Wearable devices that help you sleep? Impact of activity and non-activity on sleep quality and quantity

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Authors
O'Byrne, Claire
Issue Date
2020
Degree
MSc in Data Analytics
Publisher
Dublin Business School
Rights
Items in eSource are protected by copyright. Previously published items are made available in accordance with the copyright policy of the publisher/copyright holder.
Abstract
With the explosion of the tech wearables market in recent years there has been signi cant promises of how tracking your heart data, daily activity and exercise and sleep data will improve your quality of life. Sleep is widely known to impact mood, health and productivity.Sleep has become a hot topic culturally as self-care and wellbeing become the priority for modern society. Sleep hygiene is now as important as personal hygiene. The main objective of this study will be to research the impact of activity (step count, minutes of daily activity and lifestyle) and inactivity (sedentary mins, high BMI, and bad lifestyle habits) on sleep quantity and quality. The data utilised in this dissertation has been retrieved from the participants Fitbit trackers along with a survey investigating lifestyle over a period of one month. The supervised and unsupervised machine learning models employed in this study will try to understand the signi cance of factors that contribute to how we sleep and then in turn will be used to predict sleep quality and quantity based on training data.The main bene ts of this study are to provide better insights to sleep quality and quantity to health tracker users, especially important now during the COVID-19 pandemic, and to enable tech wearable companies to utilise predictable reminders to consumers tailored to their health data.