Test Whats new message.
Scheduled Maintenance on Monday 1/13/2025
Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.
Showing 1-12 of 12 results
- Sort
Filter Results
Show
Sort By
Results
A Measurement System to Estimate the Pleural Pressure From the CVP for Respiratory System Monitoring
Tommaso Addabbo;Gennaro Cataldo;Gabriele Cevenini;Ada Fort;Federico Franchi;Riccardo Moretti;Marco Mugnaini;Sabino Scolletta;Valerio Vignoli
We present a technique to estimate the pleural pressure combining the information provided by the central venous pressure (CVP) and electrocardiographic signals (ECG) for respiratory system monitoring. We discuss the characterization of the proposed measurement method with theoretical modeling, numerical analysis, and experiments based on signals acquired from intensive care unit patients. The res...Show More
A Novel Measurement System to Estimate the Trans-Pulmonary Pressure Exploiting the Central Venous Pressure and ECG Signals
T. Addabbo;A. Fort;R. Moretti;M. Mugnaini;V. Vignoli;G. Cataldo;G. Cevenini;F. Franchi
2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
Year: 2018 | Conference Paper |
Cited by: Papers (3)
We present a measurement system to estimate the trans-pulmonary pressure combining the information provided by the central venous pressure and the electrocardiographic signals. We discuss the characterization of the measurement system with theoretical modeling, numerical analysis and experiments based on signals acquired from intensive care unit patients. The results confirm the validity of the pr...Show More
Spitz nevus versus atypical Spitz tumor: Objective morphological differentiation by digital dermoscopy analysis
Pietro Rubegni;Linda Tognetti;Michele Pellegrino;Marco Burroni;Michele Fimiani;Clelia Miracco;Elisa Cinotti;Frédéric Cambazard;Riccardo Bono;Gabriele Cevenini
2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
Year: 2016 | Conference Paper |
Cited by: Papers (1)
Spitzoid melanocytic skin lesions (MSL) include Spitz nevi (SN) and spitzoid melanomas (SM). A third rare subset was described, atypical spitz tumors (AST), that share overlapping histologic features of SN and SM. Being difficult to diagnose lesions, both with dermoscopy and histology, there is considerable uncertainty regarding their biological potential. We aimed to investigate if digital dermos...Show More
Spitz nevus versus atypical Spitz tumor: Objective morphological differentiation by digital dermoscopy analysis
Pietro Rubegni;Linda Tognetti;Michele Pellegrino;Marco Burroni;Michele Fimiani;Clelia Miracco;Elisa Cinotti;Frédéric Cambazard;Riccardo Bono;Gabriele Cevenini
Year: 2016 | Conference Paper |
Scoring systems in dermatology
Gabriele Cevenini;Simone Furini;Paolo Barbini;Linda Tognetti;Pietro Rubegni
2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
Year: 2016 | Conference Paper |
Cited by: Papers (2)
Three scoring systems were considered and described for dermatological applications in which malignant and benign skin lesions have to be recognized: two models are derived from logistic regression and naïve Bayes rule by rounding model parameters to their nearest integer values; the third approach defines the scoring system by a direct stepwise adding of the most significant binary risk factors. ...Show More
A non-linear lumped-parameter model of the tracheobronchial tree has been recently proposed to simulate expiratory flow limitation (EFL) in mechanical ventilation. The model is based on Weibel's symmetrical description of lung anatomy subdivided into 24 generations, where the first 17 generations correspond to conductive airways and the last 7 generations belong to the respiratory zone. Thanks to ...Show More
A neural network improves the classification of high-risk intensive care patients
Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 1996 | Conference Paper |
Cited by: Patents (8)
A two-layer feedforward neural network for classifying intensive care patients as normal or at risk for severe cardiorespiratory disorders was designed and compared with the best, previously investigated, Bayesian classifier of similar complexity. At three distinct observation times soon after heart surgery, the three variables most effective in separating the two classes were measured and used to...Show More
A stepwise regression approach applied to evaluation of nonlinear patterns in breathing mechanics
Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 1996 | Conference Paper |
Cited by: Papers (1)
A multiple linear stepwise regression approach was applied to respiratory data from intensive care patients. The influence of different nonlinear viscoelastic properties on the prediction of pressure at the airway opening taken as dependent variable was studied by entering and removing potential predictive variables. These variables were derived from measured ventilatory flow data so as to quantit...Show More
Influence of flow pattern on the parameter estimates of a simple breathing mechanics model
The first-order model of breathing mechanics is widely used in clinical practice to assess the viscoelastic properties of the respiratory system. Although simple, this model takes the predominant features of the pressure-flow relationship into account but gives highly systematic residuals between measured and model-predicted variables. To achieve a better fit of the entire data set, an approach hy...Show More
Two new algorithms for tracking arterial parameters in nonstationary noise conditions
Two new algorithms with reduced sensitivity to the changing environment are applied to tracking arterial circulation parameters. They are variants of the Least-Squares (LS) algorithm with Variable Forgetting factor (LSVF), and of the Constant Forgetting factor-Covariance Modification (CFCM) LS algorithm, devised to overcome their main practical deficiencies related to noise level sensitivity and t...Show More
Tracking time-varying properties of the systemic vascular bed
G. Avanzolini;P. Barbini;A. Capello;G. Cevenini;V. Pohl;T. Sikora
The problem of tracking changes in viscoelastic properties of the systemic arterial bed is considered, and a recursive estimation procedure, belonging to the class of output-error algorithms with adjustable compensator, is developed and discussed. By means of computer simulation, suitable values are determined for the key design variable which controls the tradeoff between the tracking ability and...Show More
Electrical analogs for monitoring vascular properties in artificial heart studies
G. Avanzolini;P. Barbini;A. Cappello;G. Cevenini;D. Moller;V. Pohl;T. Sikora
The problem of choosing parametric descriptions of the systematic vascular bed suitable for monitoring beat-to-beat changes in peripheral vascular properties is considered. Three simple models with two, three, and five elements are compared, essentially exploiting the Akaike information criterion combined with reasonable requirements for estimate accuracy. Analysis of pressure data, which are eith...
Show More
First Page of the Article
Show MoreReal-time tracking of breathing parameters in mechanically ventilated dogs
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 1988 | Conference Paper |
Cited by: Papers (3)
A recursive identification algorithm with a constant forgetting factor is applied to online identification of the mechanical properties of the respiratory system. The well-known two-parameter model, accounting for pulmonary compliance and resistance, is adopted to characterize breathing mechanics. The algorithm is first tested by using flow and pressure data measured on mechanically ventilated dog...
Show More
First Page of the Article
Show MoreIEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.