Frequency-domain Measurements Research Articles

Heart Rate Variability and Decision-Making: Autonomic Responses in Making Decisions

Decision-making is one of the most crucial cognitive processes in daily life. An adaptable, rapid, and flexible decision requires integration between brain and body. Heart rate variability (HRV) indexes this brain–body connection and appears to be related to cognitive performance. However, its relationship with decision-making is poorly analyzed. This study investigates the relationship between HRV and the decision-making process, assessed through the Iowa Gambling Task (IGT). One hundred and thirty healthy university students (mean age = 23.35 ± 2.50) participated in the study. According to IGT performance, they were divided into high decision-makers (n = 79) and low decision-makers (n = 51). Heart rate variability was measured in the resting, reactivity (i.e., during IGT), and recovery phases. Higher vagally mediated HRV (vmHRV; indexed in frequency domain measures) was evidenced in good decision-makers in the resting, reactivity, and recovery phases. During the task, a higher vagal modulation after a first evaluation was highlighted in good decision-makers. In conclusion, HRV proves to be a valid index of inhibitory circuit functioning in the prefrontal cortex. The relationship with cognitive functions was also confirmed, considering the ability to inhibit disadvantageous responses and make better decisions.

Capability of processed EEG parameters to monitor conscious sedation in endoscopy is similar to general anaesthesia.

BackgroundReliable and safe sedation is a prerequisite for endoscopic interventions. The current standard is rather safe, yet, an objective device to measure sedation depth is missing. To date, anaesthesia monitors based on processed electroencephalogram (EEG) have not been utilised in conscious sedation.ObjectiveTo investigate EEG parameters to differentiate consciousness in endoscopic propofol sedation.MethodsIn total, 171 patients aged 21–83 years (ASA I–III) undergoing gastrointestinal and bronchial endoscopy were enrolled. Standard monitoring and a frontotemporal two‐channel EEG were recorded. The state of consciousness was identified by repeated requests to squeeze the investigator's hand.ResultsIn total, 1132 state‐of‐consciousness (SOC) transitions were recorded in procedures ranging from 5 to 69 min. Thirty‐four EEG parameters from the frequency domain, time‐frequency domain and complexity measures were calculated. Area under the curve ranged from 0.51 to 0.82 with complexity and optimised frequency domain parameters yielding the best results.ConclusionPrediction of the SOC with processed EEG parameters is feasible, and the results for sedation in endoscopic procedures are similar to those reported from general anaesthesia. These results are insufficient for a clinical application, but prediction capability may be increased with optimisation and modelling.

Dual-Slope Diffuse Reflectance Instrument for Calibration-Free Broadband Spectroscopy.

This work presents the design and validation of an instrument for dual-slope broadband diffuse reflectance spectroscopy. This instrument affords calibration-free, continuous-wave measurements of broadband absorbance of optically diffusive media, which may be translated into absolute absorption spectra by adding frequency-domain measurements of scattering at two wavelengths. An experiment on a strongly scattering liquid phantom (milk, water, dyes) confirms the instrument’s ability to correctly identify spectral features and measure absolute absorption. This is done by sequentially adding three dyes, each featuring a distinct spectral absorption, to the milk/water phantom. After each dye addition, the absorption spectrum is measured, and it is found to reproduce the spectral features of the added dye. Additionally, the absorption spectrum is compared to the absorption values measured with a commercial frequency-domain instrument at two wavelengths. The measured absorption of the milk/water phantom quantitatively agrees with the known water absorption spectrum (R2 = 0.98), and the measured absorption of the milk/water/dyes phantom quantitatively agrees with the absorption measured with the frequency-domain instrument in six of eight cases. Additionally, the measured absorption spectrum correctly recovers the concentration of one dye, black India ink, for which we could accurately determine the extinction spectrum (i.e., the specific absorption per unit concentration). The instrumental methods presented in this work can find applications in quantitative spectroscopy of optically diffusive media, and particularly in near-infrared spectroscopy of biological tissue.

Heart rate variability during wakefulness as a marker of obstructive sleep apnea severity.

