Frequency-domain Measurements Research Articles

Does electronic cigarette use adversely affect cardiac autonomic function?

Introduction: tobacco cigarette (TC) smoking is a predominant risk factor for cardiovascular disease and a leading preventable cause of death (Kondo et al., 2019, Circ J, 83, 1980-1985). Electronic Cigarette (EC) use has increased significantly in recent years (King et al., 2015, Nic Tob Res, 17, 219-227), mainly as it is considered a safer alternative to TC. A low heartrate variability (HRV) is an independent marker of adverse cardiovascular morbidity and all-cause mortality (Fang et al., 2020, Bio Res Nur, 22, 45-56). TC smokers have a lower HRV, and similar responses have now also been observed in EC smokers (Arastoo et al., 2020, Am J Physiol Heart Circ Physiol, 319, 262-270). However, the influence of cognitive / psychological stress on HRV in TC and EC users remains unexplored. As such, this study aims to assess the impact of cognitive stress on Time and Frequency domain measures of HRV. Methods: upon receiving ethical approval, HRV data was collected through electrocardiogram (ECG) recordings of healthy controls (HC), TC and EC smokers which were recorded using lead II ECG at 1000 Hz on LabChart during periods of rest (5 min) and cognitive stress (serial subtraction; 5 min). Time and frequency domain measures of HRV were assessed with LabChart. Data will be compared between groups using one-way analysis of variance (ANOVA) and two-way mixed methods ANOVA as appropriate. Conclusions: we hypothesise that EC smokers will present similar impaired autonomic function and reduced HRV as TC smokers during rest and cognitive stress in comparison to HC.

Lifestyle Intervention Improves Parasympathetic Activity in Hypertrophic Cardiomyopathy

Background A limited number of studies have investigated the effects of lifestyle interventions in hypertrophic cardiomyopathy (HCM). This study evaluated the effect of a novel lifestyle intervention incorporating physical activity (PA) and dietary nitrate supplementation on heart rate variability (HRV) and haemodynamic measures in HCM. Methods Twenty-eight individuals with HCM were randomised into either the intervention or control group. Frequency-domain HRV measures including low frequency power (LF), high frequency power (HF) and LF/HF were recorded at rest using bioimpedance. Non-invasive haemodynamic variables were recorded at rest using bioreactance. Participants in the intervention group consumed 6 mmol of nitrate daily (concentrated beetroot juice) and were instructed to increase and maintain daily PA by ≥ 2000 steps/day above baseline for 16 weeks. Control group participants retained their usual lifestyle and monitored daily step counts. Results There was a significant increase in post-intervention HF power (7.54 ± 2.14 vs 8.78 ± 1.60 ms2, P < .01) and LF power (6.89 ± 2.33 vs 8.17 ± 1.55, P < .01) in the intervention but not in the control group. Resting mean arterial blood pressure (MABP) in the intervention group significantly reduced at follow-up (108 ± 6 vs 102 ± 7 mmHg, P < .01). Conclusions A novel lifestyle intervention including PA and dietary nitrate supplementation enhanced parasympathetic activity and resting MABP in HCM.

Enhancing rational approximation of wideband resonant MIMO systems with frequency-domain data

Vector Fitting (VF) is a successful methodology for both time and frequency domain estimation of dynamic systems. These algorithms have gained popularity as a system identification tool due to their ability to provide a practical procedure for accurately approximating the measured frequency response behavior of complex and highly resonant dynamic systems using rational models. Instrumental Variable (IV) techniques can also be added to the VF algorithm to enhance the optimality of the solutions in the presence of measurement noise. In this context, this paper presents a multiple-input multiple-output (MIMO) generalization of instrumental variable (IV-)VF. The proposed algorithm can be applied to accurately estimating models formed by either continuous- or discrete-time rational basis functions (RBFs). We show that such a generalization preserves the main implementation features observed in Standard VF, but with improved optimality property for its solutions. Additionally, in order to alleviate convergence problems that may arise from the fixed high-frequency normalization, we also present in this paper how to incorporate in the proposed IV-VF method the relaxed formulation found in standard VF for both the continuous and discrete-time cases. The resulting MIMO IV-VF algorithm can be easily understood by VF users, and its applicability is discussed by using an estimation case study with two power system pieces of equipment (an 88 kV Transformer and a 550 kV Instrument Transformer) for which actual frequency domain measurements were collected in the field. It is shown that the proposed algorithm significantly improves the modeling accuracy when compared to standard VF algorithms.

