Circadian rhythm is the natural biological cycle manifested in human daily routines. A regular and stable rhythm is found to be correlated with good physical and mental health. With the wide adoption of mobile and wearable technology, many types of sensor data, such as GPS and actigraphy, provide evidence for researchers to objectively quantify the circadian rhythm of a user and further use these quantified metrics of circadian rhythm to infer the user's health status. Researchers in computer science and psychology have investigated circadian rhythm using various mobile and wearable sensors in ecologically valid human sensing studies, but questions remain whether and how different data types produce different circadian rhythm results when simultaneously used to monitor a user. We hypothesize that different sensor data reveal different aspects of the user's daily behavior, thus producing different circadian rhythm patterns. In this paper we focus on two data types: GPS and accelerometer data from smartphones. We used smartphone data from 225 college student participants and applied four circadian rhythm characterization methods. We found significant and interesting discrepancies in the rhythmic patterns discovered among sensors, which suggests circadian rhythms discovered from different personal tracking sensors have different levels of sensitivity to device usage and aspects of daily behavior.
翻译:环形节律是人类日常日常活动所表现的自然生物循环。一种经常和稳定的节律与良好的身心健康息息相关。随着移动和可磨损技术的广泛采用,许多类型的传感器数据,例如全球定位系统和行为法,为研究人员提供了证据,以客观地量化用户的环形节律,并进一步使用这些可计量的环形节律计量标准来推断用户的健康状况。计算机科学和心理学研究人员利用生态上有效的人类遥感研究中各种移动和可磨过的传感器对环形节律进行了调查,但仍然存在各种问题:不同数据类型是否和如何产生不同的环形节律结果,同时用于监测用户。我们假设,不同传感器数据揭示了用户日常行为的不同方面,从而产生了不同的环形节律模式。在本论文中,我们侧重于两种数据类型:全球定位系统和智能手机的感光度计数据。我们使用了225名大学生参与者的智能手机数据,并应用了四种环形节律特征鉴定方法。我们发现,在传感器中发现的节律模式存在显著和有趣的差异,表明传感器的感官的感应感官的感官的感应达到不同程度。