Journal of
Systemics, Cybernetics and Informatics
 



ISSN: 1690-4524 (Online)


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Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Editors

Journal's Reviewers
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Detection of Minimal Set of Trips Causing the Necessity to Use Extra Vehicle for Vehicle Scheduling Problem
Katerina Pastircáková, Jaromír Šulc
(pages: 1-4)

Key Factors in the Success of Self - Directed Learning of Military Personnel - Taking Smartphone as an Example
Yen-Hsi Lo, Yen-Fen Lo, Po-Yun Chiang, Jung Hsiao
(pages: 5-8)

Machine Learning Based IP Network Traffic Classification Using Feature Significance Analysis
Te-Shun Chou, John Pickard, Ciprian Popoviciu
(pages: 9-12)

The Information System for US Stock Market: Fundamental and Technical Analysis
Sergejs Hilkevics, Galina Hilkevica
(pages: 13-24)

The Impact of Environmental and Social Performance on the Market Value of Shares of Czech Joint-Stock Corporations
Alena Kocmanova, Marie Pavlakova Docekalova, Iveta Simberova
(pages: 25-31)

Play the Game! Analogue Gamification for Raising Information Security Awareness (Invited Paper)
Margit Scholl
(pages: 32-35)

Using Informatics and Technology Practices for Academic Performance Review
Kim Moorning
(pages: 36-41)

Multiple Research Perspectives as a Paradigm to Co-Create Meaningful Real-life Experiences
Jan Detand, Marina Emmanouil
(pages: 42-46)

A Methodology to Integrate Regulatory Expertise, Research and Education to Accelerate Biomedical Device Translation
Diana Easton
(pages: 47-52)

Active Learning through Smart Grid Model Site in Challenge Based Learning Course
Ellen A. Kalinga, Kwame S. Ibwe, Nerey H. Mvungi, Hannu Tenhunen
(pages: 53-64)

Non-Linear Static Analysis of Masonry Buildings under Seismic Actions
Maria Luisa Beconcini, Paolo Cioni, Pietro Croce, Paolo Formichi, Filippo Landi, Caterina Mochi
(pages: 65-70)

Toward an Engaging Hands-on Environment for a Beginning Networking and Security Class
Lopamudra Roychoudhuri
(pages: 71-76)

Designing Representations, Affecting Reality: A Meta-Model Proposal to Address the Question of Design Epistemology from the Perspective of Cognitive Science
Andrea Zammataro
(pages: 77-80)

Dielectrophoretic Movement of Cell around Surface Electrodes in Flow Channel
Yusuke Takahashi, Shigehiro Hashimoto, Manabu Watanabe
(pages: 81-87)


 

Abstracts

 


ABSTRACT


Remote ECG Monitoring Kit to Predict Patient-Specific Heart Abnormalities

Jiaming Chen, Peng Han, Abolfazl Razi


Electrocardiogram (ECG) signals are widely used to examine heart rhythms and general health conditions. However, the majority of commercial ECG kits are generic and their normal ranges are set based on the averages obtained from a large population of people with normal heart conditions. This averaging ignores the extreme inherent variability of normal heart signals. As such, many false alarms are generated if the thresholds are selected too strict and true alarms are missed if the thresholds are set too loose. Furthermore, false alarms may arise due to the high physical activity of the test person. In this paper, we developed a prototype for patient-specific heart monitoring kit, which learns the properties of a patient’s normal ECG signal over time and reports significant deviations from this normal behavior, in addition to presenting significant violations from the global norms. Further, false alarms due to high physical activity levels are eliminated through processing the utilized accelerometer signal. This personalized remote heart monitoring kit with the proposed signal processing and self-tuning capabilities and wireless connectivity provides more detailed information and insightful interpretations of ECG signals compared to generic devices, therefore can be used for remote heart monitoring of high-risk people.

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