Low Complexity Spectral Analysis of Heart-Rate-Variability through a Wavelet based FFT

In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interestingly we show that the proposed approach enables the classification of processed data into more and less significant based on their contribution to output quality. Based on such a classification a percentage of less-significant data is being pruned leading to a significant reduction of algorithmic complexity with minimal quality degradation. Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system.

Respiratory and non-respiratory sinus arrhythmia: implications for heart rate variability

The quantity of blood arriving at the left side of the heart oscillates throughout the breathing cycle due to the mechanics of breathing. Neurally regulated fluctuations in the length of the heart period act to dampen oscillations of the left ventricular stroke volume entering the aorta. We have reported that stroke volume oscillations but not spectral frequency variability stroke volume measures can be used to estimate the breathing frequency. This study investigated with the same recordings whether heart period oscillations or spectral heart rate variability measures could function as estimators of breathing frequency. Continuous 270 s cardiovascular recordings were obtained from 22 healthy adult volunteers in the supine and upright postures. Breathing was recorded simultaneously. Breathing frequency and heart period oscillation frequency were calculated manually, while heart rate variability spectral maximums were obtained using heart rate variability software. These estimates were compared to the breathing frequency using the Bland–Altman agreement procedure. Estimates were required to be \±10% (95% levels of agreement). The 95% levels of agreement measures for the heart period oscillation frequency (supine: -27.7 to 52.0%, upright: -37.8 to 45.9%) and the heart rate variability spectral maximum estimates (supine: -48.7 to 26.5% and -56.4 to 62.7%, upright: -37.8 to 39.3%) exceeded 10%. Multiple heart period oscillations were observed to occur during breathing cycles. Both respiratory and non-respiratory sinus arrhythmia was observed amongst healthy adults. This observation at least partly explains why heart period parameters and heart rate variability parameters are not reliable estimators of breathing frequency. In determining the validity of spectral heart rate variability measurements we suggest that it is the position of the spectral peaks and not the breathing

Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains

The aim of the present study was to compare heart rate variability (HRV) at rest and during exercise using a temporal series obtained with the Polar S810i monitor and a signal from a LYNX® signal conditioner (BIO EMG 1000 model) with a channel configured for the acquisition of ECG signals. Fifteen healthy subjects aged 20.9 ± 1.4 years were analyzed. The subjects remained at rest for 20 min and performed exercise for another 20 min with the workload selected to achieve 60% of submaximal heart rate. RR series were obtained for each individual with a Polar S810i instrument and with an ECG analyzed with a biological signal conditioner. The HRV indices (rMSSD, pNN50, LFnu, HFnu, and LF/HF) were calculated after signal processing and analysis. The unpaired Student t-test and intraclass correlation coefficient were used for data analysis. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV at rest and during exercise. The intraclass correlation coefficient demonstrated satisfactory correlation between the values obtained by the devices at rest (pNN50 = 0.994; rMSSD = 0.995; LFnu = 0.978; HFnu = 0.978; LF/HF = 0.982) and during exercise (pNN50 = 0.869; rMSSD = 0.929; LFnu = 0.973; HFnu = 0.973; LF/HF = 0.942). The calculation of HRV values by means of temporal series obtained from the Polar S810i instrument appears to be as reliable as those obtained by processing the ECG signal captured with a signal conditioner.

Fractal correlation property of heart rate variability in chronic obstructive pulmonary disease

