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Master Thesis at ETH Zurich: Interpret Health with Wearable Measures
The widespread adoption of wearable technology enables continuous monitoring of physiological parameters like activity levels, heart rate, and sleep patterns. This study investigates the relationship between wearable measures and well-being, focusing on physical and mental health as well as overall quality of life.
Keywords: Digital Health, Machine Learning, Data Science, Longitudinal Data Analysis
The integration of wearable technology into everyday life has revolutionized health
monitoring, offering continuous and unobtrusive data collection on various physiological
parameters, such as activity levels, heart rate, sleep patterns, and more. As wearables
become increasingly prevalent, there is a growing interest in exploring the relationship
between wearable measures and their circadian rhythm and well-being. Understanding how
data collected from wearable devices correlates with aspects of well-being such as physical
health, mental health, and overall quality of life has become a focal point for healthcare
professionals. This study aims to explore how wearable measures correlate with aspects of
well-being, discovering their potential impact on health and quality of life.
The integration of wearable technology into everyday life has revolutionized health monitoring, offering continuous and unobtrusive data collection on various physiological parameters, such as activity levels, heart rate, sleep patterns, and more. As wearables become increasingly prevalent, there is a growing interest in exploring the relationship between wearable measures and their circadian rhythm and well-being. Understanding how data collected from wearable devices correlates with aspects of well-being such as physical health, mental health, and overall quality of life has become a focal point for healthcare professionals. This study aims to explore how wearable measures correlate with aspects of well-being, discovering their potential impact on health and quality of life.
Check proposal attached.
Check proposal attached.
Please directly send your CV and grade transcript in an email to the following:
Fan Wu (fanwu@ethz.ch)
Please directly send your CV and grade transcript in an email to the following: Fan Wu (fanwu@ethz.ch)
Proposal Interpret Health with Wearable Measures.pdf
