Time and Frequency Domain Analysis of Gait Initiation in Younger and Older Adults.

The purpose of study was to demonstrate age-related changes during gait initiation (GI). Therefore, displacement, velocity, total power, mean and median frequency of COP trajectories were measured during phases of GI in anteroposterior (AP) and mediolateral (ML) directions. The older group demonstrated the slower and lesser displacement in comparison with the younger group during anticipatory phase in AP direction and during locomotor phase in AP and ML directions. In addition, the median and mean frequency were greater in the older relative to the younger group during anticipatory phase in AP direction, while these were lesser in older than younger group during locomotor phase in AP and ML directions. Moreover, total power was greater among older than younger adults during the anticipatory phase in ML direction and during all phases in AP direction. This study suggests that COP-related parameters extracted from time and frequency domains have the ability to demonstrate age-related changes.

Spectral Power Distribution of Heart Rate Variability in Contiguous Short-Term Intervals.

INTRODUCTION: Heart rate variability (HRV) is determined by the variation of consecutive cardiac electrical excitations, usually from RR intervals of an EKG. The sequence of intervals is a time series that yields three HRV parameter categories: time domain, frequency domain, and nonlinear. Parameter estimates are based on widely different EKG sample times: short-term (~5-10 minutes), longer (24 hours), and ultra-short (<5 minutes). Five-minute intervals are useful to evaluate intervention effects that change HRV in a single session by comparing pre-to-post values. This approach relies on knowing the minimal detectible change (MDC) that indicates a real change in clinical and research studies. The specific aims of this pilot study were to (1) evaluate HRV power and its spectral distribution among contiguous five-minute intervals, (2) compare the power distribution in a five-minute interval with a full 45-minute assessment, and (3) provide data to aid estimation of the MDC between pre- and post-interventions during a single session.  Methods: Twelve self-reported healthy young adults participated after signing an approved consent. Participation required subjects who had no history of cardiovascular disease or were taking vasoactive substances. Persons with diabetes were not eligible. While subjects were supine, EKG leads were placed, and EKG was recorded for 45 minutes at 1000 samples/sec. The 45 minutes were divided into nine five-minute contiguous intervals, and the spectral density in each was determined. Total power and spectral percentages within each interval were assessed in the very low (VLF, 0.003-0.04 Hz), low (LF, 0.04-0.15 Hz), and high (HF, 0.15-0.4 Hz) frequency bands. These were compared among intervals and to the full 45-minute sample. The MDC was determined by comparing powers in five-minute intervals separated by 10 minutes. The standard error of the measurement (SEME) for each pair was calculated from the square root of the mean square error (√MSE). MSE was based on a two-factor analysis of variance, and MDC was 2×√2×SEME. RESULTS: Differences in total power and spectral power distribution among intervals were not statistically significant. The total mean power±SD was 4561±1434 ms². The maximum difference in total power was 7.85%. The mean power for the VLF, LF, and HF bands was respectively 1713±1736 ms², 1574±1072 ms², and 1257±1016 ms². The maximum percentage difference in spectral power across all intervals for VLF, LF, and HF was respectively 3.75%, 8.5%, and 7.4%. The percentage of power in the VLF, LF, and HF bands was respectively 37.9%, 36.1%, and 25.9%. The ratios of spectral to total power for VLF, LF, and HF bands were respectively 0.80±0.07, 1.20±0.11, and 1.22±0.10. MDC percentage values were 21.0±4.9% for the HF band, 25.7±1.4% for the LF band, and 30.4±5.5% for the VLF band. CONCLUSION: Results offer initial estimates of variations in HRV power in the VLF, LF, and HF bands in contiguous five-minute intervals and estimates of the minimum detectible "real" changes between intervals separated by 10 minutes. The pattern of variation and data are useful in experimental planning in which HRV spectral power changes are assessed subsequent to a short-duration intervention during a single session. MDC values (21.0% in the HF band to 30.4% in the VLF band) provide initial estimates useful for estimating the number of participants needed to evaluate the impact of an intervention on spectral components of HRV.