An improvement in block matching algorithms using a dissimilarity measure in frequency domain transform

In this work, the image block matching based on dissimilarity measure is investigated. Moreover, an unsupervised approach is implemented to yield that the algorithms have low complexity (in numbers of operations) compared to the full search algorithm. The state-of-the-art experiments only use discrete cosine transform as a domain transform. In addition, some images were tested to evaluate the algorithms. However, these images were not evaluated according to specific characteristics. So, in this paper, an improved version is presented to tackle the problem of dissimilarity measure in block matching with a noisy environment, using another’s domain transforms or low-pass filters to obtain a better result in block matching implementing a quantitive measure with an average accuracy margin of ± 0.05 is obtained. The theoretical analysis indicates that the complexity of these algorithms is still accurate, so implementing Hadamard spectral coefficients and Fourier filters can easily be adjusted to obtain a better accuracy of the matched block group.

A Prebiotic Diet Increases Cardiovascular Adaptability Under Hypergravity-Induced Stress

Life in space presents significant challenges to mammalian physiology and the longer one is in space, the greater the impact. Three major stressors are present in space: 1) changes in gravitational environment, 2) psychological/physiological stress, and 3) constant low dose radiation. It is critical, therefore, to discover interventions that promote stress resilience. Dietary prebiotics selectively increase the relative abundances of probiotic bacterial species in the gut. We have previously reported that a diet enriched in galactooligosaccharide (GOS) and polydextrose (PDX) compared to control diet robustly elevates parabacteroides distasonis, clostridium leptum, and reduces the negative impact of acute and chronic stress. Interoceptors (e.g., baroreceptors) sense gravity-induced changes in blood pressure and cardiac function/structure. There is evidence that hypergravity disrupts autonomic and cardiovascular homeostasis and function. Cardiovascular homeostasis depends on a sympathetic and parasympathetic balance reflected in heart rate variability (HRV), a measure of cardiovascular stress. The following study was designed to test the hypothesis that GOS+PDX reduces the cardiovascular impacts of living in an altered gravitational environment. Adult female mice were housed in 1G or 3G and were fed GOS+PDX or a matched control diet for 4 weeks on the NASA Ames 1.22-meter radius centrifuge. We recorded electrocardiograms (ECG) in animals from all four groups immediately before, halfway through, and immediately after centrifugation. We analyzed HRV data using a Python-based Jupyter notebook and R. R was used to perform a 1F-LD-1F ANOVA with pair-wise comparisons to quantify changes in HRV longitudinally. Classic time domain based HRV metrics, standard deviation of the successive differences between adjacent R-R intervals and standard deviation of NN intervals, showed little change over time. Instead, frequency domain measures showed results were housing in 3G compared to 1G reliably changed Shannon entropy, Sample entropy, and low to high frequency ratio at each time-point. The changes across time reflected adaptation to hypergravity and a consequent reduction in HRV. Poincare plot analysis and low to high frequency ratio metrics showed divergent compensatory reactions between diets at 3G. Overall, 3G impacted HRV less in mice that were fed the prebiotic diet compared to the control diet. Further longitudinal studies with greater temporal resolution are needed to assess changes in HRV caused by gravitational changes. However, our data suggests the prebiotic diet significantly reduces 3G activation of sympathetic drive and increases parasympathetic drive, potentially reducing cardiovascular stress in animals exposed to high gravity. NASA grant 80NSSC19K1038 funded this project. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Exploratory analysis of spontaneous versus paced breathing on heart rate variability in veterans with combat-related traumatic injury.

