Digital photography based food intake prediction using artificial neural network

Gunawan, Teddy Surya and Kartiwi, Mira (2017) Digital photography based food intake prediction using artificial neural network. Malaysian Journal of Medicine, 72 (Supplement 1). p. 20. ISSN 0300-5283

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Abstract

Introduction Many wearable devices monitoring have been proposed to complement self-reporting of users’ caloric intake and eating behaviours. These devices comprise varying sensing modalities, such as acoustic, visual, inertial, EEG, EMG, capacitive and piezoelectric sensors. In this research, food intake will be predicted from the input of digital photography using ANN. Methods In this study, image of selected food or leftovers are captured using digital camera or smartphone. These two images are later compared with images of averaged portions of food. Area based comparison or trained artificial neural network could then predicted the calorie and nutrient intake. Results Preliminary results show the effectiveness of measuring food intake using digital photography. It is found that more images are required to train the artificial neural network for various image capturing position to improve the prediction accuracy. Discussion The proposed method is rather simple and easy and provides quick feedback on food intake and dietary recommendations to achieve weight loss goal. It is believe that such findings would allow general public to better achieve and maintain their healthy lifestyle.

Item Type:	Article (Meeting Abstract)
Additional Information:	5588/59505
Uncontrolled Keywords:	Digital photography; Food intake prediction; Artificial neural network
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	21 Nov 2017 14:50
Last Modified:	21 Nov 2017 14:50
URI:	http://irep.iium.edu.my/id/eprint/59505

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