Table Of ContentNicos Maglaveras · Ioanna Chouvarda
Paulo de Carvalho (Eds.)
Volume 66
Precision Medicine Powered
by pHealth and Connected Health
ICBHI 2017, Thessaloniki, Greece, 18–21 November 2017
IFMBE Proceedings
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Nicos Maglaveras Ioanna Chouvarda
(cid:129)
Paulo de Carvalho
Editors
Precision Medicine Powered
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Health
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ICBHI 2017, Thessaloniki, Greece, 18 21
November 2017
123
Editors
NicosMaglaveras IoannaChouvarda
Department ofMedicine Department ofMedicine
Aristotle University of Thessaloniki Aristotle University of Thessaloniki
Thessaloniki Thessaloniki
Greece Greece
and PaulodeCarvalho
Department ofInformatics Engineering
Department ofIndustrial Engineering and University of Coimbra
ManagementSciences,DepartmentofElectrical Coimbra
EngineeringandComputer Science, Portugal
McCormickSchoolofEngineeringandApplied
Science, Centerfor Engineering andHealth
Northwestern University
Evanston, IL
USA
ISSN 1680-0737 ISSN 1433-9277 (electronic)
IFMBE Proceedings
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Preface
The IFMBE WG on Health Informatics and eHealth and Lab of Computing Medical Infor-
matics and Biomedical-Imaging Technologies, Aristotle University of Thessaloniki, have
organized the ICBHI 2017 in Thessaloniki on November 18–21, 2017.
The ICBHI 2017 conference is the third in a series of scientific events initiated from the
IFMBE Working Group on Health Informatics and eHealth bringing together expertise from
medical, technological, biodata sciences, regulatory, and public health domains.
Theareaofbiomedicalandhealthinformaticsisexplodingatallscales.Thedevelopments
intheareasofmedicaldevices(MDD),eHealth,andpersonalizedhealth(pHealth)asenabler
factors for the evolution of precision medicine are quickly developing and demand the
development of new scaling tools and integration frameworks and methodologies in the
following areas
(cid:129) Medical devices
(cid:129) Biomedical environmental and behavioral data acquisition
(cid:129) Biodata management and analytics
(cid:129) Advanced mHealth-inspired applications
(cid:129) User interaction systems and data/information exchange
(cid:129) Applied connected health and integrated care systems
(cid:129) Personalized health systems
(cid:129) Preventive and multimorbid disease management tools
(cid:129) Patient safety and efficient public health systems
(cid:129) In silico modeling of pathophysiological mechanisms
(cid:129) Translational research
(cid:129) Biomedical informatics
(cid:129) Biomedical informatics and technology education
It is expected that ICBHI 2017 will catalyze the personal health systems development
methodologythusachievingconvergenceandintegrationmechanismsoftheabove-mentioned
main scientific areas for the enabling of precision medicine. The need for managing the new
findingsandcapabilitiesaswellasintegratingcompetenciesandthematicareasareabsolutely
necessary for the area of biomedical and health informatics.
Taking into account the current needs in the biomedical and health informatics area, the
conferencestreamlinesintwomainaxes.Thefirstaxisincludesbiosensors,mHealth/uHealth
components and systems, biorobotics, electroceuticals and micro-bio-nano-recording, and
bioparametric estimation and filtering. The second axis includes machine learning, multi-
parametric analytics, bioinformatics, big biodata/biomedical computing, medical decision
support,patientsafetyinformatics,interoperability,andsecurity.Approachesthatcanbeused
for integrating these two streams linked to precision medicine applications were addressed.
The conference featured a scientific challenge which revolved around the recent high
interest in the coordinated care theme. The interest is highly related to the increase in aged
population and the high numbers of multimorbid patients. It focused on cardiorespiratory
v
vi Preface
problems related with multimorbid COPD patients. The goals of the challenge focused on
detection of wheezes and crackles in respiratory sounds. The scientific challenge rules fol-
lowed the Physionet challenge rules (http://bhichallenge.med.auth.gr/).
ThisproceedingsvolumecoversallpresentationsattheICBHI2017.Allsubmissionshave
beencarefullyandcriticallyreviewedbyatleasttwoindependentexpertsfromotherthanthe
authors’ home countries and additionally by at least one member of the Scientific Program
Committee. The editors are indebted to the acknowledged and highly experienced reviewers
forhavingessentiallycontributedtothequalityoftheconference andthebookathand.Both
the ICBHI 2017 Conference and the publication of the proceedings by Springer would not
have been possible without the support and sponsor of the IFMBE and the WG on Health
Informatics and eHealth. The editors are also grateful to the dedicated efforts of the Local
OrganizingCommitteemembersandtheirsupportersforcarefullyandsmoothlypreparingand
operating the conference. They especially thank all the team members from AUTH Lab of
ComputingMedicalInformaticsandBiomedical-ImagingTechnologiesfortheirdedicationto
the event.
