Waveform Variation Research Articles

Assessment of dynamic variables of fluid responsiveness to predict desufflation-induced hypotension during paediatric laparoscopic surgery

BackgroundDuring laparoscopic surgery in paediatric patients, sudden hypotension may occur following peritoneal desufflation due to hypovolaemia or an acute increase in gastrointestinal venous capacitance by the release of intra-abdominal pressure. This study examined whether dynamic variables of fluid responsiveness during pneumoperitoneum can predict the occurrence of hypotension following desufflation. MethodsA total of 120 paediatric subjects were prospectively enrolled. A predictor was derived from the initial 83 subjects and validated thereafter in 37 high-risk subjects. The pleth variability index, respiratory variation in the pulse oximetry plethysmographic waveform (ΔPOP), systolic pressure variation and pulse pressure variation during pneumoperitoneum were obtained 1 min before desufflation. Predictors of desufflation-induced hypotension were investigated using the multivariable logistic regression analysis. Predictability was assessed using the area under the receiver-operating characteristic curve (AUC). ResultsIn the derivation cohort, 27% (n=23) of subjects developed hypotension. Only ΔPOP was found to be a predictor, and showed high predictability of desufflation-induced hypotension [AUC 0.87, P<0.0001, 95% confidence interval (CI): 0.78–0.93]. A ΔPOP cut-off point of 38% predicted hypotension with a sensitivity of 83% and a specificity of 90%. In the validation cohort, 43% (n=16) of subjects developed hypotension, and ΔPOP was verified to be highly predictive of the occurrence of hypotension (AUC 0.90, P<0.0001, 95% CI: 0.76–0.98). The sensitivity and specificity of a ΔPOP cut-off point of 38% to predict hypotension was 88% and 90%, respectively. ConclusionsThe ΔPOP during pneumoperitoneum is useful in predicting desufflation-induced hypotension during paediatric laparoscopic surgery. Clinical trial registrationNCT02536521.

Changes in transcranial electrical motor-evoked potentials during the early and reversible stage of permanent spinal cord ischemia predict spinal cord injury in a rabbit animal model.

The present study examined changes in the transcranial electrical motor-evoked potentials (TceMEP) waveform to predict neurological deficits and histopathological changes during the early and reversible stage of different levels of permanent spinal cord ischemic injury in a rabbit animal model. A total of 24 New Zealand rabbits were randomly divided into four groups of 6 rabbits each. Group 1 underwent a ligation of the lumbar artery at three levels (L1-L3), group 2 underwent a ligation of the lumbar artery at four levels (L1-L4) and group 3 underwent a ligation of the lumbar artery at five levels (L1-L5). The sham group contained 6 rabbits and did not receive ligation. TceMEP was recorded within 5 min of ligation and, 2 days later, motor function was assessed and the spinal cords were removed for histological examination. Following spinal cord injury, the relationship between variations in the TceMEP waveform and motor function and pathological damage was analyzed. It was observed that the amplitude of TceMEP began to decrease within 1 min of lumbar artery ligation and that the amplitude stabilized within 5 min. These amplitude changes that occurred within 5 min of different levels of permanent spinal cord ischemic injury were positively related to changes in motor function following recovery from anesthesia and 2 days after ligation. The Pearson correlation coefficient was 0.980 and 0.923 for these two time points, respectively (P<0.001). In addition, the amplitude changes were positively related to pathological damage, with a Pearson correlation coefficient of 0.945 (P<0.001). The results of the present study suggested that amplitude changes in TceMEP are particularly sensitive to ischemia. Ischemia may be detected within 1 min and the amplitude changes begin to stabilize within 5 min following ligation of the lumbar artery. The use of intraoperative monitoring of TceMEP allows for the detection of spinal cord ischemic injury with no time delay, which may allow for protective measures to be taken to prevent the occurrence of irreversible spinal cord injury.

Doppler Ultrasound Evaluation of Circulatory Support Devices.

