Analysis Of Heart Rate Time Series Research Articles

Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review.

Heart rate time series are widely used to characterize physiological states and athletic performance. Among the main indicators of metabolic and physiological states, the detection of metabolic thresholds is an important tool in establishing training protocols in both sport and clinical fields. This paper reviews the most common methods, applied to heart rate (HR) time series, aiming to detect metabolic thresholds. These methodologies have been largely used to assess energy metabolism and to identify the appropriate intensity of physical exercise which can reduce body weight and improve physical fitness. Specifically, we focused on the main nonlinear signal evaluation methods using HR to identify metabolic thresholds with the purpose of identifying a method which can represent a useful tool for the real-time settings of wearable devices in sport activities. While the advantages and disadvantages of each method, and the possible applications, are presented, this review confirms that the nonlinear analysis of HR time series represents a solid, robust and noninvasive approach to assess metabolic thresholds.

Time-series analysis of heart rate and blood pressure in response to changes in work rate before and after 60\xa0days of 6\xb0 head down tilt bed rest

PurposeCardiovascular regulation during exercise, described using time series analysis, is expected to be attenuated after bed rest (BR) and this effect will be dampened by a reactive jumps countermeasure.MethodsTwenty subjects (29 ± 6 years, 23.6 ± 1.7 kg m−2) were tested on a cycle ergometer 9 days (BDC-9) before the beginning of BR as well as 2 (R + 2) and 13 days (R + 13) after the end of BR, applying moderate pseudo-random binary (PRBS) work rate changes. Heart rate (HR) and mean arterial blood pressure (mBP) were measured beat-to-beat and interpolated to 1 s intervals. HR and mBP were cross-correlated [CCF(HR-mBP)] during the PRBS. Eleven subjects participated in a reactive jump countermeasure (JUMP) during the BR period, the other part of the group served as control group (CTRL).ResultsIn the CTRL group, significantly lower CCF(HR-mBP) values during BDC-9 were observed compared to R + 2 during the lags 20–25 s and significantly higher values during the lags − 39 s to − 35 s. In the JUMP group, significantly lower CCFs were only observed at R + 2 compared with BDC-9 during the lags 23 s and 24 s, whereas the CCFs for BDC-9 were significantly higher at several lags compared with R + 13.ConclusionAttenuations in the regulation of the cardiovascular system during cycling exercise after BR were found in the CTRL group of the RSL study. Cardiovascular regulation in the JUMP group was improved compared to values before the beginning of BR, suggesting the effectiveness of the reactive jumps countermeasure to mitigate the deleterious effects of prolonged BR.

Effects of Different Practice Task Constraints on Fluctuations of Player Heart Rate in Small-Sided Football Games

This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

Time-variant power spectral analysis of heart-rate time series by autoregressive moving average (ARMA) method

Frequency domain representation of a short-term heart-rate time series (HRTS) signal is a popular method for evaluating the cardiovascular control system. The spectral parameters, viz. percentage power in low frequency band (%PLF), percentage power in high frequency band (%PHF), power ratio of low frequency to high frequency (PRLH), peak power ratio of low frequency to high frequency (PPRLH) and total power (TP) are extrapolated from the averaged power spectrum of twenty-five healthy subjects, and 16 acute anterior-wall and nine acute inferior-wall myocardial infarction (MI) patients. It is observed that parasympathetic activity predominates in healthy subjects. From this observation we conclude that during acute myocardial infarction, the anterior wall MI has stimulated sympathetic activity, while the acute inferior wall MI has stimulated parasympathetic activity. Results obtained from ARMA-based analysis of heart-rate time series signals are capable of complementing the clinical examination results.