Predicting speaking status using full 9 Degrees Of Freedom Inertial MeasurementUnit (IMU) data

Bachelor thesis (2022)

Authors

M.A.A. Groenendijk Electrical Engineering, Mathematics and Computer Science

Contributors

H.S. Hung Pattern Recognition and Bioinformatics - EEMCS (mentor)
S. Tan Pattern Recognition and Bioinformatics - EEMCS (mentor)
O.E. Scharenborg (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Mark Groenendijk
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Published Date

28-01-2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

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.