Since the 1980s, cardiotocography (CTG) has been the most diffused technique to monitor fetal well-being during pregnancy. CTG consists of the simultaneous recording of fetal heart rate (FHR) signal and uterine contractions and its interpretation is usually performed through visual inspection by trained obstetric personnel. To reduce inter- and intraobserver variabilities and to improve the efficacy of prenatal diagnosis, new quantitative parameters, extracted from the CTG digitized signals, have been proposed as additional tools in the clinical diagnosis process. In this paper, a new parameter computed on FHR time series and based on the phase-rectified signal average curve (PRSA) is introduced. It is defined as acceleration phase-rectified slope (APRS) or deceleration phase-rectified slope (DPRS) depending on the slope sign of the PRSA curve. The new PRSA parameter was applied to FHR time series of 61 healthy and 61 intrauterine growth restricted (IUGR) fetuses during CTG nonstress tests. Performance of APRS and DPRS was compared with 1) the results provided by other parameters extracted from the PRSA curve itself but already existing in the literature, and 2) other clinical indices provided by computerized cardiotocographic systems. APRS and DPRS indices performed better than any other parameter in this study in the distinction between healthy and IUGR fetuses. Our results suggest this new index might reliably contribute to the quality of early fetal diagnosis.

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus providing necessary interventions in time. Both these two objectives can be achieved by integrating technological development with methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused on monitoring procedures applied to fetal heart rate variability (FHRV) signals, collected during pregnancy, in order to assess fetal well-being. The use of linear time and frequency techniques as well as the computation of non linear indices can contribute to enhancing the diagnostic power and reliability of fetal monitoring. The paper shows how advanced signal processing approaches can contribute to developing new diagnostic and classification indices. Their usefulness is evaluated by comparing two selected populations: normal fetuses and intra uterine growth restricted (IUGR) fetuses. Results show that the computation of different indices on FHRV signals, either linear and nonlinear, gives helpful indications to describe pathophysiological mechanisms involved in the cardiovascular and neural system controlling the fetal heart. As a further contribution, the paper briefly describes how the introduction of wearable systems for fetal ECG recording could provide new technological solutions improving the quality and usability of prenatal monitoring.

OBJECTIVEIn the search for a reliable, cooperation-independent, noninvasive alternative to invasive intracranial pressure (ICP) monitoring in children, various approaches have been proposed, but at the present time none are capable of providing fully automated, real-time, calibration-free, continuous and accurate ICP estimates. The authors investigated the feasibility and validity of simultaneously monitored arterial blood pressure (ABP) and middle cerebral artery (MCA) cerebral blood flow velocity (CBFV) waveforms to derive noninvasive ICP (nICP) estimates.METHODSInvasive ICP and ABP recordings were collected from 12 pediatric and young adult patients (aged 2–25 years) undergoing such monitoring as part of routine clinical care. Additionally, simultaneous transcranial Doppler (TCD) ultrasonography–based MCA CBFV waveform measurements were performed at the bedside in dedicated data collection sessions. The ABP and MCA CBFV waveforms were analyzed in the context of a mathematical model, linking them to the cerebral vasculature’s biophysical properties and ICP. The authors developed and automated a waveform preprocessing, signal-quality evaluation, and waveform-synchronization “pipeline” in order to test and objectively validate the algorithm’s performance. To generate one nICP estimate, 60 beats of ABP and MCA CBFV waveform data were analyzed. Moving the 60-beat data window forward by one beat at a time (overlapping data windows) resulted in 39,480 ICP-to-nICP comparisons across a total of 44 data-collection sessions (studies). Moving the 60-beat data window forward by 60 beats at a time (nonoverlapping data windows) resulted in 722 paired ICP-to-nICP comparisons.RESULTSGreater than 80% of all nICP estimates fell within ± 7 mm Hg of the reference measurement. Overall performance in the nonoverlapping data window approach gave a mean error (bias) of 1.0 mm Hg, standard deviation of the error (precision) of 5.1 mm Hg, and root-mean-square error of 5.2 mm Hg. The associated mean and median absolute errors were 4.2 mm Hg and 3.3 mm Hg, respectively. These results were contingent on ensuring adequate ABP and CBFV signal quality and required accurate hydrostatic pressure correction of the measured ABP waveform in relation to the elevation of the external auditory meatus. Notably, the procedure had no failed attempts at data collection, and all patients had adequate TCD data from at least one hemisphere. Last, an analysis of using study-by-study averaged nICP estimates to detect a measured ICP > 15 mm Hg resulted in an area under the receiver operating characteristic curve of 0.83, with a sensitivity of 71% and specificity of 86% for a detection threshold of nICP = 15 mm Hg.CONCLUSIONSThis nICP estimation algorithm, based on ABP and bedside TCD CBFV waveform measurements, performs in a manner comparable to invasive ICP monitoring. These findings open the possibility for rational, point-of-care treatment decisions in pediatric patients with suspected raised ICP undergoing intensive care.

A noninvasive intracranial pressure (ICP) estimation method is proposed that incorporates a model-based approach within a probabilistic framework to mitigate the effects of data and modeling uncertainties. Methods: A first-order model of the cerebral vasculature relates measured arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) to ICP. The model is driven by the ABP waveform and is solved for a range of mean ICP values to predict the CBFV waveform. The resulting errors between measured and predicted CBFV are transformed into likelihoods for each candidate ICP in two steps. First, a baseline ICP estimate is established over five data windows of 20 beats by combining the likelihoods with a prior distribution of the ICP to yield an a posteriori distribution whose median is taken as the baseline ICP estimate. A single-state model of cerebral autoregulatory dynamics is then employed in subsequent data windows to track changes in the baseline by combining ICP estimates obtained with a uniform prior belief and model-predicted ICP. For each data window, the estimated model parameters are also used to determine the ICP pulse pressure. Results: On a dataset of thirteen pediatric patients with a variety of pathological conditions requiring invasive ICP monitoring, the method yielded for mean ICP estimation a bias (mean error) of 0.6 mmHg and a root-mean-squared error of 3.7 mmHg. Conclusion: These performance characteristics are well within the acceptable range for clinical decision making. Significance:

Fetal Heart Rate (FHR) monitoring gives important information about the fetus health state during pregnancy. This paper presents a new prototype for remote fetal monitoring. The device will allow to monitor FHR in a domiciliary context and to send fetal ECG traces to a hospital facility, where clinicians can interpret them. In this way the mother could receive prompt feedback about fetal wellbeing. The system is characterized by two units: (i) a wearable unit endowed with textile electrodes for abdominal ECG recordings and with a Field Programmable Gate Array (FPGA) board for fetal heart rate (FHR) extraction; (ii) a dock station for the transmission of the data through the telephone line. The system will allow to reduce costs in fetal monitoring, improving the assessment of fetal conditions. The device is actually in development state. In this paper, the most crucial aspects behind its fulfillment are discussed.