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.

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.

The instant invention is a medical electrode comprising: an electrolyte; an absorbent material being in contact with the electrolyte, said absorbent material comprising a plurality of strands such that each strand is infused with the electrolyte; a pressing means being in contact with the absorbent material, said pressing means comprising a plurality of protrusions to push the strands of the absorbent material through the stratum corneum of a target skin area on a patient; and an electrically conductive means located adjacent to the pressing means, said electrically conductive means being in contact with the absorbent material. The instant medical electrode system achieves reduction of skin impedance at the site where the electrode is placed and generates low baseline noise, enabling accurate measurement of small or weak signals (FIG. 1).

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.

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.

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.

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)

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)