In the setting of mechanical circulatory support devices, including ventricular assist devices, extracorporeal membrane oxygenation, intraaortic balloon pumps, and the total artificial heart, the spectral Doppler waveform is significantly altered, reflecting systemic hemodynamic changes. As the prevalence of these devices increases, a better understanding of both the devices themselves and their associated Doppler ultrasound findings is necessary for accurate image interpretation. This article reviews the clinical indications, pathophysiology, and sonographic findings of these devices, with emphasis on the variation in arterial Doppler waveforms that can be seen with normal function, as well as the major complications.

Adaptive Waveform Learning: A Framework for Modeling Variability in Neurophysiological Signals

When analyzing brain activity such as local field potentials, it is often desired to represent neural events by stereotypic waveforms. Due to the nondeterministic nature of the neural responses, an adequate waveform estimate typically requires recording multiple repetitions of the neural events. It is common practice to segment the recorded signal into event-related epochs and calculate their average. This approach suffers from two major drawbacks: epoching can be problematic, especially in the case of overlapping neural events, and variability of the neural events across epochs (such as varying onset latencies) is not accounted for, which may lead to a distorted average. In this paper, we propose a novel method called adaptive waveform learning (AWL). It is designed to learn multicomponent representations of neural events while explicitly capturing and compensating for waveform variability, such as changing latencies or more general shape variations. Thanks to its generality, it can be applied to both epoched (i.e., segmented) and continuous (i.e., nonepoched) signals by making the corresponding specializations to the algorithm. We evaluate AWL's performance and robustness to noise on simulated data and demonstrate its empirical utility on an electrophysiological recording containing intracranial epileptiform discharges ( epileptic spikes ).

A Phase Selection Method for Wind Power Integration System Using Phase Voltage Waveform Correlation

The fault characteristics of the wind power system, which are reflected in the weak feed features, variation of system impedance, frequency deviation, and non-sinusoidal waveform, will cause the inadaptation of traditional phase selectors to a wind power integration system. In this paper, a new phase selection principle based on the waveform correlation of transient voltage is proposed, which is valid for relay protection of intermittent solar or wind power plants. First, the characteristics of transient voltage of various fault types are deduced according to their boundary conditions. And on this basis, the correlations between the fault transient voltages of every two phases can be acquired. With the differentiated waveform correlations of different fault types, the fault phase selection criterion based on correlation coefficient is formed accordingly. Because it depends on the waveform characteristics of fault transient voltages, the new phase selector is not influenced by the wind power system's fault characteristics and it can select the correct fault phase quickly with high sensitivity. The proposed novel phase selection criterion is verified by the PSCAD-based simulation results and field fault recording data of the wind power integration system.

Detecting compositional changes in dielectric materials simulated by three-dimensional RC network models

This work discusses the detection of small compositional changes in materials that have microstructures containing conducting and dielectric phases, which can be described by networks of resistive (R) and capacitive (C) components in a three-dimensional lattice. For this purpose, a principal component analysis (PCA) method is employed to discriminate normal samples from samples with altered composition on the basis of statistics extracted from the waveform of the network response to a given excitation. This approach obviates the requirement for multivariate regression and simplifies experimental workload for model-building, since only data from normal samples are required in the development of the PCA model. Waveform variability of the excitation source is also accounted for through the use of a nominal model derived using subspace identification. This enables standardization and software based metrology transfer across different labs. The effect of network size on the capability of detecting minute compositional changes was assessed. For networks of 520 components, it was possible to identify changes in the fraction of capacitors down to 10−2 at ±2σ confidence levels.