Heart Rate Variability as a Predictor of Mortality in Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

OBJECTIVE: To systematically review the medical literature to determine the utility of heart rate variability in predicting mortality for moderate to severe traumatic brain injury. METHODS: A search for randomized controlled trials, nonrandomized trials, and prospective and retrospective cohort studies was carried out using PubMed, SCOPUS, Cochrane Central Register of Controlled Trials, MEDLINE, and EMBASE. Reference lists of included studies were also searched to identify potentially eligible studies. RESULTS: Five articles comprising 542 patients met inclusion criteria. Heart rate variability as low-frequency/high-frequency ratio (area under the curve [AUC] receiver operating characteristic [ROC]) for predicting mortality was found to be statistically significant (AUC ROC 0.810, P < 0.001) with high heterogeneity (I2 = 61.98%, P = 0.032). Meta-analysis of low-frequency/high-frequency ratio, High frequency peak, and total power were statistically significant for predicting mortality. Odd's ratio for predicting mortality for LF/HF ratio, HF peak, and TP were 16.17, 19.09, 22.59 respectively. High-frequency peak in predicting mortality showed an AUC ROC of 0.986 (P ≤ 0.001) with a low level of heterogeneity. Total power (TP) showed an AUC ROC of 0.93 (P < 0.001) in predicting mortality with a high level of heterogeneity (I2 = 83.16%, P = 0.002). Funnel plot analysis to assess the presence of publication bias for TP showed a high level of heterogeneity and asymmetry among studies. CONCLUSIONS: This meta-analysis predicted high mortality based on odds ratio for variables low-frequency/high-frequency ratio, high-frequency peak, and TP. However, the statistical analysis was weakened owing to the high level of heterogeneity in the included studies. Further research is needed to generate high-quality recommendations regarding heart rate variability as a predictor of mortality after traumatic brain injury.

Non-restorative Sleep Caused by Autonomic and Electroencephalography Parameter Dysfunction Leads to Subjective Fatigue at Wake Time in Shift Workers.

Sleep is a physiological state that plays important role in the recovery of fatigue. However, the relationship between the physiological status of sleep and subjective fatigue remains unknown. In the present study, we hypothesized that the non-recovery of fatigue at wake time due to non-restorative sleep might be ascribed to changes in specific parameters of electroencephalography (EEG) and heart rate variability (HRV) in poor sleepers. Twenty healthy female shift-working nurses participated in the study. Subjective fatigue was assessed using the visual analog scale (VAS) at bedtime and wake time. During sleep on the night between 2 consecutive day shifts, the EEG powers at the frontal pole, HRV based on electrocardiograms, and distal-proximal gradient of skin temperature were recorded and analyzed. The results indicated that the subjects with high fatigue on the VAS at wake time exhibited (1) a decrease in deep non-rapid eye movement (NREM) (stageN3) sleep duration in the first sleep cycle; (2) a decrease in REM latency; (3) a decrease in ultra-slow and delta EEG powers, particularly from 30 to 65 min after sleep onset; (4) a decrease in the total power of HRV, particularly from 0 to 30 min after sleep onset; (5) an increase in the very low frequency component of HRV; and (6) a smaller increase in the distal-proximal gradient of skin temperature, than those of the subjects with low fatigue levels. The correlational and structural equation modeling analyses of these parameters suggested that an initial decrease in the total power of HRV from 0 to 30 min after sleep onset might inhibit the recovery from fatigue during sleep (i.e., increase the VAS score at wake time) via its effects on the ultra-slow and delta powers from 30 to 65 min after sleep onset, stageN3 duration in the first sleep cycle, REM latency, and distal-proximal gradient of skin temperature. These findings suggest an important role of these physiological factors in recovery from fatigue during sleep, and that interventions to modify these physiological factors might ameliorate fatigue at wake time.

A Null-Balanced Total-Power Radiometer System NCS1.

A recently developed radiometer system NCS1 is used to calibrate thermal noise temperature at any frequency between 1.0 GHz and 12.0 GHz. Any cryogenic noise source can be measured; the upper limit of noise temperatures measured without a loss of accuracy is estimated to be about 105 K. For a typical hot noise source with the noise temperature of 8400 K and a reflection coefficient magnitude of 0.1, the expanded uncertainty is ≈ 1.8%, and the system sensitivity ≈ 2 K. Implemented in Type N connector, it can be easily modified to calibrate noise sources with other coaxial connectors or waveguide flanges.

Derivation of the System Equation for Null-Balanced Total-Power Radiometer System NCS1.

A system equation of a recently developed null-balanced, total-power radiometer system is rigorously derived. Delivered noise power and temperature is related to available power (temperature) through an extension of the mismatch factor to broadband systems. The available power ratio αg, the available gain Gg and the delivered power ratio (efficiency) η1 are defined. Properties of idealized, but in principle realizable components such as an infinitely directive isolator and a lossless matched waveguide-below-cutoff attenuator are used. A cascading technique is repeatedly applied to the fundamental noise equation. Mathematically modeling the experimental procedure of sequentially attaching the two noise standards and the unknown source to the system input, we obtain the system of three equations that can be solved for the noise temperature of the unknown noise source.

Evaluation of Uncertainties of the Null-Balanced Total-Power Radiometer System NCS1.

