Projects / AI Innovation Challenge

Detecting Weight Changes Through Computer Vision

Project Kickoff: August 1


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Developing an AI-driven image analysis tool to estimate and track weight changes in individuals, enhancing remote health monitoring and patient care efficiency. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.

The problem

The current standard for monitoring weight fluctuations involves direct physical measurements, which necessitates patients being present for weigh-ins. This method can be cumbersome and sometimes impractical, especially for individuals who are remotely located or have mobility issues. Regular weight tracking is essential for managing health, particularly for patients with conditions that require close monitoring of body weight. The reliance on physical scales can pose significant challenges in such scenarios, hindering effective health management and patient care.

Impact of the Problem:

  • Limited Access and Convenience: For patients who are remotely located, mobility-impaired, or lack immediate access to healthcare facilities, regular travel for weight check-ups is not always feasible. This limits the frequency of monitoring and can delay interventions in response to critical weight changes.
  • Increased Healthcare Burden: Requiring physical presence for weight measurements not only places a logistical burden on patients but also on healthcare systems, which must allocate resources and time to manage these appointments.
  • Inadequate Monitoring in Special Populations: Certain groups, such as the elderly or those with chronic conditions, need more frequent monitoring. The traditional methods may not meet these needs adequately, potentially leading to overlooked health issues related to significant weight changes.
  • Impediments in Health Management Programs: For programs focused on weight management, the lack of frequent, accurate weight data can hinder the tracking of progress and the effectiveness of the interventions, reducing overall engagement and outcomes.

This AI Innovation Challenge aims to address these issues by utilizing image analysis to monitor weight changes. This approach will allow for a more accessible, immediate, and less invasive method of tracking weight changes, enhancing healthcare delivery and patient engagement in their own health management.

The goals

The main aim of this project is to advance the field of health monitoring by developing an AI-driven solution capable of estimating and tracking weight changes through image analysis. This technology is intended to provide a non-invasive, efficient method for monitoring weight trends, especially useful in remote or clinical settings. The project unfolds over a 8+2 weeks period, each phase planned to ensure the successful development and deployment of the weight monitoring tool:

  • Data Preparation: The team will secure initial datasets, perform data cleaning, and define data augmentation strategies. This phase focuses on preparing a robust dataset that reflects diverse demographics and body types, crucial for training the AI models effectively.
  • Preliminary Model Development: An initial set of AI models will be developed to detect weight changes from images. This phase involves establishing baseline performance metrics and beginning the exploration of different poses and image processing techniques to optimize accuracy.
  • Advanced Modeling Techniques: The team will test these advanced models with various image qualities and poses to identify the most effective approaches for weight change detection.
  • Expanding Model Capabilities: Feedback from previous phases will be incorporated to refine the AI models further. 
  • In-depth Testing and Validation: Extensive testing will be conducted across different demographics to validate the accuracy and reliability of the weight change detection. 
  • Pre-finalization Phase: Focus will be on enhancing the model’s accuracy and processing speed, alongside starting the drafting of project documentation. 
  • Finalization and Optimization: The AI models will be finalized and optimized based on comprehensive evaluations and testing. All project documentation will be completed, including recommendations for future improvements and potential uses.

Thus, the project aims to deliver an innovative AI system that revolutionizes how weight changes are monitored, providing a valuable tool for healthcare providers and enhancing patient care through advanced technology. This initiative promises significant benefits in remote health monitoring and patient engagement in weight management.

Why join? The uniqueness of Omdena AI Innovation Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will build AI solutions to make a real-world impact and go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities



Your Benefits

Address a significant real-world problem with your skills

Get hired at top companies by building your Omdena project portfolio (via certificates, references, etc.)

Access paid projects, speaking gigs, and writing opportunities



Requirements

Good English

A very good grasp in computer science and/or mathematics

(Senior) ML engineer, data engineer, or domain expert (no need for AI expertise)

Programming experience with Python

Understanding of Machine Learning, and/or Computer Vision



This challenge is hosted with our friends at


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