Respiration is a crucial determinant of autonomic balance and heart rate variability (HRV). The comparative effect of spontaneous versus paced breathing on HRV has been almost exclusively explored in healthy adults and never been investigated in an injured military cohort. To examine the effect of spontaneous versus paced breathing on HRV in veterans with combat-related traumatic injury (CRTI). Observational cohort study. ArmeD serVices trAuma rehabilitatioN outComE (ADVANCE) study, Stanford Hall, UK. The sample consisted of 100 randomly selected participants who sustained CRTI (eg, amputation) during their deployment (Afghanistan 2003-2014) and were recruited into the ongoing ADVANCE prospective cohort study. Not applicable. HRV was recorded using a single-lead ECG. HRV data were acquired during a sequential protocol of 5-minute spontaneous breathing followed immediately by 5 minutesof paced breathing (six cycles/minute) among fully rested and supine participants. HRV was reported using time domain (root mean square of successive differences), frequency domain (low frequency and high frequency) and nonlinear (sample entropy) measures. The agreement between HRV during spontaneous versus paced breathing was examined using the Bland-Altman analysis. The mean age of participants was 36.5 ± 4.6 years. Resting respiratory rate was significantly higher with spontaneous versus paced breathing (13.4 ± 3.4 vs. 7.6 ± 2.0 breaths/minute; p < .001), respectively. Resting mean heart rate and root mean square of successive differences were significantly higher with paced breathing than spontaneous breathing (p < .001). Paced breathing significantly increased median low frequency power than spontaneous breathing (p < .001). No significant difference was found in the absolute power of high frequency between the two breathing protocols. The Bland-Altman analysis revealed poor agreement between HRV values during spontaneous and paced breathing conditions with wide limits of agreement. Slow-paced breathing leads to higher HRV than spontaneous breathing and could overestimate resting "natural-state" HRV.

Prediction and Detection of Ventricular Fibrillation Using Complex Features and AI-Based Classification

We analyzed the possibility of detecting and predicting ventricular fibrillation (VF), a medical emergency that may put people’s lives at risk, as the medical prognosis depends on the time in which medical personnel intervene. Therefore, besides immediate detection of VF, the possibility of predicting VF 40 or even 50 min in advance was analyzed. For testing the proposed algorithm, we used ECG signals taken from the MIT-BIH database, namely, Malignant Ventricular Ectopy Database, Sudden Cardiac Death Holter Database and Normal Sinus Rhythm Database. The presented method is based on features extracted from the ECG signals in the time domain, frequency domain and complexity measures. For VF detection, the possibility of identifying the VF episode in the first 3 s after its occurrence was tested. For this, the first 3 s immediately after the appearance of VF were cut out and the features were computed on these sections. For VF prediction, 3 min of the ECG signal clipped 40 or 50 min before VF onset was used. Then, on these pieces of ECG signal, the specific features were calculated for 1 s segments. For the normal signal situation, 3 min was randomly selected from the database with normal ECGs. For the classification or detection stage, both an MLP-type neural network and the classifiers from the Machine Learning toolbox of the MATLAB® environment were used. The results obtained for both detection and classification are over 94% in both cases. The novelty of our results compared to those previously obtained is the time interval with which the possibility of prediction was analyzed, namely, 50 min in advance of the VF installation date. This means that the patient will be informed that it is possible to suffer a VF and has time to take the necessary measures to overcome a possible medical emergency.

359 Low-Intensity Focused Ultrasound to Human Dorsal Anterior Cingulate Cortex and Insula Attenuates Measures of Central Sensitization

INTRODUCTION: Central sensitization is the abnormal amplified response to pain and is associated with chronic pain. Increased insula and dorsal anterior cingulate cortex (dACC) activity is associated with central sensitization. Low-intensity focused ultrasound (LIFU) is a novel form of non-invasive neuromodulation that can precisely target the anterior insula (AI), posterior insula (PI) and dACC. METHODS: N = 18 healthy participants underwent conditioned pain modulation (CPM) and temporal summation of pain (TSP) tasks before and after 10 minutes of LIFU or sham stimulations. For CPM, the conditioning stimulus (CS) was a cold pressor test to the left hand and the test stimulus (TS) was a brief transient heat stimulus to the dorsum of the right hand. For TSP, 10 transient heat stimuli (&gt;0.33 Hz) were administered to the dorsum of the right hand. The primary outcome measure for both tasks was perceived pain ratings (0-9). Electrodermal response and electrocardiogram was collected to evaluate the effect of LIFU on autonomic reactivity. RESULTS: LIFU to PI increased CPM 0.5 ± 0.181 compared to sham (p = 0.024). LIFU to PI also significantly reduced perceived pain during the TSP task compared to sham (p &lt; 0.001). We also found a significant difference between dACC and sham conditions during TSP by -0.55 ± 0.05 (p &lt; 0.001). LIFU to the AI increases frequency domain measures of heart-rate variability. CONCLUSIONS: LIFU to the insula and dACC affects pain processing in measures of central sensitization. This demonstrates the neuromodulation abilities of LIFU and is a promising tool to develop noninvasive clinical therapies for chronic pain conditions.