Patients with obstructive sleep apnea (OSA) exhibit heterogeneous heart rate variability (HRV) during wakefulness and sleep. We investigated the influence of OSA severity on HRV parameters during wakefulness in a large international clinical sample. 1247 subjects (426 without OSA and 821 patients with OSA) were enrolled from the Sleep Apnea Global Interdisciplinary Consortium. HRV parameters were calculated during a 5-minute wakefulness period with spontaneous breathing prior to the sleep study, using time-domain, frequency-domain and nonlinear methods. Differences in HRV were evaluated among groups using analysis of covariance, controlling for relevant covariates. Patients with OSA showed significantly lower time-domain variations and less complexity of heartbeats compared to individuals without OSA. Those with severe OSA had remarkably reduced HRV compared to all other groups. Compared to non-OSA patients, those with severe OSA had lower HRV based on SDNN (adjusted mean: 37.4 vs. 46.2 ms; p < 0.0001), RMSSD (21.5 vs. 27.9 ms; p < 0.0001), ShanEn (1.83 vs. 2.01; p < 0.0001), and Forbword (36.7 vs. 33.0; p = 0.0001). While no differences were found in frequency-domain measures overall, among obese patients there was a shift to sympathetic dominance in severe OSA, with a higher LF/HF ratio compared to obese non-OSA patients (4.2 vs. 2.7; p = 0.009). Time-domain and nonlinear HRV measures during wakefulness are associated with OSA severity, with severe patients having remarkably reduced and less complex HRV. Frequency-domain measures show a shift to sympathetic dominance only in obese OSA patients. Thus, HRV during wakefulness could provide additional information about cardiovascular physiology in OSA patients. A Prospective Observational Cohort to Study the Genetics of Obstructive Sleep Apnea and Associated Co-Morbidities (German Clinical Trials Register - DKRS, DRKS00003966) https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00003966.

Is jaw muscle activity impaired in adults with persistent temporomandibular disorders? A systematic review and meta-analysis.

Understanding jaw muscle activity changes in temporomandibular disorders (TMD) is crucial to guide clinical management. The nature of these changes is currently unclear. Explore changes in jaw muscle activity in TMD. Electronic databases (PubMed, EMBASE, CINAHL, Scopus, Web of Science, Cochrane) and bibliographies were searched from inception to 9 July 2020 for eligible studies, including grey literature. Case-control and interventional studies reporting time-domain and frequency-domain electromyographic measures of jaw muscle activity in TMD and control groups were included. SIGN checklist for case-control studies was used to evaluate risk of bias. Results were pooled for meta-analysis using random-effects model. Confidence in cumulative evidence was established using American Academy of Neurology guidelines. Forty-five studies were included. Most were rated moderate risk of bias. Activity of four muscles (masseter, temporalis, lateral pterygoid, suprahyoids) was assessed across six domains (resting, clenching, chewing, swallowing, concentrating, resisted mandibular movements), with partial meta-analysis scope. Masseter and temporalis activity were significantly higher at rest (P=.05, P<.0001), but lower during brief maximal clenching (P=.005, P=.04) in TMD vs controls. Insufficient data precluded meta-analysis of remaining outcomes and subgroup analysis. Confidence in cumulative evidence ranged from moderate to very low. Changes in jaw muscle activity exist in TMD, which are both task-specific and muscle-specific. It remains unclear whether jaw muscle activity changes vary between TMD subgroups. Muscle function should be considered in clinical management of TMD. Insufficient subgroup data highlight future direction for research.

A numerical fitting routine for frequency-domain thermoreflectance measurements of nanoscale material systems having arbitrary geometries

In this work, we develop a numerical fitting routine to extract multiple thermal parameters using frequency-domain thermoreflectance (FDTR) for materials having non-standard, non-semi-infinite geometries. The numerical fitting routine is predicated on either a 2D or 3D finite element analysis that permits the inclusion of non-semi-infinite boundary conditions, which cannot be considered in the analytical solution to the heat diffusion equation in the frequency domain. We validate the fitting routine by comparing it with the analytical solution to the heat diffusion equation used within the wider literature for FDTR and known values of thermal conductivity for semi-infinite substrates (SiO2, Al2O3, and Si). We then demonstrate its capacity to extract the thermal properties of Si when etched into micropillars that have radii on the order of the pump beam. Experimental measurements of Si micropillars with circular and square cross sections are provided and fit using the numerical fitting routine established as part of this work. Likewise, we show that the analytical solution is unsuitable for the extraction of thermal properties when the geometry deviates significantly from the standard semi-infinite case. This work is critical for measuring the thermal properties of materials having arbitrary geometries, including ultra-drawn glass fibers and laser gain media.

