Working closely with the client, the Taazaa team developed the Early Detection Neuromotor Assessment (EDNA) desktop and corresponding web applications.
EDNA connects to the GMat via Bluetooth. When a diagnostician places an infant on the sensor mat, EDNA measures the child’s movements via the GMat’s pressure sensors, taking a reading every second for three minutes.
The software converts the data to an Excel file and sends it to the Python AI application for analysis. The AI responds with either “detected” or “not detected.” EDNA generates a PDF report that includes the patient’s information and the test result.
The desktop app sends the anonymized data to the web application for storage in the cloud. The web application is also used to create user accounts and set permissions based on their role.
The Taazaa team built the EDNA desktop app using the Windows Presentation Foundation (WPF). They developed the web application using Angular 13 for the front-end and .Net 6 and EF Core for the back-end. The database was built on PostgreSQL.
Although the client provided the GMat hardware to our US team, the India team developed the software. This meant coordinating testing between the two teams.
Midway through development, the client pivoted to a new hardware vendor. Thanks to Taazaa’s agile, iterative development process, the team made the necessary changes quickly.
When it came time to test the applications, the QA team had to get creative. Without a real infant to test with, they placed water bottles on the GMat as a stand-in. This workaround only returned a “not detected” result. The client’s later internal testing confirmed that the application returned a “detected” result when dysfunction was present.