A Web Application for Automatic Analysis on Life-style Factors Affecting Personal Health from Self-tracking Data Towards User-side Statistics Free Personal Data Analysis

摘要

The advent of commercial portable sensing devices has enabled many non-experts to collect their own data, and there has been a boom in health-centric self-monitoring and tracking (Swan, 2013). However, huge amount of these data remain unanalyzed simply because many of the data owners have no idea what to do with the large amount of data they have collected. Even for patients who are self-monitoring their vital health metrics, it is unrealistic to expect the doctors or physicians who are overloaded already to help them analyze their personal data individual by individual, let alone for healthy people who simply track for the purpose of prevention. Although some tracking device vendors offer software applications to synchronize the data collected, the analysis of these data is primitive because the applications simply visualize the temporal change of the tracked metric, leaving the potential causes of the change unanswered. Someone claim that simply by looking at the rise of blood pressure curve could further raise the blood pressure of a user. On the other hand, there are many independent data analysis software tools available. However, these tools were designed for experts such as statisticians and data scientists. Learning how to use them could be time-consuming or even torturing for nonexperts who do not have expertise on statistics and other skills such as programming. In one word, it is difficult, if not impossible, for non-experts to use existing data analysis software tools to gain insights from their data.