Winding Response under Difference Effective Inductance for Single Phase High Voltage Transformer

Early studies of transformer winding parameters were focused on the determination via its physical dimensions and empirical formulas. In most cases it is divided into several parts namely coil section pairs, coils distance, disc coils diameter and thickness of insulation. Maxwell’s equations are often the solution to the problem, which satisfy related boundary conditions between conductors for mutual inductance and capacitor equations. Such solutions often led to errors and hence its mathematical model. To counter the problem, it was suggested that such approximations must be conducted with experimental model windings at the same time. Frequency domain measurements and time domain measurements can be conducted to effectively determine these parameters. This in turn will investigate the behaviour of transformer winding electromagnetic transient at high frequency. From theoretical point of view, predominantly capacitive winding model often considered to represent its behaviour at high frequency and will give the results of its initial distribution. Under this consideration, a single phase plain winding is considered for investigation. A single rectangular wave was considered to represent infinitive impinge incident wave, injected at one end of transformer winding and the measured response signals of the wavetail were considered for measurement. The experimental response and modelling results were compared and proved to have high agreement between the two.

Work stress and changes in heart rate variability among employees after first acute coronary syndrome: a hospital-based longitudinal cohort study.

Work stress is considered as a risk factor for coronary heart disease, but its link with heart rate variability (HRV) among heart attack survivors is unknown yet. The aim of this study was to investigate associations between baseline work stress and the changes of HRV over one-year after onset of acute coronary syndrome (ACS). Hundred and twenty-two patients with regular paid work before their first ACS episode were recruited into this hospital-based longitudinal cohort study. During hospitalization (baseline), all patients underwent assessments of work stress by job strain (JS) and effort-reward imbalance (ERI) models, and were assigned into low or high groups; simultaneously, sociodemographic and clinical data, as well depression, anxiety, and job burnout, were collected. Patients were followed up 1, 6, and 12 months after discharge, with HRV measurements at baseline and each follow-up point. Generalized estimating equations were used to analyze the effects of baseline work stress on HRV over the following 1 year. After adjusting for baseline characteristics and clinical data, anxiety, depression, and burnout scores, high JS was not associated with any HRV measures during follow-up (all p > 0.10), whereas high ERI was significantly related to slower recovery of 5 frequency domain HRV measures (TP, HF, LF, VLF, and ULF) (all p < 0.001), and marginally associated with one time domain measure (SDNN) (p = 0.069). When mutually adjusting for both work stress models, results of ERI remained nearly unchanged. Work stress in terms of ERI predicted lower HRV during the one-year period after ACS, especially frequency domain measures.

Heart Rate Variability and Pulse Rate Variability: Do Anatomical Location and Sampling Rate Matter?

Wearable technology and neuroimaging equipment using photoplethysmography (PPG) have become increasingly popularized in recent years. Several investigations deriving pulse rate variability (PRV) from PPG have demonstrated that a slight bias exists compared to concurrent heart rate variability (HRV) estimates. PPG devices commonly sample at ~20-100 Hz, where the minimum sampling frequency to derive valid PRV metrics is unknown. Further, due to different autonomic innervation, it is unknown if PRV metrics are harmonious between the cerebral and peripheral vasculature. Cardiac activity via electrocardiography (ECG) and PPG were obtained concurrently in 54 participants (29 females) in an upright orthostatic position. PPG data were collected at three anatomical locations: left third phalanx, middle cerebral artery, and posterior cerebral artery using a Finapres NOVA device and transcranial Doppler ultrasound. Data were sampled for five minutes at 1000 Hz and downsampled to frequencies ranging from 20 to 500 Hz. HRV (via ECG) and PRV (via PPG) were quantified and compared at 1000 Hz using Bland-Altman plots and coefficient of variation (CoV). A sampling frequency of ~100-200 Hz was required to produce PRV metrics with a bias of less than 2%, while a sampling rate of ~40-50 Hz elicited a bias smaller than 20%. At 1000 Hz, time- and frequency-domain PRV measures were slightly elevated compared to those derived from HRV (mean bias: ~1-8%). In conjunction with previous reports, PRV and HRV were not surrogate biomarkers due to the different nature of the collected waveforms. Nevertheless, PRV estimates displayed greater validity at a lower sampling rate compared to HRV estimates.

