TY - GEN
T1 - Utilization of Behavior Data Due to Differences in Determination of Activity
AU - Anzai, Ryusei
AU - Yang, Won Seok
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The Behavior Data has been widely used to promote healthy exercise. In this research, we used Stages of Change of the Transtheoretical Model (TTM) to classify exercisers into three types: Low-Will, Middle-Will, and Strong-Will, and then conducted a survey on the characteristics of exercise and the use of behavior data for each type. It was found that the Low-Will type tended to be less active than the Middle-Will, and the Middle-Will type tended to enjoy exercise less than the Strong-Will type. In addition, it was found that as will type increased, there was a tendency to seek specialized behavior data such as average pace and a tendency to increase the amount of data that could be managed. These findings suggest that the method of providing Visualization data using the Stages of Change is effective as a method of providing data to encourage exercise. In this research, we also proposed a data provision method for each type based on the survey results.
AB - The Behavior Data has been widely used to promote healthy exercise. In this research, we used Stages of Change of the Transtheoretical Model (TTM) to classify exercisers into three types: Low-Will, Middle-Will, and Strong-Will, and then conducted a survey on the characteristics of exercise and the use of behavior data for each type. It was found that the Low-Will type tended to be less active than the Middle-Will, and the Middle-Will type tended to enjoy exercise less than the Strong-Will type. In addition, it was found that as will type increased, there was a tendency to seek specialized behavior data such as average pace and a tendency to increase the amount of data that could be managed. These findings suggest that the method of providing Visualization data using the Stages of Change is effective as a method of providing data to encourage exercise. In this research, we also proposed a data provision method for each type based on the survey results.
KW - Behavior data
KW - Data visualization
KW - Transtheoretical model
KW - Wearable Devices
UR - http://www.scopus.com/inward/record.url?scp=85112157790&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112157790&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-80829-7_6
DO - 10.1007/978-3-030-80829-7_6
M3 - Conference contribution
AN - SCOPUS:85112157790
SN - 9783030808280
T3 - Lecture Notes in Networks and Systems
SP - 40
EP - 46
BT - Advances in Industrial Design - Proceedings of the AHFE 2021 Virtual Conferences on Design for Inclusion, Affective and Pleasurable Design, Interdisciplinary Practice in Industrial Design, Kansei Engineering, and Human Factors for Apparel and Textile Engineering, 2021
A2 - Shin, Cliff Sungsoo
A2 - Di Bucchianico, Giuseppe
A2 - Fukuda, Shuichi
A2 - Ghim, Yong-Gyun
A2 - Montagna, Gianni
A2 - Carvalho, Cristina
PB - Springer Science and Business Media Deutschland GmbH
T2 - AHFE International Conferences on Design for Inclusion, Interdisciplinary Practice in Industrial Design, Affective and Pleasurable Design, Kansei Engineering, and Human Factors for Apparel and Textile Engineering, 2021
Y2 - 25 July 2021 through 29 July 2021
ER -