Wearable devices that measure physiological signals to help develop self-health management habits have become increasingly popular in recent years. These records are conducive for follow-up health and medical care. In this study, based on the characteristics of the observed physiological signal records- 1) a large number of users, 2) a large amount of data, 3) low information variability, 4) data privacy authorization, and 5) data access by designated users-we wish to resolve physiological signal record-relevant issues utilizing the advantages of the Database as a Service (DaaS) model. Storing a large amount of data using file patterns can reduce database load, allowing users to access data efficiently; the privacy control settings allow users to store data securely. The results of the experiment show that the proposed system has better database access performance than a traditional relational database, with a small difference in database volume, thus proving that the proposed system can improve data storage performance.
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Chang et al. (2016) studied this question.
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