MG
M.A.A. Groenendijk
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2 records found
1
Designing a dashboard for wellbeing data
A recommendation system for individual wellbeing
Bachelor thesis
(2022)
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M.A.A. Groenendijk, W.L.A. van der Maden, G.M. Allen, U.K. Gadiraju, J.D. Lomas, Z. Erkin
Due to COVID-19 the overall wellbeing worldwide decreased. Assessing and improving wellbeing became a more important subject. This article describes the design research that uses the My Wellness Check survey created by the Delft University for Technology and aims to create a dashboard for wellbeing. That includes a way of authenticating users to very sensitive data. Also, finding ways how to improve personal wellbeing by using a recommendation system based on different types of filtering and the additional elements that are needed for a recommendation system.
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Due to COVID-19 the overall wellbeing worldwide decreased. Assessing and improving wellbeing became a more important subject. This article describes the design research that uses the My Wellness Check survey created by the Delft University for Technology and aims to create a dashboard for wellbeing. That includes a way of authenticating users to very sensitive data. Also, finding ways how to improve personal wellbeing by using a recommendation system based on different types of filtering and the additional elements that are needed for a recommendation system.
The goal for this paper is to find out what the smart badge provided by the Social Perceptive Computive Lab (SPCL) group is and what it contains. The sensors that are used in the smart badge are the Accelerometer, Gyroscope and Magnetometer. The main question of this paper is ”What is the benefit of using full 9-DOF IMU data in predicting speaking status, as opposed to using only accelerometer signals?”. The three senors all contribute in their own way and complement each other to give an estimate about the speaking status. The ability to estimate the speaking status using the smart badge opens up the potential for analyzing more about the social aspects of people without the need to record what they are saying.
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The goal for this paper is to find out what the smart badge provided by the Social Perceptive Computive Lab (SPCL) group is and what it contains. The sensors that are used in the smart badge are the Accelerometer, Gyroscope and Magnetometer. The main question of this paper is ”What is the benefit of using full 9-DOF IMU data in predicting speaking status, as opposed to using only accelerometer signals?”. The three senors all contribute in their own way and complement each other to give an estimate about the speaking status. The ability to estimate the speaking status using the smart badge opens up the potential for analyzing more about the social aspects of people without the need to record what they are saying.