Sensitivity of frequency-domain optical measurements to brain hemodynamics: simulations and human study of cerebral blood flow during hypercapnia.

This study characterizes the sensitivity of noninvasive measurements of cerebral blood flow (CBF) by using frequency-domain near-infrared spectroscopy (FD-NIRS) and coherent hemodynamics spectroscopy (CHS). We considered six FD-NIRS methods: single-distance intensity and phase (SDI and SDϕ), single-slope intensity and phase (SSI and SSϕ), and dual-slope intensity and phase (DSI and DSϕ). Cerebrovascular reactivity (CVR) was obtained from the relative change in measured CBF during a step hypercapnic challenge. Greater measured values of CVR are assigned to a greater sensitivity to cerebral hemodynamics. In a first experiment with eight subjects, CVRSDϕ was greater than CVRSDI (p < 0.01), whereas CVRDSI and CVRDSϕ showed no significant difference (p > 0.5). In a second experiment with four subjects, a 5 mm scattering layer was added between the optical probe and the scalp tissue to increase the extracerebral layer thickness (L ec ), which caused CVRDSϕ to become significantly greater than CVRDSI (p < 0.05). CVRSS measurements yielded similar results as CVRDS measurements but with a greater variability, possibly resulting from instrumental artifacts in SS measurements. Theoretical simulations with two-layered media confirmed that, if the top (extracerebral) layer is more scattering than the bottom (brain) layer, the relative values of CVRDSI and CVRDSϕ depend on L ec . Specifically, the sensitivity to the brain is greater for DSI than DSϕ for a thin extracerebral layer (L ec < 13 mm), whereas it is greater for DSϕ than DSI for a thicker extracerebral layer.

Connectedness in International Crude Oil Markets

This paper proposes study framework that investigates the globalization–regionalization debate using both the time domain and frequency domain measures of connectedness. Seven international global crude oil benchmarks are used to analyse whether crude oil market is globalized or regionalized. To this end, we first utilize the Bayesian inference of dynamic correlation in multivariate factor stochastic framework proposed by Kastner et al. (Sparse Bayesian time-varying covariance estimation many dimensions, 2017. arXiv:1608.08468 ). Next, we employ the Diebold and Yilmaz (Int J Forecast 28:57–66, 2012) and Barunik and Krehlik (J Financ Econom, 2018. http://doi.org/10.1093/jjfinec/nby001Barunik ) spillover indices to analyse the connectedness among the set of oil prices under consideration. The period of the study is 15/05/1996 to 07/03/2018. The dynamic correlation results reveal persistent correlation between different pairs of crude oil market over the whole sample period. The overall connectedness results indicate that crude oil market is well integrated. The volatility spillover results show that Forcado is the most affected by shocks from other markets. The return series of Brent at all frequencies appear to be the main source of volatility transmission in crude oil market. The results of overall connectedness show that connectedness is similar across frequencies. These findings are very important from the perspective of understanding the connectedness of global oil market.

Identifying DQ-Domain Admittance Models of a 2.3-MVA Commercial Grid-Following Inverter via Frequency-Domain and Time-Domain Data

In this paper, we present two methods to identify the admittance of a 2.3-MVA commercial grid-following inverter through frequency-domain data and time-domain data. In addition to the well-known harmonic injection method to obtain the admittance at frequency points followed by vector fitting, we adopt a step response-based method where the step response data of the converter are collected and their s-domain expressions are obtained. In turn, the s-domain admittance model of the converter is found. The two methods can be used for cross validation. Step responses and frequency-domain responses obtained from the two methods are compared. Results show that the time-domain data-based method leads to an admittance comparable with that from the frequency-domain measurement in the range less than 60 Hz. In addition, two insights are obtained from the frequency-domain admittance measurements. First, when the dq-frame is aligned to the point of common coupling (PCC) voltage, the per unit DQ-domain admittance directly reflects operating conditions. Second, existence of negative-sequence control can be detected via sequence-domain admittances.

