Comparison Of Manual And Automatic Detection Of Muscle Activation Moments
but.event.date | 25.04.2019 | cs |
but.event.title | Student EEICT 2019 | cs |
dc.contributor.author | Svozilová, Veronika | |
dc.date.accessioned | 2020-04-16T07:19:36Z | |
dc.date.available | 2020-04-16T07:19:36Z | |
dc.date.issued | 2019 | cs |
dc.description.abstract | Detection of muscle activation moments is very important characteristic of human mobility. Muscle activation is used to describe how muscles work during some action. There are differences between muscle activation of healthy people and people suffering from neurodegenerative diseases or musculoskeletal disorders. The aim of this article is to compare results from manual and automatic detection of muscle activation moments from which driver reaction time is estimated. The main interest of this work is to find out if reaction time of healthy people differs from reaction time of people suffering by Parkinson disease. | en |
dc.format | text | cs |
dc.format.extent | 457-462 | cs |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Proceedings of the 25st Conference STUDENT EEICT 2019. s. 457-462. ISBN 978-80-214-5735-5 | cs |
dc.identifier.isbn | 978-80-214-5735-5 | |
dc.identifier.uri | http://hdl.handle.net/11012/186715 | |
dc.language.iso | en | cs |
dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
dc.relation.ispartof | Proceedings of the 25st Conference STUDENT EEICT 2019 | en |
dc.relation.uri | http://www.feec.vutbr.cz/EEICT/ | cs |
dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
dc.rights.access | openAccess | en |
dc.title | Comparison Of Manual And Automatic Detection Of Muscle Activation Moments | en |
dc.type.driver | conferenceObject | en |
dc.type.status | Peer-reviewed | en |
dc.type.version | publishedVersion | en |
eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- 457_eeict2019.pdf
- Size:
- 710.2 KB
- Format:
- Adobe Portable Document Format
- Description: