Advances in connected health through the Internet of Things (IOT) are helping healthcare organizations thrive in this changing environment in three fundamental ways: by defining patient-centered care strategies, improving care collaboration, and empowering patients to take ownership of their health.
What it does
- The IoT solution collects vitals for registered persons from various devices over BLE (Bluetooth Low Energy) on parameters like weight, blood pressure, pulse, oxygen levels etc.,
- Through a gateway device, (Rasberry Pi / Android phone) to push that data into predix cloud
- Aanalyzes the variations and longitudinal data, and come up with a calculated risk score
- Provides a user friendly UI for continuous tracking and visibility to care providers, doctors or anyone else authoried to access the data
How I built it
The solution is built using nodejs, AngularJS, java spring boot. The solution is deployed on Predix cloud. We have also used Azure Machine learning for risk stratification.
Challenges I ran into
Challenges were mostly in the initial part of user authentication. Non-availability of Healthcloud, but we built it on Predix such that it can be easily ported to healthcloud when it's ready
Accomplishments that I'm proud of
The solution leverages key features of predix like UAA, assets, time series, analytics and also integrating solution on predix with Azure Machine learning
What I learned
To develop solutions on predix and the entire stack, deploy application on Predix and integrate with external services, use of timeseries and many other services on Predix.
What's next for Connected Patients Risk Monitoring
Improve up on the analytics and machine learning part. Integrate the solution with many more devices. Bring in more personas and use cases. Commercialize the solution and roll out.
To try out the demo, use the link below with user name charlie and password PrediX@123. this login is for the role of a doctor or hospital staff. The doctor can see the list of patients, edit patient details, register a new patient, see the list of devices. The doctor can also view the patients readings segregated on risk factor, and see a graph depicting the variations in the vital characteristics.