Determining the Electrical Charging Speed Limit of ReRAM Devices

Redox-based random-access memory (ReRAM) has the potential to successfully address the technological barriers that today's memory technologies face. One of its promising features is its fast switching speed down to 50 ps. Identifying the limiting process of the switching speed is, however, difficult. At sub-nanosecond timescales three candidates are being discussed: An intrinsic limitation, being the migration of mobile donor ions, e.g., oxygen vacancies, the heating time, and its electrical charging time. Usually, coplanar waveguides (CPW) are used to bring the electrical stimuli to the device. Based on the data of previous publications, we show, that the rise time of the effective electrical stimulus is mainly responsible for limiting the switching speed at the sub-nanosecond timescale. For this purpose, frequency domain measurements up to 40 GHz were conducted on three Pt\TaO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> \Ta devices with different sizes. By multiplying the obtained scattering parameters of these devices with the Fourier transform of the incoming signal, and building the inverse Fourier transform of this product, the voltage at the ReRAM device can be determined. Finally, the rise time of the voltage at the ReRAM device is calculated, which is a measure to the electrical charging time. It was shown that this rise time amounts to 2.5 ns for the largest device, which is significantly slower than the pulse generator's rise time. Reducing the device's rise time down to 66 ps is possible, but requires smaller features sizes and other optimizations, which we summarize in this paper.

Review on Electrolytic Conductivity Sensors

Electrolytic conductivity (EC) sensors are widely used in diverse industries, including: pharmaceuticals, food, power, manufacturing, and environmental monitoring. This article presents an overview and analysis of EC sensors used in these industries from the lowest to the highest range of conductivities and in applications, where there are strong requirements for accurate and traceable conductivity measurements of water and electrolyte solutions. Included are reported sensor designs based on two- and four-electrodes with parallel plates, coaxial cylinders, van der Pauw configurations, planar and miniature configurations, and contactless inductive or capacitive coupling. A comprehensive list of exact analytical formulas for computation of cell constants for the configurations is provided. The advantages and disadvantages of using frequency domain or time domain measurement schemes in these sensors are discussed, and the reader is guided to select the suitable method of sensor calibration among the methods available, computing uncertainty budgets, ensuring traceability to the International System of Units (SI) and compliance with standards, such as Pharmacopeias. Finally, trends in the development of EC sensors and the related challenges in relation to calibration and compliance with standards are presented. This article also introduces the reader to the EC cell of a sensor, which can be modeled by solving the Poisson-Nernst-Planck equations or using appropriate equivalent circuit diagrams. It is stepwise described how the models can be extended to include effects such as electrode polarization and steric effects of ions, and it is illustrated by means of an ideal EC cell, where guards eliminate fringe fields, that the simplest equivalent circuit with a single resistor and a single capacitor models electrolytic sensor data very well in the lower range of electrolytic conductivities.

Fourier Multiplexed Fluorescence Lifetime Imaging.

Fluorescence lifetime imaging microscopy (FLIM) is a widely used functional imaging method in bioscience. Fourier multiplexed FLIM (FmFLIM), a frequency-domain lifetime measurement method, explores the principle of Fourier (frequency) multiplexing to achieve parallel lifetime detection on multiple fluorescence labels. Combining FmFLIM with a confocal scanning microscope allows multiplexed 3D lifetime imaging of cells and tissues. FmFLIM can also be integrated with the scanning laser tomography imaging method to perform 3D multiplex lifetime imaging of whole embryos and thick tissues.

A Comparison of Time-Domain and Frequency-Domain Microwave Imaging of Experimental Targets

An existing forward-backward time-stepping (FBTS) time-domain quantitative imaging algorithm is augmented with a discontinuous Galerkin method (DGM) forward solver. The resulting DGM-FBTS imaging algorithm is capable of solving the electromagnetic inverse scattering problem using high-order expansions of the fields and unknown target constitutives, decoupling the solution from the unstructured grid. DGM-FBTS provides a time-domain alternative to our previous development of flexible DGM-based frequency-domain imaging codes, and enables us to present a comparison of the performance of time-domain and frequency-domain imaging algorithms for synthetic and experimental targets. For experimental targets, a procedure for obtaining calibrated time-domain data from frequency-domain broadband VNA-collected data is explained and applied to a system with a reduced number of transmitters and receivers to highlight the potential benefits of time-domain methods. Results highlight the potential capabilities of time-domain experimental imaging using the same hardware configuration used to collect broadband frequency-domain measurements and suggest future work on hybrid frequency- and time-domain imaging algorithms and efforts to improve the computational performance of DGM-FBTS.

