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Assessment of the Sleep Quality Tracking: Activity Tracker vs Baseline Scores
This project focuses on data mining, and correlating the sleep quality data acquired with activity trackers with baseline scores from the questionnaires. The aim is to find patterns in the data of sleep tracking, and correlate these patterns to established sleep monitoring methods.
Keywords: Mobile Health, Sleep Quality, Sleep Pattern Recognition, Wearable Sensors, Activity Trackers, Data Mining, Statistical Analysis, Engineering
Sleep plays an important role in the physical health. Sleep disorders can lead to significant morbidity, and sleep disturbances may cause severe problems, such as depression, anxiety, and impaired daytime functioning.
We aim to investigate the sleep quality of 50 study participants and correlate the quality measures to established sleep assessment methods.
With the newly developed models we will be able to design novel sleep monitoring tools that can be used for sleep research.
**Type of work:** 40% data analysis, 60% algorithm development.
Sleep plays an important role in the physical health. Sleep disorders can lead to significant morbidity, and sleep disturbances may cause severe problems, such as depression, anxiety, and impaired daytime functioning. We aim to investigate the sleep quality of 50 study participants and correlate the quality measures to established sleep assessment methods. With the newly developed models we will be able to design novel sleep monitoring tools that can be used for sleep research.
**Type of work:** 40% data analysis, 60% algorithm development.
The aim of this project is to correlate sleep quality data obtained from the activity trackers with the baseline sleep scores from established questionnaires.
The aim of this project is to correlate sleep quality data obtained from the activity trackers with the baseline sleep scores from established questionnaires.
Piotr Wilczynski
Mobile Health Systems Lab, BAA
E-mail: piotr@hest.ethz.ch
Telephone number: 044 510 72 28