Food intake and eating habits have a significant impact on people’s health. Widespread diseases, such as diabetes and obesity, are directly related to eating habits. Therefore, monitoring diet can be a substantial base for developing methods and services to promote healthy lifestyle and improve personal and national health economy. Studies have demonstrated that manual reporting of food intake is inaccurate and often impractical. Thus, several methods have been proposed to automate the process. This article reviews the most relevant and recent researches on automatic diet monitoring, discussing their strengths and weaknesses. In particular, the article reviews two approaches to this problem, accounting for most of the work in the area. The first approach is based on image analysis and aims at extracting information about food content automatically from food images. The second one relies on wearable sensors and has the detection of eating behaviours as its main goal.

Automatic diet monitoring: a review of computer vision and wearable sensor-based methods / Hassannejad, Hamid; Matrella, Guido; Ciampolini, Paolo; DE MUNARI, Ilaria; Mordonini, Monica; Cagnoni, Stefano. - In: INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION. - ISSN 0963-7486. - 68:6(2017), pp. 656-670. [10.1080/09637486.2017.1283683]

Automatic diet monitoring: a review of computer vision and wearable sensor-based methods

HASSANNEJAD, Hamid;MATRELLA, Guido;CIAMPOLINI, Paolo;DE MUNARI, Ilaria;MORDONINI, Monica;CAGNONI, Stefano
2017-01-01

Abstract

Food intake and eating habits have a significant impact on people’s health. Widespread diseases, such as diabetes and obesity, are directly related to eating habits. Therefore, monitoring diet can be a substantial base for developing methods and services to promote healthy lifestyle and improve personal and national health economy. Studies have demonstrated that manual reporting of food intake is inaccurate and often impractical. Thus, several methods have been proposed to automate the process. This article reviews the most relevant and recent researches on automatic diet monitoring, discussing their strengths and weaknesses. In particular, the article reviews two approaches to this problem, accounting for most of the work in the area. The first approach is based on image analysis and aims at extracting information about food content automatically from food images. The second one relies on wearable sensors and has the detection of eating behaviours as its main goal.
Automatic diet monitoring: a review of computer vision and wearable sensor-based methods / Hassannejad, Hamid; Matrella, Guido; Ciampolini, Paolo; DE MUNARI, Ilaria; Mordonini, Monica; Cagnoni, Stefano. - In: INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION. - ISSN 0963-7486. - 68:6(2017), pp. 656-670. [10.1080/09637486.2017.1283683]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2823532
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 42
  • ???jsp.display-item.citation.isi??? 37
social impact