Development, Validation, and Comparison of a Novel Nociception/Anti-Nociception Monitor against Two Commercial Monitors in General Anesthesia.

In this paper, we present the development and the validation of a novel index of nociception/anti-nociception (N/AN) based on skin impedance measurement in time and frequency domain with our prototype AnspecPro device. The primary objective of the study was to compare the Anspec-PRO device with two other commercial devices (Medasense, Medstorm). This comparison was designed to be conducted under the same conditions for the three devices. This was carried out during total intravenous anesthesia (TIVA) by investigating its outcomes related to noxious stimulus. In a carefully designed clinical protocol during general anesthesia from induction until emergence, we extract data for estimating individualized causal dynamic models between drug infusion and their monitored effect variables. Specifically, these are Propofol hypnotic drug to Bispectral index of hypnosis level and Remifentanil opioid drug to each of the three aforementioned devices. When compared, statistical analysis of the regions before and during the standardized stimulus shows consistent difference between regions for all devices and for all indices. These results suggest that the proposed methodology for data extraction and processing for AnspecPro delivers the same information as the two commercial devices.

Robust fingerprint recognition approach based on diagonal slice of polyspectra in the polar space

Although fingerprint recognition is a mature technology and nowadays commercial state-of-the-art systems can be successfully used in a number of real applications, not all the problems have been solved and the research is still very active in the field. This paper presents a new approach for estimating the shift and rotation parameters between fingerprint images stored in the dadabase that operates in the third-order frequency-domain measure called the auto-bispectrum, which, allows us to estimate the shift and the rotation separately. The diagonal slices and their spectra of auto- and cross-bispectrum are proposed. The rotation parameters are estimated from the remaining polar sampled the third-order spectrum using cross-correlation, and then, after compensating for rotation, we may easily estimate the translational component, e.g., by using phase correlation.Experimental evidence of this performance is presented, and the mathematical reasons behind these characteristics are explained in depth. We compare our approach in a simulation to other frequency-domain fingerprint recognition algorithms. We find that our algorithm can better estimate shift and rotation parameters than the other methods.

Real-time breast lesion classification combining diffuse optical tomography frequency domain data and BI-RADS assessment.

Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated potential for breast cancer diagnosis, in which real-time or near real-time diagnosis with high accuracy is desired. However, DOT's relatively slow data processing and image reconstruction speeds have hindered real-time diagnosis. Here, we propose a real-time classification scheme that combines US breast imaging reporting and data system (BI-RADS) readings and DOT frequency domain measurements. A convolutional neural network is trained to generate malignancy probability scores from DOT measurements. Subsequently, these scores are integrated with BI-RADS assessments using a support vector machine classifier, which then provides the final diagnostic output. An area under the receiver operating characteristic curve of 0.978 is achieved in distinguishing between benign and malignant breast lesions in patient data without image reconstruction.

Air-coupled ultrasound for testing of batteries and components

This work describes the use of an air-coupled and through transmission ultrasonic (0.2–1.5 MHz) technique, both at normal and oblique incidence, for the characterization and test of pouch-cell Li-ion (and similar types) batteries and components. Time domain measurements show that it is possible to measure ultrasonic velocity in the battery. Frequency domain measurements reveal the generation of thickness resonances. From them, solution of the inverse problem permit to extract: ultrasound velocity and attenuation (and variation with frequency), thickness and density. At normal incidence, these resonances provide information about the compressional wave. At oblique incidence, it is first observed that there is a range of incidence angles where propagation is no permitted. This response can be explained in terms of the battery layered structure, once these angles are exceeded, the shear wave is generated, propagated and observed, giving rise to the generation of thickness resonances. Shear wave propagation is strongly anisotropic: lower velocity in the direction of the battery plane, compared with a higher velocity in the direction normal to the battery plane. No limit angle for the shear wave is observed. Possibilities of this technique for the testing of new batteries, continuous state monitoring and battery sorting for re-use or recycling are discussed.

Assessment of Drivers' Mental Workload by Multimodal Measures during Auditory-Based Dual-Task Driving Scenarios.

