Search

During labor, uterine contractions trigger the response of the autonomic nervous system (ANS) of the fetus, producing sawtooth-like decelerations in the fetal heart rate (FHR) series. Under chronic hypoxia, ANS is known to regulate FHR differently with respect to healthy fetuses. In this study, we hypothesized that such different ANS regulation might also lead to a change in the FHR deceleration morphology. The hypothesis was tested in an animal model comprising 7 normoxic and 5 chronically hypoxic fetuses that underwent a protocol of umbilical cord occlusions (UCOs). Deceleration morphologies in the fetal inter-beat time interval (FRR) series were modeled using a trapezoid with four parameters, i.e., baseline b, deceleration depth a, UCO response time τu and recovery time τr. Comparing normoxic and hypoxic sheep, we found a clear difference for τu (24.8 ± 9.4 vs 39.8 ± 9.7 s; p < 0.05), a (268.1 ± 109.5 vs 373.0 ± 46.0 ms; p < 0.1) and Δτ = τu − τr (13.2 ± 6.9 vs 23.9 ± 7.5 s; p < 0.05). Therefore, the animal model supported the hypothesis that hypoxic fetuses have a longer response time τu and larger asymmetry Δτ as a response to UCOs. Assessing these morphological parameters during labor is challenging due to non-stationarity, phase desynchronization and noise. For this reason, in the second part of the study, we quantified whether acceleration capacity (AC), deceleration capacity (DC), and deceleration reserve (DR), computed through Phase-Rectified Signal Averaging (PRSA, known to be robust to noise), were correlated with the morphological parameters. DR and DC correlated with Δτ and τu for a wide range of the PRSA parameter T (max Pearson’s correlation ρ = 0.9, p < 0.05, and ρ = 0.6, p < 0.1, respectively). In conclusion, deceleration morphologies have been found to differ between normoxic and hypoxic sheep fetuses during UCOs. The same difference can be assessed through PRSA based parameters, further motivating future investigations on the translational potential of this methodology on human data.

Recent studies have suggested that cardiac abnormalities can be detected from the electrocardiogram (ECG) using deep machine learning (DL) models. However, most DL algorithms lack interpretability, since they do not provide any justification for their decisions. In this study, we designed two new frameworks to interpret the classification results of DL algorithms trained for 12-lead ECG classification. The frameworks allow us to highlight not only the ECG samples that contributed most to the classification, but also which between the P-wave, QRS complex and T-wave, hereafter simply called ‘waves’, were the most relevant for the diagnosis. The frameworks were designed to be compatible with any DL model, including the ones already trained. The frameworks were tested on a selected Deep Neural Network, trained on a publicly available dataset, to automatically classify 24 cardiac abnormalities from 12-lead ECG signals. Experimental results showed that the frameworks were able to detect the most relevant ECG waves contributing to the classification. Often the network relied on portions of the ECG which are also considered by cardiologists to detect the same cardiac abnormalities, but this was not always the case. In conclusion, the proposed frameworks may unveil whether the network relies on features which are clinically significant for the detection of cardiac abnormalities from 12-lead ECG signals, thus increasing the trust in the DL models.This article is part of the theme issue ‘Advanced computation in cardiovascular physiology: new challenges and opportunities’.

Background Bipolar disorder (BD) broadly affects brain structure, in particular areas involved in emotion processing and cognition. In the last years, the psychiatric field's interest in machine learning approaches has been steadily growing, thanks to the potentiality of automatically discriminating patients from healthy controls. Methods In this work, we employed cortical thickness of 58 regions of interest obtained from magnetic resonance imaging scans of 41 BD patients and 34 healthy controls, to automatically identify the regions which are mostly involved with the disease. We used a semi-supervised method, addressing the criticisms on supervised methods, related to the fact that the diagnosis is not unaffected by uncertainty. Results Our results confirm findings in previous studies, with a classification accuracy of about 75% when mean thickness and skewness of up to five regions are considered. We obtained that the parietal lobe and some areas in the temporal sulcus were the regions which were the most involved with BD. Limitations The major limitation of our work is the limited size or our dataset, but in line with other recent machine learning works in the field. Moreover, we considered chronic patients, whose brain characteristics may thus be affected. Conclusions The automatic selection of the brain regions most involved in BD may be of great importance when dealing with the pathogenesis of the disorder. Our method selected regions which are known to be involved with BD, indicating that damage to the identified areas can be considered as a marker of disease.

Atrial fibrillation (AF) is an irregular heart rhythm due to disorganized atrial electrical activity, often sustained by rotational drivers called rotors. In the present work, we sought to characterize and discriminate whether simulated single stable rotors are located in the pulmonary veins (PVs) or not, only by using non-invasive signals (i.e., the 12-lead ECG). Several features have been extracted from the signals, such as Hjort descriptors, recurrence quantification analysis (RQA), and principal component analysis. All the extracted features have shown significant discriminatory power, with particular emphasis to the RQA parameters. A decision tree classifier achieved 98.48% accuracy, 83.33% sensitivity, and 100% specificity on simulated data.Clinical Relevance-This study might guide ablation procedures, suggesting doctors to proceed directly in some patients with a pulmonary veins isolation, and avoiding the prior use of an invasive atrial mapping system.

This study assessed the internal and external workload of starters and non-starters in a professional top-level soccer team during a congested fixture period. Twenty Serie A soccer players were monitored in this study during two mesocycles of 21 days each. Starters and non-starters were divided based on the match time played in each mesocycle. The following metrics were recorded: exposure time, total distance, relative total distance, high-speed running distance over 20 km·h−1, very high-speed running distance over 25 km·h−1, individual very high-speed distance over 80% of maximum peak speed, and rating of perceived exertion. Differences between starters and non-starters were found for: exposure time (effect size=large to very large), rating of perceived exertion (large to very large), total distance (large to very large), and individual very high-speed distance over 80% of maximum peak speed (moderate to large). Furthermore, differences for relative total distance, high-speed running distance over 20 km·h−1 and very high-speed running distance over 25 km·h−1 were small to moderate, but not significant. This study reports that during congested fixture periods, starters had higher exposure time, rating of perceived exertion, total distance, and individual very high-speed distance over 80% of maximum peak speed than non-starters.

Many techniques have been developed to cancel the ventricular interference in atrial electrograms (AEG) during atrial fibrillation. In particular, average beat subtraction (ABS) and interpolation are among those mostly adopted. However, ABS usually leaves high power residues and discontinuity at the borders, whereas interpolation totally substitutes the residual activity with a forecasting that might fail at the center of the cancellation segment. In this study, we proposed a new algorithm to refine the ventricular estimate provided by ABS, in such a way that the residual activity should likely be distributed as the local atrial activity. Briefly, the local atrial activity is first modeled with an autoregressive (AR) process, then the estimate is refined by maximizing the log likelihood of the atrial residual activity according to the fitted AR model. We tested the new algorithm on both synthetic and real AEGs, and compared the performance with other four algorithms (two variants of ABS, interpolation and zero substitution). On synthetic data, our algorithm outperformed all the others in terms of average root mean square error (0.043 vs 0.046 for interpolation; p < 0.05). On real data, our methodology outperformed two variants of ABS (p < 0.05) and performed similarly to interpolation when considering the high power residues left (both < 5%), and the log likelihood with the fitted AR model.

