Search NASA⌕ Search

SEARCH · Search NASA

Results for “HEART”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

Effects of Vibration and G-Loading on Heart Rate, Breathing Rate, and Response Time

Aerospace and applied environments commonly expose pilots and astronauts to G-loading and vibration, alone and in combination, with well-known sensorimotor (Cohen, 1970) and performance consequences (Adelstein et al., 2008). Physiological variables such as heart rate (HR) and breathing rate (BR) have been shown to increase with G-loading (Yajima et al., 1994) and vibration (e.g. Guignard, 1965, 1985) alone. To examine the effects of G-loading and vibration, alone and in combination, we measured heart rate and breathing rate under aerospace-relevant conditions (G-loads of 1 Gx and 3.8 Gx; vibration of 0.5 gx at 8, 12, and 16 Hz).

Godinez, Angelica↗

Uncertainty in Heart Rate Complexity Metrics Caused by R-Peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Napoli, Nicholas J.↗

Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, it is found that for subjects at high risk of sudden death (e.g., congestive heart failure patients), these long-range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic.

NASA Discipline Cardiopulmonary↗

Effects of moderate heart failure and functional overload on rat plantaris muscle

It is thought that changes in sarco(endo)plasmic reticulum Ca(2+)-ATPase (SERCA) of skeletal muscle contribute to alterations in skeletal muscle function during congestive heart failure (CHF). It is well established that exercise training can improve muscle function. However, it is unclear whether similar adaptations will result from exercise training in a CHF patient. Therefore, the purpose of this study was to determine whether skeletal muscle during moderate CHF adapts to increased activity, utilizing the functional overload (FO) model. Significant increases in plantaris mass of the CHF-FO and sham-FO groups compared with the CHF and control (sham) groups were observed. Ca(2+) uptake rates were significantly elevated in the CHF group compared with all other groups. No differences were detected in Ca(2+) uptake rates between the CHF-FO, sham, and sham-FO groups. Increases in Ca(2+) uptake rates in moderate-CHF rats were not due to changes in SERCA isoform proportions; however, FO may have attenuated the CHF-induced increases through alterations in SERCA isoform expression. Therefore, changes in skeletal muscle Ca(2+) handling during moderate CHF may be due to alterations in regulatory mechanisms, which exercise may override, by possibly altering SERCA isoform expression.

Non-NASA Center↗

Blood flow dynamics in heart failure

BACKGROUND: Exercise intolerance in heart failure (HF) may be due to inadequate vasodilation, augmented vasoconstriction, and/or altered muscle metabolic responses that lead to fatigue. METHODS AND RESULTS: Vascular and metabolic responses to rhythmic forearm exercise were tested in 9 HF patients and 9 control subjects (CTL) during 2 protocols designed to examine the effect of HF on the time course of oxygen delivery versus uptake (protocol 1) and on vasoconstriction during exercise with 50 mm Hg pressure about the forearm to evoke a metaboreflex (protocol 2). In protocol 1, venous lactate and H+ were greater at 4 minutes of exercise in HF versus CTL (P<0.05) despite similar blood flow and oxygen uptake responses. In protocol 2, mean arterial pressure increased similarly in each group during ischemic exercise. In CTL, forearm blood flow and vascular conductance were similar at the end of ischemic and ambient exercise. In HF, forearm blood flow and vascular conductance were reduced during ischemic exercise compared with the ambient trial. CONCLUSIONS: Intrinsic differences in skeletal muscle metabolism, not vasodilatory dynamics, must account for the augmented glycolytic metabolic responses to moderate-intensity exercise in class II and III HF. The inability to increase forearm vascular conductance during ischemic handgrip exercise, despite a normal pressor response, suggests that enhanced vasoconstriction of strenuously exercising skeletal muscle contributes to exertional fatigue in HF.

NASA Discipline Cardiopulmonary↗