About 30% of children with drug-resistant epilepsy (DRE) continue to have seizures after epilepsy surgery. Since epilepsy is increasingly conceptualized as a network disorder, understanding how brain regions interact may be critical for planning re-operation in these patients. We aimed to estimate functional brain connectivity using scalp EEG and its evolution over time in patients who had repeated surgery (RS-group, n = 9) and patients who had one successful surgery (seizure-free, SF-group, n = 12). We analyzed EEGs without epileptiform activity at varying time points (before and after each surgery). We estimated functional connectivity between cortical regions and their relative centrality within the network. We compared the pre- and post-surgical centrality of all the non-resected (untouched) regions (far or adjacent to resection) for each group (using the Wilcoxon signed rank test). In alpha, theta, and beta frequency bands, the post-surgical centrality of the untouched cortical regions increased in the SF group (p < 0.001) whereas they decreased (p < 0.05) or did not change (p > 0.05) in the RS group after failed surgeries; when re-operation was successful, the post-surgical centrality of far regions increased (p < 0.05). Our data suggest that removal of the epileptogenic focus in children with DRE leads to a gain in the network centrality of the untouched areas. In contrast, unaltered or decreased connectivity is seen when seizures persist after surgery.
Intracranial electroencephalographic (icEEG) studies show that interictal ripples propagate across the brain of children with medically refractory epilepsy (MRE), and the onset of this propagation (ripple onset zone [ROZ]) estimates the epileptogenic zone. It is still unknown whether we can map this propagation noninvasively. The goal of this study is to map ripples (ripple zone [RZ]) and their propagation onset (ROZ) using high‐density EEG (HD‐EEG) and magnetoencephalography (MEG), and to estimate their prognostic value in pediatric epilepsy surgery.
We retrospectively analyzed simultaneous HD‐EEG and MEG data from 28 children with MRE who underwent icEEG and epilepsy surgery. Using electric and magnetic source imaging, we estimated virtual sensors (VSs) at brain locations that matched the icEEG implantation. We detected ripples on VSs, defined the virtual RZ and virtual ROZ, and estimated their distance from icEEG. We assessed the predictive value of resecting virtual RZ and virtual ROZ for postsurgical outcome. Interictal spike localization on HD‐EEG and MEG was also performed and compared with ripples.
We mapped ripple propagation in all patients with HD‐EEG and in 27 (96%) patients with MEG. The distance from icEEG did not differ between HD‐EEG and MEG when mapping the RZ (26–27mm, p = 0.6) or ROZ (22–24mm, p = 0.4). Resecting the virtual ROZ, but not virtual RZ or the sources of spikes, was associated with good outcome for HD‐EEG (p = 0.016) and MEG (p = 0.047).
HD‐EEG and MEG can map interictal ripples and their propagation onset (virtual ROZ). Noninvasively mapping the ripple onset may augment epilepsy surgery planning and improve surgical outcome of children with MRE. ANN NEUROL 2021
OBJECTIVE: Photoplethysmography (PPG) is an optical technique measuring variations of blood perfusion in peripheral tissues. We evaluated alterations in PPG signals in relationship to the occurrence of generalized tonic-clonic seizures (GTCSs) in patients with epilepsy to evaluate the feasibility of seizure detection.
METHODS: During electroencephalographic (EEG) long-term monitoring, patients wore portable wristband sensor(s) on their wrists or ankles recording PPG signals. We analyzed PPG signals during three time periods, which were defined with respect to seizures detected on EEG: (1) baseline (>30 minutes prior to seizure), (2) preseizure period, and (3) postseizure period. Furthermore, we selected five random control segments during seizure-free periods. PPG features, including frequency, amplitude, duration, slope, smoothness, and area under the curve, were automatically calculated. We used a linear mixed-effect model to evaluate changes in PPG features between different time periods in an attempt to identify signal changes that detect seizures.
RESULTS: We prospectively enrolled 174 patients from the epilepsy monitoring unit at Boston Children's Hospital. Twenty-five GTCSs were recorded from 13 patients. Data from the first recorded GTCS of each patient were included in the analysis. We observed an increase in PPG frequency during pre- and postseizure periods that was higher than the changes during seizure-free periods (frequency increase: preseizure = 0.22 Hz, postseizure = 0.58 Hz vs changes during seizure-free period = 0.05 Hz). The PPG slope decreased significantly by 56.71 nW/s during preseizure periods compared to seizure-free periods. Additionally, the smoothness increased significantly by 0.22 nW/s during the postseizure period compared to seizure-free periods.