Assessing drivers' mental workload is crucial for reducing road accidents. This study examined drivers' mental workload in a simulated auditory-based dual-task driving scenario, with driving tasks as the main task, and auditory-based N-back tasks as the secondary task. A total of three levels of mental workload (i.e., low, medium, high) were manipulated by varying the difficulty levels of the secondary task (i.e., no presence of secondary task, 1-back, 2-back). Multimodal measures, including a set of subjective measures, physiological measures, and behavioral performance measures, were collected during the experiment. The results showed that an increase in task difficulty led to increased subjective ratings of mental workload and a decrease in task performance for the secondary N-back tasks. Significant differences were observed across the different levels of mental workload in multimodal physiological measures, such as delta waves in EEG signals, fixation distance in eye movement signals, time- and frequency-domain measures in ECG signals, and skin conductance in EDA signals. In addition, four driving performance measures related to vehicle velocity and the deviation of pedal input and vehicle position also showed sensitivity to the changes in drivers' mental workload. The findings from this study can contribute to a comprehensive understanding of effective measures for mental workload assessment in driving scenarios and to the development of smart driving systems for the accurate recognition of drivers' mental states.

Domain-wall dark pulse generation with SMF-GIMF-SMF structure as artificial saturable absorber

We experimentally demonstrated the generation of domain-wall dark pulse in an Erbium-doped fiber laser using the combination of a 10 cm graded index multimode fiber sandwiched by single mode fibers as artificial saturable absorber. The interaction of phase difference in grade index multimode fiber allowed the stable dual-wavelength oscillation in the cavity. The dual-wavelength centered at 1567.2 nm and 1569.4 nm produces the topological defect in temporal domain and achieved a dark pulse formation with repetition rate of 21.5 MHz. The highest average pulse energy is calculated as 769.6 pJ with pulse width of 5 ns. Throughout the operating pump power range, the average pulse energy and output power increase linearly, with R2 of 0.9999 and achieved the laser efficiency of 9.33%. From the measurement in frequency domain, the signal-to-noise ratio is measured as 49 dB. As compared to reported DW dark pulse works, the proposed structure only required a short length of multimode fiber, which allowed the domain-wall dark pulse to achieve higher pulse repetition rate. The venture of domain wall dark pulse is potentially to pave the foundation toward sustainable industrial growth.

Combustion characteristics of diisopropoxymethane, a low-reactivity oxymethylene ether

Oxymethylene ethers (OMEs) have been studied for use as low-sooting diesel fuel additives or substitutes; very little literature discusses OMEs as spark-ignition (SI) fuels due to their typically high cetane numbers. In this work, a lower-reactivity, branched OME, diisopropoxymethane (DIPM), is evaluated to determine its effectiveness as a spark-ignition fuel, as it is the lowest-reactivity OME (as determined by Indicated Cetane Number) thus far evaluated in the literature. DIPM is synthesized in-house via acetalization from isopropanol (iPrOH) and trioxane using standard OME production practices. DIPM was then tested in a rapid compression machine (RCM) for autoignition and spark ignition characteristics, and in a modified CFR engine to determine effective octane numbers. In the RCM, an autoignition temperature sweep was performed at stoichiometric conditions from 1000/T = 1.7 - 1.0, at 5:1 inert ratio (comparable to approximately 25% EGR), where it was found that DIPM has ignition delay times 5–10x faster than isooctane and displays NTC ignition behavior. Blends with iPrOH indicate that reactivity can be matched with isooctane with low blend ratios of iPrOH in DIPM. Flame speeds were tested with a laser spark for ignition in the RCM, where the flame speed of DIPM and isooctane is determined to be comparable at engine relevant conditions. In the CFR engine, effective RON and MON based on pressure trace frequency domain measurements were determined for DIPM and a 15 vol% iPrOH in DIPM blend. Neat DIPM has (R+M)/2 = 59 and a negative sensitivity of S = -18, consistent with its NTC behavior and higher reactivity. The DIPM/iPrOH blend has positive sensitivity and a pump-gasoline range (R+M)/2 = 89.3. DIPM on its own is unlikely to be an effective SI fuel, however, when blended with iPrOH as an ON booster, it may be a promising SI candidate fuel.

Assessment of Autonomic Nervous System Activity Using Spectral Analysis of Heart Rate Variability After Continuous Positive Airway Pressure (CPAP) Therapy in Patients With Sleep Apnea.

