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Annotation framework for the physical activity evaluation in real-time
Miroslav Mužný, Jan Mužík
Jazyk angličtina Země Česko Médium elektronický zdroj
- MeSH
- lidé MeSH
- monitorování fyziologických funkcí * metody přístrojové vybavení MeSH
- techniky cvičení a pohybu * metody MeSH
- vibrace * MeSH
- Check Tag
- lidé MeSH
Objectives: Work aims to create a portable tool with a decision support, providing relevant methods for purposes of physical activity evaluation in real-time. Methods: We have utilized accelerometer equipped ez430Chronos watch in conjunction with a preconfigured RaspberryPi-based setup. Wireless transmission of accelerometer data into a running web application instance, which served as a user frontend, is provided through the WebSocket protocol. Decision support is based on a Weka classifier. Results: The proposed framework is ready to be used for the annotation and basic evaluation of physical activity data in a Wi-Fi covered areas. Minor issues are related to the occasional instability of data transmission, which has to be handled consequently. Conclusions: We found the overall framework architecture robust enough to serve its purpose. Next steps in the development will lead to an expansion of outlined functionality.
Annotation framework for the physical activity evaluation in real-time [elektronický zdroj] /
Citace poskytuje Crossref.org
Literatura
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- $a Mužný, Miroslav $7 xx0253017 $u Spin-off Application Centre, First Medical Faculty, Charles University in Prague, Czech Republic
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- $a Annotation framework for the physical activity evaluation in real-time $h [elektronický zdroj] / $c Miroslav Mužný, Jan Mužík
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- $a Literatura
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- $a Objectives: Work aims to create a portable tool with a decision support, providing relevant methods for purposes of physical activity evaluation in real-time. Methods: We have utilized accelerometer equipped ez430Chronos watch in conjunction with a preconfigured RaspberryPi-based setup. Wireless transmission of accelerometer data into a running web application instance, which served as a user frontend, is provided through the WebSocket protocol. Decision support is based on a Weka classifier. Results: The proposed framework is ready to be used for the annotation and basic evaluation of physical activity data in a Wi-Fi covered areas. Minor issues are related to the occasional instability of data transmission, which has to be handled consequently. Conclusions: We found the overall framework architecture robust enough to serve its purpose. Next steps in the development will lead to an expansion of outlined functionality.
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