Final Report Summary - PRENATAL DIAGNOSIS (Prenatal diagnosis - indices of fetal developmental disturbances enabled by advanced signal identification techniques)
In the present project we applied innovative developments of advanced signal separation and identification methods in order to improve the identification of fetal heart beats and fetal auditory evoked cortical responses from biomagnetic recordings. Additionally, we explored simultaneously behavioural state dependent heart rate patterns, fetal heart rate variability indices and reliable fetal auditory evoked response indices. The developed methods were evaluated using different clinical biomagnetic measurements from a comprehensive clinical database.
The novel signal processing framework developed in the present project enables the detection of the fetal auditory evoked responses in low signal-to-noise ratio conditions. To achieve this, we combined different approaches that address data cleaning, response determination and statistical validation. Our novel processing framework provides an objective way to identify and eliminate non-physiological variation in the data induced by artifacts. We observed a consistent decrease in the latencies of the auditory evoked potentials with the increase of gestational age.
Part of the algorithms used for extracting the fetal auditory evoked responses was used also for an accurate fetal heart beat detection. This enabled the extraction of linear and nonlinear parameters of fetal heart rate variability.
Fetal programming of mental and cardiovascular diseases by adverse prenatal environmental influences is a main issue of developmental medicine.
The assessment of key parameters with respect to the underlying processes of fetal brain maturation or autonomic nervous system disturbances could foster the early detection of developmental problems and hence the design of therapeutic strategies and save immense cost for public health. However, due to the technical limitations in fetal monitoring, this aspect was not sufficiently addressed in the literature. This project addressed unsolved problems in the field bringing an important contribution in filling this gap in the prenatal diagnostic.
The novel signal processing framework developed in the present project enables the detection of the fetal auditory evoked responses in low signal-to-noise ratio conditions. To achieve this, we combined different approaches that address data cleaning, response determination and statistical validation. Our novel processing framework provides an objective way to identify and eliminate non-physiological variation in the data induced by artifacts. We observed a consistent decrease in the latencies of the auditory evoked potentials with the increase of gestational age.
Part of the algorithms used for extracting the fetal auditory evoked responses was used also for an accurate fetal heart beat detection. This enabled the extraction of linear and nonlinear parameters of fetal heart rate variability.
Fetal programming of mental and cardiovascular diseases by adverse prenatal environmental influences is a main issue of developmental medicine.
The assessment of key parameters with respect to the underlying processes of fetal brain maturation or autonomic nervous system disturbances could foster the early detection of developmental problems and hence the design of therapeutic strategies and save immense cost for public health. However, due to the technical limitations in fetal monitoring, this aspect was not sufficiently addressed in the literature. This project addressed unsolved problems in the field bringing an important contribution in filling this gap in the prenatal diagnostic.