SYSTEMS, APPARATUSES AND METHODS FOR SENSING FETAL ACTIVITY
A method includes receiving a plurality of raw PCG data inputs; applying at least one binary classification technique to each of the raw PCG data inputs to generate a respective plurality of filtered PCG data inputs; applying at least one divide-and-conquer algorithm to detect heartbeat compartments in each of the plurality of the filtered PCG data inputs based, at least on part, on assumptions that noise signals and S1-S2 alternation acoustic signals are non-stationary over a one-minute time interval; classifying each compartment of the heartbeat compartments in each of the plurality of the filtered PCG data input as a maternal compartment or a fetal compartment based at least on a plurality of referenced maternal QRS positions; combining a plurality of maternal compartments to identify at least one actual maternal heartbeat; combining a plurality of fetal compartments to identify at least one actual fetal heartbeat.
1 . A computer-implemented method, comprising:
receiving, by at least one computer processor executing specific programmable instructions configured for the method, a plurality of raw phonocardiogram (PCG) data inputs, each of the plurality of raw PCG data inputs being received from a corresponding one of a plurality of acoustic sensors:
applying, by the at least one computer processor, at least one binary classification technique to each of the plurality of raw PCG data inputs signals to generate a respective plurality of filtered PCG data inputs, by filtering each respective raw PCG data input based, at least in part, on one or more of:
i) a root-mean-square (RMS) value of each respective raw PCG data input,
ii) a RMS value of a first derivative of each respective raw PCG data input,
iii) a variance value of each respective raw PCG data input, and
iv) any combination thereof:
applying, by the at least one computer processor, at least one divide-and-conquer (Div-Conq) algorithm to detect heartbeat compartments in each of the plurality of the filtered PCG data inputs based, at least on part, on assumptions that noise signals are non-stationary over a one-minute time interval and that S1-S2 alternation acoustic signals are non-stationary over the one-minute time interval;
classifying each compartment of the heartbeat compartments in each of the plurality of the filtered PCG data input as a maternal compartment or a fetal compartment based at least on a plurality of referenced maternal QRS positions;
combining a plurality of maternal compartments to identify at least one actual maternal heartbeat;
combining a plurality of fetal compartments to identify at least one actual fetal heartbeat; and
outputting at least one visual indication corresponding to at least one of (a) the at least one actual maternal heartbeat and (b) the at least one actual fetal heartbeat.
2 . The method of claim 1 , wherein the Div-Conq algorithm includes at least the steps of:
i) filtering each of the pre-processed PCG signals using at least one digital filter to generate a plurality of filtered PCG signals, each of the plurality of the filtered PCG signals being generated based on a corresponding one of the pre-processed PCG signals;
ii) segmenting each of the filtered PCG signals into PCG signal segments having a predetermined length;
iii) detecting compartments in the PCG signal segments, wherein the step of detecting compartments comprises the sub-steps of:
a) identifying related beats;
b) shifting each beat, related to the beat with the mean RMS energy;
c) finding sub-compartments of each beat; and
d) linking sub-compartments from different beats using dynamic programming to generate an indication of a heartbeat.
3 . The method of claim 2 , wherein the predetermined length is 10 seconds.
4 . The method of claim 2 , wherein the compartments include at least one S1, at least one S2, or at least one S1 and at least one S2.
5 . The method of claim 1 , wherein the compartments include at least one of a fetal heartbeat, a maternal heartbeat, and/or both a maternal heartbeat and a fetal heartbeat.
6 . The method of claim 1 , wherein the at least one digital filter includes a complex Hilbert transform filter.
7 . The method of claim 2 , wherein if more than one group of compartments have been detected, the Div-Conq algorithm further comprises testing the groups of compartments.
8 . The method of claim 7 , wherein the step of testing the groups of compartments includes a mean absolute deviation process.
9 . The method of claim 1 , wherein the step of detecting compartments in the PCG signal segments further comprises the sub-step of dissecting compartments into sub-compartments.
10 . The method of claim 9 , wherein the dissecting compartments into sub-compartments comprises:
a) defining a global reference frame;
b) aligning sub-compartments; and
c) applying a predetermined scoring schema to exclude unacceptable sub-compartments.
11 . The method of claim 10 , wherein the defining a global reference frame is based on mQRS positions.
12 . The method of claim 10 , wherein the defining a global reference frame is based on a best sub-compartment.
13 . The method of claim 12 , wherein the best sub-compartment is identified by a pre-determined scoring.
14 . The method of claim 10 , wherein the unacceptable compartments are identified as compartments having a mean absolute deviation that is greater than a mean absolute deviation threshold.
15 . The method of claim 14 , wherein the mean absolute deviation threshold is 50.
16 . The method of claim 1 , wherein the step of detecting compartments is performed using a binary SVM classifier.