Smartwatch/Smartphone Cooperative Indoor Lifelogging System
In this study, a lifelogging system is proposed for logging the daily activities of a user using a smartphone and a smartwatch cooperatively in indoor environments. The proposed system attempts to recognize a user’s activities of daily living, including sleeping behavior and various physical activit...
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Taiwan Association of Engineering and Technology Innovation
2018-09-01
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doaj-da487deacaad404ba5d974bc64479c592020-11-25T01:14:14ZengTaiwan Association of Engineering and Technology InnovationInternational Journal of Engineering and Technology Innovation2223-53292226-809X2018-09-0184354Smartwatch/Smartphone Cooperative Indoor Lifelogging SystemKhanh Nguyen-Huu0Chang Geun Song1Seon-Woo Lee2Hallym UniversityHallym UniversityHallym UniversityIn this study, a lifelogging system is proposed for logging the daily activities of a user using a smartphone and a smartwatch cooperatively in indoor environments. The proposed system attempts to recognize a user’s activities of daily living, including sleeping behavior and various physical activities, and to estimate the user’s daily total energy expenditure (TEE) based on the recognized lifelogs. The TEE has the potential to be useful in personal healthcare management. The system includes both mobile and server systems. The mobile system consists of both a smartwatch and a smartphone used to classify ten activities, including sleeping activities, using sensors on both devices. The server system includes a database server and a set of programs to handle the collected lifelogs for users. An Android app is also developed to display the collected lifelogs and the estimated daily TEE on smartphones to assist in managing users’ health. The experimental results show that the overall average recognition rate of seven activities is 97.5% with four subjects, and the total average error for the three states of sleeping behaviors is 6.64%.http://ojs.imeti.org/index.php/IJETI/article/view/1389lifelogging systemsmartphonesmartwatchactivity recognition |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Khanh Nguyen-Huu Chang Geun Song Seon-Woo Lee |
spellingShingle |
Khanh Nguyen-Huu Chang Geun Song Seon-Woo Lee Smartwatch/Smartphone Cooperative Indoor Lifelogging System International Journal of Engineering and Technology Innovation lifelogging system smartphone smartwatch activity recognition |
author_facet |
Khanh Nguyen-Huu Chang Geun Song Seon-Woo Lee |
author_sort |
Khanh Nguyen-Huu |
title |
Smartwatch/Smartphone Cooperative Indoor Lifelogging System |
title_short |
Smartwatch/Smartphone Cooperative Indoor Lifelogging System |
title_full |
Smartwatch/Smartphone Cooperative Indoor Lifelogging System |
title_fullStr |
Smartwatch/Smartphone Cooperative Indoor Lifelogging System |
title_full_unstemmed |
Smartwatch/Smartphone Cooperative Indoor Lifelogging System |
title_sort |
smartwatch/smartphone cooperative indoor lifelogging system |
publisher |
Taiwan Association of Engineering and Technology Innovation |
series |
International Journal of Engineering and Technology Innovation |
issn |
2223-5329 2226-809X |
publishDate |
2018-09-01 |
description |
In this study, a lifelogging system is proposed for logging the daily activities of a user using a smartphone and a smartwatch cooperatively in indoor environments. The proposed system attempts to recognize a user’s activities of daily living, including sleeping behavior and various physical activities, and to estimate the user’s daily total energy expenditure (TEE) based on the recognized lifelogs. The TEE has the potential to be useful in personal healthcare management. The system includes both mobile and server systems. The mobile system consists of both a smartwatch and a smartphone used to classify ten activities, including sleeping activities, using sensors on both devices. The server system includes a database server and a set of programs to handle the collected lifelogs for users. An Android app is also developed to display the collected lifelogs and the estimated daily TEE on smartphones to assist in managing users’ health. The experimental results show that the overall average recognition rate of seven activities is 97.5% with four subjects, and the total average error for the three states of sleeping behaviors is 6.64%. |
topic |
lifelogging system smartphone smartwatch activity recognition |
url |
http://ojs.imeti.org/index.php/IJETI/article/view/1389 |
work_keys_str_mv |
AT khanhnguyenhuu smartwatchsmartphonecooperativeindoorlifeloggingsystem AT changgeunsong smartwatchsmartphonecooperativeindoorlifeloggingsystem AT seonwoolee smartwatchsmartphonecooperativeindoorlifeloggingsystem |
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1725158015520210944 |