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Faculté des Sciences appliquées
Faculté des Sciences appliquées
MASTER THESIS
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Detection of the type of physical activity based on an IMU sensor

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Paolino, Alessia ULiège
Promotor(s) : Bruls, Olivier ULiège ; Schwartz, Cédric ULiège
Date of defense : 5-Sep-2024/6-Sep-2024 • Permalink : http://hdl.handle.net/2268.2/20850
Details
Title : Detection of the type of physical activity based on an IMU sensor
Author : Paolino, Alessia ULiège
Date of defense  : 5-Sep-2024/6-Sep-2024
Advisor(s) : Bruls, Olivier ULiège
Schwartz, Cédric ULiège
Committee's member(s) : Ruffoni, Davide ULiège
Drion, Guillaume ULiège
Language : English
Number of pages : 129
Keywords : [en] Human Activity Recognition (HAR),
[en] Wearable Sensors
[en] Machine Learning Algorithms
[en] Physical Activity Monitoring
[en] Multilayer Perceptron (MLP)
[en] Motion Analysis
[en] Inertial Measurement Units (IMUs)
Discipline(s) : Engineering, computing & technology > Multidisciplinary, general & others
Target public : Researchers
Professionals of domain
Student
Institution(s) : Université de Liège, Liège, Belgique
Degree: Cours supplémentaires destinés aux étudiants d'échange (Erasmus, ...)
Faculty: Master thesis of the Faculté des Sciences appliquées

Abstract

[en] The primary goal of this research is to develop a Human Activity Recognition (HAR) system using Inertial Measurement Units (IMUs), such as accelerometers and gyroscopes, to accurately identify and classify various types of physical movements.
The study specifically explores the use of wearable sensors for monitoring motor activities, offering an alternative solution to traditional camera-based motion capture systems, which have significant limitations, such as high costs and privacy concerns. The thesis discusses various stages of the process, including data acquisition through an experimental setup, data preprocessing, feature extraction and selection, and finally, the application of machine learning algorithms, such as Multilayer Perceptron (MLP) neural networks, for activity recognition and analysis.
The research also includes a comparative evaluation of the performance of models based on sensors positioned in different parts of the body (wrist, thigh, pocket) and provides detailed results regarding the accuracy of the models used.


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Access Alessia_Paolino_Master_Thesis.pdf
Description: Thesis without the annexe, the section 6 is the Annexe A
Size: 4.13 MB
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Access Erratum_Alessia_Paolino_Master_Thesis.pdf
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Annexe(s)

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Access Annexe A.pdf
Description: section 6 is the Annexe A
Size: 142.89 kB
Format: Adobe PDF

Author

  • Paolino, Alessia ULiège Université de Liège > conv. Erasmus en sc. appl.

Promotor(s)

Committee's member(s)

  • Ruffoni, Davide ULiège Université de Liège - ULiège > Département d'aérospatiale et mécanique > Mécanique des matériaux biologiques et bioinspirés
    ORBi View his publications on ORBi
  • Drion, Guillaume ULiège Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
    ORBi View his publications on ORBi
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  • Total number of downloads 1










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