A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

Figures

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  Figure 1. Sample recordings of electrocardiogram (ECG) and phonocardiography (PCG) signals.

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  Figure 2. Noninvasive interferometric measurement probe.

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  Figure 3. Basic schematic diagram for our noninvasive PPG-based interferometric sensors and adaptive system for fHR monitoring.

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  Figure 4. Normalized Power Spectrum Density of data acquired from the test subject.

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  Figure 5. Basic scheme of an adaptive N-th order FIR filter with transversal structure and the LMS Algorithm.

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  Figure 6. Sample plots of real raw data acquired from the thoracic and abdominal sensors of two different test subjects. (a) volunteer No. 1; (b) volunteer No. 2.

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  Figure 7. Modelled raw signal measured by IST in the abdominal region (mRR ∈ <12–16> rpm; mHR ∈ <65–85> bpm). (Left) 60 s; (Right) detail in the form of 2.3 s.

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  Figure 8. Modelled raw signal represented by ISA in the abdominal region (mRR ∈ <12–16> rpm; mHR ∈ <65–85> bpm, fHR ∈ <80–155> bpm, GA = 35 weeks, orientation of fetus: Right Occiput Posterior (ROP)). (Left) 60 s; (Right) detail in the form of 2.3 ss.

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  Figure 9. Recording of a reference signal for the adaptive system represented by IST in the thoracic region.

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  Figure 10. Input signal of the adaptive system formed by a mixture of maternal heart rate (mHR) and fetal heart rate (fHR).

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  Figure 11. Output of the adaptive system when using (a) the Least Mean Square Algorithm (LMS) and (b) the Normalized Least Mean Square (NLMS) Algorithms.

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  Figure 12. Modelled reference (ideal) signal represented by ISA in the abdominal region without a maternal component (fHR ∈ <80–155> bpm, GA = 35 weeks, fetus position: Right Occiput Posterior (ROP)).