SIGNIFICANCE: Monitoring of PPG signals may assist in the detection of GTCSs in patients with epilepsy. PPG may serve as a promising biomarker for future seizure detection systems and may contribute to future seizure prediction systems.
OBJECTIVES: Photoplethysmography (PPG) reflects variations of blood perfusion in tissues, which may signify seizure-related autonomic changes. The aim of this study is to assess the variability of PPG signals and their value in detecting peri-ictal changes in patients with focal impaired awareness seizures (FIASs).
METHODS: PPG data were recorded using a wearable sensor placed on the wrist or ankle of children with epilepsy admitted for long-term video-electroencephalographic monitoring. We analyzed PPG data in four different periods: seizure-free, preictal, ictal, and postictal. Multiple features were automatically extracted from the PPG signal-frequency, duration, amplitude, increasing and decreasing slopes, smoothness, and area under the curve (AUC)-and were used to identify preictal, ictal, or postictal changes by comparing them with seizure-free periods and with each other using a linear mixed-effects model.
RESULTS: We studied PPG in 11 patients (18 FIASs), including seizure-free, preictal, and postictal periods, and a subset of eight patients (12 FIASs) including the ictal period. Compared to the seizure-free period, we found significant changes in PPG (1) during the ictal period across all features; (2) during the preictal period in amplitude, duration, increasing slope, and AUC; and (3) during the postictal period in decreasing slope.
SIGNIFICANCE: Specific PPG changes can be seen before, during, and after FIASs. The peri-ictal changes in the PPG features of patients with FIASs suggest potential applications of PPG monitoring for seizure detection.
OBJECTIVE: To localize the seizure onset zone (SOZ) and irritative zone (IZ) using electric source imaging (ESI) on intracranial EEG (iEEG) and assess their clinical value in predicting epilepsy surgery outcome in children with focal cortical dysplasia (FCD). METHODS: We analyzed iEEG data from 25 children with FCD-associated medically refractory epilepsy (MRE) who underwent surgery. We performed ESI on ictal onset to localize SOZ (ESI-SOZ) and on interictal discharges to localize IZ (ESI-IZ). We tested whether resection of ESI-SOZ and ESI-IZ predicted good surgical outcome (Engel 1). We further compared the prediction performance of ESI-SOZ and ESI-IZ to those of SOZ and IZ defined using conventional methods, i.e. by identifying iEEG-contacts showing ictal onsets (conventional-SOZ) or being the most interictally active (conventional-IZ). RESULTS: The proximity of ESI-SOZ (p = 0.043, odds-ratio = 3.9) and ESI-IZ (p = 0.011, odds-ratio = 7.04) to resection has higher effect on patients' outcome than proximity of conventional-SOZ (p = 0.17, odds-ratio = 1.7) and conventional-IZ (p = 0.038, odds-ratio = 2.6). Resection of ESI-SOZ and ESI-IZ presented higher discriminative power in predicting outcome (68% and 60%) than conventional-SOZ and conventional-IZ (48% and 53%). CONCLUSIONS: Localizing SOZ and IZ via ESI on iEEG offers higher predictive value compared to conventional-iEEG interpretation. SIGNIFICANCE: iEEG-ESI may help surgical planning and facilitate prognostic assessment of children with FCD-associated MRE.
