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Time-series data of home blood flow velocity measurements from the radial artery of six female subjects who felt they had poor peripheral circulation were analyzed in relation to their lifestyle factors, such as nightly sleeping hours and the number of walking steps. Correlations between time-series data of daily blood flow velocity and lifestyles were examined using a time-delayed correlation analysis...
A personal healthcare system used with cloud computing has been developed. It enables a daily time-series of personal health and lifestyle data to be stored in the cloud through mobile devices. The cloud automatically extracts personally useful information, such as rules and patterns concerning the user's lifestyle and health condition embedded in their personal big data, by using healthcare- data-mining...
The time-series data analysis described here is based on the simple idea that the accumulation of the effects of lifestyle events, such as ingestion and exercise, could affect personal health with some delay. The delay may reflect complex bio-reactions such as those of metabolism in a human body. In the analysis, the accumulation of the effects of lifestyle events is represented by a summation of...
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