An extended nonlinear Bayesian filtering framework is introduced for the analysis of atrial fibrillation (AF), in particular with single-channel electrocardiographical (ECG) recordings. It is suitable for simultaneously tracking the fundamental frequency of atrial fibrillatory waves (f-waves), and separating signals, linked to atrial and ventricular activity, during AF. In this framework, high-power ECG components, i.e., Q, R, S, and T waves, are modeled using sum of Gaussian functions. The atrial activity dynamical model is instead based on a trigonometrical function, with a fundamental frequency (the inverse of the dominant atrial cycle length), and its harmonics. The state variables of both dynamical models (QRS-T and f-waves) are hidden and, then estimated, sample by sample, using a Kalman smoother. Remarkably, the scheme is capable of separating ventricular and atrial activity signals, while contemporarily tracking the atrial fundamental frequency in time. The proposed method was evaluated using synthetic signals. In 290 ECGs in sinus rhythm from the PhysioNet PTB Diagnostic ECG Database, the P-waves were replaced with a synthetic f-wave. Broadband noise at different signal-to-noise ratio (SNR) (from 0 to 40 dB) was added to study the performance of the filter, under different SNR conditions. The results of the study demonstrated superior results in atrial and ventricular signal separation when compared with traditional average beat subtraction (ABS), one of the most widely used method for QRS-T cancellation (normalized mean square error = 0.045 for extended Kalman smoother (EKS) and 0.18 for ABS, SNR improvement was 21.1 dB for EKS and 12.2 dB for ABS in f-wave extraction). Various advantages of the proposed method have been addressed and demonstrated, including the problem of tracking the fundamental frequency of f-waves (root mean square error (RMSE) ≈ 0.03 ± 0.005 Hz for gradually changing frequency at SNR=15 dB) and of estimating robust QT/RR values during AF (RMSE ≈ 0.008 ± 0.001 at SNR = 10 dB, R 2 = 0.99).

Background: The increase in life expectancy is accompanied by a growing number of elderly subjects affected by chronic comorbidities, a health issue which also implies important socioeconomic consequences. Shifting from hospital or community dwelling care towards a home personalized healthcare paradigm would promote active aging with a better quality of life, along with a reduction in healthcare-related costs. Objective: The aim of the SMARTA project was to develop and test an innovative personal health system integrating standard sensors as well as innovative wearable and environmental sensors to allow home telemonitoring of vital parameters and detection of anomalies in daily activities, thus supporting active aging through remote healthcare. Methods: A first phase of the project consisted in the definition of the health and environmental parameters to be monitored (electrocardiography and actigraphy, blood pressure and oxygen saturation, weight, ear temperature, glycemia, home interaction monitoring - water tap, refrigerator, and dishwasher), the feedbacks for the clinicians, and the reminders for the patients. It was followed by a technical feasibility analysis leading to an iterative process of prototype development, sensor integration, and testing. Once the prototype had reached an advanced stage of development, a group of 32 volunteers - including 15 healthy adult subjects, 13 elderly people with cardiac diseases, and 4 clinical operators - was recruited to test the system in a real home setting, in order to evaluate both technical reliability and user perception of the system in terms of effectiveness, usability, acceptance, and attractiveness. Results: The testing in a real home setting showed a good perception of the SMARTA system and its functionalities both by the patients and by the clinicians, who appreciated the user interface and the clinical governance system. The moderate system reliability of 65-70% evidenced some technical issues, mainly related to sensor integration, while the patient's user interface showed excellent reliability (100%). Conclusions: Both elderly people and clinical operators considered the SMARTA system a promising and attractive tool for improving patients' healthcare while reducing related costs and preserving quality of life. However, the moderate reliability of the system should prompt further technical developments in terms of sensor integration and usability of the clinical operator's user interface.

Objective: The interpretation of Average Acceleration and Deceleration Capacities (AC/DC), computed through Phase-Rectified Signal Averaging (PRSA), in intrapartum fetal heart rate (FHR) monitoring is still matter of investigation. We aimed to elucidate some behaviors of AC/DC. Methods: We derived the theoretical value of PRSA for stationary stochastic Gaussian processes and proved that for these time series AC and DC are necessarily identical in absolute value. The difference between DC and AC, termed Deceleration Reserve (DR), was introduced to detect signal's asymmetric trends. DR was tested on FHR signals from: near-term pregnant sheep model of labor consisting of chronically hypoxic and normoxic fetuses with both groups developing acidemia due to umbilical cord occlusions (UCO); and the CTU-UHB dataset containing fetal CTG recordings collected during labor of newborns that resulted acidotic and non-acidotic, respectively. DR was compared with AC and DC in terms of discriminatory power (AUC), between the groups, after correcting for signal power or deceleration area, respectively. Results: DR displayed higher discriminatory power on the animal model during severe acidemia, with respect to AC/DC ( $p ) but also distinguished correctly all chronically hypoxic from normoxic fetuses at baseline prior to UCO. DR also outperformed AC/DC on the CTU-UHB dataset in distinguishing acidemic fetuses at birth (AUC: 0.65). Conclusion: Theoretical results motivated the introduction of DR, that proved to be superior than AC/DC for risk stratification during labor. Significance: DR, measured during labor, might permit to distinguish acidemic fetuses due to their different autonomic regulation, paving the way for new monitoring strategies.

Coronary angioplasty (CA) is a surgical procedure meant to break the plaque and restore the blood flow in obstructed coronary arteries. It is based on inserting an inflatable balloon with a catheter in the clogged artery. When the balloon inflation is prolonged, it also provides an excellent model to investigate the electrophysiological changes due to early ischemia. In this work, we tested whether early cardiac ischemia induced by prolonged balloon inflations might lead to changes in spatial heterogeneity of ventricular repolarization (SHVR), as measured by the V-index on the 12-lead ECG. The metric was recently shown to significantly improve the ECG sensitivity for the diagnosis of non-ST elevation myocardial infarction, in patients presenting to the emergency department. The analysis was retrospectively performed on the data of 104 patients who underwent prolonged CA (STAFF III dataset). The V-index was estimated before, during and post-occlusion (limiting the analysis to the first inflation). Successively, it was quantified on short 90 s overlapping windows, during occlusion, to assess the time evolution of SHVR. V-index values estimated during occlusion were significantly larger (median: 6.2 ms, p; 0.05) than baseline room values. Also, pre- and post-occlusion values did not differ (p0.05), suggesting a complete recovery after CA. SHVR progressively increased during the occlusion with respect to baseline (median reaching 55.6 ms vs 34.2 ms). In conclusion, the V-index detected changes in SHVR due to early-stage cardiac ischemia.

