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Emography Evaluation Datamodel


Philips had a problem and asked us to solve it. 

In parnership with Philips we developed a highly efficient datamodel to record and retrieve stress related samples in real-time. The datamodel works together with the Philips Emography Stress Management System and allows a user to view his or her stress related data on any device.

The data model we developed allows Philips to handle millions of stress related samples efficiently using a custom designed data compression algorithm. Traditional sample methods require a lot of storage, with as a result inefficient lookups and expensive queries. Our datamodel analyzes incoming data immediately and collapses the various samples into larger chunks of data without loosing precision. The result is a data model with an extremely low memory footprint and vastly improved response time.

The datamodel is written in C++ using NAP and can be compiled and deployed on any platform, including mobile, desktop and the cloud. Next to being fast, small and performant: NAP offers Philips the opportunity to easily edit and extend the existing data-model without our active involvement. The model is currently part of the Android Evaulation Application and will become available as an option to customers interested in adopting the Philips Emography Stress Management System.