Is it possible to monitor fetal movements with a wearable device? A review of novel technologies

Stillbirth is often preceded by reduced fetal movements and obstetric intervention is necessitated for stillbirth prevention. Yet, despite fetal movements being one of the few tangible ways a pregnant woman and the clinical team can assess the wellbeing of her baby, there are few validated, objective means for pregnant women to quantify the frequency and nature of an unborn baby's movements. Traditional methods of assessing fetal wellbeing such as cardiotocography and fetal movement charts have a lack of diagnostic accuracy, and often lead to false positive intervention. The need for fetal movement counting has led to the development of objective methods to attempt to quantify movements. Some are based on electrocardiography, others on the principles of accelerometery, phonography and optical fibre technology. This review paper not only explores these technologies and evaluates the state-of the-art fetal movement monitoring, but explains the engineering principles underpinning the various technologies, and explores the importance and practice of fetal movement monitoring. To this end, we conclude that there is still a need for the continued development of innovations which will enable a pregnant woman to carry out everyday activities, whilst confident in the knowledge that her unborn child's wellbeing is being accurately monitored, and that feedback from the monitoring device is readily accessible to her.

Timing the opening and closure of the aortic valve using a phonocardiogram envelope: a performance test for systolic time intervals measurement

OBJECTIVE

This work explored the reliability of using points on the heart sounds envelope as indicators of the opening and closure of the aortic valve (AVO, AVC) to measure the pre-ejection period (PEP) and the left ventricular ejection time (LVET).

APPROACH

36 phonocardiograms (PCGs) from healthy subjects and cardiovascular disease subjects were denoised using single-channel independent component analysis (SCICA) and, from the Hilbert envelopes, the positions of the S1 and S2 peaks were detected (pS1, pS2). Complementarily, the positions of the local maxima of S1 and S2 (mS1, mS2) and the points surrounding pS1 and pS2 (tS1, tS2) were obtained. Finally, the reliability of these points (and the corresponding PEP and LVET intervals) was evaluated by the calculation of three error indexes (ePEP, eLVET, and score) and by comparison to reference annotations provided by echocardiography using the Bland-Altman analysis and the paired T-test.

MAIN RESULTS

The results indicated that, from a total of 920 and 341 heartbeats in the healthy and diseased groups, respectively, the timing points given by pS1 and pS2 (or mS1 and mS2) were unlikely to substitute for the reference annotations and, thus, are unreliable for measuring the PEP and LVET intervals in the PCG. The t-points evaluation, on the other hand, indicated that tS1 was likely to substitute for AVO and was thus reliable for measuring the PEP using the PCG, with median and interquartile ranges of 0.3(8.3) ms and -0.2(7.5) ms for each group. Future work will generate an envelope with higher temporal resolution, from where tS1 and tS2 can be more accurately detected to improve the PEP and LVET measurements on a larger dataset.

SIGNIFICANCE

The statistical tests revealed that the envelope of S1 is suitable for extracting a timing point from which the pre-ejection interval can be reliably quantified, and discarded the local maximum used in other studies.

Source separation from single-channel abdominal phonocardiographic signals based on independent component analysis

Purpose: Continuous monitoring of fetal heart rate (FHR) is essential to diagnose heart abnormalities. Therefore, FHR measurement is considered as the most important parameter to evaluate heart function. One method of FHR extraction is done by using fetal phonocardiogram (fPCG) signal, which is obtained directly from the mother abdominal surface with a medical stethoscope. A variety of high-amplitude interference such as maternal heart sound and environmental noise cause a low SNR fPCG signal. In addition, the signal is nonstationary because of changes in features that are highly dependent on pregnancy age, fetal position, maternal obesity, bandwidth of the recording system and nonlinear transmission environment. Methods: In this paper, a sources separation process from the recorded fPCG signal is proposed. Independent component analysis (ICA) has always been one of the most efficient methods for extracting background noise from multichannel data. In order to extract the source signals from the single-channel fPCG data using ICA algorithm, it is necessary to first decompose the signal into multivariate data using a proper decomposition technique. In this paper, we implemented three combined methods of SSA-ICA, Wavelet-ICA and EEMD-ICA. Results: In order to validate the performance of the methods, we used simulated and real fPCG signals. The results indicated that SSA-ICA recovers sources of single-channel signals with different SNRs. Conclusion: The performance criteria such as power spectral density (PSD) peak and cross correlation value show that the SSA-ICA method has been more successful in extracting independent sources.