Background and Objectives In contrast to potassium channel blockers, drugs affecting multiple channels seem to reduce torsadogenic risks. However, their effect on spatial heterogeneity of ventricular repolarization (SHVR) is still matter of investigation. Aim of this work is to assess the effect of four drugs blocking the human ether-a-go-go-related gene (hERG) potassium channel, alone or in combination with other ionic channel blocks, on SHVR, as estimated by the V-index on short triplicate 10 s ECG. Methods The V-index is an estimate of the standard deviation of the repolarization times of the myocytes across the entire myocardium, obtained from multi-lead surface electrocardiograms. Twenty-two healthy subjects received a pure hERG potassium channel blocker (dofetilide) and 3 other drugs with additional varying degrees of sodium and calcium (L‐type) channel block (quinidine, ranolazine, and verapamil), as well as placebo. A one-way repeated-measures Friedman test was performed to compare the V-index over time. Results Computer simulations and Bland-Altman analysis supported the reliability of the estimates of V-index on triplicate 10 s ECG. Ranolazine, verapamil and placebo did not affect the V-index. On the contrary, after quinidine and dofetilide administration, an increase of V-index from predose to its peak value was observed (ΔΔV-index values were 19 ms and 27 ms, respectively, p Conclusions High torsadogenic drugs (dofetilide and quinidine) affected significantly the SHVR, as quantified by the V-index. The metric has therefore a potential in assessing drug arrhythmogenicity.

Drug-induced alterations of ventricular heterogeneity must be limited to avoid induction of lethal ventricular arrhythmias. In here, a new parameter called [Formula: see text]-index, able to measure the standard deviation of myocites' repolarization times, was evaluated after moxifloxacin and sotalol administration. The two drugs are known to provide different alteration of the QT interval length ranging from subtle (moxifloxacin) to evident (sotalol). In fact, while the former is employed as active-comparator in thorough QT studies, the latter might induce torsades de pointes. 24 h Holter ECGs of 39 (sotalol) and 68 (moxifloxacin) healthy subjects were retrospectively analyzed. The recordings were performed after infusion of the drugs and after the placebo (moxifloxacin) or at baseline (sotalol). The corrected QT interval (QTc) was included as well in the study, for a direct comparison. In both populations, [Formula: see text]-index and QTc increased along with the drugs' serum concentration and were statistically different from values in the placebo arm or at baseline (p < 0.05).With sotalol, the maximum value of [Formula: see text]-index occurred, on average, after 5.64 h from the infusion, whereas for QTc after about 4.27 h. The two metrics displayed evident changes ([Formula: see text]-index: 27.79 ms ± 4.89 ms versus 60.13 ms ± 18.52 ms; QT corrected: 387.07 ms ± 19.84 ms versus 437.76 ± 32.05 ms; p < 0.05). Regarding moxifloxacin, maximum values were reached, on average, 5.01 h after administration for [Formula: see text]-index (30.70 ms ± 8.32 ms versus 40.48 ms ± 7.61 ms; p < 0.05), and 4.37 h for QTc (404.29 ms ± 29.05 ms versus 426.77 ± 36.67 ms; p < 0.05). They were statistically different from baseline values. With both drugs, the maximal percent variation after administration was higher for [Formula: see text]-index than QTc (moxifloxacin: 34.56% ± 24.60% versus 5.56% ± 2.98% ; sotalol: 114.77% ± 33.15% versus 12.13% ± 2.85% ; p < 0.05).The study suggests that the standard deviation of the ventricular repolarization times, as quantified by the [Formula: see text]-index, might be an effective measure of spatial heterogeneity.

There is an interest in looking at sub-intervals of the QT in the Comprehensive in-vitro Proarrhythmia Assay (CiPA) initiative. Here, we performed a sensitivity analysis of JT peak and T-wave morphology (TWM) parameters computed on transmural ECGs, generated by a highresolution human left-ventricular wedge model, with a modified version of the ten Tusscher 2006 cardiac cell model, with respect to the block of the slow and rapid potassium channels (IKs and IKr), and the late sodium channel (NaL), from 0% to 90%. Moreover, we simulated the effects of Dofitilide and Ranolazine. TWM parameters were QT interval (QT), T-peak to T-end (TpTe), T amplitude (Tamp), J to T-peak (JTpeak), Flatness Score (FS), Asymmetry Score (AS), average APD90 (APD90avg), APD Dispersion (APD90Disp) and standard deviation of the repolarization times (s p ). Sensitivities were computed as the percentage variation normalized at 50% block and they varied across ion channels and amount of block. QT interval, JTpeak and APD90avg performed similarly across channels (0.29). TpTe and s p provided similar sensitivities (0.80 for both IKr and NaL, and 0.13 for IKs). AS resulted with the highest sensitivity to NaL block (8.35). Morover, the wedge model was capable to simulate the effects of the drugs. In conclusion, TWM parameters reflected ion channel alterations with different proportions.

When spatial heterogeneity of ventricular repolarization (SHVR) increases, vulnerability to ventricular arrhythmias, including lethal ones, has also been observed to increase. Drug-induced multi-ion-channel blocks may increase SHVR. Aim of this study is to non-invasively assess whether quinidine, a strong hERG potassium channel blocker with weaker effects on calcium and late sodium currents, increases SHVR. We analyzed data from 21 healthy subjects that received both the drug and a placebo and underwent to 12 leads Holter monitoring. From the recording, three 10-s ECGs were extracted at each of 16 predefined time-points. SHVR was assessed by the V-index, which evaluates the standard deviation of the repolarization times from multi-lead ECG recordings. At any time point, a value of V-index was computed for each of the three 10s ECGs and averaged if the difference in the mean RR of the 10s ECGs was lower than 50 ms. The V-index did not change after the placebo (V-index pre-dose = 29.2 ± 9.9 ms vs. V-indexpost-dose1h = 26.7 ± 10.3, ns), whereas, after quinidine, it significantly increased one hour post-dose (V-index pre-dose = 29.5 ± 10.2 ms vs. V-indexpost-dose1h = 46.5 ± 33.8 ms, p = 0.01). Quinidine had its maximum effect on the V-index 2.5 h after dose (V-index post-dose2.5h =53.6 ± 39.6 ms).

Gait and balance disorders are among the main predisposing factors of falls in elderly. Clinical scales are widely employed to assess the risk of falling, but they require trained personnel. We investigate the use of objective measures obtained from a wearable accelerometer to evaluate the fall risk, determined by the Tinetti clinical scale. Seventy-nine patients and eleven volunteers were enrolled in two rehabilitation centers and underwent a full Tinetti test, while wearing a triaxial accelerometer at the chest. Tinetti scores were assessed by expert physicians and those subjects with a score

Falling in elderly is a worldwide major problem and it can lead to severe injuries or death. Despite the effort made to ensure home environments safe and foster healthy lifestyles, it is still necessary to provide methodologies that can be used at home for detect risk factors associated with falls. In this study, we proposed a new simple non-linear model, i.e., Linear-Sigmoidal model (LS), easy to fit and simple to interpret, used to model accelerometer features and outcome of the clinical scale Tinetti (clinical scale for fall risk prediction). Also, subjects with a score ≤ 18 were considered as high risk of falling. One-hundred-twelve subjects underwent to a Tinetti test while wearing a 3D axis accelerometer at the chest, and the Tinetti score used as gold standard. Ninety subjects were used as training set and twenty-two ones were employed to test the model. The same sets were used to assess the performance of the standard linear regression (LR). Seven accelerometer features and the body mass index were used in the model regression. LS resulted better than LR in terms of model agreement (R2: 0.76 vs 0.72) and classification accuracy (0.91 vs 0.86) on the test set.

