a probability distribution for a reference wave interval which is a time interval between peaks of consecutive predetermined reference waves in the acquired electrocardiogram signal.

A fetal state estimation apparatus estimates a state of a fetus in a maternal body based on a potential signal indicating a change in potential on a surface of the maternal body. The fetal state estimation apparatus is configured to include a rotation angle estimation unit which estimates a rotation angle of the fetus with respect to the maternal body at every beating of a heart of the fetus based on the potential signal and a fetal movement estimation unit which estimates a fetal movement which is a movement of the fetus based on the potential signal and the estimated rotation angle.

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.