1,720,972 research outputs found
Analysis of the circadian rhythm of cardiovascular signals and their prognostic use in decision support systems
No full textThe focus of my research activity has been on the processing of cardiovascular signals in order to be able to use them as a support tool for doctors in their clinical decision making. Although the analysis of these cardiovascular signals has mainly been based on the punctual estimation of blood pressure and heart rate parameters, it is well known that the outpatient information, obtained from the 24h ambulatory monitoring, can provide prognostic support. Therefore I have tried to examine in detail how the values of the parameters related to blood pressure and heart rate over 24h change and how the relationship between them varies. Since the cardiovascular risk factors alter the trend of these biological signals, I have performed an analysis of the effects of each single risk factors on the circadian trend of the two signals and their relationship. Since, in recent years, mathematical approaches have been developed for the construction of clinical decision support systems applied, in the cardiovascular field, only to the classification of single heart beats of different etiologies; I have developed decision support systems to identify subjects with or without cardiovascular diseases. The pathologies examined were ischemic heart (IHD) and dilated cardiomyopathy (DCM). The described problems have been addressed using linear and nonlinear methods of signal processing and applying artificial intelligence algorithms. The average circadian trends of pressure and heart rate and their relationship on different categories of subjects were obtained. The linear and non-linear parameters were calculated from the heart rate variability signal and machine learning techniques were developed, the Artificial Neural Network (ANN) and Classification and Regression Tree (CART), applied to the previous parameters in addition to age, gender and to a specific clinical parameter. The results showed that the cardiovascular signals over 24h show a characteristic linear circadian rhythm divisible into four time intervals for the pressure signal (three intervals for the heart rate) in both normotensive and hypertensive subjects highlighting the importance of taking into account the time of day in which the signal is measured. The relationship between these two signals evaluated over 24h could be useful for understanding the control mechanism of the autonomic nervous system. The examination of the effects of risk factors such as smoking, obesity and dyslipidemia on cardiovascular signals showed that each factor modifies the physiological signals. The investigation of the influence of age and gender on cardiovascular signals highlighted an inversion of the trend in linear and non-linear parameters of heart rate variability in subjects>60 years of age and a gender differentiation only during the night. Finally, the results obtained by developing decision support systems based on machine learning techniques applied to various combinations of parameters, selected through principal component analysis, stepwise regression or correlated for less than 90%, showed that the ANN technique identify normal subjects and IHD with an accuracy of 80% and that the CART algorithm classify DCM patients with an accuracy of 97%. The latter technique was also able to distinguish these two etiologies from each other and from normal subjects with an accuracy of 81%. The results of my PhD activity highlight the importance of circadian analysis of cardiovascular signals, suggesting that particular attention should be paid to the time in which the measurements are performed providing useful information for the evaluation of the mechanisms that regulate the physiological control of the examined signals. Furthermore, the use of decision support systems based on machine learning techniques applied to parameters obtained in a non-invasive way from the processing of the heart rate variability is useful for diagnosing various cardiovascular diseases
Relationship Between Blood Pressure and Heart Rate Circadian Rhythms in Normotensive and Hypertensive Subjects
Get PDFThis paper focuses on the relationship between blood pressure (BP) and heart rate (HR) during 24 hours in 423 normotensive (NO) and 205 hypertensive (HE) subjects. Although considerable knowledge has been gained about BP and HR signals, their relationship over 24 hours has never been completely described. By using a Holter Blood Pressure Monitor, it was possible to record BP and HR for 24 hours. Systolic, Diastolic and Mean BP in both NO and HE subjects showed four different time intervals presenting well-defined trends The results demonstrated that changes in HR present closely parallel changes in BP with a marked reduction of both signals during nocturnal rest. On the contrary, in the period between 15:30 and 19:30, HR and BP showed an inverse relationship with decreasing heart rate and increasing blood pressure
Handwriting Kinematic Differences Between Copying and Dictation
No full textHandwriting is a human activity that may be affected by the modality used as input of the information to be written, mainly copying or dictation. Many processes at different levels are involved to produce motor planning and graphomotor automation of handwriting. In order to quantify possible kinematic differences due to the influence of auditory or visual input modalities to these processes, three different tests were proposed to a sample of 101 young students and several kinematics parameters measuring handwriting characteristics were evaluated. The tests required to copy as accurate (CA) and as fast (CF) as possible an Italian sentence and to write the same sentence under dictation (DF). All parameters showed significant differences between each pair of the three tests. The best performance was obtained in the CF test followed by the DF and CA tests; in the latter the greater accuracy required to produce writing yielded lower velocity and automation as well as a longer motor planning time. On the other hand, the dictation response was more similar to that of CF than CA showing a larger planning time, probably due to a different time necessary to correctly identify the words to reproduce. The combination of the two tests could be useful to study the impairment of either visual or auditory input
Influence of hypertension and other risk factors on the onset of sublingual varices
Get PDFBackground: Sublingual varices (SV) are dilatations of tortuous veins that increased with age. Previous studies showed that this pathology could be correlated to some risk factors such as hypertension, age, gender and diabetes mellitus. In this study we evaluated, on a large number of subjects, the relationship between SV and different grades of hypertension as well as some risk factors extending the analysis to new risk factors such as dyslipidemia, obesity and antihypertensive therapy, modelling a possible dependence of SV on all these factors.Methods: In the study 1008 subjects, 284 with and 724 without SV, were examined. The blood pressure was measured in office condition and, to exclude subjects with white coat syndrome or masked hypertension, also using a 24 h Holter pressure monitor. Hypertensive subjects were divided in resistant, drugs controlled (compensated) and patients with prior unknown hypertension (new diagnosed) groups. The presence or absence of SV as well as of the risk factors was assessed clinically. We tested the influence of age on the presence of SV by using the chi-square test and the relation between each risk factor and SV by the Cochran-Mantel-Haenszel test. Finally, we carried out a multivariate regression tree analysis in order to predict the presence of SV.Results: We confirmed the influence of age on SV and found a significant relationship between SV and both the compensated and resistant hypertension grades. We highlighted a relationship between SV and dyslipidemia in subjects with new diagnosed hypertension, and between SV and smoking in subjects with compensated hypertension grade. The regression tree showed a classification accuracy of about 75% using as variables hypertension grades, age and antihypertensive treatment.Conclusions: We confirmed the SV dependence on age, resistant hypertension and smoking, highlighting a new association with dyslipidemia in new diagnosed hypertensive subjects and new relations depending on the hypertension grades. Thus, the SV inspection could be used to suggest a lipidologist as well as a hypertension specialist visit for a pharmacological and pressure check particularly in subjects presenting SV and dyslipidemia. However, further parameters are to be considered to improve the sensitivity of the prognostic tree model
Ambulatory blood pressure monitoring versus office blood pressure measurement: Are there sex differences?
