A comparative analysis of preprocessing techniques of cardiac event series for the study of heart rhythm variability using simulated signals

In the present study, using noise-free simulated signals, we performed a comparative examination of several preprocessing techniques that are used to transform the cardiac event series in a regularly sampled time series, appropriate for spectral analysis of heart rhythm variability (HRV). First, a group of noise-free simulated point event series, which represents a time series of heartbeats, was generated by an integral pulse frequency modulation model. In order to evaluate the performance of the preprocessing methods, the differences between the spectra of the preprocessed simulated signals and the true spectrum (spectrum of the model input modulating signals) were surveyed by visual analysis and by contrasting merit indices. It is desired that estimated spectra match the true spectrum as close as possible, showing a minimum of harmonic components and other artifacts. The merit indices proposed to quantify these mismatches were the leakage rate, defined as a measure of leakage components (located outside some narrow windows centered at frequencies of model input modulating signals) with respect to the whole spectral components, and the numbers of leakage components with amplitudes greater than 1%, 5% and 10% of the total spectral components. Our data, obtained from a noise-free simulation, indicate that the utilization of heart rate values instead of heart period values in the derivation of signals representative of heart rhythm results in more accurate spectra. Furthermore, our data support the efficiency of the widely used preprocessing technique based on the convolution of inverse interval function values with a rectangular window, and suggest the preprocessing technique based on a cubic polynomial interpolation of inverse interval function values and succeeding spectral analysis as another efficient and fast method for the analysis of HRV signals

Circadian rhythms in blood pressure in free-ranging three-toed sloths (Bradypus variegatus)

Blood pressure (BP) profiles were monitored in nine free-ranging sloths (Bradypus variegatus) by coupling one common carotid artery to a BP telemetry transmitter. Animals moved freely in an isolated and temperature-controlled room (24ºC) with 12/12-h artificial light-dark cycles and behaviors were observed during resting, eating and moving. Systolic (SBP) and diastolic (DBP) blood pressures were sampled for 1 min every 15 min for 24 h. BP rhythm over 24 h was analyzed by the cosinor method and the mesor, amplitude, acrophase and percent rhythm were calculated. A total of 764 measurements were made in the light cycle and 721 in the dark cycle. Twenty-four-hour values (mean ± SD) were obtained for SBP (121 ± 22 mmHg), DBP (86 ± 17 mmHg), mean BP (MBP, 98 ± 18 mmHg) and heart rate (73 ± 16 bpm). The SBP, DBP and MBP were significantly higher (unpaired Student t-test) during the light period (125 ± 21, 88 ± 15 and 100 ± 17 mmHg, respectively) than during the dark period (120 ± 21, 85 ± 17 and 97 ± 17 mmHg, respectively) and the acrophase occurred between 16:00 and 17:45 h. This circadian variation is similar to that observed in cats, dogs and marmosets. The BP decreased during "behavioral sleep" (MBP down from 110 ± 19 to 90 ± 19 mmHg at 21:00 to 8:00 h). Both feeding and moving induced an increase in MBP (96 ± 17 to 119 ± 17 mmHg at 17:00 h and 97 ± 19 to 105 ± 12 mmHg at 15:00 h, respectively). The results show that conscious sloths present biphasic circadian fluctuations in BP levels, which are higher during the light period and are mainly synchronized with feeding.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

Anthropometric midarm measurements can detect systemic fat-free mass depletion in patients with chronic obstructive pulmonary disease

Our objective was to determine whether anthropometric measurements of the midarm (MA) could identify subjects with whole body fat-free mass (FFM) depletion. Fifty-five patients (31% females; age: 64.6 ± 9.3 years) with mild/very severe chronic obstructive pulmonary disease (COPD), 18 smokers without COPD (39% females; age: 49.0 ± 7.3 years) and 23 never smoked controls (57% females; age: 48.2 ± 9.6 years) were evaluated. Spirometry, muscle strength and MA circumference were measured. MA muscle area was estimated by anthropometry and MA cross-sectional area by computerized tomography (CT) scan. Bioelectrical impedance was used as the reference method for FFM. MA circumference and MA muscle area correlated with FFM and biceps and triceps strength. Receiver operating characteristic curve analysis showed that MA circumference and MA muscle area cut-off points presented sensitivity and specificity >82% to discriminate FFM-depleted subjects. CT scan measurements did not provide improved sensitivity or specificity. For all groups, there was no significant statistical difference between MA muscle area [35.2 (29.3-45.0) cm²] and MA cross-sectional area values [36.4 (28.5-43.3) cm²] and the linear correlation coefficient between tests was r = 0.77 (P < 0.001). However, Bland-Altman plots revealed wide 95% limits of agreement (-14.7 to 15.0 cm²) between anthropometric and CT scan measurements. Anthropometric MA measurements may provide useful information for identifying subjects with whole body FFM depletion. This is a low-cost technique and can be used in a wider patient population to identify those likely to benefit from a complete body composition evaluation.

