Systems, devices, and methods utilizing bio-potential data obtained by a plurality of bio-potential sensors for prenatal tracking
A method includes receiving an input data set for an expectant mother during a time window, the input data set including fetal heart rate data; completing the input data set with a missing data sample to produce a completed data set; removing a segment from the completed data set based a criterion to produce a corrected data set; calculating a baseline fetal heart rate based on the corrected data set; detecting an event occurring during the time window based on the corrected data set and/or the baseline fetal heart rate; classifying the event as either an acceleration, a deceleration, or a baseline change based on the corrected data set and/or the baseline fetal heart rate; and generating an output indicative of the event to enable an action with respect to the expectant mother.
1. A computer-implemented method, comprising:
receiving, by a computing device comprising a communication circuitry, a raw bio-potential data set from a plurality of bio-potential sensors disposed within a garment worn by an expectant mother during a fetal heart rate (FHR) session,
wherein the garment is configured to position and contact the plurality of bio-potential sensors on skin of an abdomen of the expectant mother, and
wherein the plurality of bio-potential sensors are configured to detect cardiac electrical activity and to output the raw bio-potential data,
calculating, by the computing device, fetal heart rate data based at least on the raw bio-potential data set,
generating, by the computing device, data set for the expectant mother during a time window,
wherein the input data set comprises at least the fetal heart rate data;
completing, by the computing device, the input data set with at least one missing data sample to provide a completed data set;
removing, by the computing device, at least one segment from the completed data set based on at least one criterion to provide a corrected data set;
calculating, by the computing device, a baseline fetal heart rate based at least on the corrected data set;
detecting, by the computing device, at least one event occurring during the time window based at least on at least one of the corrected data set or the baseline fetal heart rate;
classifying, by the computing device, the at least one event as either an acceleration, a deceleration, or a baseline change based at least on at least one of the corrected data set or the baseline fetal heart rate; and
classifying, by the computing device, the FHR session as reactive based on a determination that at least two accelerations were detected during the FHR session; and
generating, by the computing device, an FHR session output indicative of the classification of the FHR session as reactive; and
transmitting, by the computing device, via the communication circuitry, an instruction to display on a graphical interface associated with the user, the FHR session output to enable at least one action being taken with respect to the expectant mother.
2. The method of claim 1 , wherein the at least one criterion for the step of removing the at least one segment from the completed data set comprises removing the at least one segment based on the at least one segment including a periodic change in the fetal heart rate.
3. The method of claim 2 , wherein the periodic change in the fetal heart rate includes at least one of (a) the fetal heart rate varying by more than 25 beats per minute in consecutive samples or (b) applying a threshold based on median and standard deviation.
4. The method of claim 1 , further comprising:
determining, by the computing device, whether the input data set is valid or is not valid; and
if the input data set is determined to be not valid, receiving a further input data set prior to the step of performing the completing, by the computing device, the input data set, wherein the step of completing, by the computing device, the input data set is performed on the further input data set.
5. The method of claim 4 , wherein the step of determining whether the input data set is valid or is not valid is performed by a process comprising:
identifying, by the computing device, plurality of stable segments of the corrected data set,
wherein each stable segment comprises a sequence of a predetermined quantity of consecutive samples having a fetal heart rate variability that is less than a predetermined threshold variability;
determining, by the computing device, a total duration of the plurality of stable segments; and
determining, by the computing device, whether the input data set is valid or is not valid based at least on a comparison of the total duration of the plurality of stable segments to a predetermined threshold duration.
6. The method of claim 1 , wherein the step of determining, by the computing device, the baseline fetal heart rate is performed by a process comprising:
calculating, by the computing device, a virtual baseline fetal heart rate;
calculating, by the computing device, a virtual high fetal heart rate limit;
calculating, by the computing device, a virtual low fetal heart rate limit;
removing, by the computing device, outlier data points from the corrected data set, wherein outlier data points are data points having a fetal heart rate higher than the virtual high fetal heart rate limit or having a fetal heart rate lower than the virtual low fetal heart rate limit; and
calculating, by the computing device, the baseline fetal heart rate based at least on applying rounding to the corrected data set following removing the outlier data points.
7. The method of claim 6 , wherein the virtual baseline fetal heart rate is a mean average of fetal heart rates in the corrected data set.
8. The method of claim 6 , wherein the steps of calculating the virtual high fetal heart rate limit and calculating the virtual low fetal heart rate limit are performed by a process comprising:
calculating, by the computing device, a standard deviation for the virtual baseline fetal heart rate;
calculating, by the computing device, the virtual high fetal heart rate limit as the virtual baseline fetal heart rate plus two times the standard deviation; and
calculating, by the computing device, the virtual low fetal heart rate limit as the virtual baseline fetal heart rate minus two times the standard deviation.