P207 Affecting declarative long-term memory with transcranial alternating current stimulation (tACS)

Introduction and objective Previous studies imply that tACS can entrain the ongoing physiological neuronal oscillations depending on the targeted function and the parameters (frequency, intensity and phase) of the stimulation. The aim of the present study was to clarify if tACScould influence the performance of healthy subjects on a verbal paired-associate learning paradigm. Methods For that, we conducted three different crossover, randomized, single-blind, placebo-controlled studies, using a battery-driven Starstim stimulator system (Neuroelectrics, Barcelona, Spain). In the first study ( n = 6), we applied 100 Hz tACS with 1.5 mA (active electrode T7, return Fpz and T8); in the second one ( n = 6), 1.0 mA, 6 Hz (3 s) followed by 80 Hz (5 s) tACS during ISI and Stimulus presentation using the same electrodes configuration; in the third one ( n = 15), we combined a temporal- and pre-frontal stimulation using 7 electrodes. Here the stimulation intensity was 1 mA at 6 Hz (temporal) and 80 Hz (pre-frontal) combined stimulation. For all the studies, we used 8 cm 2 round rubber electrodes inside a saline-soaked sponge pocket, applying 10 min stimulation during the word-pairs learning phase. After the learning phase, the subjects had a 10 min pause, followed by a test phase with a cued recall. The subjects returned after 24 h for a second cued-recall test. All subjects receivedactive and sham tACS in a counterbalanced, randomized-manner. Results In the first two studies, no significant difference were found in the accuracy performance between days across conditions, as well as between days within conditions; in the third study, we found no significant difference between days across conditions, but significant difference between days in the active ( t = 2.98, p = 0.010) and sham ( t = 2.52, p = 0.024) stimulation. Conclusion The stimulation parameters tested could not influence the memory performance assessed by this memory task with the present number of subjects in the first two studies. Further variations of waveforms, intensity and stimulation parameters should be tested with the same task in order to probe the possible influence of tACS on episodic long-term memory. The final results will be presented in the conference.

Action Potential Heterogeneity in Murine Sinoatrial Node Myocytes

Sinoatrial node myocytes (SAMs) act as cardiac pacemakers by generating spontaneous action potentials (APs). SAMs are characterized by the expression of the “funny current” (If) that contributes to the spontaneous diastolic depolarization phase of the sinoatrial AP. SAMs exhibit a large heterogeneity of morphological and electrophysiological properties. However, limited information is available about the intrinsic variability in AP waveforms in SAMs. In this study, we co-recorded APs and If from acutely isolated SAMs from mice using voltage and current clamp recordings in the same cells. We refined the definitions of commonly used AP waveform parameters to document the heterogeneity of APs in both perforated patch (PP) and whole-cell (WC) recordings. These definitions were then implemented in an open-source data analysis program (“paramAP”) written in Python 3 using NumPy, SciPy, and Matplotlib. ParamAP was utilized to characterize APs from more than 100 SAMs. Correlation analysis was used to evaluate relationships among AP waveform parameters and to identify parameters that are strongly correlated with If and AP firing rate. Furthermore, we document time-dependent changes in AP waveform parameters during both PP and WC recordings. In summary, paramAP is a powerful tool to help standardize AP waveform analysis and parameter definitions in murine SAMs. Our data suggest that commonly-held assumptions about sinoatrial node APs should be extended to accommodate a wider range of AP waveforms. In addition, the time-dependent changes in AP waveform parameters should be considered when comparing data from different studies.

Optimised band‐pass filter to ensure accurate ECG‐based identification of exercising human subjects

Waveform distortions generated by exercise cause erroneous predictions in human identification based on the electrocardiogram (ECG). An approach for the ECG-based identification to achieve accurate predictions while exercising is proposed. In the proposed scheme, passband of a band-pass filter is optimised to compensate for the distortion. As a result, the proposed scheme archives 100% identification accuracy is revealed when the subject is resting and 99.7% during exercise. The investigation is an important building block in the development of robust ECG-based identification systems that are consistently accurate despite significant ECG waveform variation due to exercise.