The relation between fetal heart rate and the value of umbilical cord artery pH is not something new for the scientific community. However, the problem has not been investigated sufficiently. One reason for that is the lack of open databases with a large number of recordings. Such a database is used here, recently publicly available, with cardiotocographic data recorded approximately two hours before delivery and until the end of the delivery. We use entropy measures to investigate how the value of umbilical cord artery pH is correlated to the variability of the fetal heart rhythm. We select different ranges of pH values and estimate the entropy of the time series for these recordings. We discuss the differences presented in the fetal heart rhythm and make conclusions about the correlation of the umbilical cord artery pH and the fetal heart rhythm, as well as the entropy as a means to express these differences.

Background In clinical practice, data archiving of resting 12–lead electrocardiograms (ECGs) is mainly achieved by storing a PDF report in the hospital electronic health record (EHR). When available, digital ECG source data (raw samples) are only retained within the ECG management system. Objective The widespread availability of the ECG source data would undoubtedly permit successive analysis and facilitate longitudinal studies, with both scientific and diagnostic benefits. Methods & results PDF-ECG is a hybrid archival format which allows to store in the same file both the standard graphical report of an ECG together with its source ECG data (waveforms). Using PDF-ECG as a model to address the challenge of ECG data portability, long-term archiving and documentation, a real-world proof-of-concept test was conducted in a northern Italy hospital. A set of volunteers undertook a basic ECG using routine hospital equipment and the source data captured. Using dedicated web services, PDF-ECG documents were then generated and seamlessly uploaded in the hospital EHR, replacing the standard PDF reports automatically generated at the time of acquisition. Finally, the PDF-ECG files could be successfully retrieved and re-analyzed. Conclusion Adding PDF-ECG to an existing EHR had a minimal impact on the hospital's workflow, while preserving the ECG digital data.

The concurrent usage of actigraphy and heart rate variability (HRV) for sleep efficiency quantification is still matter of investigation. This study compared chest (CACT) and wrist (WACT) actigraphy (actigraphs positioned on chest and wrist, respectively) in combination with HRV for automatic sleep vs wake classification. Accelerometer and ECG signals were collected during polysomnographic studies (PSGs) including 18 individuals (25-53 years old) with no previous history of sleep disorders. Then, an experienced neurologist performed sleep staging on PSG data. Eleven features from HRV and accelerometry were extracted from series of different lengths. A support vector machine (SVM) was used to automatically distinguish sleep and wake. We found 7 min as the optimal signal length for classification, while maximizing specificity (wake detection). CACT and WACT provided similar accuracies (78% chest vs 77% wrist), larger than what yielded by HRV alone (66%). The addition of HRV to CACT reduced slightly the accuracy, while improving specificity (from 33% to 51%, p 0.05). On the contrary, the concurrent usage of HRV and WACT did not provide statistically significant improvements over WACT. Then, a subset of features (3 from HRV + 1 from actigraphy) was selected by reducing redundancy using a strategy based on Spearman's correlation and area under the ROC curve. The usage of the reduced set of features and SVM classifier gave only slightly reduced classification performances, which did not differ from the full sets of features. The study opens interesting possibilities in the design of wearable devices for long-term monitoring of sleep at home.

In certain severe mental diseases, like schizophrenia, structural alterations of the brain are detectable by magnetic resonance imaging (MRI). In this work, we try to automatically distinguish, by using anatomical features obtained from MRI images, schizophrenia patients from healthy controls. We do so by exploiting contextual similarity of imaging data, enhanced with a distance metric learning strategy (DML - by providing “must-be-in-the-same-class” and “must-not-be-in-the-same-class” pairs of subjects). To learn from contextual similarity of the subjects brain anatomy, we use a graph-based semi-supervised label propagation algorithm (graph transduction, GT) and compare it to standard supervised techniques (SVM and K-nearest neighbor, KNN). We performed out tests on a population of 20 schizophrenia patients and 20 healthy controls. DML+GT achieved a statistically significant advantage in classification performance (Accuracy: 0.74, Sensitivity: 0.79, Specificity: 0.69, Ck: 0.48). Enhanced contextual similarity improved performance of GT, SVM and KNN offering promising perspectives for MRI images analysis.

The growing number of elderly people with health issues is the consequence of the increase in life expectancy. Tele-homecare applications have already reported promising results on reducing health care costs and improving quality of life. In this study, we present the SMARTA platform (www.smarta-project.it): a fully integrated system capable to monitor its user’s health condition. The latest telemedicine and wearable technologies have been used to make cooperating users and caregivers. The system integrates wearable (ECG and accelerometry), non-wearable (temperature, weight, blood pressure etc.) and environmental (light, refrigerator etc.) sensors.

Aims Dynamics of cardiovascular series may be explored with non-linear techniques. It is unknown if the arterial pressure irregularity commonly observed in patients with atrial fibrillation (AF) might be further increased by a sympathetic stimulus such as orthostatic tilt. Methods and results Twenty patients (62 ± 14 years, 15 men) were recruited for the study. Continuous beat-to-beat non-invasive arterial pressure was acquired at rest and during a passive orthostatic stimulus (‘tilt test’). Systolic (SAP) and diastolic (DAP) arterial pressure series of 300 samples were analysed in both conditions. Approximate (ApEn) and sample entropy (SampEn) were computed, as irregularity measures. Equivalent metrics (ApEnAR and SampEnAR) derived from an autoregressive model of the series were also obtained through numerical simulations, to further elucidate the non-linear mechanisms present in the series. In 11 patients (Group A), SAP significantly increased during tilt (from 103 ± 13 to 114 ± 17 mmHg, P < 0.001 rest vs. tilt), whereas in 9 patients (Group B) SAP remained almost unchanged (SAP: 110 ± 18 vs. 106 ± 19 mmHg, rest vs. tilt). No clinical differences were found between Groups A and B. When analysing Group A, all irregularity measures significantly increased in SAP (ApEn: 1.75 ± 0.20 vs. 1.88 ± 0.16, P < 0.05; SampEn: 1.71 ± 0.30 vs. 1.88 ± 0.27, P < 0.05; ApEnAR: 1.87 ± 0.20 vs. 1.96 ± 0.18, P < 0.05; SampEnAR: 1.94 ± 0.27 vs. 2.06 ± 0.18, P < 0.05; rest vs. tilt), whereas no differences were found in DAP series. No significant differences were found in Group B for either SAP or DAP. Conclusion The alterations of SAP during tilt in AF patients are not uniform and seem associated with different regularity patterns. The pressor response to sympathetic stimulation was also associated with an increase of SAP series irregularity.