Background: It was reported that autonomic nervous system function is altered in subjects with chronic obstructive pulmonary disease (COPD). We evaluated short-and long-term fractal exponents of heart rate variability (HRV) in COPD subjects.Patients and methods: We analyzed data from 30 volunteers, who were divided into two groups according to spirometric values: COPD (n = 15) and control (n = 15). For analysis of HRV indices, HRV was recorded beat by beat with the volunteers in the supine position for 30 minutes. We analyzed the linear indices in the time (SDNN [standard deviation of normal to normal] and RMSSD [root-mean square of differences]) and frequency domains (low frequency [LF], high frequency [HF], and LF/HF), and the short-and long-term fractal exponents were obtained by detrended fluctuation analysis. We considered P < 0.05 to be a significant difference.Results: COPD patients presented reduced levels of all linear exponents and decreased short-term fractal exponent (alpha-1: 0.899 +/- 0.18 versus 1.025 +/- 0.09, P = 0.026). There was no significant difference between COPD and control groups in alpha-2 and alpha-1/alpha-2 ratio.Conclusion: COPD subjects present reduced short-term fractal correlation properties of HRV, which indicates that this index can be used for risk stratification, assessment of systemic disease manifestations, and therapeutic procedures to monitor those patients.

Nonlinear methods of heart rate variability analysis in diabetes

Background: The autonomic dysfunction stands out among the complications associated to diabetes mellitus (DM) and may be evaluated through the heart rate variability (HRV), a noninvasive tool to investigate the autonomic nervous system that provides information of health impairments and may be analyzed by using linear and nonlinear methods. Several studies have shown that HRV measured in a linear form is altered in DM. Nevertheless, a few studies investigate the nonlinear behavior of HRV. Therefore, this study aims at gathering information regarding the autonomic changes in subjects with DM identified by nonlinear analysis of HRV.Methods: For that, searches were performed on Medline, SciELO, Lilacs and Cochrane databases using the crossing between the key-words: diabetic autonomic neuropathy, autonomic nervous system, diabetes mellitus and heart rate variability. As inclusion criteria, articles published on a period from 2000 to 2010 with DM type land type II population which assessed the autonomic nervous system by nonlinear indices HRV were considered.Results: The electronic search resulted in a total of 1873 references with the exclusion of 1623 titles and abstracts and from the 250 abstracts remaining, 8 studies were selected to the final analysis that completed the inclusion criteria.Conclusions: In general, the analysis showed that the nonlinear techniques of HRV allowed detecting autonomic changes in DM. The methods of nonlinear analysis are indicated as a possible tool to be used for early diagnosis and prognosis of autonomic dysfunction in DM.

A snoring classifier based on heart rate variability analysis

The effect of snoring on the cardiovascular system is not well-known. In this study we analyzed the Heart Rate Variability (HRV) differences between light and heavy snorers. The experiments are done on the full-whole-night polysomnography (PSG) with ECG and audio channels from patient group (heavy snorer) and control group (light snorer), which are gender- and age-paired, totally 30 subjects. A feature Snoring Density (SND) of audio signal as classification criterion and HRV features are computed. Mann-Whitney statistical test and Support Vector Machine (SVM) classification are done to see the correlation. The result of this study shows that snoring has close impact on the HRV features. This result can provide a deeper insight into the physiological understand of snoring. © 2011 CCAL.

Poincaré plot indexes of heart rate variability: Relationships with other nonlinear variables

The Poincaré plot for heart rate variability analysis is a technique considered geometrical and non-linear, that can be used to assess the dynamics of heart rate variability by a representation of the values of each pair of R-R intervals into a simplified phase space that describes the system's evolution. The aim of the present study was to verify if there is some correlation between SD1, SD2 and SD1/SD2 ratio and heart rate variability nonlinear indexes either in disease or healthy conditions. 114 patients with arterial coronary disease and 65 healthy subjects underwent 30. minute heart rate registration, in supine position and the analyzed indexes were as follows: SD1, SD2, SD1/SD2, Sample Entropy, Lyapunov Exponent, Hurst Exponent, Correlation Dimension, Detrended Fluctuation Analysis, SDNN, RMSSD, LF, HF and LF/HF ratio. Correlation coefficients between SD1, SD2 and SD1/SD2 indexes and the other variables were tested by the Spearman rank correlation test and a regression analysis. We verified high correlation between SD1/SD2 index and HE and DFA (α1) in both groups, suggesting that this ratio can be used as a surrogate variable. © 2013 Elsevier B.V.

