Prediction of sleep efficiency from big physical exercise data

Xiaoli Liu,Satu Tamminen,Topi Korhonen,Juha Röning,Jukka Riekki

Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers（2019）

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摘要

Physical exercise can improve sleep quality. However, how to perform physical exercise to achieve the best possible improvements is not clear. In this article, we build predictive models based on volume real data collected from wearable devices to predict the sleep efficiency related to users' daily exercise information. As far as we know, this is the first study to investigate insights of prediction of sleep efficiency from volume physical exercise data collected from real world.

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关键词

physical exercise, predictive models, sleep quality

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