Mixotrophic cultivation of microalgae provides a very promising alternative for producing carbohydrate-rich biomass to convert into bioethanol and value-added biocompounds, such as vitamins, pigments, proteins, lipids and antioxidant compounds. Spirulina platensis may present high yields of biomass and carbohydrates when it is grown under mixotrophic conditions using cheese whey. However, there are no previous studies evaluating the influence of this culture system on the profile of fatty acids or antioxidant compounds of this species, which are extremely important for food and pharmaceutical applications and would add value to the cultivation process. S. platensis presented higher specific growth rates, biomass productivity and carbohydrate content under mixotrophic conditions; however, the antioxidant capacity and the protein and lipid content were lower than that of the autotrophic culture. The maximum biomass yield was 2.98 ±0.07 g/L in growth medium with 5.0% whey. The phenolic compound concentration was the same for the biomass obtained under autotrophic and mixotrophic conditions with 2.5% and 5.0% whey. The phenolic compound concentrations showed no significant differences except for that in the growth medium with 10.0% whey, which presented an average value of 22.37±0.14 mg gallic acid/g. Mixotrophic cultivation of S. platensis using whey can be considered a viable alternative to reduce the costs of producing S. platensis biomass and carbohydrates, shorten cultivation time and produce carbohydrates, as it does not require adding expensive chemical nutrients to the growth medium and also takes advantage of cheese whey, an adverse dairy industry byproduct.

Background: Epidemiologic evidences suggest a strong association between low birth weight and some diseases in adult life ( hypertension, diabetes, cardiovascular diseases).Aim of this study was to evaluate the obesity/overweight prevalence in a population of children born small for gestation age, SGA children 400, 208 males and 192 females compared to a population of children born appropriate for gestational age 6818 AGA children, 3502 males and 3316 females, during childhood. Our intention was also to build the natural history of weight gain during prepubertal age in children born SGA and AGA. Design and Methods: Observational prospective longitudinal study. We followed our patients from January2001 up to December 2010; weight, height and body mass index (BMI) were evaluated in all the SGA and AGA children. BMI z-score range for defining overweight and obesity was, respectively, 1.13 to 1.7 and >1.7 according to CDC growth charts. Results: In transversal evaluation, we prove that 10-year-old SGA females are twice obese and more overweight compared to equal age AGA females. In longitudinal evaluation, we highlight different observations: SGA children obese at 2 years are still obese at 10 years; the number of obese SGA children increases gradually until the age of 10; AGA children, appear to be less obese than SGA children at 10 years. Conclusion: SGA males and females are more obese at 5 and 10 years compared to the AGA population. Primary care pediatricians, through early detection of the children at risk, can carry out an effective obesity prevention project in SGA children.

Insufficient amount of physical activity, and hence storage of calories may lead depression, obesity, cardiovascular diseases, and diabetes. The amount of consumed calorie depends on the type of activity. The recognition of physical activity is very important to estimate the amount of calories spent by a subject every day. There are some research works already published in the literature for activity recognition through accelerometers (body worn sensors). The accuracy of any recognition system depends on the robustness of selected features and classifiers. The typical features reported for most physical activities recognitions are autoregressive coefficients (ARcoeffs), signal magnitude area (SMA), tilt angle (TA), and standard deviation (STD). In this study, we have studied the feasibility of using single value of sample entropy estimated parametrically (SE TH ) of an AR model instead of ARcoeffs. After feasibility study, we also compared the recognition accuracies between two popular classifiers i.e. artificial neural network (ANN) and support vector machines (SVM). The recognition accuracies using linear structure (where all types of activities are classified using a single classifier) and hierarchical structure (where activities are first divided into static and dynamic events, and then activities of each event are classified in the second stage). The study showed that the use of SE TH provides similar recognition accuracy (69.82%) as provided by ARcoeffs (67.67%) using ANN. The linear structure of SVM performs better (average accuracy of SVM: 98.22%) than linear ANN (average accuracy with ANN: 94.78%). The use of hierarchical structure of ANN increases the average recognition accuracy of static activities to about 100%. However, no significant changes are observed using hierarchical SVM than the linear one.

Objective Phase rectified signal averaging (PRSA) is a new method of fetal heart rate variability (fHRV) analysis that quantifies the average acceleration (AC) and deceleration capacity (DC) of the heart. The aim of this study was to evaluate AC and DC of fHR [recorded by trans-abdominal fetal electrocardiogram (ta-fECG)] in relation to Doppler velocimetry characteristics of intrauterine growth restriction (IUGR). Design Prospective case–control study. Setting Single third referral centre. Population IUGR (n = 66) between 25 and 40 gestational weeks and uncomplicated pregnancies (n = 79). Methods In IUGR the nearest ta-fECG monitoring to delivery was used for PRSA analysis and Doppler velocimetry parameters obtained within 48 hours. AC and DC were computed at s = T = 9. The relation was evaluated between either AC or DC and Doppler velocimetry parameters adjusting for gestational age at monitoring, as well as the association between either AC or DC and IUGR with or without brain sparing. Results In IUGRs there was a significant association between either AC and DC and middle cerebral artery pulsatility index (PI; P = 0.01; P = 0.005), but the same was not true for uterine or umbilical artery PI (P > 0.05). Both IUGR fetuses with and without brain sparing had lower AC and DC than controls, but this association was stronger for IUGRs with brain sparing. Conclusions Our study observed for the first time that AC and DC at PRSA analysis are associated with middle cerebral artery PI, but not with uterine or umbilical artery PI, and that there is a significant decrease of AC and DC in association with brain sparing in IUGR fetuses from 25 weeks of gestation to term. Tweetable abstract Brain sparing in IUGR fetuses is associated with decreased acceleration and deceleration capacities of the heart.

T-wave alternans (TWA) is an alteration of the ECG T-wave which repeats every other beat. An alternating pattern has been also observed at myocytes level, involving both action potential duration and morphology (mainly in phases 2 and 3). While this might happen in a specific region (i.e., myocardial ischemia), it can also involve the entire myocardium. It is still unclear how alternations at the myocytes level are reflected on surface ECG modification of T-waves, especially when in vivo human hearts are considered. We have recently proposed a simple stochastic model of ventricular repolarization (IEEE Trans. Biomed. Eng., 2011), which takes into account both repolarization heterogeneity across the myocardium as well as random beat-to-beat variations in cells' activity. In this work, we generalized that model incorporating a term which describes myocytes alternans related to T-wave variability. Starting from the model and using the electrophysiological formulation developed by van Oosterom, we derived an analytical formula relating surface ECG to variations at the myocytes' level. Several theoretical results were then obtained. First, temporal small random variations in repolarization heterogeneity affect the precision of TWA estimates in a significant way. Second, TWA theoretically differs across leads, but multilead configuration can be used to reduce the effect of noise. Finally, the dependency between TWA and T-wave amplitude was analyzed.

The aim of this study was to test, in delayed antibiotic strategy, if the usages of a point-of-care leukocyte count would significantly decrease the prescription rate of antibiotics for children with nonspecific upper respiratory tract infections. A prospective clinical trial was performed in 23 primary care pediatric doctors’ offices on children with nonspecific upper respiratory tract infection with fever for at least 48 hours. The children were randomized into 2 groups: one using a point-of-care white blood cell (WBC) count as guidance and the other prescribing antibiotics to all children, according to delayed antibiotics prescription strategy. A total of 792 patients participated. In the WBC group (n = 437), 56 patients had WBC >15 000/mm3 and received antibiotics. At follow-up, an additional 44 children received antibiotics. In the control group (n = 355), antibiotics were prescribed to all children. The reduction of antibiotic usage was 77% between the groups. The decrease in antibiotic usage gave no influence on recovery, complications, or other medical outcome.

