A passive DSP approach to fetal movement detection for monitoring fetal health

Abstract

Fetal movement can help clinicians understand fetal functional development. Active methods for fetal monitoring such as ultrasound are expensive and there are objections to their long term usage. This paper presents a passive approach for fetal monitoring which uses solid state accelerometers placed on the mother's abdomen for the collection of fetal movements.The proposed fetal movement detection is based on the root-mean-square (RMS) of time series. The detection performance is evaluated against real-time ultrasound imaging. A good detection rate of 80% and a positive predictive value of 77% were achieved based on the analysis of 4 subjects.Time-frequency (TF) analysis of fetal movement signals, using a number of quadratic TF distributions, has shown that some fetal movements are spectrally characterized by nonstationary and nonlinear behavior and that fetal activity is generally below 20 Hz. More data are needed for further TF analysis and future detections will depend on the outcome of this analysis.

Non-Contact Monitoring of Fetal Movement Using Abdominal Video Recording

“…The FM interval was defined as the elapsed time between two adjacent FMs. The FM duration referred to the time interval between two adjacent spikes less than 6 s [ 34 , 35 , 36 ]. The FM percentage was the total FM duration as a percentage of the recording time.…”

A Wearable System for In-Home and Long-Term Assessment of Fetal Movement

“…In recent years, with the advancement of microelectronic technology as well as the development in signal processing, automatic detection of fetal movements by using accelerometers and advanced signal processing technologies has gained a lot of attention [9,10,11,12,13,14,15,16,17,18,19]. When contacted with the maternal abdominal wall, a movement of fetal body parts with sufficient force generates vibrations that could be detected by one or a set of accelerometers placed on the surface of the abdomen.…”

“…For automatic fetal movement monitoring based on accelerometer-recorded signals, some studies utilized threshold-based algorithms [15,16,17,18], under the prerequisite that the mother keeps quiet throughout the measurement so that fetal movement signals are identifiable against ongoing low amplitude background noise. However, this approach may not reach a decent performance since it is highly sensitive to noises.…”

“…In some other studies feature extraction was applied on the original acceleration signals to obtain information that was not readily available in the raw data. The concerned methods include statistical features in time domain [18] and time-frequency features [10,16,17,19]. Then, based on the extracted features, signal classification was performed to identify fetal movement signals from other signals.…”