Body composition measures of obese adolescents by the deuterium oxide dilution method and by bioelectrical impedance

The objectives of the present study were to describe and compare the body composition variables determined by bioelectrical impedance (BIA) and the deuterium dilution method (DDM), to identify possible correlations and agreement between the two methods, and to construct a linear regression model including anthropometric measures. Obese adolescents were evaluated by anthropometric measures, and body composition was assessed by BIA and DDM. Forty obese adolescents were included in the study. Comparison of the mean values for the following variables: fat body mass (FM; kg), fat-free mass (FFM; kg), and total body water (TBW; %) determined by DDM and by BIA revealed significant differences. BIA overestimated FFM and TBW and underestimated FM. When compared with data provided by DDM, the BIA data presented a significant correlation with FFM (r = 0.89; P < 0.001), FM (r = 0.93; P < 0.001) and TBW (r = 0.62; P < 0.001). The Bland-Altman plot showed no agreement for FFM, FM or TBW between data provided by BIA and DDM. The linear regression models proposed in our study with respect to FFM, FM, and TBW were well adjusted. FFM obtained by DDM = 0.842 x FFM obtained by BIA. FM obtained by DDM = 0.855 x FM obtained by BIA + 0.152 x weight (kg). TBW obtained by DDM = 0.813 x TBW obtained by BIA. The body composition results of obese adolescents determined by DDM can be predicted by using the measures provided by BIA through a regression equation.

Development of gluten-free cookie from medicinal plants (Guaraná - Paullinea cupana and Catuaba - Anemopaegma mirandum) aiming at copper, iron, and zinc supplementation

Two flavors of cookies were developed (savory and peppery) containing a mixture of plants such as "guaraná" (Paullinia cupana) and "catuaba" (Anemopaegma mirandum). A test of acceptance and buying intention was applied to 48 consumers through a structured hedonic scale of 9 points. Afterwards, the centesimal compositions of these cookies were obtained as well as their total contents of copper, iron, and zinc through the method of atomic absorption spectrometry with flame. Sensorial tests indicated that the cookies presented good acceptance with potential to sensorial growth. The amount of fibers in the samples, 3 g/100 g, surpassed expectations since the product was not invented with the intention of being a source of this nutrient. The total amount of copper (0.41 mg.100 g-1), iron (4.50 mg.100 g-1), and zinc (1.32 mg.100 g-1) was considered good. The cookies produced can be considered good sources of fibers, copper, iron, and zinc. Furthermore, they are beneficial to people affected by celiac disease because they lack gluten. They also present functional properties. In addition, the medicinal plants used are considered energetic.

Characterization of new sources of derivative starches as wall materials of essential oil by spray drying

Starch derivatives of taro (Colocasia esculenta L. Schott) and rice were characterized as wall materials of orange oil (d-limonene) by spray drying. Native starches were initially hydrolyzed with HCl and then esterified. Succinylated starches were modified using a conventional method in a slurry and were extruded; whereas, the phosphorylated starches were modified using the extrusion process. Viscosity and solubility of starches reduced after acid hydrolysis, derivatization, and extrusion. The particle size of the wall materials ranged between 20.05 and 31.81 µm. The encapsulation efficiency of the phosphorylated taro, rice, and waxy corn starches was 96.9, 96.8 and 97.1% respectively, and 98.6, 98.1, and 98.8% for succynilated taro, rice, and waxy corn starches, respectively. Starch derivatives of taro and rice could potentially be used as wall materials of orange oil d-limonene.