Falling in elderly is a worldwide major problem because it can lead to severe injuries, and even sudden death. Fall risk prediction would provide rapid intervention, as well as reducing the over burden of healthcare systems. Such prediction is currently performed by means of clinical scales. Among them, the Tinetti Scale is one of the better established and mostly used in clinical practice. In this work, we proposed an automatic method to assess the Tinetti scores using a wearable accelerometer. The balance and gait characteristics of 13 elderly subjects have been scored by an expert clinician while performing 8 different motor tasks according to the Tinetti Scale protocol. Two statistical analysis were selected. First, a linear regression study was performed between the Tinetti scores and 8 features (one feature for each task). Second, the generalization quality of the regression model was assessed using a Leave-One SubjectOut approach. The multiple linear regression provided a high correlation between the Tinetti scores and the features proposed (adj. R(2) = 0.948; p = 0.003). Moreover, six of the eight features added statistically significantly to the prediction of the scores (p

Background The knee is the weight-bearing joint most commonly associated with sports injuries, and therefore is most at risk of developing degenerative changes, including osteoarthritis. Skyrunners can be considered to be at risk of developing symptoms of post-traumatic osteoarthritis due to downhill running. Aim The aim of this study was to analyze the health of the knee joints of a large group of these athletes via a specific self-report questionnaire. Methods This study was carried out by asking the participants of seven official Skyraces (22.4±3.1 km length; 1596±393 m elevation) to fill out a questionnaire. Information regarding age, sex, downhill elevation (m) during training and competitions over the last month, and history of previous knee injury was also collected before the participants filled out the Knee injury and Osteoarthritis Outcome Score (KOOS), which is a reliable and validated instrument designed to assess patients’ opinions about their knees and associated problems that can result in post-traumatic osteoarthritis. Athletes were divided into six age groups (from 17 to 70 years) and 12 groups based on the downhill gradient they had covered over the last month (from 1,000 to 40,000 m). Results Six hundred twenty-one questionnaires were collected from 45% of the participants in the seven races. Multivariate analysis revealed that self-reported KOOS scores were unrelated to age, sex and monthly downhill gradient. Only 74 (12%) of the participants reported previous knee injuries. Significant differences in the five subscales of the KOOS were found between skyrunners with and without previous knee injuries (P

The spatial heterogeneity of ventricular repoalarization (SHVR) is an important factor in arrhythmogenesis and it is related to increased vulnerability to fatal arrhythmia. The V-index is a non-invasive estimator of SHVR based on the analysis of the surface ECG. A significant correlation between the V-index and SHVR has been previously demonstrated theoretically and by means of numerical simulations. Also, the V-index has been shown to track expected changes in SHVR after infusion of drugs that alter the cardiac electrophysiology. In this study, we compare for the first time estimates from the V-index with direct measures of SHVR derived from unipolar elecrograms simultaneously recorded in the left and right ventricular endocardium and in the left ventricular epicardium. In 22 recordings collected in 14 patients with normal ventricles, the V-index showed a tight and significant correlation with directed measures of SHVR, with correlation coefficients as high as r = 0.80, whereas other ECG-derived estimates of SHVR based on T-peak and T-peak to T-end measures showed lower correlations (r ≤ 0.41 and r ≤ 0.36, respectively). The results of this study suggest that the V-index provides reliable estimates of SHVR.

Implantable cardioverter defibrillators (ICD) are the most effective way of preventing sudden cardiac death (SCD). However, the implantation of an ICD is an invasive procedure with associated risks and a high cost. Therefore, it is necessary to determine non-invasive risk markers that identify patients at a higher risk of suffering malignant arrhytmias. One of the most promising non-invasive indices is T-wave alternans (TWA). This work assesses T-wave alternans using the Amplitude of Dominant T-Wave Alternans (ADTWA), that is derived from the dominant T wave associated to a number of consecutive beats. Data from 650 patients with heart failure enrolled in the MUSIC study were analyzed. ADTWA have higher values increasing heart rate. ADTWA was also significantly higher in SCD patients than in survivors (survivors vs. SCD: 6.60±1.98 vs. 7.55±2.53, p=0.01). ADTWA seems a promising index to identify patients with heart failure at higher risk of SCD.

OBJECTIVE: Intrauterine growth restriction (IUGR) is characterized by chronic nutrient deprivation and hypoxemia that alters the autonomous nervous system regulation of fetal heart rate variability (fHRV). Phase-rectified signal averaging (PRSA) is a new algorithm capable to identify periodic and quasi-periodic patterns of HR, and which is used to quantify the average acceleration and deceleration capacity (AC/DC) of the heart. The computation of AC/DC depends on the parameters T and s, which we set so that s=T. T and s determine the periodicities that can be detected (the larger T the smaller the frequency of oscillations for which the method is most sensitive). The aim of the study was to evaluate the influence of the parameter T on PRSA computation, based on trans-abdominally acquired fetal ECG (ta-fECG), in early IUGR (0.05), respectively. The AUCs of AC-T9 and DC-T9 significantly outperformed that obtained by short-term variation (AUC 0.77, 95% CI 0.65-0.90; p=0.009 and p=0.003, respectively). CONCLUSIONS: Our study shows that within the range of T parameter 1÷45, T=9 proved to be the best value to discriminate the AC and DC of the fetal heart rate of IUGR from AGA fetuses prior to 34 weeks of gestation. These significant differences are emphasized in very preterm gestational age epochs.

Recently, the research efforts in the context of electrocardiographical recording during atrial fibrillation (AF) has been directed to broaden the understandings on the electrophysiological and structural remodelling occurring during the arrhythmia and on characterizing the different types of AF. Following this line, both surface ECG and endocardial electrograms have been thoroughly studied and a series of linear and non-linear parameters were computed either directly on the electrograms or on the derived activation series. In this paper, we reviewed some signal processing methods used to characterize surface ECG and endocardial electrograms during AF, focusing on spectral and non-linear analysis. In particular, parametric and non-parametric methods for spectral analysis of the residual ECG, i.e. atrial waves obtained from surface ECG after removing ventricular activity, and endocardial recordings are described. The different purposes of spectral analysis (exploring autonomic functions, analysis of spontaneous AF behaviour and predicting therapeutic effects) are illustrated with some examples. In addition, we described some more recent non-linear methods applied to AF, assessing the organization of atrial signals as well as ventricular response in AF. In particular, methods derived from embedding time series and based on entropy computation are illustrated and exemplified.

