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Telehealth Platform

The health startup, based in Chicago and specialized in remote consultation, worked with several agencies in order to realize their project. Not satisfied by the previous results, they reached out to me and my team at Falcon, who realized a project MVP to prove the technical feasibility of this cutting-edge project, and allowing the client to raise money for the development of the complete platform.

  • User Research
  • DB Architecture
  • Development
  • ML Integration
  • Code Reviews
  • Deployment
A mediapipe playground screen showing a pose model.

Project description

Telehealth platform (project name is confidential) is a US web and mobile application which allows physiotherapists to analyze the movements of their patients remotely. The patient is recorded through his own phone, performing different types of exercises, and the tool detects and calculates the angles of the patient body (such as his legs, arms, foot, waist, etc...). The program then analyzes the data based on internal rules and indicates whether the movements are abnormal or not.

The detection of the movements is done with the help of a Media pipe, ARKit and ARCore, and requires advanced knowledge in terms of image processing to ensure fluidity and accuracy of the final results. The health experts can also create custom-made motion exercises by using the exercise generator feature of the platform.

This is a complex and cutting-edge technology which allows to define automatically the internal rules of the exercises generated (allowing to know when a patient is correctly realizing the movements or not).

Short story

Based on client requirement, We developed and launched the MVP, which got validated and realized in the first half of 2022. After the confirmation of the product-market fit and approval from FDA, the client asked us to create the complete platform, based on its requirement. We started work on the complete app and it's still in progress.

Random mediapipe picture collage as the real ones are not allowed to share
Tech stacks in which the project was developed.

Tech stack

The project was developed using the MERN stack and Tensorflow Mediapipe. MERN stands for MongoDB, Express.js, React.js, and Node.js. MongoDB served as the flexible NoSQL database, Express.js handled the backend operations, React.js built the interactive user interface, and Node.js provided the runtime environment. MediaPipe is an open-source framework for building pipelines to perform computer vision inference over arbitrary sensory data such as video or audio.

Project outcomes

After the confirmation of the product-market fit and approval from FDA, the client asked us to create the complete platform, based on its requirement. We started work on the complete app and it's still in progress.