142 research outputs found
Effects of bright light treatment on psychomotor speed in athletes
Purpose: A recent study suggests that transcranial brain targeted light treatment via ear canals may have physiological effects on brain function studied by functional magnetic resonance imaging (fMRI) techniques in humans. We tested the hypothesis that bright light treatment could improve psychomotor speed in professional ice hockey players. Methods: Psychomotor speed tests with audio and visual warning signals were administered to a Finnish National Ice Hockey League team before and after 24 days of transcranial bright light or sham treatment. The treatments were given during seasonal darkness in the Oulu region (latitude 65 degrees north) when the strain on the players was also very high (10 matches during 24 days). A daily 12-min dose of bright light or sham (n = 11 for both) treatment was given every morning between 8â12 am at home with a transcranial bright light device. Mean reaction time and motor time were analyzed separately for both psychomotor tests. Analysis of variance for repeated measures adjusted for age was performed. Results: Time x group interaction for motor time with a visual warning signal was p = 0.024 after adjustment for age. In Bonferroni post-hoc analysis, motor time with a visual warning signal decreased in the bright light treatment group from 127 ± 43 to 94 ± 26 ms (p = 0.024) but did not change significantly in the sham group 121 ± 23 vs. 110 ± 32 ms (p = 0.308). Reaction time with a visual signal did not change in either group. Reaction or motor time with an audio warning signal did not change in either the treatment or sham group. Conclusion: Psychomotor speed, particularly motor time with a visual warning signal, improves after transcranial bright light treatment in professional ice-hockey players during the competition season in the dark time of the year
Postexercise Heart Rate Recovery in Adults Born Preterm
Objective To evaluate postexercise heart rate recovery (HRR) in adults born preterm. Study design We studied the association between preterm birth and postexercise HRR in 545 adults (267 women) at 23.3 years of age (range 19.9-26.3 years). One hundred three participants were born early preterm ( Results Mean peak HR was 159.5 bpm in the early preterm (P = .16 with controls), 157.8 bpm in the late preterm (P = .56), and 157.0 bpm in the control group. Mean HRR 30 seconds after exercise was 3.2 bpm (95% CI 1.1-5.2) lower in the early preterm group and 2.1 bpm (0.3-3.8) lower in the late preterm group than the full term controls. Mean 60s HRR was 2.5 (-0.1 to 5.1) lower in the early preterm group and 2.8 bpm (0.6-4.9) lower in the late preterm group. Mean maximum slope after exercise was 0.10 beats/s (0.02-0.17) lower in the early preterm group and 0.06 beats/s (0.00-0.12) lower in the late preterm group. Conclusions Our results suggest reduced HRR after exercise in adults born preterm, including those born late preterm. This suggests altered reactivation of the parasympathetic nervous system, which may contribute to cardiovascular risk among adults born preterm.Peer reviewe
Heart Rate Dynamics after Exercise in Cardiac Patients with and without Type 2 Diabetes
Purpose: The incidence of cardiovascular events is higher in coronary artery disease patients with type 2 diabetes (CADâ+âT2D) than in CAD patients without T2D. There is increasing evidence that the recovery phase after exercise is a vulnerable phase for various cardiovascular events. We hypothesized that autonomic regulation differs in CAD patients with and without T2D during post-exercise condition. Methods: A symptom-limited maximal exercise test on a bicycle ergometer was performed for 68 CADâ+âT2D patients (age 61â±â5âyears, 78% males, ejection fraction (EF) 67â±â8, 100% on ÎČ-blockade), and 64 CAD patients (age 62â±â5âyears, 80% males, EF 64â±â8, 100% on ÎČ-blockade). Heart rate (HR) recovery after exercise was calculated as the slope of HR during the first 60âs after cessation of exercise (HRRslope). RâR intervals were measured before (5âmin) and after exercise from 3 to 8âmin, both in a supine position. RâR intervals were analyzed using time and frequency methods and a detrended fluctuation method (α1). Results: BMI was 30â±â4 vs. 27â±â3âkgâm2 (pâ<â0.001); maximal exercise capacity, 6.5â±â1.7 vs. 7.7â±â1.9 METs (pâ<â0.001); maximal HR, 128â±â19 vs. 132â±â18âbpm (pâ=âns); and HRRslope, â0.53â±â0.17 vs. â0.62â±â0.15âbeats/s (pâ=â0.004), for CAD patients with and without T2D, respectively. There was no differences between the groups in HRRslope after adjustment for METs, BMI, and medication (ANCOVA, pâ=â0.228 for T2D and, e.g., pâ=â0.030 for METs). CADâ+âT2D patients had a higher HR at rest than non-diabetic patients (57â±â10 vs. 54â±â6âbpm, pâ=â0.030), but no other differences were observed in HR dynamics at rest or in post-exercise condition. Conclusion: HR recovery is delayed in CADâ+âT2D patients, suggesting impairment of vagal activity and/or augmented sympathetic activity after exercise. Blunted HR recovery after exercise in diabetic patients compared with non-diabetic patients is more closely related to low exercise capacity and obesity than to T2D itself
Hypertension Does Not Alter the Increase in Cardiac Baroreflex Sensitivity Caused by Moderate Cold Exposure
Inhomogeneous point-process entropy: an instantaneous measure of complexity in discrete systems
Measures of entropy have been widely used to characterize complexity, particularly in physiological dynamical systems modeled in discrete time. Current approaches associate these measures to finite single values within an observation window, thus not being able to characterize the system evolution at each moment in time. Here, we propose a new definition of approximate and sample entropy based on the inhomogeneous point-process theory. The discrete time series is modeled through probability density functions, which characterize and predict the time until the next event occurs as a function of the past history. Laguerre expansions of the Wiener-Volterra autoregressive terms account for the long-term nonlinear information. As the proposed measures of entropy are instantaneously defined through probability functions, the novel indices are able to provide instantaneous tracking of the system complexity. The new measures are tested on synthetic data, as well as on real data gathered from heartbeat dynamics of healthy subjects and patients with cardiac heart failure and gait recordings from short walks of young and elderly subjects. Results show that instantaneous complexity is able to effectively track the system dynamics and is not affected by statistical noise properties