Cyanobacteria are widely distributed in terrestrial, freshwater and marine environments, and over the past decades have been recognized as a powerful source of bioactive compounds. In this study, some cyanobacterial strains were isolated from samples of seawater, brackish water and tissue of reef benthic invertebrates (zoanthid Protopalythoa variabilis, the sponges Cynachrella sp. and Haliclona sp., the coral Siderastrea stellata, and ascidians), collected at the states of Paraíba and Rio Grande do Norte (Northeast of Brazil), during the period between July 2010 and February 2014. After standard isolation methods, the cultivation of the strains was carried out in acclimatized culture chamber (25 °C) under constant aeration, for 15 days at 12-hour photoperiod, using Conway and BG11 media made with filtered seawater. After ethanolic and methanolic extracts, the strains were analysed for the microcystin production by the ELISA technique and for the antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa by the agar well diffusion method. The detection of the mcyB gene, one of the genes related to the microcystin synthesis, was done by the Polymerase Chain Reaction (PCR) technique. The majority of the eighteen cyanobacterial strains belonged to Synechococcaceae Family. The genera of Synechocystis, Synechococcus and Romeria were represented by ten, six and two strains, respectively. The production of microcystins was observed in five strains belonging to the genus Synechocystis. The presence of mcyB gene was detected in 12 strains of cyanobacteria: Synechocystis (three strains), Synechococcus (six strains) and Romeria (two strains). Only one strain (Synechocystis aquatilis) showed both the microcystin production and the mcyB gene presence. The antibacterial activity was observed for one strain of Romeria gracilis, one strain of Synechocystis aquatilis and two strains of Synechococcus sp. The ethanolic extracts of R. gracilis strain and two Synechococcus spp. strains inhibited the growth of P. aeruginosa. Among methanolic extracts of cyanobacteria, only one strain of S. aquatilis showed activity against S. aureus, and one R. gracilis strain against P. aeruginosa. Some cyanobacterial strains studied were positive for the microcystin production and antibacterial activity against pathogenic bacteria S. aureus and P. aeuruginosa, and may be further explored for additional biotechnological applications. Las cianobacterias se encuentran ampliamente distribuidas en ecosistemas terrestres, de agua dulce y marinos, y en las últimas décadas han sido reconocidas como una poderosa fuente de compuestos bioactivos. En este estudio, las cepas de cianobacterias fueron aisladas a partir de agua de mar, agua salobre y muestras de tejidos de invertebrados bentónicos de arrecifes (zoanthid Protopalythoa variabilis, las esponjas Cynachrella sp. y Haliclona sp., el coral Siderastrea stellata y ascidias) recogidas en los estados de Paraíba y Rio Grande do Norte, en el noreste de Brasil, en el período comprendido entre julio 2010 y febrero 2014. La mayoría de las dieciocho cepas de cianobacterias pertenecían a la Familia Synechococcaceae. Los géneros: Synechocystis, Synechococcus y Romeria estuvieron representados por diez, seis y dos cepas, respectivamente. Las cepas fueron analizadas para la producción de microcistina por ELISA y para la actividad antibacteriana contra Staphylococcus aureus y Pseudomonas aeruginosa por el método de difusión en agar. La detección del gen mcyB, uno de los genes relacionados con la síntesis de microcistina, se realizó mediante la técnica de reacción en cadena de la polimerasa (PCR). El cultivo de las cepas se realizó en cámara de cultivo aclimatada (25 ° C) bajo aireación constante durante 15 días con un fotoperíodo de 12 horas utilizando los medios Conway y BG11 elaborados con agua de mar filtrada. Se observó la producción de microcistina en cinco cepas pertenecientes al género Synechocystis. La presencia del gen mcyB fue detectada en doce cepas de cianobactérias: Synechocystis (tres cepas), Synechococcus (seis cepas) y Romeria (dos cepas). Sólo una cepa (Synechocystis aquatilis) mostró tanto la producción de microcistina como la presencia del gen mcyB. Se observó la actividad antibacteriana de una cepa de Romeria gracilis, de una cepa de Synechocystis aquatilis y dos cepas de Synechococcus sp. Los extractos etanólicos de las cepas de R. gracilis y Synechococcus sp. inhibieron el crecimiento de P. aeruginosa. Entre los extractos metanólicos de cianobacterias solamente S. aquatilis mostró actividad contra S. aureus y R. gracilis contra P. aeruginosa. Varias cepas de cianobacterias estudiadas en este trabajo fueron positivas para la producción de microcistina y actividad antibacteriana frente a bacterias patógenas de S. aureus y P. aeuruginosa, y pueden ser explotadas para aplicaciones biotecnológicas.

Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a number of articles have been published to describe new HRV methodologies and their application in different physiological and clinical studies. This document presents a critical review of the new methods. A particular attention has been paid to methodologies that have not been reported in the 1996 standardization document but have been more recently tested in sufficiently sized populations. The following methods were considered: Long-range correlation and fractal analysis; Short-term complexity; Entropy and regularity; and Nonlinear dynamical systems and chaotic behaviour. For each of these methods, technical aspects, clinical achievements, and suggestions for clinical application were reviewed. While the novel approaches have contributed in the technical understanding of the signal character of HRV, their success in developing new clinical tools, such as those for the identification of high-risk patients, has been rather limited. Available results obtained in selected populations of patients by specialized laboratories are nevertheless of interest but new prospective studies are needed. The investigation of new parameters, descriptive of the complex regulation mechanisms of heart rate, has to be encouraged because not all information in the HRV signal is captured by traditional methods. The new technologies thus could provide after proper validation, additional physiological, and clinical meaning. Multidisciplinary dialogue and specialized courses in the combination of clinical cardiology and complex signal processing methods seem warranted for further advances in studies of cardiac oscillations and in the understanding normal and abnormal cardiac control processes.

Drug-induced alterations of ventricular heterogeneity must be limited to avoid induction of lethal ventricular arrhythmias. In here, a new parameter called V-index, able to measure the standard deviation of myocites' repolarization times, was evaluated after moxifloxacin administration. 24-h Holter ECGs of 68 healthy subjects enrolled for a thorough QT study were retrospectively analyzed. The placebo and active-comparator (moxifloxacin) arms were considered. The standard QT interval (Fridericia's correction) was included as well, for a direct comparison. V-index and QT increased along with the drug's serum concentration and were statistically different from values in the placebo arm (p c : 428.77 ± 25.17 ms at 5h vs 418.08 ± 23.37 ms at 0h; V-index: 31.67 ± 11.01 ms at 5h vs 27.72 ± 7.59 at 0h) and both were statistically different from predose (p

Atrial electrogram (AEGs) recorded invasively inside the atrium can be analyzed to assess the organization of the atrial electrical activity. These organization measures are commonly based either on the repeatability/regularity of the atrial activations or on the correlation/synchronicity among electrograms recorded in different sites. For many applications, it could be useful to have a synthetic AEG generator to test new methods on. So far, models capable to reproduce realistic AEGs do not exist yet. Aim of this study is to propose a unified approach to generate synthetic AEGs during sinus rhythm (SR) and atrial tachyarrhythmias, namely atrial fibrillation (AF) and atrial flutter (AFL). In particular, three different Wells organizations classes and different atrio-ventricular conductions will be considered during AF and AFL, respectively. A database of simulated signals during AF was created, containing AEGs with different degrees of Wells’ organization and different dominant frequencies. These AEGs were tested using spectral analysis assessing spectral concentration (SC), and wave-morphology similarity (WMS). Both indexes were in agreement with those presented in the relevant literature.

