MobilityAI is a team from McMaster University researching Human Activity Recognition (HAR) in conjunction with Juravinski Hospital. It is shown that early mobilization and physical therapy is a safe and effective intervention method that can have a significant impact on patient health. We are using a wireless sensor band to record patient mobility data and extract activity information using machine learning. The nurses can then use this data to determine how mobile a patient is during their stay compared to their pre-hospitalization mobility levels. We currently have 3 positions available, focusing on Frontend, Backend and Machine Learning respectively. This project is openly developed at https://github.com/pgunasekara/4zp6. If you would like additional information about the project, take a look at the README.
Each position requires:
- 2+ years of experience in the listed technologies
- Degree in Computer Science or related field
- Understanding of Git and version control
- Experience with Github issues workflow
- HTML/CSS/Javascript - React Native
- Java - Android
As a Frontend developer, you will be working closely with the doctors and nurses are Juravinski Hospital to develop new visualizations for patient activity data. As well as working to take full advantage of the MetaWear API to develop rich insights into patient mobility.
- C# - ASP.NET Core
- SQL - Postgres
Every day our servers will process 100s of hours of data. As a Backend developer, you will be working on optimizing sensor data ingestion. Furthermore, you will work closely with our Frontend team to develop ergonomic APIs and support on-demand data visualization.
- Python - SciKit Learn
- Jupyter Notebook - Google CoLab
Our machine learning model is integral to classifying patient activities. As a Machine Learning developer, you will be researching tools and techniques to improve the quality of the machine learning model by leveraging the state of the art cloud based infrastructure backing Google CoLab.