Loss of lag-response curvilinearity of indices of heart rate variability in congestive heart failure
BACKGROUND: Heart rate variability (HRV) is known to be impaired in patients with congestive heart failure (CHF). Time-domain analysis of ECG signals traditionally relies heavily on linear indices of an essentially non-linear phenomenon. Poincaré plots are commonly used to study non-linear behavior of physiologic signals. Lagged Poincaré plots incorporate autocovariance information and analysis of Poincaré plots for various lags can provide interesting insights into the autonomic control of the heart. METHODS: Using Poincaré plot analysis, we assessed whether the relation of the lag between heart beats and HRV is altered in CHF. We studied the influence of lag on estimates of Poincaré plot indices for various lengths of beat sequence in a public domain data set (PhysioNet) of 29 subjects with CHF and 54 subjects with normal sinus rhythm. RESULTS: A curvilinear association was observed between lag and Poincaré plot indices (SD1, SD2, SDLD and SD1/SD2 ratio) in normal subjects even for a small sequence of 50 beats (p value for quadratic term 3 à 10(-5), 0.002, 3.5 à 10(-5 )and 0.0003, respectively). This curvilinearity was lost in patients with CHF even after exploring sequences up to 50,000 beats (p values for quadratic term > 0.5). CONCLUSION: Since lagged Poincaré plots incorporate autocovariance information, these analyses provide insights into the autonomic control of heart rate that is influenced by the non-linearity of the signal. The differences in lag-response in CHF patients and normal subjects exist even in the face of the treatment received by the CHF patients
A family based tailored counselling to increase non-exercise physical activity in adults with a sedentary job and physical activity in their young children: design and methods of a year-long randomized controlled trial
Background.
Epidemiological evidence suggests that decrease in sedentary behaviour is beneficial for health. This family based randomized controlled trial examines whether face-to-face delivered counselling is effective in reducing sedentary time and improving health in adults and increasing moderate-to-vigorous activities in children.
Methods.
The families are randomized after balancing socioeconomic and environmental factors in the JyvÀskylÀ region, Finland. Inclusion criteria are: healthy men and women with children 3-8 years old, and having an occupation where they self-reportedly sit more than 50% of their work time and children in all-day day-care in kindergarten or in the first grade in primary school. Exclusion criteria are: body mass index > 35 kg/m2, self-reported chronic, long-term diseases, families with pregnant mother at baseline and children with disorders delaying motor development.
From both adults and children accelerometer data is collected five times a year in one week periods. In addition, fasting blood samples for whole blood count and serum metabonomics, and diurnal heart rate variability for 3 days are assessed at baseline, 3, 6, 9, and 12 months follow-up from adults. Quadriceps and hamstring muscle activities providing detailed information on muscle inactivity will be used to realize the maximum potential effect of the intervention. Fundamental motor skills from children and body composition from adults will be measured at baseline, and at 6 and 12 months follow-up. Questionnaires of family-influence-model, health and physical activity, and dietary records are assessed. After the baseline measurements the intervention group will receive tailored counselling targeted to decrease sitting time by focusing on commute and work time. The counselling regarding leisure time is especially targeted to encourage toward family physical activities such as visiting playgrounds and non-built environments, where children can get diversified stimulation for play and practice fundamental of motor skills. The counselling will be reinforced during the first 6 months followed by a 6-month maintenance period.
Discussion.
If shown to be effective, this unique family based intervention to improve lifestyle behaviours in both adults and children can provide translational model for community use. This study can also provide knowledge whether the lifestyle changes are transformed into relevant biomarkers and self-reported health.
Trial registration number.
ISRCTN: ISRCTN28668090peerReviewe
Chaotic Signatures of Heart Rate Variability and Its Power Spectrum in Health, Aging and Heart Failure
A paradox regarding the classic power spectral analysis of heart rate variability (HRV) is whether the characteristic high- (HF) and low-frequency (LF) spectral peaks represent stochastic or chaotic phenomena. Resolution of this fundamental issue is key to unraveling the mechanisms of HRV, which is critical to its proper use as a noninvasive marker for cardiac mortality risk assessment and stratification in congestive heart failure (CHF) and other cardiac dysfunctions. However, conventional techniques of nonlinear time series analysis generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level. Here, we apply a âlitmus testâ for heartbeat chaos based on a novel noise titration assay which affords a robust, specific, time-resolved and quantitative measure of the relative chaos level. Noise titration of running short-segment Holter tachograms from healthy subjects revealed circadian-dependent (or sleep/wake-dependent) heartbeat chaos that was linked to the HF component (respiratory sinus arrhythmia). The relative âHF chaosâ levels were similar in young and elderly subjects despite proportional age-related decreases in HF and LF power. In contrast, the near-regular heartbeat in CHF patients was primarily nonchaotic except punctuated by undetected ectopic beats and other abnormal beats, causing transient chaos. Such profound circadian-, age- and CHF-dependent changes in the chaotic and spectral characteristics of HRV were accompanied by little changes in approximate entropy, a measure of signal irregularity. The salient chaotic signatures of HRV in these subject groups reveal distinct autonomic, cardiac, respiratory and circadian/sleep-wake mechanisms that distinguish health and aging from CHF
Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics
Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis
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