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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3S4Q5ES
Repositorysid.inpe.br/sibgrapi/2018/10.26.04.25
Last Update2018:10.26.04.25.12 (UTC) davibeltrao@dcc.ufmg.br
Metadata Repositorysid.inpe.br/sibgrapi/2018/10.26.04.25.12
Metadata Last Update2022:05.18.22.18.35 (UTC) administrator
Citation KeyBeltrãoNazaSchw:2018:AuGyWo
TitleAutomatic Gym Workout Recognition using Wearable Devices
FormatOn-line
Year2018
Access Date2024, May 03
Number of Files1
Size1079 KiB
2. Context
Author1 Beltrão, Davi Faria de Assis
2 Nazare, Antônio Carlos
3 Schwartz, William Robson
Affiliation1 Universidade Federal de Minas Gerais
2 Universidade Federal de Minas Gerais
3 Universidade Federal de Minas Gerais
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
e-Mail Addressdavibeltrao@dcc.ufmg.br
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Date29 Oct.-1 Nov. 2018
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2018-10-26 04:25:12 :: davibeltrao@dcc.ufmg.br -> administrator ::
2022-05-18 22:18:35 :: administrator -> :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsgym recognition
smartwatch
AbstractIt is well known among people that sports practice leads to a better quality of life and prevent diseases. Furthermore, according to some sources, the use of smartwatches is spreading worldwide, reaching almost 20% of U.S. population nowadays. Aiming at helping people at gym, we proposed a work that employs smartwatches to recognize and classify activities executed by the users, allowing users to exercise properly and easily. This way, the users will be able to control their exercise series more precisely, for instance. We develop a new open source application capable of capturing and providing data easily. We use all sensors available (e.g., accelerometer, gyroscope, magnetometer, barometer and linear acceleration) to capture as much data as possible to perform exercise classification after performing feature extraction.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2018 > Automatic Gym Workout...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 26/10/2018 01:25 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3S4Q5ES
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3S4Q5ES
Languageen
Target File2018_wip_gymsensors.pdf
User Groupdavibeltrao@dcc.ufmg.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3RPADUS
Citing Item Listsid.inpe.br/sibgrapi/2018/09.03.20.37 12
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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