Fernando Seoane

Prof. Fernando Seoane

Karolinska Institute
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Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 January 2022 in Journal of Biomedical Informatics
Verified
Journal Article
Open access
Jorge Munoz-GamaJorge Munoz-Gama
Jorge Munoz-Gama
Niels MartinNiels Martin
Niels Martin
CFCarlos Fernandez-Llatas
Carlos Fernandez-Llatas
OJOwen A. Johnson
Owen A. Johnson
Marcos SepulvedaMarcos Sepulveda
Marcos Sepulveda
FZFrancesca Zerbato
Francesca Zerbato
Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.
22 April 2014 in Sensors
Verified
Journal Article
Open access
PDF file
FSFernando Seoane
Fernando Seoane
IMInmaculada Mohino-Herranz
Inmaculada Mohino-Herranz
JFJavier Ferreira
Javier Ferreira
LALorena Alvarez
Lorena Alvarez
RBRuben Buendia
Ruben Buendia
Roberto Gil PitaRoberto Gil Pita
Roberto Gil Pita
The Spanish Ministry of Defense, through its Future Combatant program, has sought to develop technology aids with the aim of extending combatants’ operational capabilities. Within this framework the ATREC project funded by the “Coincidente” program aims at analyzing diverse biometrics to assess by real time monitoring the stress levels of combatants. This project combines multidisciplinary disciplines and fields, including wearable instrumentation, textile technology, signal processing, pattern recognition and psychological analysis of the obtained information. In this work the ATREC project is described, including the different execution phases, the wearable biomedical measurement systems, the experimental setup, the biomedical signal analysis and speech processing performed. The preliminary results obtained from the data analysis collected during the first phase of the project are presented, indicating the good classification performance exhibited when using features obtained from electrocardiographic recordings and electrical bioimpedance measurements from the thorax. These results suggest that cardiac and respiration activity offer better biomarkers for assessment of stress than speech, galvanic skin response or skin temperature when recorded with wearable biomedical measurement systems.
7 December 2012 in Sensors
Verified
Journal Article
Open access
PDF file
JLJohan Löfhede
Johan Löfhede
FSFernando Seoane
Fernando Seoane
MTMagnus Thordstein
Magnus Thordstein
The overall aim of our research is to develop a monitoring system for neonatal intensive care units. Long-term EEG monitoring in newborns require that the electrodes don’t harm the sensitive skin of the baby, an especially relevant feature for premature babies. Our approach to EEG monitoring is based on several electrodes distributed over the head of the baby, and since the weight of the head always will be on some of them, any type of hard electrode will inevitably cause a pressure-point that can irritate the skin. Therefore, we propose the use of soft conductive textiles as EEG electrodes, primarily for neonates, but also for other kinds of unobtrusive long-term monitoring. In this paper we have tested two types of textile electrodes on five healthy adults and compared them to standard high quality electrodes. The acquired signals were compared with respect to morphology, frequency distribution, spectral coherence, correlation and power line interference sensitivity, and the signals were found to be similar in most respects. The good measurement performance exhibited by the textile electrodes indicates that they are feasible candidates for EEG recording, opening the door for long-term EEG monitoring applications.
1 June 2008 in Physiological Measurement
Verified
Journal Article
Closed access
FSFernando Seoane
Fernando Seoane
JFJavier Ferreira
Javier Ferreira
JSJuan José Sanchéz
Juan José Sanchéz
RBRamon Bragós
Ramon Bragós
The increasing number of applications of electrical bioimpedance measurements in biomedical practice, together with continuous advances in textile technology, has encouraged several researchers to make the first attempts to develop portable, even wearable, electrical bioimpedance measurement systems. The main target of these systems is personal and home monitoring. Analog Devices has made available AD5933, a new system-on-chip fully integrated electrical impedance spectrometer, which might allow the implementation of minimum-size instrumentation for electrical bioimpedance measurements. However, AD5933 as such is not suitable for most applications of electrical bioimpedance. In this work, we present a relatively simple analog front-end that adapts AD5933 to a four-electrode strategy, allowing its use in biomedical applications for the first time. The resulting impedance measurements exhibit a very good performance in aspects like load dynamic range and accuracy. This type of minimum-size, system-on-chip-based bioimpedance measurement system would lead researchers to develop and implement light and wearable electrical bioimpedance systems for home and personal health monitoring applications, a new and huge niche for medical technology development.
1 September 2020 in Artificial Intelligence in Medicine
Verified
Journal Article
Closed access
Niels MartinNiels Martin
Niels Martin
JWJochen De Weerdt
Jochen De Weerdt
Carlos Fernandez-LlatasCarlos Fernandez-Llatas
Carlos Fernandez-Llatas
AGAvigdor Gal
Avigdor Gal
RGRoberto Gatta
Roberto Gatta
BABart Van Acker
Bart Van Acker
1 September 2009
Verified
Conference Paper
Closed access
DADavid Ayllon
David Ayllon
FSFernando Seoane
Fernando Seoane
Roberto Gil PitaRoberto Gil Pita
Roberto Gil Pita
Since there are several applications of Electrical Bioimpedance (EBI) that use the Cole parameters as base of the analysis, to fit EBI measured data onto the Cole equation is a very common practice within Multifrequency-EBI and spectroscopy. The aim of this paper is to compare different fitting methods for EBI data in order to evaluate their suitability to fit the Cole equation and estimate the Cole parameters. Three of the studied fittings are based on the use of Non-Linear Least Squares on the Cole model, one using the real part only, a second using the imaginary part and the third using the complex impedance. Furthermore, a novel fitting method done on the impedance plane, without using any frequency information has been implemented and included in the comparison. Results show that the four methods perform relatively well but the best fitting in terms of standard error of estimate is the fitting obtained from the resistance only. The results support the possibility of measuring only the resistive part of the bioimpedance to accurately fit Cole equation and estimate the Cole parameters, with entailed advantages.