Physiotherapy assessment app that uses google teachable machine.
This project is made by Ouail Bni and Artur Matusiak. It serves as a bridge between image recognition and Physiotherapy with a focus on the pelvic floor area. We used google teachable machine as a tool. The prototype is a web app made with reactJs.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
What things you need to install the software and how to install them.
NodeJs / NPM
Updated Browser
Webcam
A step by step series of examples that tell you how to get a development env running.
Clone the github repo to your local system
git clone
Navigate to the folder
cd schoolproject-/frontend
Install the required libraries
npm install
Run the app
npm start
Then you can use the app through your browser
N/A
The app contains two views,
- Physiotherapist
- Patient
Choose what you identify as or would like to test.
Deployment should be straight forward:
npm build
and then deploy to any host (netlify for example)
- ReactJs - Front-end
- Python - Backend
- Google Teachable Machine - Image recognition
- Supervisor: Magnus Johnsson - Mau.se