期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：18
页码：4358
出版社：Journal of Theoretical and Applied
摘要：In this paper, we introduce an algorithm and an application for modeling user�s circadian rhythm with activity trackers, also known as smart bands (e.g., Misfit Shine or Fitbit). The proposed algorithm detects anomalies in the users circadian rhythm pattern (i.e., activity pattern of 24-hour cycle). Diurnal biorhythm data were collected using smart bands and the data were analyzed using Levenshtein distance. We evaluate the performance of the proposed algorithm to distinguish between ordinary days and abnormal days. During the experiment period, the users recorded the mood, fatigue, and event occurrence of the day, and evaluated the performance of the proposed algorithm through comparison with users recorded opinions. In the user study, the proposed method detected normal or abnormal patterns of life rhythm with 86% accuracy.
