The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Lorsque nous collectons des données vitales auprès des utilisateurs en leur plaçant des nœuds de capteurs sans fil, la fiabilité de la collecte de données sans fil dépend de la position du nœud sur le corps de l'utilisateur. Par conséquent, afin de déterminer la position appropriée du corps, il est essentiel de évaluer les performances de la collecte de données en modifiant la position du corps des nœuds dans des expériences impliquant des sujets humains. Cependant, leur comparaison équitable est problématique, car les expériences n’ont pas de répétabilité, c’est-à-dire que nous ne pouvons pas évaluer simultanément les performances pour plusieurs positions du corps dans une expérience. Dans cet article, nous prédisons les performances d'un simulateur de réseau logiciel. En utilisant deux fonctions principales telles qu'une fonction d'état de canal et une fonction de mobilité, le simulateur de réseau peut générer de manière répétée les mêmes conditions de canal et de mobilité pour les nœuds. Le résultat numérique obtenu par le simulateur de réseau montre que lors de la collecte des données vitales de vingt-deux footballeurs dans un match, parmi trois positions du corps telles que la taille, l'avant-bras et le mollet, la position de l'avant-bras donne le taux de collecte de données le plus élevé et les taux de collecte de données prévus concordent bien. avec ceux obtenus par une expérience impliquant des sujets réels.
Takuma HAMAGAMI
Oki Electric Industry Co., Ltd.
Shinsuke HARA
Osaka City University
Hiroyuki YOMO
Kansai University
Ryusuke MIYAMOTO
Meiji University
Yasutaka KAWAMOTO
Oki Electric Industry Co., Ltd.
Takunori SHIMAZAKI
Osaka City University
Hiroyuki OKUHATA
Soliton Systems K.K.
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Takuma HAMAGAMI, Shinsuke HARA, Hiroyuki YOMO, Ryusuke MIYAMOTO, Yasutaka KAWAMOTO, Takunori SHIMAZAKI, Hiroyuki OKUHATA, "Performance Prediction of Wireless Vital Data Collection System for Exercisers by a Network Simulator" in IEICE TRANSACTIONS on Communications,
vol. E103-B, no. 6, pp. 653-661, June 2020, doi: 10.1587/transcom.2019HMP0004.
Abstract: When we collect vital data from exercisers by putting wireless sensor nodes to them, the reliability of the wireless data collection is dependent on the position of node on the body of exerciser, therefore, in order to determine the suitable body position, it is essential to evaluate the data collection performances by changing the body positions of nodes in experiments involving human subjects. However, their fair comparison is problematic, because the experiments have no repeatability, that is, we cannot evaluate the performances for multiple body positions in an experiment at the same time. In this paper, we predict the performances by a software network simulator. Using two main functions such as a channel state function and a mobility function, the network simulator can repeatedly generate the same channel and mobility conditions for nodes. Numerical result obtained by the network simulator shows that when collecting vital data from twenty two footballers in a game, among three body position such as waist, forearm and calf, the forearm position gives the highest data collection rate and the predicted data collection rates agree well with the ones obtained by an experiment involving real subjects.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2019HMP0004/_p
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@ARTICLE{e103-b_6_653,
author={Takuma HAMAGAMI, Shinsuke HARA, Hiroyuki YOMO, Ryusuke MIYAMOTO, Yasutaka KAWAMOTO, Takunori SHIMAZAKI, Hiroyuki OKUHATA, },
journal={IEICE TRANSACTIONS on Communications},
title={Performance Prediction of Wireless Vital Data Collection System for Exercisers by a Network Simulator},
year={2020},
volume={E103-B},
number={6},
pages={653-661},
abstract={When we collect vital data from exercisers by putting wireless sensor nodes to them, the reliability of the wireless data collection is dependent on the position of node on the body of exerciser, therefore, in order to determine the suitable body position, it is essential to evaluate the data collection performances by changing the body positions of nodes in experiments involving human subjects. However, their fair comparison is problematic, because the experiments have no repeatability, that is, we cannot evaluate the performances for multiple body positions in an experiment at the same time. In this paper, we predict the performances by a software network simulator. Using two main functions such as a channel state function and a mobility function, the network simulator can repeatedly generate the same channel and mobility conditions for nodes. Numerical result obtained by the network simulator shows that when collecting vital data from twenty two footballers in a game, among three body position such as waist, forearm and calf, the forearm position gives the highest data collection rate and the predicted data collection rates agree well with the ones obtained by an experiment involving real subjects.},
keywords={},
doi={10.1587/transcom.2019HMP0004},
ISSN={1745-1345},
month={June},}
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TY - JOUR
TI - Performance Prediction of Wireless Vital Data Collection System for Exercisers by a Network Simulator
T2 - IEICE TRANSACTIONS on Communications
SP - 653
EP - 661
AU - Takuma HAMAGAMI
AU - Shinsuke HARA
AU - Hiroyuki YOMO
AU - Ryusuke MIYAMOTO
AU - Yasutaka KAWAMOTO
AU - Takunori SHIMAZAKI
AU - Hiroyuki OKUHATA
PY - 2020
DO - 10.1587/transcom.2019HMP0004
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E103-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2020
AB - When we collect vital data from exercisers by putting wireless sensor nodes to them, the reliability of the wireless data collection is dependent on the position of node on the body of exerciser, therefore, in order to determine the suitable body position, it is essential to evaluate the data collection performances by changing the body positions of nodes in experiments involving human subjects. However, their fair comparison is problematic, because the experiments have no repeatability, that is, we cannot evaluate the performances for multiple body positions in an experiment at the same time. In this paper, we predict the performances by a software network simulator. Using two main functions such as a channel state function and a mobility function, the network simulator can repeatedly generate the same channel and mobility conditions for nodes. Numerical result obtained by the network simulator shows that when collecting vital data from twenty two footballers in a game, among three body position such as waist, forearm and calf, the forearm position gives the highest data collection rate and the predicted data collection rates agree well with the ones obtained by an experiment involving real subjects.
ER -