A. Macerata

Cardiac and respiratory monitoring through non-invasive and contactless radar technique

The aim of this study was the evaluation of a microwave (MW) device for vital signs monitoring of patients and for MW signal characterization in terms of physiological content and meaning. Experimental tests were executed on volunteers in selected and controlled conditions and with different device setting. In each test session the MW signal was digitally acquired and saved together with true physiological signals coming from standard medical instrumentation. Single and multichannel data processing were applied in order to extract characteristic features from each signal and to identify any significant correlation. The results show the ability of the method to obtain precise indications on small physiological movements such as breathing or heartbeat; the received MW signal seems to offer specific information about the mechanical dynamics of the cardiac system. With our configuration settings, main limitations of this approach come from its low capacity to penetrate deeply into the body and to the poor spatial resolution.

Use of an electronic medical record in a department of cardiology

A computer-network infrastructure was realized to integrate the different remote cardiovascular diagnostic laboratories with the data derived from CCU and the administrative information. A variety of heterogeneous data, texts, signals, images is gathered from each peripheral unit, stored into a relational database (ARCA), processed and presented to health-care personnel by network-connected clinical workstations. From August 1999 to August 2000 the Electronic Medical Records (EMR) of 754 patients hospitalized in a Cardiological department were collected; 7808 procedures were digitally integrated and for each patient was possible to calculate the number of tests performed during hospitalization and the quantity of drugs assumed. The use of EMR allowed to obtain rapidly a clinical data integration, to access to patient data from any clinical lab; to collect information to obtain patient cost definition.

Electronic medical records in a cardiological outpatient clinic

In an outpatient clinic, a huge amount of information, administrative, clinical and instrumental, has to be handled every day for patient care. A computerized method has been developed in our Institute that is able to track the patient from administrative admission up to discharge. For the purpose of obtaining electronic medical records in the patient who undergoes clinical and instrumental examinations, even on the same day, each clinical laboratory is provided by networked computers and results from instrumental data can be obtained on-line. The system is based on a relational database with clinical and administrative information and is integrated with a large hospital information system where the system covers the role of a functional island. Use of Java language, with its multiplatform capabilities, allows extensive installation in the clinical environment and full integration with other subsystems. A protected Web front-end allows remote consultation of data. For follow up purposes, all the data collected from 1999 to the present day during hospital admission of in- or out-patients can be collected, retrieved and updated. At present 4600 cardiological outpatients have been treated by this system with substantial clinical achievements, time saving, and better follow up organization.

QRS morphological classification using artificial neural networks

Artificial neural networks (ANNs) were applied to electrocardiographic (ECG) signals to classify QRS complexes. Several ANN paradigms were considered, and two were selected for the ECG analysis: backpropagation (BP) and the Kohonen feature map (KFM). ANNs were trained on 8 groups of 20 QRS complexes each, extracted from the VALE database (DB); each group was related to a QRS morphology as obtained by the DB annotations. The ANN performances were evaluated using both the learning set and the whole case as a recall set. The BP network showed a good specificity and was found able to separate morphologies with ambiguous DB annotations. The KFM network was able to create a clustering of QRS morphologies with a high agreement with the original annotations.<<ETX>>

Analysis of variability: a system for comparing classical, parametric, adaptive and Wigner-Ville power spectral estimators

The typical approach to the study of variability of physiopathological conditions consists of the analysis of a power spectral density (PSD) function estimation, computed on a time series extracted from the signal of interest. In order to facilitate the correct choice among the available methods for PSD estimation in practical situations, different PSD estimators have been applied extensively to identify their performance. It is shown that with the classical, fast Fourier transform (FFT) based approach, 39 tapering windows can be tested, allowing the computation of the FFT-based spectrograms, with a variety of options. The parametric approach allows different estimators to be tested in different situations. The Wigner-Ville PSD estimator is introduced, which is able to associate a PSD to each time domain sample, allowing an appreciation of the variability of the PSD even in nonstationary data segments. A comprehensive graphical interface allows a visual comparison among the different estimators.<<ETX>>

Effectiveness of adaptive filtering in cancelling the respiratory component from cardiovascular series

Spectral analysis of cardiovascular variability signals is currently used as a tool for investigating autonomic neural control of heart activity and vasomotion. However, in many different pathophysiological conditions variations in tidal volume and/or respiratory rate may account for a possible respiratory parasympathetic contribution to low frequency variability of heart rate and blood pressure, currently interpreted as associated with sympathetic modulation. By cancelling respiratory contribution, adaptive filtering allows a better estimation of the purely vasomotor LF component of cardiovascular variability.

