Print Email Facebook Twitter Detect chewing episodes with an Inertial Measurement Unit (IMU) sensor around the ear Title Detect chewing episodes with an Inertial Measurement Unit (IMU) sensor around the ear: Detect chewing episodes with an Inertial Measurement Unit (IMU) sensor around the ear Author Nguyen, Vivian (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Pawełczak, Przemysław (mentor) Dsouza, V.K.P. (graduation committee) Hung, H.S. (mentor) Degree granting institution Delft University of Technology Corporate name Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2023 Abstract Tracking food intake provides a valuable source of information to gain insights in dietary habits for the health industry. Currently, the main method to track food intake to is do it manually. To take a step towards tracking food intake manually, this these aims to answer the following research question: ”How to detect chewing episodes with an IMU sensor around the ear?”. The IMU collect x, y, z axis data for the accerelometer an gyrscope. The data of the axis was down sampled to 20Hz and passed through a low-pass filter. Chewing detecting was done by determining chewing episode in time win- dows of 30 seconds. Feature were extracted from those time windows. Then random forest, decision tree, k-neareast neigbours, support vector machine and logistic regression machine learning models were used to classify the data, for which f1-scored higher than 0.8 have been achieved. Therefore it can be concluded is it possible to detect chewing episodes with a single IMU around the ear. Feature selection and performance analysis has been done, and it seem to be that features that use auto correlation and Fast Fourier Transform (FFT), play a significant role increasing the classification performance. They are computationally expensive and are not ideal for embedded system. However there is room for finding features that are less computationally expensive. Subject IMU sensorchewing detectingtracking food intake To reference this document use: http://resolver.tudelft.nl/uuid:e492dd45-ee5c-48b8-bed0-47e0bf10ab39 Part of collection Student theses Document type bachelor thesis Rights © 2023 Vivian Nguyen Files PDF CSE3000_Final_Paper_done.pdf 2.09 MB Close viewer /islandora/object/uuid:e492dd45-ee5c-48b8-bed0-47e0bf10ab39/datastream/OBJ/view