Conference Paper2024

Design and Evaluation of the PustiPothika mHealth App: A Machine Learning-Enabled Solution for Daily Nutritional Monitoring and Recommendations in Bangladesh

Nabarun Halder, Yousra Tabassum, Anika Islam, Nusrat Sultana, J. M. Sadik-Ul Islam Smaron, Ashraful Islam

IEEE 2024 International Advances in Science & Engineering Technology (ASET) Multi-Conferences

IEEE, pp. 01-07

  • Zero Hunger — Relevance: 85%
  • Good Health and Well-being — Relevance: 88%

Abstract

Eating healthy is important, but it is not enough; consuming all the necessary nutrients the body requires is equally important. Nutrients are essential for all bodily systems' growth, repair, and proper functioning. In this study, we have surveyed to understand the views and practices among Bangladeshi people, how they make their dietary choices, and the use of the mobile health (mHealth) app. We developed a mobile application for the people of Bangladesh, where providing physiological information allows the users to know their nutritional needs and make their grocery choices accordingly. We developed a recommendation system that can create a list depending on the user's nutritional requirements, with just a little preference for food items. Through our survey, among 72 participants, 75% wanted this kind of solution and among 10 testers, all of them liked using our system.

Keywords

  • mobile health apps
  • nutritional monitoring
  • food choice
  • personalized food recommendation
  • nutrient requirements
  • mobile application design
  • user preferences

CCDS Authors

Nabarun Halder
Nabarun Halder

Nabarun Halder

  • Research Assistant, CCDS

Published at

UbiComp, IJCNN, HCII, IEEE Access

Research Interests

Machine Learning, Deep Learning, Natural Language Processing, Health Informatics, Human-Computer Interaction

Ashraful Islam, PhD
Ashraful Islam

Ashraful Islam, PhD

  • Center Director, CCDS
  • Director, HCI Wing

Assistant Professor

Department of Computer Science and Engineering

Independent University, Bangladesh (IUB)

Published at

CHI, UIST, UbiComp, IJCNN, ICIP, HCII, ICDMW, BLP, IEEE Internet of Things Journal, JMIR, JMIR Human Factors, JMIR Formative Research, IEEE Access, Smart Agricultural Technology, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Human-Computer Interaction, AI for Social Good, AI for Public Health, AI for Impact

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