9. The method of claim 1 , wherein at least one of the at least one event is classified as an acceleration, and wherein the at least one of the at least one event is classified as an acceleration based on a process comprising:
identifying, by the computing device, a first intersection between a trace of the corrected data set and the baseline fetal heart rate;
identifying, by the computing device, a second intersection between the trace of the corrected data set and the baseline fetal heart rate;
identifying, by the computing device, a maximum fetal heart rate during a time interval between the first intersection and the second intersection; and
identifying, by the computing device, the time interval as including the acceleration based at least on a duration of the time interval and the maximum fetal heart rate during the time interval.
10. The method of claim 9 , wherein the step of identifying the time interval as including the acceleration is further based on a gestational week of the expectant mother.
11. The method of claim 9 , further comprising:
determining, by the computing device, fetal heart rate baseline variability.
12. The method of claim 11 , wherein the step of determining, by the computing device, the fetal heart rate baseline variability is performed by a process comprising:
determining, by the computing device, a highest fetal heart rate during a variability time interval following the second intersection,
wherein the variability time interval extends from the second intersection until a sooner of (1) a predetermined duration following the second intersection or (2) onset of a subsequent acceleration or deceleration;
determining, by the computing device, a lowest fetal heart rate during the variability time interval; and
subtracting, by the computing device, the lowest fetal heart rate during the variability time interval from the highest fetal heart rate during the variability time interval to provide the fetal heart rate baseline variability.
13. The method of claim 1 , wherein the at least one event comprises a deceleration, and wherein the at least one event is classified as a deceleration based on a process comprising:
identifying, by the computing device, a first intersection between a trace of the corrected data set and the baseline fetal heart rate;
identifying, by the computing device, a second intersection between the trace of the corrected data set and the baseline fetal heart rate;
identifying, by the computing device, a minimum fetal heart rate during a time interval between the first intersection and the second intersection; and
identifying, by the computing device, the time interval as including the deceleration based at least on a difference between the baseline fetal heart rate and the minimum fetal heart rate during the time interval.
14. The method of claim 13 , further comprising:
classifying, by the computing device, the deceleration as one of an early deceleration, a late deceleration, a variable deceleration, or a prolonged deceleration.
15. The method of claim 14 , wherein the input data set further comprises a uterine contraction signal, and wherein the deceleration is classified as the one of the early deceleration, the late deceleration, the variable deceleration, or the prolonged deceleration based on a process comprising:
determining, by the computing device, a delay, wherein the delay is an amount of elapsed time between the first intersection and a time of the minimum fetal heart rate during the time interval;
determining, by the computing device, a time of a peak of a uterine contraction during the time interval;
determining, by the computing device, a time difference between the time of the minimum fetal heart rate during the time interval and the time of the peak of the uterine contraction signal during the time interval; and
classifying, by the computing device, the deceleration as the one of the early deceleration, the late deceleration, the variable deceleration, or the prolonged deceleration based at least on the delay, the time difference, and a duration of the uterine contraction.
16. The method of claim 1 , wherein two iterations of the steps of (1) removing, by the computing device, at least one segment from the completed data set based on at least one criterion to provide a corrected data set, (2) calculating, by the computing device, a baseline fetal heart rate based at least on the corrected data set, and (3) detecting, by the computing device, at least one event occurring during the time window based at least on at least one of the corrected data set or the baseline fetal heart rate, are performed for the time window.
17. The method of claim 1 , further comprising repeating, for a subsequent time window, the steps of:
receiving, by the computing device, data set for the expectant mother;
completing, by the computing device, the input data set with at least one missing data sample to provide a completed data set;
removing, by the computing device, at least one segment from the completed data set based on at least one criterion to provide a corrected data set;
calculating, by the computing device, a baseline fetal heart rate based at least on the corrected data set;
detecting, by the computing device, at least one event occurring during the time window based at least on at least one of the corrected data set or the baseline fetal heart rate; and
classifying, by the computing device, the at least one event as either an acceleration, a deceleration, or a baseline change based at least on at least one of the corrected data set or the baseline fetal heart rate.
18. The method of claim 17 , wherein the subsequent time window does not overlap the time window.
19. The method of claim 17 , wherein the subsequent time window overlaps the time window by an overlap duration.
20. The method of claim 19 , wherein the overlap duration is between 5% of a duration of the time window and 95% of the duration of the time window.