The effects of auditory stimulation with music on heart rate variability in healthy women

OBJECTIVES: There are no data in the literature with regard to the acute effects of different styles of music on the geometric indices of heart rate variability. In this study, we evaluated the acute effects of relaxant baroque and excitatory heavy metal music on the geometric indices of heart rate variability in women. METHODS: We conducted this study in 21 healthy women ranging in age from 18 to 35 years. We excluded persons with previous experience with musical instruments and persons who had an affinity for the song styles. We evaluated two groups: Group 1 (n = 21), who were exposed to relaxant classical baroque musical and excitatory heavy metal auditory stimulation; and Group 2 (n = 19), who were exposed to both styles of music and white noise auditory stimulation. Using earphones, the volunteers were exposed to baroque or heavy metal music for five minutes. After the first music exposure to baroque or heavy metal music, they remained at rest for five minutes; subsequently, they were re-exposed to the opposite music (70-80 dB). A different group of women were exposed to the same music styles plus white noise auditory stimulation (90 dB). The sequence of the songs was randomized for each individual. We analyzed the following indices: triangular index, triangular interpolation of RR intervals and Poincaré plot (standard deviation of instantaneous beat-by-beat variability, standard deviation of the long-term RR interval, standard deviation of instantaneous beat-by-beat variability and standard deviation of the long-term RR interval ratio), low frequency, high frequency, low frequency/high frequency ratio, standard deviation of all the normal RR intervals, root-mean square of differences between the adjacent normal RR intervals and the percentage of adjacent RR intervals with a difference of duration greater than 50 ms. Heart rate variability was recorded at rest for 10 minutes. RESULTS: The triangular index and the standard deviation of the long-term RR interval indices were reduced during exposure to both music styles in the first group and tended to decrease in the second group whereas the white noise exposure decreased the high frequency index. We observed no changes regarding the triangular interpolation of RR intervals, standard deviation of instantaneous beat-by-beat variability and standard deviation of instantaneous beat-by-beat variability/standard deviation in the long-term RR interval ratio. CONCLUSION: We suggest that relaxant baroque and excitatory heavy metal music slightly decrease global heart rate variability because of the equivalent sound level.

Influence of the resistance training on heart rate variability, functional capacity and muscle strength in the chronic obstructive pulmonary disease

Background. The chronic obstructive pulmonary disease (COPD) is associated with the strength and resistance decreasing in addition to the dysfunction on autonomic nervous system (ANS). The aerobic training isolated or in association with the resistance training showed evidence of beneficial effects on an autonomic modulation of COPD; however, there are no studies addressing the effect of isolated resistance training.Aims. This study aims at investigating the influence of resistance training on an autonomic modulation through heart rate variability (HRV), functional capacity and muscle strength in individuals with COPD.Design. Clinical series study.Setting. Outpatients.Population. The study involved 13 individuals with COPD.Methods. The experimental protocol was composed by an initial and final evaluation that consisted in autonomic evaluations (HRV), cardiopulmonary functional capacity evaluation (6-minute walk test) and strength evaluation (dynamometry) in addition by the resistance training performed by 24 sessions lasted 60 minutes each one and on a frequency of three times a week. The intensity was determined initially with 60% of one maximum repetition and was progressively increased in each five sessions until 80%.Results. The HRV temporal and spectral indexes analysis demonstrates improvement of autonomic modulation, with significant statistical increases to sympathetic and parasympathetic components of ANS representing by SDNN, LF and HF. In addition, it was observed significant statistical increases to shoulder abduction and. knee flexion strength and functional capacity.Conclusion. The exclusive resistance training performed was able to positively influence the autonomic modulation; in addition it promoted benefits on cardiorespiratory functional capacity and strength benefits in individuals with COPD.Clinical Rehabilitation Impact. This study could contribute to clinical and professionals researchers that act with COPD, even though the resistance component of pulmonary rehabilitation presents consensual benefits on several healthy indicators parameters. There is no evidence about the effects on HRV before. Moreover, this study showed, on clinical practice, the HRV uses as an ANS activity on sinus node evaluation and highlights further importance on scientific context.