A Generic Waveform Abnormality Detection Method for Utility Equipment Condition Monitoring

In recent years, power quality (PQ) disturbance data are increasingly applied to extract useful information about the condition of power systems, such as monitoring incipient equipment failures. A prerequisite for such applications is the ability for a PQ monitor to detect abnormal waveforms. In response to this need, a generic method for waveform abnormality detection is proposed in this paper. The proposed method has two unique features. First, abnormalities are detected by comparing the statistical distributions of waveform variations with and without disturbances. Kullback-Leibler divergence (KLD) is used to assess the difference of the distributions. An abnormality exists if the KLD is larger than a threshold. Second, current waveforms are used for detection since they are more sensitive to equipment conditions. The difficulty to set a proper threshold due to large variations of current values is overcome through the adoption of KLD as the distance measure and a systematic threshold selection scheme. The scheme maximizes the detection probability for a given false alarm probability. Field-measured data and simulated data are applied to verify the effectiveness of the method.

反応性大電力パルススパッタリング（R-HiPIMS）における遷移領域制御技術

This is to review a novel approach stabilizing reactive mode at transition regime in reactive high-power impulse magnetron sputtering (R-HiPIMS). The proposed method is based on a real-time monitoring of peak discharge current. To stabilize the process conditions at a given set point, a feedback control system, which automatically regulates the pulse frequency, and thereby the average sputtering power, was implemented to maintain a constant maximum discharge current. As a representative result, the variation of the pulse current waveforms over a wide range of reactive gas flows and pulse frequencies during a R-HiPIMS of Hf in an Ar-N2 atmosphere illustrates that the discharge current waveform is an excellent indicator of the process conditions. Applicability of the proposed method was successfully demonstrated.

Nonlinear methods of analysis to examine respiratory waveform variability during oral feeding in preterm infants

In a novel exploratory study, nonlinear methods of analysis for respiratory patterns were used to examine respiratory waveform variability during oral feeding in preterm infants. Twelve healthy preterm infants were studied using a within-subject cross over design to compare semi-upright and the elevated sidelying position during bottle feeding. Outcome measures were physiologic indicators of cardiopulmonary status: heart rate, respiratory rate, oxygen saturation and respiratory pattern variability. Preliminary results suggest that analysis of respiratory waveform variability is feasible and may be a more sensitive measure of cardiopulmonary physiology than means for heart rate, respiratory rate and percent haemoglobin oxygen saturation. Nonlinear methods of analysis of the respiratory data provide a distinct perspective on the adaptability of infants' breathing patterns while feeding. The clinical application of monitoring respiratory waveforms using nonlinear methods may be helpful in identifying readiness to initiate and advance feeds orally in preterm infants.

Nonlinear methods of analysis to examine respiratory waveform variability during oral feeding in preterm infants

Nonlinear methods of analysis to examine respiratory waveform variability during oral feeding in preterm infants

Pulse Oximetry: Beyond SpO2.

Newer pulse oximetry technology is available that uses multiple wavelengths of light and is thereby able to measure more than 2 forms of hemoglobin, including carboxyhemoglobin (SpCO), methemoglobin (SpMet), and total hemoglobin (SpHb). Several studies have shown relatively low bias, but poor precision, for SpCO compared with HbCO. Evaluations of SpMet have been conducted primarily in normal subjects. Clinical evaluations of SpHb suggest that it might not yet be accurate enough to make transfusion decisions. Respiratory waveform variability of the pulse oximeter plethysmogram might be useful to assess pulsus paradoxus in patients with airway obstruction; it might also be used to measure the breathing frequency. The change in pulse pressure over the respiratory cycle has been used to assess fluid responsiveness in mechanically ventilated patients, and similarly, the pulse oximetry plethysmogram waveform amplitude variability might be used to assess fluid responsiveness. However, there are limitations to this approach, and it remains to be determined how well it can be applied clinically using existing pulse oximetry technology. The pulse oximeter signal is probably useful for applications beyond SpO2 However, the current technology is not mature, and improvements are necessary. With technology improvements, the use of pulse oximetry to detect SpCO, SpMet, SpHb, pulsus paradoxus, breathing frequency, and fluid responsiveness is likely to improve in the future.