Frequency-Domain Data-Driven Controller Synthesis for Unstable LPV Systems

Abstract Synthesizing controllers directly from frequency-domain measurement data is a powerful tool in the linear time-invariant framework. Ever-increasing performance requirements necessitate extending these approaches to account for plant variations. The aim of this paper is to develop frequency-domain analysis and synthesis conditions for local internal stability and H∞-performance of single-input single-output linear parameter-varying systems. The developed synthesis procedure only requires frequency-domain measurement data of the system and does not need a parametric model of the plant. The capabilities of the synthesis procedure are demonstrated on an unstable nonlinear system.

Conversion of Scattering Parameters to Time-Domain for Imaging Applications: Rules and Examples

This article discusses the conversion of scattering parameters from an antenna input port to time domain for imaging applications. Frequency-domain measurements offer some advantages to time-domain methods, and the complex data encoded in the scattering matrix convey target geometric and material information which can be later used to reproduce the scene image illuminated by the antenna. Three different examples using the inverse discrete Fourier transform are discussed. Trade-offs in the data acquisition, bandwidth, sampling and topics related to the antennas used as probes are covered.

On negative induced polarization in frequency domain measurements

SUMMARY Induced polarization (IP) has been widely used to non-invasively characterize electrical conduction and polarization in the subsurface resulting from an applied electric field. Earth materials exhibit a lossy capacitance defined by a negative intrinsic phase in frequency-domain IP (FDIP) or a positive intrinsic chargeability in time-domain IP (TDIP). However, error-free positive apparent phase or negative apparent chargeability (i.e. negative IP effects) can occur in IP measurements over heterogeneous media. While negative IP effects in TDIP data sets have been discussed, no studies have addressed this topic in detail for FDIP measurements. We describe theory and numerical modelling to explain the origin of negative IP effects in FDIP measurements. A positive apparent phase may occur when a relatively high polarizability feature falls into negative sensitivity zones of complex resistivity measurements. The polarity of the apparent phase is determined by the distribution of subsurface intrinsic phase and resistivity, with the resistivity impacting the apparent phase polarity via its control on the sensitivity distribution. A physical explanation for the occurrence of positive apparent phase data is provided by an electric circuit model representing a four-electrode measurement. We also show that the apparent phase polarity will be frequency dependent when resistivity changes significantly with frequency (i.e. in the presence of significant IP effects). Consequently, negative IP effects manifest themselves in the shape of apparent phase spectra recorded with multifrequency (spectral IP) data sets. Our results imply that positive apparent phase measurements should be anticipated and should be retained during inversion and interpretation of single frequency and spectral IP data sets.

Time-Domain Measurement-Based $DQ$-Frame Admittance Model Identification for Inverter-Based Resources

Unprecedented dynamic phenomena appear in power grids due to integration of more and more inverter-based resources (IBR). A major challenge is that inverter models are proprietary information and usually only real code models are provided to grid operators. Thus, measurement based characterization of IBR is a popular approach to find the frequency-domain measurements of an IBR's admittance or impedance. The predominant methods rely on injecting perturbation and extracting frequency-domain information via fast Fourier transform (FFT). The goal of this research is to design time-domain measurement-based admittance identification methods so that event data can be utilized for online admittance identification. The proposed method has a key step: converting $dq$ -frame voltage and current transient responses into $s$ -domain expressions using eigensystem realization algorithm (ERA) or dynamic mode decomposition (DMD). From there, $s$ -domain admittance or frequency-domain admittance measurement will be computed. Proof of concept is first demonstrated using the data generated from an analytical model representing a grid-integrated IBR. The identified admittance is shown to be the exact match of the known admittance in the subsynchronous frequency range. The identified $s$ -domain admittance is employed for eigenvalue analysis and accurate stability prediction can be made. The tool is then tested on two electromagnetic transient (EMT) computer simulation testbeds: a PV grid-integration system and a type-4 wind grid-integration system. In the first case, offline admittance identification is demonstrated. In the second case, online admittance identification using data from two events is demonstrated.