Remote biosignal monitoring, display, online analysis and retrieval

A model for distributed signal acquisition and processing has been designed and implemented. The model is based on a LAN client-server structure: it allows signal acquisition on a dedicated server and acquired samples distribution to different client workstations for signal representation and/or processing. The communication between server and clients is based on TCP/IP protocol. A set of specific commands allows the client to get the server acquisition configuration and to request/receive signal samples. In order to facilitate the development of client own system for signal analysis a library of Java functions (or classes) was created including the basis of biosignal processing and display; these classes have to be included by the developer into the user specific program for signal acquisition and elaboration. The system is under test in the research LAN of our Institute. It consists of one PC-server with an AID converter board and one client workstation for displaying and processing cardiovascular and respiratory signals obtained from patients studied with autonomic testing.

Analysis of non-stationary heart rate series by evolutionary periodogram

The study of heart rate variability (HRV) in the frequency domain provides information to evaluate the sympathetic and parasympathetic activities of the autonomic nervous system (ANS) as related to the cardiovascular system. Many diagnostic procedures require that patients will be submitted to tests and manoeuvres able to provoke well known cardiac answers associated to specific ANS behaviour. As result of these provocative tests a non-stationary heart rate time series is often produced. Classical spectral analysis, performed by FFT or AR modelling, can be applied under steady-state condition only. Methods capable of detecting time variations of spectral components can be adopted to overcome these shortcomings. Among these methods, in this paper the Evolutionary Periodogram is evaluated. This approach decomposes the original non-stationary signal by means of basic functions of oscillatory form; these functions are non-stationary but the notion of frequency is still dominant. The method was tested on non-stationary simulated signals and real HR series recorded during tilt test, Valsalva manoeuvres, baroreflex evocation by intravenous phenylephrine administration. The same series were submitted to the STFT for comparison of the results.

A workstation for data consultation and clinical decision-support in the department of cardiology

A project for the realization of a Local Area Network in the department of Cardiology (LAN-C) is in progress at our institute with the objective of the integration of heterogeneous data acquired from diagnostic equipment to help clinical decision making. A special workstation of LAN-C, presented in this paper, has been designed for supporting data consultation and decision making. It integrates a set of applications: data retrieval and presentation, diagnostic and treatment planning protocols, in-depth analysis clinical decision support. Initially, the protocol for diagnosis of coronary artery disease and a module for the analysis of follow-up data were developed. Relevant diagnostic information is retrieved from the LAN-C database according to a protocol logic, defined by the cardiological staff. Regional myocardial wall motion and perfusion are represented at rest and during stress by 2-D synthetic diagrams. The module for statistical analysis allows one to select patients, followed up after discharge, for the identification of prognostic variables by the use of Cox regression model (BMDP 2L).<<ETX>>

Heart rate variability modified by altitude exposure

To study the influence of altitude exposure on heart rate variability (HRV) and the possible detection of apnea by ECG 11 male climbers performed 24-hour ECG and respiratory signal monitoring during an expedition to the Everest. Recordings were done as soon as they reached the altitude (=>5000 m, P1), after at least 15 days of acclimatization (P2) and at sea level (before and after the expedition, B1, B2). HRV indices were computed on the RR time series, and their mean hourly values were fitted by a harmonic regression model to quantify the circadian periodic structure. Significant changes of HPV indices were detected after altitude exposure: altitude distress induces tachycardia, reduces HRV indices and blunts circadian heart rate variability. Respiratory pattern greatly interferes with RR interval time series.