Heart rate variability (HRV) measurements have emerged as a valuable tool for understanding the functioning of the autonomic nervous system (ANS) and assessing the health outcomes of obstructive sleep apnea (OSA) in patients. Sleep and the ANS exert a mutual influence on each other. Sleep promotes relaxation and recovery of the ANS. Conversely, ANS activity plays a role in regulating the onset and maintenance of sleep. The impact of continuous positive airway pressure (CPAP) therapy on patient recovery levels was investigated by assessing the restoration of ANS activity using HRV indicators. The study included patients with OSA who had been on CPAP for at least eight weeks. The patients were divided into two groups, namely the experimental group (CPAP-compliant) and the control group (CPAP-non-compliant). The study included a total of 38 patients, with 20 in the CPAP-compliant group and 18 in the CPAP-non-compliant group. The HRV analysis included time- and frequency-domain measures. Data was collected in various resting conditions, including lying down, standing, regular breathing, and under physiological stress induced by deep breathing and the Valsalva maneuver. After CPAP treatment, there was an increase in the average values for SDNN for deep breathing and Valsalva maneuvers. The mean changes in SDNN for CPAP-non-compliant versus CPAP-compliant groups for normal breathing increased from 32.50±5.33 to 42.40±8.03, while the values for Valsalva increased from 20.16±2.47 to 25.45±3.03. Despite the observed variations in SDNN, there was no significant change in the average change in heart rate (∆ HR), except during the Valsalva maneuver. Post-CPAP values for the Valsalva ratio were significantly decreased in deep breathing. The E:I ratio for the CPAP-compliant group during normal breathing was 1.08±.16 compared to 1.55±.09; t (36) =-11.15, p <0.001 in the CPAP-non-compliant group. During deep breathing, the ratio was 1.36±.15 versus 1.59±.24; t (36) =-3.578, p <0.001. The high frequency (HF)nu mean values for deep breathing were 34.06±5.546 compared to 35.00±6.358; t (36) = -.485, p=.630. For the Valsalva maneuver, the values were 29.94±4.721 versus 26.95±6.621; t (36) =1.589, p=.060. The HF/low frequency (LF) ratio was found to be significant only in supine, standing, and normal breathing. The utilization of CPAP therapy was found to be effective in achieving and sustaining autonomic balance during tasks like standing and engaging in regular breathing patterns. During activities that involve intense physical effort, like the Valsalva maneuver, the HRV metrics did not indicate any significant balance between sympathetic and parasympathetic activity. However, using CPAP therapy for a prolonged period can be beneficial in consistently improving the sympathovagal balance in these patients.

A cross-sectional comparative assessment of diabetic autonomic neuropathy using heart rate variability and galvanic skin response – Effect of disease progression

Background: Type 2 diabetes mellitus (T2DM) poses a significant health-care challenge and is a primary contributor to both mortality and morbidity. Diabetic autonomic neuropathy (DAN) is a frequently occurring complication associated with diabetes mellitus. Autonomic nerve damage leading to cardiac autonomic dysfunction and peripheral sympathetic neuropathy can lead to changes in heart rate variability (HRV) and galvanic skin resistance (GSR), respectively. Aims and Objectives: The study was designed and done to evaluate the impact of T2DM on HRV and GSR for assessing DAN. Materials and Methods: A total of 100 individuals diagnosed with T2DM (cases) and 100 healthy individuals (controls) participated in this study. Physio Pac (PC-2004) was used to record the necessary data. Statistical analysis was performed using the non-parametric Mann–Whitney test to see the comparison of the cases and controls. In addition, to measure the statistical relationship between the duration of the disease and the HRV and GSR parameters, Spearman’s rank correlation coefficient was utilized. The study received approval from the Ethical and Research Committee at the Government Medical College, Patiala. Results: Significant statistical differences were observed between the cases and controls in all time domain measures, as well as GSR and the majority of frequency domain measures of HRV. The correlation analysis revealed a strong association between the duration of T2DM and a decrease in HRV as well as an increase in GSR. Conclusion: The findings from the present study provide evidence that T2DM has an impact on HRV, which suggests the presence of cardiac autonomic neuropathy among diabetic patients, leading to an increased risk of cardiovascular morbidity. In addition, the study indicates that reduced sudomotor function, as assessed by Galvanic Skin Resistance (GSR), serves as a predictive measure for autonomic neuropathy. Therefore, these tests can serve as valuable tools in facilitating the assessment of DAN.