Performance of a wearable acoustic system for fetal movement discrimination

Fetal movements (FM) are a key factor in clinical management of high-risk pregnancies such as fetal growth restriction. While maternal perception of reduced FM can trigger self-referral to obstetric services, maternal sensation is highly subjective. Objective, reliable monitoring of fetal movement patterns outside clinical environs is not currently possible. A wearable and non-transmitting system capable of sensing fetal movements over extended periods of time would be extremely valuable, not only for monitoring individual fetal health, but also for establishing normal levels of movement in the population at large. Wearable monitors based on accelerometers have previously been proposed as a means of tracking FM, but such systems have difficulty separating maternal and fetal activity and have not matured to the level of clinical use. We introduce a new wearable system based on a novel combination of accelerometers and bespoke acoustic sensors as well as an advanced signal processing architecture to identify and discriminate between types of fetal movements. We validate the system with concurrent ultrasound tests on a cohort of 44 pregnant women and demonstrate that the garment is capable of both detecting and discriminating the vigorous, whole-body ‘startle’ movements of a fetus. These results demonstrate the promise of multimodal sensing for the development of a low-cost, non-transmitting wearable monitor for fetal movements.

A Comparative Study on Fetal Heart Rates Estimated from Fetal Phonography and Cardiotocography

The aim of this study is to investigate that fetal heart rates (fHR) extracted from fetal phonocardiography (fPCG) could convey similar information of fHR from cardiotocography (CTG). Four-channel fPCG sensors made of low cost (<$1) ceramic piezo vibration sensor within 3D-printed casings were used to collect abdominal phonogram signals from 20 pregnant mothers (>34 weeks of gestation). A novel multi-lag covariance matrix-based eigenvalue decomposition technique was used to separate maternal breathing, fetal heart sounds (fHS) and maternal heart sounds (mHS) from abdominal phonogram signals. Prior to the fHR estimation, the fPCG signals were denoised using a multi-resolution wavelet-based filter. The proposed source separation technique was first tested in separating sources from synthetically mixed signals and then on raw abdominal phonogram signals. fHR signals extracted from fPCG signals were validated using simultaneous recorded CTG-based fHR recordings.The experimental results have shown that the fHR derived from the acquired fPCG can be used to detect periods of acceleration and deceleration, which are critical indication of the fetus' well-being. Moreover, a comparative analysis demonstrated that fHRs from CTG and fPCG signals were in good agreement (Bland Altman plot has mean = -0.21 BPM and ±2 SD = ±3) with statistical significance (p < 0.001 and Spearman correlation coefficient ρ = 0.95). The study findings show that fHR estimated from fPCG could be a reliable substitute for fHR from the CTG, opening up the possibility of a low cost monitoring tool for fetal well-being.

A Noise Reduction Technique Based on Nonlinear Kernel Function for Heart Sound Analysis

The main difficulty encountered in interpretation of cardiac sound is interference of noise. The contaminated noise obscures the relevant information, which are useful for recognition of heart diseases. The unwanted signals are produced mainly by lungs and surrounding environment. In this paper, a novel heart sound denoising technique has been introduced based on a combined framework of wavelet packet transform and singular value decomposition (SVD). The most informative node of the wavelet tree is selected on the criteria of mutual information measurement. Next, the coefficient corresponding to the selected node is processed by the SVD technique to suppress noisy component from heart sound signal. To justify the efficacy of the proposed technique, several experiments have been conducted with heart sound dataset, including normal and pathological cases at different signal to noise ratios. The significance of the method is validated by statistical analysis of the results. The biological information preserved in denoised heart sound signal is evaluated by the k-means clustering algorithm. The overall results show that the proposed method is superior than the baseline methods.