OBJECTIVE: To assess the ability of high-density Electroencephalography (HD-EEG) and magnetoencephalography (MEG) to localize interictal ripples, distinguish between ripples co-occurring with spikes (ripples-on-spike) and independent from spikes (ripples-alone), and evaluate their localizing value as biomarkers of epileptogenicity in children with medically refractory epilepsy. METHODS: We retrospectively studied 20 children who underwent epilepsy surgery. We identified ripples on HD-EEG and MEG data, localized their generators, and compared them with intracranial EEG (icEEG) ripples. When ripples and spikes co-occurred, we performed source imaging distinctly on the data above 80 Hz (to localize ripples) and below 70 Hz (to localize spikes). We assessed whether missed resection of ripple sources predicted poor outcome, separately for ripples-on-spikes and ripples-alone. Similarly, predictive value of spikes was calculated. RESULTS: We observed scalp ripples in 16 patients (10 good outcome). Ripple sources were highly concordant to the icEEG ripples (HD-EEG concordance: 79%; MEG: 83%). When ripples and spikes co-occurred, their sources were spatially distinct in 83-84% of the cases. Removing the sources of ripples-on-spikes predicted good outcome with 90% accuracy for HD-EEG (P = 0.008) and 86% for MEG (P = 0.044). Conversely, removing ripples-alone did not predict outcome. Resection of spike sources (generated at the same time as ripples) predicted good outcome for HD-EEG (P = 0.036; accuracy = 87%), while did not reach significance for MEG (P = 0.1; accuracy = 80%). INTERPRETATION: HD-EEG and MEG localize interictal ripples with high precision in children with refractory epilepsy. Scalp ripples-on-spikes are prognostic, noninvasive biomarkers of epileptogenicity, since removing their cortical generators predicts good outcome. Conversely, scalp ripples-alone are most likely generated by non-epileptogenic areas.
OBJECTIVE: To determine the relationship between nutritive sucking and microstructural integrity of sensorimotor tracts in newborns with brain injury.
STUDY DESIGN: Diffusion imaging was performed in ten newborns with brain injury. Nutritive sucking was assessed using Nfant®. The motor, sensory, and corpus callosum tracts were reconstructed via tractography. Fractional anisotropy, radial, axial, and mean diffusivity were estimated for these tracts. Multiple regression models were developed to test the association between sucking features and diffusion parameters.
RESULTS: Low-sucking smoothness correlated with low-fractional anisotropy of motor tracts (p = 0.0096). High-sucking irregularity correlated with high-mean diffusivity of motor (p = 0.030) and corpus callosum tracts (p = 0.032). For sensory tracts, high-sucking irregularity (p = 0.018) and low-smoothness variability (p = 0.002) correlated with high-mean diffusivity.
INTERPRETATION: We show a correlation between neuroimaging-demonstrated microstructural brain abnormalities and variations in sucking patterns of newborns. The consistency of this relationship should be shown on larger cohorts.
Despite extensive literature showing damages in the sensorimotor projection fibers of children with hemiplegic cerebral palsy (HCP), little is known about how these damages affect the global brain network. In this study, we assess the relationship between the structural integrity of sensorimotor projection fibers and the integrity of intergyral association white matter connections in children with HCP. Diffusion tensor imaging was performed in 10 children with HCP and 16 typically developing children. We estimated the regional and global white-matter connectivity using a region-of-interest (ROI)-based approach and a whole-brain gyrus-based parcellation method. Using the ROI-based approach, we tracked the spinothalamic (STh), thalamocortical (ThC), corticospinal (CST), and sensorimotor U- (SMU) fibers. Using the whole-brain parcellation method, we tracked the short-, middle-, and long-range association fibers. We observed for the more affected hemisphere of children with HCP: (i) an increase in axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) for the STh and ThC fibers; (ii) a decrease in fractional anisotropy (FA) and an increase in MD and RD for the CST and SMU fibers; in (iii) a decrease in FA and an increase in AD, MD, and RD for the middle- and long-range association fibers; and (iv) an association between the integrity of sensorimotor projection and intergyral association fibers. Our findings indicate that altered structural integrity of the sensorimotor projection fibers disorganizes the intergyral association white matter connections among local and distant regions in children with HCP.
OBJECTIVE: To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs). METHODS: Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (E) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (D) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome. RESULTS: MEG presented lower E than HD-EEG and conv-EEG. For all modalities, D was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome. CONCLUSIONS: MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance. SIGNIFICANCE: Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.
