Adaptive Analysis of Electrocardiogram Prediction Using a Dynamic Cubic Neural Unit
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F22%3A43896610" target="_blank" >RIV/44555601:13440/22:43896610 - isvavai.cz</a>
Result on the web
<a href="http://10.1007/978-3-030-99619-2_41" target="_blank" >http://10.1007/978-3-030-99619-2_41</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-99619-2_41" target="_blank" >10.1007/978-3-030-99619-2_41</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive Analysis of Electrocardiogram Prediction Using a Dynamic Cubic Neural Unit
Original language description
In this work, the implementation of a dynamic cubic neural unit for the prediction of heartbeats using a wireless method is presented. The data were recorded with the BITalino biomedical acquisition card using its ECG input and output module via Bluetooth. This paper aims to predict a prediction horizon according to the learning rate, the number of samples used to train the model, and the specified times required for training. The signal (input) was acquired from electrodes, which were placed on the surface of the chest near the heart. The signal was visualized and presented through a graphical interface. For the interface evaluation, tests are performed using the obtained signal in real time
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Networks and Systems
ISBN
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ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
10
Pages from-to
431-440
Publisher name
Springer International Publishing AG
Place of publication
Cham
Event location
Sydney, Australia
Event date
Apr 13, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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