Standard uncertainties are evaluated for the null-balanced, total-power, heterodyned radiometer system with a switched input that was recently developed at NIST to calibrate thermal noise sources. Eight significant sources of uncertainty due to systematic effects are identified, two attributable to the two noise standards, and one each to connectors, the input mismatch, the input switch asymmetry, the isolator, the broadband mismatch and the attenuator. The combined standard uncertainty of a typical coaxial noise source calibration at a representative frequency of 2 GHz is about 1%, A strategy for reducing uncertainties is discussed.

Myocardial repolarization dispersion and autonomic nerve activity in a canine experimental acute myocardial infarction model.

BACKGROUND: Evidence from a canine experimental acute myocardial infarction (MI) model shows that until the seventh week after MI, the relationship between stellate ganglion nerve activity (SGNA) and vagal nerve activity (VNA) progressively increases. OBJECTIVE: The purpose of this study was to evaluate how autonomic nervous system activity influences temporal myocardial repolarization dispersion at this period. METHODS: We analyzed autonomic nerve activity as well as QT and RR variability from recordings previously obtained in nine dogs. From a total of 48 short-term ECG segments, 24 recorded before and 24 recorded 7 weeks after experimentally-induced MI, we obtained three indices of temporal myocardial repolarization dispersion: QTe (from Q-wave to T-wave end), QTp (from Q-wave to T-wave peak), and Te (from T-wave peak to T-wave end) variability index (QTeVI, QTpVI, TeVI). We also performed heart rate variability power spectral analysis on the same segments. RESULTS: After MI, all the QT variables increased QTeVI (median [interquartile range]) (from -1.76[0.82] to -1.32[0.68]), QTeVI (from -1.90[1.01] to -1.45[0.78]), and TeVI (from -0.72[0.67] to -0.22[1.00]), whereas all RR spectral indices decreased (P <.001 for all). Distinct circadian rhythms in QTeVI (P <.05,) QTpVI (P <.001) and TeVI (P <.05) appeared after MI with circadian variations resembling that of SGNA/VNA. The morning QTpVI and TeVI acrophases approached the SGNA/VNA acrophase. Conversely, the evening QTeVI acrophase coincided with another SGNA/VNA peak. After MI, regression analysis detected a positive relationship between SGNA/VNA and TeVI (R(2): 0.077; ß: 0.278; p< 0.001). CONCLUSION: Temporal myocardial repolarization dispersion shows a circadian variation after MI reaching its peak at a time when sympathetic is highest and vagal activity lowest.

Noninvasive assessment of vascular function and hydraulic power and efficiency in pediatric Fontan patients.

BACKGROUND: Invasive studies have shown that children with Fontan palliation have abnormal arterial stiffness, impedance, and hydraulic power and efficiency. The aim of this study was to assess these indexes noninvasively in a cohort of children with Fontan circulation using Doppler echocardiography and compare their results with those of healthy peers. METHODS: This was a case-control study of 22 Fontan patients and 31 healthy control children. Using standard two-dimensional, M-mode, and Doppler echocardiographic imaging and carotid artery applanation tonometry, aortic flows, dimensions, and pulse-wave velocity were measured, and vascular impedance and arterial stiffness were calculated. Hydraulic power and efficiency were calculated from standard fluid dynamics formulae. RESULTS: The median age was similar between groups. Stroke volume index (39 vs 39 mL/min/m(2)) and cardiac index (2.6 vs 2.5 L/min/m(2)) were similar. Aortic cross-sectional area (3.3 vs 2.8 cm(2)), peak aortic flow (302 vs 261 cm(3)/sec), and myocardial performance index (0.47 vs 0.25) were higher and ejection fraction (50% vs 66%) was lower in Fontan patients. Input impedance (61 vs 83 dyne · sec/cm(5)/m(2)) was lower in Fontan patients. Pulse-wave velocity (488 vs 364 cm/sec), elastic pressure-strain modulus (305 vs 263 torr), and stiffness index (4.15 vs 3.04) were higher in Fontan patients. Total arterial compliance (1.29 vs 1.32 mL/torr/m(2)) and mean power (606 vs 527 mW/m(2)) were similar and total hydraulic power (716 vs 627 mW/m(2)) was higher in Fontan patients. Efficiency and the power cost per unit of forward flow were similar. CONCLUSIONS: Despite stiffer aortas, Fontan patients generate more hydraulic power associated with decreased ventricular function to achieve a similar hydraulic efficiency. In Fontan patients, therapy that is given to improve ventricular function may need to target vascular stiffness as well. This technique may be used to monitor the efficacy of therapeutic interventions.