Optimising Measurements using Low-Power Headworn Sensors

Master Thesis (2024)
Author(s)

J.S. Pronk (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

P. Pawetczak – Mentor (TU Delft - Embedded Systems)

V.K.P. Dsouza – Graduation committee member (TU Delft - Embedded Systems)

Burcu Ozkan – Coach (TU Delft - Software Engineering)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
18-06-2024
Awarding Institution
Delft University of Technology
Programme
['Computer Science | Software Technology']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Even though much research has been conducted on body worn sensors, little research has been performed on specialized (non-ear-worn) headworn sensors. These sensors could be used to perform a variety of health related research. Therefore, this thesis focusses on a new low-power specialized (non-ear-worn) headworn sensor platform and explores how it can be improved.

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