INTRODUCTION: Patients with medically refractory epilepsy (MRE) need surgical resection of the epileptogenic zone (EZ) to gain seizure-freedom. High-frequency oscillations (HFOs, > 80 Hz) are promising biomarkers of the EZ that are typically localized using intracranial electroencephalography (icEEG). The goal of this study was to localize the cortical generators of HFOs non-invasively using high-density (HD) EEG and magnetoencephalography (MEG) and validate the localization against the gold-standard given by the icEEGdefined HFO-zone. METHODS: We analyzed simultaneous HDEEG and MEG data from six children with MRE who underwent icEEG and surgery. We detected interictal HFOs (80-160 Hz) on HD-EEG and MEG separately, using an inhouse automatic detector followed by visual human review, and distinguished between HFOs with and without spikes. We localized the cortical generators of each HFO on HD-EEG or MEG using the wavelet Maximum Entropy on the Mean (wMEM). For the HFOs localized in the brain area covered by icEEG, we estimated the localization error (E) with respect to the gold-standard, and classified them as either concordant (E≤15mm) or not. RESULTS: We found that: (i) HD-EEG presented a higher rate of HFOs than MEG (1 vs 0.5 HFOs/min, p=0.031); (ii) HFOs without spikes were more likely to be localized outside the brain regions of interest (i.e. covered by icEEG) than HFOs with spikes; and (iii) both HD-EEG and MEG showed high precision to the gold-standard (92% and 96%). CONCLUSION: We reported quantitative evidence that HDEEG and MEG can localize the HFO cortical generators with high precision to the icEEG gold-standard in children with MRE, suggesting that they may possibly limit the need for icEEG prior to surgery. We also showed that HFOs with spikes on HD-EEG/MEG are more likely to be epileptogenic than those independent from spikes, which may represent physiological events from normal brain.
BACKGROUND: The purpose of this study is to clarify the source distribution patterns of magnetoencephalographic spikes correlated with postsurgical seizure-free outcome in pediatric patients with focal cortical dysplasia.
PATIENTS AND METHODS: Thirty-two patients with pathologically confirmed focal cortical dysplasia were divided into seizure-free and seizure-persistent groups according to their surgical outcomes based on Engel classification. In each patient, presurgical magnetoencephalography was reviewed. Dipole sources of magnetoencephalographic spikes were calculated according to a single dipole model. We obtained the following quantitative indices for evaluating dipole distribution: maximum distance over all pairs of dipoles, standard deviation of the distances between each dipole and the mean coordinate of all dipoles, average nearest neighbor distance, the rate of dipoles located within 10, 20, and 30 mm from the mean coordinate, and the rate of dipoles included in the resection. These indices were compared between the two patient groups.
RESULTS: Average nearest neighbor distance was significantly smaller in the seizure-free group than in the seizure-persistent group (P = 0.008). The rates of dipoles located within 10, 20, and 30 mm from the mean coordinate were significantly higher in the seizure-free group (P = 0.001, 0.001, 0.005, respectively). The maximum distance, standard deviation, and resection rate of dipoles did not show a significant difference between the two groups.
CONCLUSIONS: A spatially restricted dipole distribution of magnetoencephalographic spikes is correlated with postsurgical seizure-free outcomes in patients with focal cortical dysplasia. The distribution can be assessed by quantitative indices that are clinically useful in the presurgical evaluation of these patients.
OBJECTIVE: In patients with medically refractory epilepsy (MRE), interictal ripples (80-250Hz) are observed in large brain areas whose resection may be unnecessary for seizure freedom. This limits their utility as epilepsy biomarkers for surgery. We assessed the spatiotemporal propagation of interictal ripples on intracranial electroencephalography (iEEG) in children with MRE, compared it with the propagation of spikes, identified ripples that initiated propagation (onset-ripples), and evaluated their clinical value as epilepsy biomarkers.
METHODS: Twenty-seven children who underwent epilepsy surgery were studied. We identified propagation sequences of ripples and spikes across multiple iEEG contacts and calculated each ripple or spike latency from the propagation onset. We classified ripples and spikes into categories (ie, onset, spread, and isolated) based on their spatiotemporal characteristics and correlated their mean rate inside and outside resection with outcome (good outcome, Engel 1 versus poor outcome, Engel≥2). We determined, as onset-zone, spread-zone, and isolated-zone, the areas generating the corresponding ripple or spike category and evaluated the predictive value of their resection.
RESULTS: We observed ripple propagation in all patients and spike propagation in 25 patients. Mean rate of onset-ripples inside resection predicted the outcome (odds ratio = 5.37; p = 0.02) and correlated with Engel class (rho = -0.55; p = 0.003). Resection of the onset-ripple-zone was associated with good outcome (p = 0.047). No association was found for the spread-ripple-zone, isolated-ripple-zone, or any spike-zone.
