LULLABY ALGORITHM - FETAL PEAK DETECTION USING PERIODICITY

    公开(公告)号:US20230363687A1

    公开(公告)日:2023-11-16

    申请号:US18198200

    申请日:2023-05-16

    CPC classification number: A61B5/344 A61B5/352 A61B5/725

    Abstract: A computer-implemented method for detecting fetal peaks in a maternal ECG signal includes steps of receiving the maternal ECG signal and preprocessing the maternal ECG signal wherein preprocessing includes removal of mECG R-peaks to form a process ECG signal that includes both fetal and noise peaks. Both fetal and noise peaks are detected using a peak detection algorithm which yields an array of peaks Xk×1. Permutations of all peak differences are calculated by subtracting elements of Xk×1 from its transpose Xk×1T to form a matrix Mk×k. Characteristically, elements in the matrix Mk×k corresponds to different sample periods that are used to determine peak positions. An array of periods denoted an array LP×1 is calculated. A 3-dimensional matrix GP×k×k is constructed by dividing Mk×k by each element of LP×1. An optimal Mk×k is determined by finding the Mk×k in the 3-dimensional matrix GP×k×k that has it's first row with the most elements near a whole number.

    SYSTEM AND METHOD FOR OPTIMAL SENSOR PLACEMENT AND SIGNAL QUALITY FOR MONITORING MATERNAL AND FETAL ACTIVITIES

    公开(公告)号:US20230218219A1

    公开(公告)日:2023-07-13

    申请号:US17928864

    申请日:2021-06-04

    CPC classification number: A61B5/282 A61B5/344 A61B5/6833 A61B2562/166

    Abstract: 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.

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