Name
Abstract | ||
|---|---|---|
The increasing number of people with lifestyle-related diseases has become a social problem. It is well known that improving lifestyle habits is effective in preventing illness. We focus on regulating the rhythm of daily life and investigate a support technology that adjusts the user's schedule to enhance health outcomes. Its main goals are to schedule the ideal goal (target action at desired time given by the user) and advise what actions should be taken and when to perform them to achieve the goal. This paper proposes a method to find trigger actions whose scheduling is flexible and that should precede the target action. Our study started with the collection of activity logs and flex logs. The flex logs record the periods in which the user feels the actions could be performed. We report on the preliminary findings from analyzing the collected logs and discuss how the findings can be used in designing future studies.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3341162.3343809 | Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers |
Keywords | Field | DocType |
behavior change, healthcare, interruptibility, intervention, mobile health, personal informatics | Computer vision,Computer science,Human–computer interaction,Artificial intelligence,Rhythm | Conference |
ISBN | Citations | PageRank |
978-4503-6869-8 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Masami Takahashi | 1 | 1 | 3.73 |
| Masahiro Kohjima | 2 | 0 | 2.03 |
| Takeshi Kurashima | 3 | 315 | 24.21 |
| Tatsushi Matsubayashi | 4 | 40 | 8.85 |
| Hiroyuki Toda | 5 | 58 | 14.72 |