Heart Rate Variability in Children With Autism Spectrum Disorder and Associations With Medication and Symptom Severity.

Decreased heart rate variability (HRV) is considered a common marker of autonomic dysfunction that contributes to poor health outcomes. While some studies have suggested that children with autism spectrum disorder (ASD) show reduced HRV, research is yet to consider whether this may be associated with medication use and symptom severity. This study examined the relationship between resting state HRV, medication use and symptom severity in children diagnosed with ASD. Children with ASD (N = 86), aged between 3 and 12 years (M = 8.09), were compared to 44 neurotypical children of similar age (M = 7.15). Laboratory assessment of HRV involved 5 min of non-invasive baseline electrocardiogram assessments while participants viewed an age-appropriate non-verbal animated video. Time-domain and frequency-domain HRV measures were analyzed. ASD symptom severity was assessed using the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) and Social Responsiveness Scale (SRS-2). Results indicated that children with ASD exhibited reduced resting HRV relative to neurotypical children. Subsequent analyses within the ASD group suggested that this group difference was greater in children who were taking psychotropic medication (N = 36). Our data also provides tentative evidence of a relationship between HRV and social impairment symptoms in children with ASD, with more severe repetitive behaviors (as measured by the ADOS-2) associated with decreased resting HRV. Overall, these findings suggest that HRV may be atypical in children with ASD and suggest the importance of exploring HRV as a risk factor for cardiovascular health in this group. LAY SUMMARY: Cardiac activity, such as heart rate variability (HRV), can provide insight into the autonomic nervous system. This study reports on the association between resting-state HRV and autonomic nervous system activity in young children with autism spectrum disorder (ASD) compared to neurotypical children. These results may help us understand what underlies autonomic nervous system dysfunction and the potential pathophysiological mechanisms leading to increased cardiovascular risk in ASD.

Sex Differences in Time-Domain and Frequency-Domain Heart Rate Variability Measures of Fatigued Drivers.

The effects of fatigue on a driver’s autonomic nervous system (ANS) were investigated through heart rate variability (HRV) measures considering the difference of sex. Electrocardiogram (ECG) data from 18 drivers were recorded during a simulator-based driving experiment. Thirteen short-term HRV measures were extracted through time-domain and frequency-domain methods. First, differences in HRV measures related to mental state (alert or fatigued) were analyzed in all subjects. Then, sex-specific changes between alert and fatigued states were investigated. Finally, sex differences between alert and fatigued states were compared. For all subjects, ten measures showed significant differences (Mann-Whitney U test, p < 0.01) between different mental states. In male and female drivers, eight and four measures, respectively, showed significant differences between different mental states. Six measures showed significant differences between males and females in an alert state, while ten measures showed significant sex differences in a fatigued state. In conclusion, fatigue impacts drivers’ ANS activity, and this impact differs by sex; more differences exist between male and female drivers’ ANS activity in a fatigued state than in an alert state.

Deep learning with wearable based heart rate variability for prediction of mental and general health

The ubiquity and commoditisation of wearable biosensors (fitness bands) has led to a deluge of personal healthcare data, but with limited analytics typically fed back to the user. The feasibility of feeding back more complex, seemingly unrelated measures to users was investigated, by assessing whether increased levels of stress, anxiety and depression (factors known to affect cardiac function) and general health measures could be accurately predicted using heart rate variability (HRV) data from wrist wearables alone. Levels of stress, anxiety, depression and general health were evaluated from subjective questionnaires completed on a weekly or twice-weekly basis by 652 participants. These scores were then converted into binary levels (either above or below a set threshold) for each health measure and used as tags to train Deep Neural Networks (LSTMs) to classify each health measure using HRV data alone. Three data input types were investigated: time domain, frequency domain and typical HRV measures. For mental health measures, classification accuracies of up to 83% and 73% were achieved, with five and two minute HRV data streams respectively, showing improved predictive capability and potential future wearable use for tracking stress and well-being.