# A Survey of Automatic Methods for Nutritional Assessment

## TL;DR

This survey reviews emerging computer science technologies and methods, both academic and commercial, that aim to improve nutritional assessment through objective data collection and analysis, addressing longstanding issues like under-reporting.

## Contribution

It provides a comprehensive overview and categorization of recent technological approaches supporting nutritional assessment, highlighting advancements and challenges.

## Key findings

- Wearable biometric devices are increasingly used for nutritional data collection.
- Existing methods face issues like under-reporting and data collection challenges.
- Emerging technologies are poised to significantly impact nutritional assessment practices.

## Abstract

Nutritional assessment is key in order to make decisions about the nature and cause of nutrition related health issues that affect an individual. The systematic process of collecting and interpreting relevant nutrition information, however, is still in its technological infancy. Despite technological advances in storage and analysis of nutritional data, methods for collecting data are largely unchanged over the past two decades. It is well documented that these methods have issues that cause under-reporting. Meanwhile, new developments in wearable biometric logging devices have seen increased traction among individuals. This is sometimes referred to as the Quantified Self movement. One part of this movement is the development of technological means for objectively collecting nutritional data. Nutritional assessment, however, is about to be heavily impacted by emerging computer science technologies, and this survey provides an overview of promising technology approaches supporting nutritional assessment. Both academic and commercial systems are reviewed and categorized.