Get PDFThe accurate measurement of blood pressure (BP) is an important prerequisite for the reliable diagnosis and efficient management of hypertension and other medical conditions. Office Blood Pressure Measurement (OBP) is a technique performed in-office with the sphygmomanometer, while Ambulatory Blood Pressure Monitoring (ABPM) is a technique that measures blood pressure during 24h. The BP fluctuations also depend on other factors such as physical activity, temperature, mood, age, sex, any pathologies, a hormonal activity that may intrinsically influence the differences between OBP and ABPM. The aim of this study is to examine the possible influence of sex on the discrepancies between OBP and ABPM in 872 subjects with known or suspected hypertension. A significant correlation was observed between OBP and ABPM mean values calculated during the day, night and 24h (ABPMday, ABPMnight, ABPM24h) in both groups (p<0.0001). The main finding of this study is that no difference between sexes was observed in the relation between OBP and mean ABMP values except between systolic OBP and systolic ABPM during the night. In addition, this study showed a moderate correlation between BPs obtained with the two approaches with a great dispersion around the regression line which suggests that the two approaches cannot be used interchangeably
Detection of subjects with ischemic heart disease by using machine learning technique based on heart rate total variability parameters
Get PDFOBJECTIVE: Ischemic heart disease (IHD), in its chronic stable form, is a subtle pathology due to its silent behavior before developing in unstable angina, myocardial infarction or sudden cardiac death. The clinical assessment is based on typical symptoms and finally confirmed, invasively, by coronary angiography. Recently, heart rate variability (HRV) analysis as well as some machine learning algorithms like Artificial Neural Networks (ANNs) were used to identify cardiovascular arrhythmias and, only in few cases, to classify IHD segments in a limited number of subjects. The goal of this study was the identification of the ANN structure and the HRV parameters producing the best performance to identify IHD patients in a non-invasive way, validating the results on a large sample of subjects. Moreover, we examined the influence of a clinical non-invasive parameter, the left ventricular ejection fraction (LVEF), on the classification performance.APPROACH: To this aim, we extracted several linear and non-linear parameters from 24h RR signal, considering both normal and ectopic beats (Heart Rate Total Variability), of 251 normal and 245 IHD subjects, matched by age and gender. ANNs using several different combinations of these parameters together with age and gender were tested. For each ANN, we varied the number of hidden neurons from 2 to 7 and simulated 100 times changing randomly training and test dataset.MAIN RESULTS: The HRTV parameters showed significant greater variability in IHD than in normal subjects. The ANN applied to meanRR, LF, LF/HF, Beta exponent, SD2 together with age and gender reached a maximum accuracy of 71.8% and, by adding as input LVEF, an accuracy of 79.8%.SIGNIFICANCE: The study provides a deep insight into how a combination of some HRTV parameters and LVEF could be exploited to reliably detect the presence of subjects affected by IHD
Toward a diagnostic CART model for Ischemic heart disease and idiopathic dilated cardiomyopathy based on heart rate total variability
Get PDFDiagnosis of etiology in early-stage ischemic heart disease (IHD) and dilated cardiomyopathy (DCM) patients may be challenging. We aimed at investigating, by means of classification and regression tree (CART) modeling, the predictive power of heart rate variability (HRV) features together with clinical parameters to support the diagnosis in the early stage of IHD and DCM. The study included 263 IHD and 181 DCM patients, as well as 689 healthy subjects. A 24 h Holter monitoring was used and linear and non-linear HRV parameters were extracted considering both normal and ectopic beats (heart rate total variability signal). We used a CART algorithm to produce classification models based on HRV together with relevant clinical (age, sex, and left ventricular ejection fraction, LVEF) features. Among HRV parameters, MeanRR, SDNN, pNN50, LF, LF/HF, LFn, FD, Beta exp were selected by the CART algorithm and included in the produced models. The model based on pNN50, FD, sex, age, and LVEF features presented the highest accuracy (73.3%). The proposed approach based on HRV parameters, age, sex, and LVEF features highlighted the possibility to produce clinically interpretable models capable to differentiate IHD, DCM, and healthy subjects with accuracy which is clinically relevant in first steps of the IHD and DCM diagnostic process. GRAPHICAL ABSTRACT: [Image: see text
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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