Mobile Applications for the Promotion and Support of Healthy Nutrition and Physical Activity Habits: A Systematic Review, Extraction of Features and Taxonomy Proposal

María Vanessa Villasana,Petre Lameski,Juliana Sá,Nuno M Garcia,Ivan Miguel Pires,Ivan Chorbev,Francisco Flórez-Revuelta,Eftim Zdravevski

doi:10.2174/1874196701907010050

Abstract

Background:Mobile applications can be used for the monitoring of lifestyles and physical activity. It can be installed in commodity mobile devices, which are currently used by different types of people in their daily activities worlwide .Objective:This paper reviews and categorizes the mobile applications related to diet, nutrition, health, physical activity and education, showing the analysis of 73 mobile applications available on Google Play Store with the extraction of the different features.Methods:The mobile applications were analyzed in relation to each proposed category and their features, starting with the definition of the search keywords used in the Google Play Store. Each mobile application was installed on a smartphone, and validated whether it was researched in scientific studies. Finally, all mobile applications and features were categorized.Results:These mobile applications were clustered into four groups, including diet and nutrition, health, physical activity and education. The features of mobile applications were also categorized into six groups, including diet, anthropometric parameters, social, physical activity, medical parameters and vital parameters. The most available features of the mobile applications are weight, height, age, gender, goals, calories needed calculation, diet diary, food database with calories, calories burned and calorie intake.Conclusion:With this review, it was concluded that most mobile applications available in the market are related to diet, and they are important for different types of people. A promising idea for future work is to evaluate the acceptance by young people of such mobile applications.

Highlights

Informatics procedures are employed in various disciplines for string pattern identification including biology, genetic works, computer sciences, engineering, medicine, etc
After the development of fuzzy number representation of the text string coupled with crisp pattern string their relationships are searched at different shift operations, and the possibility of defaulters are identified in the text string with a certain degree of membership
Bioinformatics string match algorithms provide a wide range of applications, especially, in biology and computer information for the identification of a given pattern to match a basic text string

Summary

Introduction

Informatics procedures are employed in various disciplines for string pattern identification including biology, genetic works, computer sciences, engineering, medicine, etc. The main idea is to match two parallel strings composed of different and alike numerical or symbolic bits of different sizes Such methodologies are used frequently in DNA researches. Nsira et al [2] tackled online exact string matching to a pattern in a set of highly similar sequences In this sentence “highly” implies a fuzzy word, which means that text sequence may not be crisply feasible, i.e., fuzzy to a certain extent. They have considered the application of two well-known string matching procedures, namely, the classical Morris-Pratt and Knuth-Morris-Pratt algorithms with error boundaries. These are successfully applicable procedures in DNA bioinformatics researches even by taking into consideration probabilistic random variability components based on the probability distribution functions of various types

Methods

Results

Conclusion