Tracking and Counting Motion for Monitoring Food Intake Based-On Depth Sensor and UDOO Board: A Comprehensive Review

International Research and Innovation Summit 2017

Bin Kassim, Muhammad Fuad^1 ; Haji Mohd, Mohd Norzali^1,2

Embedded Computing Systems (EmbCos), Department of Computer Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Johor, Batu Pahat

86400, Malaysia^1

Modeling and Simulation (BIOMEMS) Research Group, Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Johor, Batu Pahat

86400, Malaysia^2

关键词: Depth sensors;    Eating disorders;    False alarm ratio;    Health concerns;    Microcontroller boards;    Monitoring foods;    Non-wearables;    Recent trends;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/226/1/012089/pdf
DOI  :  10.1088/1757-899X/226/1/012089

来源: IOP

【 摘 要 】

Technology is all about helping people, which created a new opportunity to take serious action in managing their health care. Moreover, Obesity continues to be a serious public health concern in the Malaysia and continuing to rise. Obesity has been a serious health concern among people. Nearly half of Malaysian people overweight. Most of dietary approach is 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 for daily use. We will be developing a new tool that counts the food intake bite by monitoring hand gesture and face jaw motion movement of caloric intake. The Bite count method showed a good significant that can lead to a successful weight loss by simply monitoring the bite taken during eating. The device used was Kinect Xbox One which used a depth camera to detect the motion on person hand and face during food intake. Previous studies showed that most of the method used to count bite device is worn 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 that will be monitoring the hand and face gesture of the user while eating. Then, the gesture of hand and face data is sent to the microcontroller board to recognize and start counting bite taken by the user. The system recognizes the patterns of bite taken from user by following the algorithm of basic eating type either using hand or chopstick. This system can help people who are trying to follow a proper way to reduce overweight or eating disorders by monitoring their meal intake and controlling eating rate.