De-noising the abdominal phonogram for foetal heart rate extraction: blind source separation versus empirical filtering

This work explored the suitability of using the foetal phonocardiogram (FPCG) blindly separated from the abdominal phonogram as a source for foetal heart rate (FHR) measuring in antenatal surveillance. To this end, and working on a dataset of 15 abdominal phonograms, the FPCG was estimated by using two de-noising approaches (1) single-channel independent component analysis (SCICA) to produce FPCG(e) and (2) empirical filtering to produce FPCG(g). Next, the FPCGs were further processed to collect the beat-to-beat FHR and the resulting time-series (FCTG(e) and FCTG(g) were compared to the reference signal given by the abdominal ECG (FCTG(r)). Results are promising, the FPCG(e) gives rise to a FCTG(e) that resembles FCTG(r) and, most importantly, whose mean FHR value is statistically equivalent to that given by FCTG(r) (p > 0.05). Thus, the mean FHR value obtained from the FPCG(e), is likely to be equivalent to the value given by the abdominal ECG, which is especially significant since the FPCG(e) is retrieved from the noisy abdominal phonogram. Hence, as far as this study has gone, it can be said that, when using SCICA to de-noise the abdominal phonogram, the resulting FPCG is likely to become a useful source for FHR collection in antenatal surveillance.

Antenatal surveillance through estimates of the sources underlying the abdominal phonogram: a preliminary study

Today, it is generally accepted that current methods for biophysical antenatal surveillance do not facilitate a comprehensive and reliable assessment of foetal well-being and that continuing research into alternative methods is necessary to improve antenatal monitoring procedures. In our research, attention has been paid to the abdominal phonogram, a signal that is recorded by positioning an acoustic sensor on the maternal womb and contains valuable information about foetal status, but which is hidden by maternal and environmental sources. To recover such information, previous work has used single-channel independent component analysis (SCICA) on the abdominal phonogram and successfully retrieved estimates of the foetal phonocardiogram, the maternal phonocardiogram, the maternal respirogram and noise. The availability of these estimates made it possible for the current study to focus on their evaluation as sources for antenatal surveillance purposes. To this end, the foetal heart rate (FHR), the foetal heart sounds morphology, the maternal heart rate (MHR) and the maternal breathing rate (MBR) were collected from the estimates retrieved from a dataset of 25 abdominal phonograms. Next, these parameters were compared with reference values to quantify the significance of the physiological information extracted from the estimates. As a result, it has been seen that the instantaneous FHR, the instantaneous MHR and the MBR collected from the estimates consistently followed the trends given by the reference signals, which is a promising outcome for this preliminary study. Thus, as far as this study has gone, it can be said that the independent traces retrieved by SCICA from the abdominal phonogram are likely to become valuable sources of information for well-being surveillance, both foetal and maternal.

On the interpretation of the independent components underlying the abdominal phonogram: a study of their physiological relevance

Recorded by positioning a sensitive acoustic sensor over the maternal womb, the abdominal phonogram is a signal that contains valuable information for foetal surveillance (e.g. heart rate), which is hidden by maternal and environmental sources. To recover such information, previous work used single-channel independent component analysis (SCICA) to separate the abdominal phonogram into statistically independent components (ICs) that, once acquired, must be objectively associated with the real sources underlying the abdominal phonogram-either physiological or environmental. This is a typical challenge for blind source separation methodologies and requires further research on the signals of interest to find a suitable solution. Here, we have conducted a joint study on 75 sets of ICs by means of statistical, spectral, complexity and time-structure analysis methods. As a result, valuable and consistent characteristics of the components separated from the abdominal phonogram by SCICA have been revealed: (1) the ICs are spectrally disjoint and sorted according to their frequency content, (2) only the ICs with lower frequency content present strong regular patterns and (3) such regular patterns are driven by well-known physiological processes given by the maternal breathing rate, the maternal heart rate and the foetal heart rate. This information was so promising that it has been used in current work for automatic classification of ICs and recovery of the traces of the physiological sources underlying the abdominal phonogram. Future work will look for the extraction of information useful for surveillance (e.g. heart rate), not only about foetal well-being, but also about maternal condition.