INTERPRETATION: Interictal ripples propagate across iEEG contacts in children with MRE. The association between the onset-ripple-zone resection and good outcome indicates that onset-ripples are promising epilepsy biomarkers, which estimate the epileptogenic tissue better than spread-ripples or onset-spikes. Ann Neurol 2018;84:331-346.
INTRODUCTION: This study evaluates magnetoencephalographic (MEG) spike population as compared with intracranial electroencephalographic (IEEG) spikes using a quantitative method based on distributed source analysis. METHODS: We retrospectively studied eight patients with medically intractable epilepsy who had an MEG and subsequent IEEG monitoring. Fifty MEG spikes were analyzed in each patient using minimum norm estimate. For individual spikes, each vertex in the source space was considered activated when its source amplitude at the peak latency was higher than a threshold, which was set at 50% of the maximum amplitude over all vertices. We mapped the total count of activation at each vertex. We also analyzed 50 IEEG spikes in the same manner over the intracranial electrodes and created the activation count map. The location of the electrodes was obtained in the MEG source space by coregistering postimplantation computed tomography to MRI. We estimated the MEG- and IEEG-active regions associated with the spike populations using the vertices/electrodes with a count over 25. RESULTS: The activation count maps of MEG spikes demonstrated the localization associated with the spike population by variable count values at each vertex. The MEG-active region overlapped with 65 to 85% of the IEEG-active region in our patient group. CONCLUSIONS: Mapping the MEG spike population is valid for demonstrating the trend of spikes clustering in patients with epilepsy. In addition, comparison of MEG and IEEG spikes quantitatively may be informative for understanding their relationship.
Up to one-third of patients with epilepsy are medically intractable and need resective surgery. To be successful, epilepsy surgery requires a comprehensive preoperative evaluation to define the epileptogenic zone (EZ), the brain area that should be resected to achieve seizure freedom. Due to lack of tools and methods that measure the EZ directly, this area is defined indirectly based on concordant data from a multitude of presurgical non-invasive tests and intracranial recordings. However, the results of these tests are often insufficiently concordant or inconclusive. Thus, the presurgical evaluation of surgical candidates is frequently challenging or unsuccessful. To improve the efficacy of the surgical treatment, there is an overriding need for reliable biomarkers that can delineate the EZ. High-frequency oscillations (HFOs) have emerged over the last decade as new potential biomarkers for the delineation of the EZ. Multiple studies have shown that HFOs are spatially associated with the EZ. Despite the encouraging findings, there are still significant challenges for the translation of HFOs as epileptogenic biomarkers to the clinical practice. One of the major barriers is the difficulty to detect and localize them with non-invasive techniques, such as magnetoencephalography (MEG) or scalp electroencephalography (EEG). Although most literature has studied HFOs using invasive recordings, recent studies have reported the detection and localization of HFOs using MEG or scalp EEG. MEG seems to be particularly advantageous compared to scalp EEG due to its inherent advantages of being less affected by skull conductivity and less susceptible to contamination from muscular activity. The detection and localization of HFOs with MEG would largely expand the clinical utility of these new promising biomarkers to an earlier stage in the diagnostic process and to a wider range of patients with epilepsy. Here, we conduct a thorough critical review of the recent MEG literature that investigates HFOs in patients with epilepsy, summarizing the different methodological approaches and the main findings. Our goal is to highlight the emerging potential of MEG in the non-invasive detection and localization of HFOs for the presurgical evaluation of patients with medically refractory epilepsy (MRE).
Neonatal feeding has been traditionally understudied so guidelines and evidence-based support for common feeding practices are limited. A major contributing factor to the paucity of evidence-based practice in this area has been the lack of simple-to-use, low-cost tools for monitoring sucking performance. We describe new methods for quantifying neonatal sucking performance that hold significant clinical and research promise. We present early results from an ongoing study investigating neonatal sucking as a marker of risk for adverse neurodevelopmental outcomes. We include quantitative measures of sucking performance to better understand how movement variability evolves during skill acquisition. Results showed the coefficient of variation of suck duration was significantly different between preterm neonates at high risk for developmental concerns (HRPT) and preterm neonates at low risk for developmental concerns (LRPT). For HRPT, results indicated the coefficient of variation of suck smoothness increased from initial feeding to discharge and remained significantly greater than healthy full-term newborns (FT) at discharge. There was no significant difference in our measures between FT and LRPT at discharge. Our findings highlight the need to include neonatal sucking assessment as part of routine clinical care in order to capture the relative risk of adverse neurodevelopmental outcomes at discharge.
