Personal Recommendation System for Improving Sleep Quality

被引：1

作者：

Datko, Patrick ^{[1
]}

Scherz, Wilhelm Daniel ^{[1
]}

Velicu, Oana Ramona ^{[1
]}

Seepold, Ralf ^{[1
]}

Madrid, Natividad Martinez ^{[2
]}

机构：

[1] HTWG Konstanz, Ubiquitous Comp Lab, CH-78462 Constance, Baden Wurttembe, Germany

[2] Reutlingen Univ, Internet Things Lab, D-72762 Reutlingen, Baden Wurttembe, Germany

来源：

INTELLIGENT DECISION TECHNOLOGIES 2016, PT I | 2016年 / 56卷

关键词：

SENSOR;

D O I：

10.1007/978-3-319-39630-9_34

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Sleep is an important aspect in life of every human being. The average sleep duration for an adult is approximately 7 h per day. Sleep is necessary to regenerate physical and psychological state of a human. A bad sleep quality has a major impact on the health status and can lead to different diseases. In this paper an approach will be presented, which uses a long-term monitoring of vital data gathered by a body sensor during the day and the night supported by mobile application connected to an analyzing system, to estimate sleep quality of its user as well as give recommendations to improve it in real-time. Actimetry and historical data will be used to improve the individual recommendations, based on common techniques used in the area of machine learning and big data analysis.

引用

页码：405 / 412

页数：8

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