BACKGROUND: Fetal heart rate (FHR) variability is an indirect index of fetal autonomic nervous system (ANS) integrity. FHR variability analysis in labor fails to detect early hypoxia and acidemia. Phase-rectified signal averaging (PRSA) is a new method of complex biological signals analysis that is more resistant to non-stationarities, signal loss and artifacts. It quantifies the average cardiac acceleration and deceleration (AC/DC) capacity. OBJECTIVE: The aims of the study were: (1) to investigate AC/DC in ovine fetuses exposed to acute hypoxic-acidemic insult; (2) to explore the relation between AC/DC and acid-base balance; and (3) to evaluate the influence of FHR decelerations and specific PRSA parameters on AC/DC computation. METHODS: Repetitive umbilical cord occlusions (UCOs) were applied in 9 pregnant near-term sheep to obtain three phases of MILD, MODERATE, and SEVERE hypoxic-acidemic insult. Acid-base balance was sampled and fetal ECGs continuously recorded. AC/DC were calculated: (1) for a spectrum of T values (T = 1÷50 beats; the parameter limits the range of oscillations detected by PRSA); (2) on entire series of fetal RR intervals or on "stable" series that excluded FHR decelerations caused by UCOs. RESULTS: AC and DC progressively increased with UCOs phases (MILD vs. MODERATE and MODERATE vs. SEVERE, p

Recent studies in biometrics focus on one dimensional physiological signals commonly acquired in medical applications, like electrocardiogram (ECG), electroencephalograms (EEG), phonocardiogram (PCG), and photoplethysmogram (PPG). In this context, an important application is in continuous authentication scenarios since physiological signals are frequently captured for long time periods in order to monitor the health status of the patients.

We surely agree with Wessel et al. that heart period fluctuations are linked to many physiological oscillations. As already explained in the 1996 heart rate variability (HRV) standards,1 these oscillations include those of respiration,2 blood pressure,3 etc. The shifts in the respiration-related HRV components into the nominal low-frequency band are also known4 as is the fact that the low-frequency HRV modulations cannot be taken as a single reliable expression of sympathetic activity.1 It is difficult to consider respiration as an overwhelming determinant of short-term HRV. Adding additional provocations to constant controlled breathing still leads …

During atrial fibrillation (AF), cancellation of ventricular activity from atrial electrograms (AEG) is commonly performed by template matching and subtraction (TMS): a running template, built in correspondence of QRSs, is subtracted from the AEG to uncover atrial activity (AA). However, TMS can produce poor cancellation, leaving high-power residues. In this study, we propose to modulate the templates before subtraction, in order to make the residuals as similar as possible to the nearby atrial activity, avoiding high-power ones. The coefficients used to modulate the template are estimated by maximizing, via Multi-swarm Particle Swarm Optimization, a fitness function. The modulated TMS method (mTMS) was tested on synthetic and real AEGs. Cancellation performances were assessed using: normalized mean squared error (NMSE, computed on simulated data only), reduction of ventricular activity (VDR), and percentage of segments (PP) whose power was outside the standard range of the atrial power. All testings suggested that mTMS is an improvement over TMS alone, being, on simulated data, NMSE and PP significantly decreased while VDR significantly increased. Similar results were obtained on real electrograms (median values of CS1 recordings PP: 2.44 vs. 0.38 p < 0.001; VDR: 6.71 vs. 8.15 p < 0.001).

Injuries caused by venomous animals reported by the agricultural workers from the municipality of Cuité, Curimataú region of Paraiba State, Northeast of Brazil, and the practices of folk medicine which they use to treat these cases were studied in this work from June to August 2010. The farmers studied aged from 11 to 90 years. The number of people who reported cases of injury by these animals in their families was high (89.3%). Scorpions, wasps, bees and snakes were the most cited and the extremities of the body (hands, feet, legs and head) were the most affected. The practice of folk medicine to treat these injuries includes various procedures ranging from ritualistic treatments, use of animals or parts of them, and some herbal preparations. The folk treatment was reported as effective by most of the workers injured (63.9%). Body parts of dead snakes are used in various zootherapic treatments. In the imaginary of the agricultural workers the venomous animals are considered hazardous (48.7%) or disgusting (11.3%), and several parts of such animals as the rattle, bee sting or snake leather are used as amulet. Several legends have also been reported about snakes, scorpions and bees. The need for educational activities that aim to clarify these workers about the dangers of such practices is urgent. Acidentes por animais peçonhentos ocorridos com agricultores sindicalizados do município de Cuité, região do Curimataú paraibano, e práticas de medicina popular por eles utilizadas foram estudadas neste trabalho, através de entrevistas livres e questionários semiestruturados durante o período de junho a agosto de 2010. A idade dos agricultores pesquisados variou de 11 a 90 anos e a incidência de pessoas que sofreram algum acidente com esses animais chegou a 89,3%. Escorpiões, marimbondos, abelhas e serpentes foram os animais mais citados. As extremidades do corpo (mãos, pés, pernas e cabeça) foram as regiões mais atingidas. A prática da medicina popular para tratar desses acidentes inclui vários procedimentos que vão desde tratamentos ritualísticos, uso de animais ou partes dele, até preparos fitoterápicos. O tratamento caseiro é reconhecido como sendo eficaz pela maioria dos que sofreram acidentes (63,9%). Serpentes mortas têm várias partes do corpo arrancadas e usadas em tratamentos zooterápicos diversos. No imaginário dos agricultores, os animais peçonhentos são vistos como perigosos (48,7%) ou nojentos (11,3%), e diversas partes desses animais como chocalho, ferrão da abelha ou couro da cobra são usadas como amuletos de sorte. Inúmeras lendas também foram relatadas com cobras, escorpiões e abelhas. A necessidade de atividades educacionais visando esclarecer esses trabalhadores sobre os perigos dessas práticas é urgente.

Temporal heterogeneity of ventricular repolarization is a key quantity for the development of ventricular reentrant arrhythmia. In this paper, we introduce the V-index, a novel ECG-based estimator of the standard deviation of ventricular myocytes' repolarization times s(ϑ). Differently from other ECG metrics of repolarization heterogeneity, the V-index was derived from the analysis of a biophysical model of the ECG, where repolarization is described by the dominant T-wave (DTW) paradigm. The model explains the shape of T-waves in each lead as a projection of a main waveform (the DTW) and its derivatives weighted by scalars, the lead factors. A mathematical formula is derived to link the heterogeneity of ventricular repolarization s(ϑ) and the V-index. The formula was verified using synthetic 12-lead ECGs generated with a direct electrophysiological model for increasing values of s(ϑ) (in the range 20-70 ms). A linear relationship between the V-index and s(ϑ) was observed, V ≈ 0.675 s(ϑ) + 1.8 ms (R(2) = 0.9992). Finally, 68 ECGs from the E-OTH-12-0068-010 database of the Telemetric and Holter ECG Warehouse were analyzed. The V-index coherently increased after sotalol administration, a drug known to have QT-prolonging potential (p0.001).