The assessment of oral-motor behavior (OMB) represents one the earliest noninvasive ways to evaluate newborns' well-being and neuromotor behavior. This work aimed at developing a new low-cost, easy-to-use and noninvasive system for a technology-aided assessment of newborns' OMB during bottle feeding. A SUcking MOnitoring Device (SUMOD) was designed and developed to be easily integrated on a typical feeding bottle. A software system was developed to automatically treat and analyze the acquired data: proper algorithms for a fully automatic segmentation and features extraction are proposed and implemented. A set of measures of motor control and coordination are introduced and implemented for the specific application to the OMB analysis. Experimental data were collected on two groups of newborns (healthy versus low birth weight) with the SUMOD in a clinical setting.
Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery. The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the presurgical evaluation for pediatric patients with epilepsy.
In this work a novel unobtrusive technology-aided system is presented and tested for the assessment of newborns' oral-motor behavior and coordination during bottle feeding. A low-cost monitoring device was designed and developed in order to record Suction (S) and Expression (E) pressures from a typical feeding bottle. A software system was developed to automatically treat the data and analyze them. A set of measures of motor control and coordination has been implemented for the specific application to the analysis of sucking behavior. Experimental data were collected with the developed system on two groups of newborns (Healthy vs. Low Birth Weight) in a clinical setting. We identified the most sensitive S features to group differences, and analyzed their correlation with S/E coordination measures. Then, Principal Component Analysis (PCA) was used to explore the system suitability to automatically identify peculiar oral behaviors. Results suggest the suitability of the proposed system to perform an objective technology-aided assessment of the newborn's oral-motor behavior and coordination during the first days of life.
Nutritive Sucking (NS) is a highly organized process that can reflect infants' maturation during the early post-natal period. The assessment of NS may provide a sensitive means of evaluating early motor skills and their development. Thus, a reliable tool for assessing sucking behavior may benefit diagnostics and treatment of newborns since the first days of life. The aim of this work is to propose an automatized system to measure sucking ability and calculate a set of objective and quantitative indices for its assessment. We focused on the analysis of the Intraoral Pressure (IP) generated by infants while feeding: an ad-hoc designed software application was developed to analyze the signal obtained by a pressure transducer connected with a catheter placed through a standard bottle teat into the oral cavity during feeding. Automatic algorithms for suck and burst identification and for their characterization are described. We carried out a preliminary test of the system, analyzing data from two healthy term newborns, tested twice over time (1-2 days old and 6-10 weeks later). We calculated a set of different sucking parameters (e.g. sucking amplitude, frequency and area), and proposed some indices, that are typically used for the assessment of motor control, in order to assess the smoothness of IP. Results encourage further investigation of the proposed system for monitoring the development of early sucking skills.
In newborns, a poor coordination between sucking, swallowing and breathing may undermine the effectiveness of oral feeding and signal immaturity of Central Nervous System. The aim of this work is to develop and validate a non-invasive device for recording respiratory events of newborns during bottle feeding. The proposed device working principle is based on the convective heat exchanged between two hot bodies and the infants' breathing. The sensing elements are inserted into a duct and the gas exchanged by infants is conveyed into this duct thanks to an ad hoc designed system to be mounted on a commercial feeding bottle. Two sets of experiments have been carried out in order to investigate the discrimination threshold of the device and characterize the sensor response at oscillating flows. The effect of distance and tilt between nostrils and device, and the breathing frequency, have been investigated simulating nostrils and neonatal respiratory pattern. The device has a discrimination threshold lower than 0.5 L/min at both 10° and 20° of tilt. Distance for these two settings does not affect the threshold in the investigated range (10-20 mm). Moreover, the device is able to detect breathing events, and to discriminate the onset of expiratory phase, during a neonatal respiratory task delivered by a lung simulator. The results foster the successful application of this device to the assessment of the temporal breathing pattern of newborns during bottle feeding with a non-invasive approach.