Cycling Segments Multimodal Analysis and Classification Using Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63516820" target="_blank" >RIV/70883521:28140/17:63516820 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/17:00318548 RIV/00216208:11150/17:10367933 RIV/60461373:22340/17:43903861
Result on the web
<a href="http://www.mdpi.com/2076-3417/7/6/581/xml" target="_blank" >http://www.mdpi.com/2076-3417/7/6/581/xml</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app7060581" target="_blank" >10.3390/app7060581</a>
Alternative languages
Result language
angličtina
Original language name
Cycling Segments Multimodal Analysis and Classification Using Neural Networks
Original language description
This paper presents methodology for the processing of GPS and heart rate signals acquired during long-term physical activities. The data analysed include geo-positioning and heart rate multichannel signals recorded for 272.2 h of cycling across the Andes mountains over a 5694-km long expedition. The proposed computational methods include multimodal data de-noising, visualization, and analysis in order to determine specific biomedical features. The results include the correspondence between the heart rate and slope for downhill and uphill cycling and the mean heart rate evolution on flat segments: a regression coefficient of -0.014 bpm/km related to altitude. The classification accuracy of selected cycling features by neural networks, support vector machine, and k-nearest neighbours methods is between 91.3% and 98.6%. The proposed methods allow the analysis of data during physical activities, enabling an efficient human-machine interaction.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Sciences-Basel
ISSN
2076-3417
e-ISSN
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Volume of the periodical
7
Issue of the periodical within the volume
6
Country of publishing house
CH - SWITZERLAND
Number of pages
11
Pages from-to
1-11
UT code for WoS article
000404449800057
EID of the result in the Scopus database
2-s2.0-85020253439