Tracking and counting motion for monitoring food intake based on depth sensor

Obesity has been a serious health concern among people. Moreover, obesity continues to be a serious public health concern in Malaysia and continuing to rise. Nearly half of Malaysians are overweight. Most of the dietary approaches are not tracking and detecting the right calorie intake for wei...

Full description

Saved in:
Bibliographic Details
Main Author: Kassim, Muhammad Fuad
Format: Thesis
Language:English
English
English
Published: 2020
Subjects:
Online Access:http://eprints.uthm.edu.my/1041/2/24p%20MUHAMMAD%20FUAD%20KASSIM.pdf
http://eprints.uthm.edu.my/1041/1/MUHAMMAD%20FUAD%20KASSIM%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/1041/3/MUHAMMAD%20FUAD%20KASSIM%20WATERMARK.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-uthm-ep.1041
record_format uketd_dc
spelling my-uthm-ep.10412021-09-21T04:18:23Z Tracking and counting motion for monitoring food intake based on depth sensor 2020-06 Kassim, Muhammad Fuad TK7885-7895 Computer engineering. Computer hardware Obesity has been a serious health concern among people. Moreover, obesity continues to be a serious public health concern in Malaysia and continuing to rise. Nearly half of Malaysians are overweight. Most of the dietary approaches are not tracking and detecting the right calorie intake for weight loss, but currently used tools such as food diaries require users to manually record and track the food calories, making them difficult to be utilized for daily use. Therefore, this project developed a new tool that counts the food intake by monitoring eating motion movement of caloric intake to overcome health issues. The food intake counting method showed a good significance that can lead to a successful weight loss by simply monitoring the food intake taken during eating. The device used was Kinect Xbox One which used a depth camera to detect the motion of a person’s gesture and posture during food intake. Previous studies have shown that most of the methods used to count food intake device is worn device type. The recent trend is now going towards non-wearable devices due to the difficulty when wearing devices and it has high false alarm ratio. The proposed system gets data from the Kinect camera and monitors the gesture of the user while eating. Then, the gesture data is collected to be recognized and it will start counting the food intake taken by the user. The system recognizes the patterns of the food intake from the user by following the algorithm design in this thesis to analyze the gesture of the basic eating type and the system get an average accuracy of 96.2%. This system can help people who are trying to follow a proper way to avoid being overweight or having eating disorders by monitoring their meal intake and controlling their eating rate. 2020-06 Thesis http://eprints.uthm.edu.my/1041/ http://eprints.uthm.edu.my/1041/2/24p%20MUHAMMAD%20FUAD%20KASSIM.pdf text en public http://eprints.uthm.edu.my/1041/1/MUHAMMAD%20FUAD%20KASSIM%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/1041/3/MUHAMMAD%20FUAD%20KASSIM%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution Universiti Tun Hussein Onn Malaysia
collection UTHM Institutional Repository
language English
English
English
topic TK7885-7895 Computer engineering
Computer hardware
spellingShingle TK7885-7895 Computer engineering
Computer hardware
Kassim, Muhammad Fuad
Tracking and counting motion for monitoring food intake based on depth sensor
description Obesity has been a serious health concern among people. Moreover, obesity continues to be a serious public health concern in Malaysia and continuing to rise. Nearly half of Malaysians are overweight. Most of the dietary approaches are not tracking and detecting the right calorie intake for weight loss, but currently used tools such as food diaries require users to manually record and track the food calories, making them difficult to be utilized for daily use. Therefore, this project developed a new tool that counts the food intake by monitoring eating motion movement of caloric intake to overcome health issues. The food intake counting method showed a good significance that can lead to a successful weight loss by simply monitoring the food intake taken during eating. The device used was Kinect Xbox One which used a depth camera to detect the motion of a person’s gesture and posture during food intake. Previous studies have shown that most of the methods used to count food intake device is worn device type. The recent trend is now going towards non-wearable devices due to the difficulty when wearing devices and it has high false alarm ratio. The proposed system gets data from the Kinect camera and monitors the gesture of the user while eating. Then, the gesture data is collected to be recognized and it will start counting the food intake taken by the user. The system recognizes the patterns of the food intake from the user by following the algorithm design in this thesis to analyze the gesture of the basic eating type and the system get an average accuracy of 96.2%. This system can help people who are trying to follow a proper way to avoid being overweight or having eating disorders by monitoring their meal intake and controlling their eating rate.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Kassim, Muhammad Fuad
author_facet Kassim, Muhammad Fuad
author_sort Kassim, Muhammad Fuad
title Tracking and counting motion for monitoring food intake based on depth sensor
title_short Tracking and counting motion for monitoring food intake based on depth sensor
title_full Tracking and counting motion for monitoring food intake based on depth sensor
title_fullStr Tracking and counting motion for monitoring food intake based on depth sensor
title_full_unstemmed Tracking and counting motion for monitoring food intake based on depth sensor
title_sort tracking and counting motion for monitoring food intake based on depth sensor
granting_institution Universiti Tun Hussein Onn Malaysia
granting_department Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate 2020
url http://eprints.uthm.edu.my/1041/2/24p%20MUHAMMAD%20FUAD%20KASSIM.pdf
http://eprints.uthm.edu.my/1041/1/MUHAMMAD%20FUAD%20KASSIM%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/1041/3/MUHAMMAD%20FUAD%20KASSIM%20WATERMARK.pdf
_version_ 1747830728504115200