Nondestructive examination of polymethacrylimide composite structures with terahertz time-domain spectroscopy

THz reflective time domain spectroscopy (THz-RTDS) has been considered as an effective method to detect hidden objects with potential for supplementing other NDE technologies for foam composite adhesive structure debonding defects. PMI (Polymethacrylimide) is a heat-resistant foam material, with the highest strength and stiffness to weight ratio. It is widely used in various parts of airplanes, especially the wing leading edge and rudder, landing gear doors, wing-body/wingtip fairings and so on. We analyzed the features of adhesive debonding defect based mainly on the variation of the time-domain wave form and compared with the inclusion defect. The quantification of degrees of adhesive debonding can be readily achieved with THz-RTDS images based on the delay of the wave front and the main reflection time-domain waveforms. Typical accuracy of about 100 μm was achieved.

Basal conditions at the grounding zone of Whillans Ice Stream, West Antarctica, from ice‐penetrating radar

We present a comprehensive ice‐penetrating radar survey of a subglacial embayment and adjacent peninsula along the grounding zone of Whillans Ice Stream, West Antarctica. Through basal waveform and reflectivity analysis, we identify four distinct basal interfaces: (1) an ice‐water‐saturated till interface inland of grounding; (2) a complex interface in the grounding zone with variations in reflectivity and waveforms caused by reflections from fluting, sediment deposits, and crevasses; (3) an interface of anomalously low‐reflectivity downstream of grounding in unambiguously floating areas of the embayment due to basal roughness and entrained debris; and (4) a high‐reflectivity ice‐seawater interface that occurs immediately seaward of grounding at the subglacial peninsula and several kilometers seaward of grounding in the embayment, occurring after basal debris and grounding zone flutes have melted off the ice bottom. Sediment deposition via basal debris melt‐out occurs in both locations. The higher basal melt rate at the peninsula contributes to greater grounding line stability by enabling faster construction of a stabilizing sediment wedge. In the embayment, the low slopes of the ice bottom and bed prevent development of a strong thermohaline circulation leading to a lower basal melt rate and less rapid sediment deposition. Thus, grounding lines in subglacial embayments are more likely to lack stabilizing sediment deposits and are more prone to external forcing, whether from the ocean, the subglacial water system, or large‐scale ice dynamics. Our conclusions indicate that subglacial peninsulas and embayments should be treated differently in ice sheet‐ocean models if these models are to accurately simulate grounding line response to external forcing.

Uncertainty quantification of wall shear stress in intracranial aneurysms using a data-driven statistical model of systemic blood flow variability

Adverse wall shear stress (WSS) patterns are known to play a key role in the localisation, formation, and progression of intracranial aneurysms (IAs). Complex region-specific and time-varying aneurysmal WSS patterns depend both on vascular morphology as well as on variable systemic flow conditions. Computational fluid dynamics (CFD) has been proposed for characterising WSS patterns in IAs; however, CFD simulations often rely on deterministic boundary conditions that are not representative of the actual variations in blood flow. We develop a data-driven statistical model of internal carotid artery (ICA) flow, which is used to generate a virtual population of waveforms used as inlet boundary conditions in CFD simulations. This allows the statistics of the resulting aneurysmal WSS distributions to be computed. It is observed that ICA waveform variations have limited influence on the time-averaged WSS (TAWSS) on the IA surface. In contrast, in regions where the flow is locally highly multidirectional, WSS directionality and harmonic content are strongly affected by the ICA flow waveform. As a consequence, we argue that the effect of blood flow variability should be explicitly considered in CFD-based IA rupture assessment to prevent confounding the conclusions.

Test-Retest Reliability of the Binaural Interaction Component of the Auditory Brainstem Response.