Thessaloniki, Greece Nicos Maglaveras
Thessaloniki, Greece Ioanna Chouvarda
Coimbra, Portugal Paulo de Carvalho
Committees
Organization
Conference Chairperson
Prof. Nicos Maglaveras, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
Conference Secretary
Ms. Maria Giaga, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
Ms. Lina Nikolopoulou, Mindwork Business Solutions, Greece
IFMBE Administrative Council Officers
President
Prof. James Goh, National University of Singapore, Singapore
Vice President
Prof. Shankar Krishnan, Boston, USA
Past President
Prof. Ratko Magjarević, University of Zagreb, Croatia
Secretary-General
Prof. Kang Ping Lin, Chun-Yuan Christian University, Taiwan
Treasurer
Prof. Marc Nyssen, Vrije Universiteit Brussel, Belgium
IFMBE WG on Health Informatics and eHealth
Chair
Paulo de Carvalho
Co-Chair
Ratko Magjarevic
Advisor
Yuan-Ting Zhang
Members
Shankar Krishnan
Zhi-Pei Liang
Nicos Maglaveras
Marc Nyssen
Esteban Pino
Nitish Thakor
May Wang
Bruce Wheeler
vii
viii Committees
International Scientific Program Committee
Ioanna Chouvarda, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
Anthony H. Aletras, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
Paolo Bonato, Harvard Medical School, USA
Electra Gizeli, IMBB-FORTH/Department of Biology, University of Crete, Greece
Mark van Gils, VTT, Technical Research Centre, Finland
Anna Bianchi, Polytecnico di Milano, Italy
Elske Ammenwerth, Institute for Biomedical Informatics, UMIT, Austria
Spyros Kitsiou, University of Illinois Chicago, USA
Catherine Chronaki, HL7 International Foundation, Greece
Vassilis Koutkias, Center for Research and Technology—Institute of Applied Biosciences,
Greece
Dimitris Kougioumtzis, Department of Electrical and Computer Engineering, Aristotle
University, Greece
John Mantas, EFMI, University of Athens, Greece
Rita Paradiso, SMARTEX, Italy
Paulo Carvalho, Universidad de Coimbra, Portugal
Jorge Henriquez, Universidad de Coimbra, Portugal
Alan V. Sahakian, Northwestern University, USA
May Wang, Georgia Institute of Technology, USA
Y. T. Zhang, Chinese University of Hong Kong, China
Konstantina Nikita, NTUA, Greece
Dimitris Fotiadis, University of Ioannina, Greece
Maria Teresa Arredondo, Universidad Politécnica de Madrid, Spain
Pantelis Angelidis, University of Western Macedonia, President of the Thessaloniki
Innovation Zone
Local Organizing Committee
Ioanna Chouvarda, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
Anthony H. Aletras, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
Anastasios Delopoulos, Department of Electrical and Computer Engineering, Aristotle
University, Greece
Eleutherios Angelis, Department of Computer Science, Aristotle University, Greece
Theodoros Agorastos, Department of Medicine, Aristotle University, Greece
Vassilis Koutkias, Center for Research and Technology—Institute of Applied Biosciences,
Greece
Andreas Triantafyllidis, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
KonstantinosVotis,CenterforResearchandTechnology—InformationTechnologiesInstitute
(CERTH/ITI)
Christos Maramis, Lab of Computing Medical Informatics and Biomedical-Imaging
Technologies, Aristotle University, Greece
Vassilis Kilintzis, Lab of Computing Medical Informatics and Biomedical-Imaging Tech-
nologies, Aristotle University, Greece
Katerina Lourida, Lab of Computing Medical Informatics and Biomedical-Imaging Tech-
nologies, Aristotle University, Greece
Contents
Part I Big Data Analytics for Precision Medicine
Hybrid Hierarchical Clustering Algorithm Used for Large Datasets:
A Pilot Study on Long-Term Sleep Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
V. Gerla, M. Murgas, A. Mladek, E. Saifutdinova, M. Macas, and L. Lhotska
Epileptic Seizure Prediction with Stacked Auto-encoders: Lessons
from the Evaluation on a Large and Collaborative Database. . . . . . . . . . . . . . . 9
R. Barata, B. Ribeiro, A. Dourado, and C. A. Teixeira
Deep Learning Techniques on Sparsely Sampled Multichannel
Data—Identify Deterioration in ICU Patients . . . . . . . . . . . . . . . . . . . . . . . . . . 15
A. Chytas, K. Vaporidi, Y. Surlatzis, D. Georgopoulos,
N. Maglaveras, and I. Chouvarda
Convolutional Neural Networks for Early Seizure Alert System. . . . . . . . . . . . . 19
T. Iešmantas and R. Alzbutas
Prediction of Cardiac Arrest in Intensive Care Patients Through
Machine Learning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
E. Akrivos, V. Papaioannou, N. Maglaveras, and I. Chouvarda
Part II Scientific Challenge—Lung Sounds Analysis
A Respiratory Sound Database for the Development
of Automated Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
B. M. Rocha, D. Filos, L. Mendes, I. Vogiatzis, E. Perantoni, E. Kaimakamis,
P. Natsiavas, A. Oliveira, C. Jácome, A. Marques, R. P. Paiva, I. Chouvarda,
P. Carvalho, and N. Maglaveras
Hidden Markov Model Based Respiratory Sound Classification. . . . . . . . . . . . . 39
N. Jakovljević and T. Lončar-Turukalo
An Automated Lung Sound Preprocessing and Classification System
Based OnSpectral Analysis Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Gorkem Serbes, Sezer Ulukaya, and Yasemin P. Kahya
Detection of Cough and Adventitious Respiratory Sounds in Audio
Recordings by Internal Sound Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
B. M. Rocha, L. Mendes, I. Chouvarda, P. Carvalho, and R. P. Paiva
ix