The binaural interaction component (BIC) is the residual auditory brainstem response (ABR) obtained after subtracting the sum of monaurally evoked from binaurally evoked ABRs. The DN1 peak-the first negative peak of the BIC-has been postulated to have diagnostic value as a biomarker for binaural hearing abilities. Indeed, not only do DN1 amplitudes depend systematically upon binaural cues to location (interaural time and level differences), but they are also predictive of central hearing deficits in humans. A prominent issue in using BIC measures as a diagnostic biomarker is that DN1 amplitudes not only exhibit considerable variability across subjects, but also within subjects across different measurement sessions. In this study, the authors investigate the DN1 amplitude measurement reliability by conducting repeated measurements on different days in eight adult guinea pigs. Despite consistent ABR thresholds, ABR and DN1 amplitudes varied between and within subjects across recording sessions. However, the study analysis reveals that DN1 amplitudes varied proportionally with parent monaural ABR amplitudes, suggesting that common experimental factors likely account for the variability in both waveforms. Despite this variability, the authors show that the shape of the dependence between DN1 amplitude and interaural time difference is preserved. The authors then provide a BIC normalization strategy using monaural ABR amplitude that reduces the variability of DN1 peak measurements. Finally, the authors evaluate this normalization strategy in the context of detecting changes of the DN1 amplitude-to-interaural time difference relationship. The study results indicate that the BIC measurement variability can be reduced by a factor of two by performing a simple and objective normalization operation. The authors discuss the potential for this normalized BIC measure as a biomarker for binaural hearing.

Modeling Electrophysiological Coupling and Fusion between Human Mesenchymal Stem Cells and Cardiomyocytes.

Human mesenchymal stem cell (hMSC) delivery has demonstrated promise in preclinical and clinical trials for myocardial infarction therapy; however, broad acceptance is hindered by limited understanding of hMSC-human cardiomyocyte (hCM) interactions. To better understand the electrophysiological consequences of direct heterocellular connections between hMSCs and hCMs, three original mathematical models were developed, representing an experimentally verified triad of hMSC families with distinct functional ion channel currents. The arrhythmogenic risk of such direct electrical interactions in the setting of healthy adult myocardium was predicted by coupling and fusing these hMSC models to the published ten Tusscher midcardial hCM model. Substantial variations in action potential waveform—such as decreased action potential duration (APD) and plateau height—were found when hCMs were coupled to the two hMSC models expressing functional delayed rectifier-like human ether à-go-go K+ channel 1 (hEAG1); the effects were exacerbated for fused hMSC-hCM hybrid cells. The third family of hMSCs (Type C), absent of hEAG1 activity, led to smaller single-cell action potential alterations during coupling and fusion, translating to longer tissue-level mean action potential wavelength. In a simulated 2-D monolayer of cardiac tissue, re-entry vulnerability with low (5%) hMSC insertion was approximately eight-fold lower with Type C hMSCs compared to hEAG1-functional hMSCs. A 20% decrease in APD dispersion by Type C hMSCs compared to hEAG1-active hMSCs supports the claim of reduced arrhythmogenic potential of this cell type with low hMSC insertion. However, at moderate (15%) and high (25%) hMSC insertion, the vulnerable window increased independent of hMSC type. In summary, this study provides novel electrophysiological models of hMSCs, predicts possible arrhythmogenic effects of hMSCs when directly coupled to healthy hCMs, and proposes that isolating a subset of hMSCs absent of hEAG1 activity may offer increased safety as a cell delivery cardiotherapy at low levels of hMSC-hCM coupling.

Investigation of statistical characteristics of interaction between the low-frequency oscillations in heart rate variability and photoplethysmographic waveform variability in healthy subjects and myocardial infarction patients

Investigation of statistical characteristics of interaction between the low-frequency oscillations in heart rate variability and photoplethysmographic waveform variability in healthy subjects and myocardial infarction patients