Kaasa’s New Data Collector 2.0 Helps to Record and Manage Large Sets of Movesense Sensor Data -- MEDICA - World Forum for Medicine


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Kaasa’s New Data Collector 2.0 Helps to Record and Manage Large Sets of Movesense Sensor Data

German Kaasa solution GmbH is publishing Data Collector 2.0, a powerful iOS solution for recording Movesense raw data and to manage data sets in projects where sensor data is collected in several locations and by multiple people.

– We developed the Data Collector originally for our own Movesense projects but noticed that many developers need such a tool. Therefore, we are now making the improved 2.0 version available to other companies as well, says Nico Kaartinen, Kaasa CEO who will speak about one of their consumer projects at Medica Medicine + Sports Conference on Nov 21 .

The new Data Collector connects quickly to up to five Movesense sensors and records their data to synchronized files. User can simply select which sensor data to record (acceleration, gyro, magnetometer, heart rate, ECG, temperature) and adjust the sampling rate and other settings. The app makes storing and sharing sensor settings within a project very fast and easy, ensuring that the settings are kept identical across all sensors, locations and users in a project. 

Another big benefits of the app for developrers is its very practical real time data annotation options through video, audio, hot buttons and free text. This meta data is stored and automatically synchronized with the raw data, speeding up algorithm development and utilization of AI based analytics with the collected data.

One of the first users of Data Collector 2.0 is professor Sampsa Vanhatalo, leading researcher at BABA center, Helsinki Children’s Hospital.

– We are developing medical wearables for neurological assessment of spontaneously moving infants. It was necessary to find a tool that allows recording synchronous data from multiple sensor, and Data Collector 2.0 was the only solution that could carry out the task. In addition, the ability to collect synchronized video as well as manual and audio annotations was extremely useful for us. Such tool will be crucial for anyone who wants to collect well characterized datasets for future training of analysis algorithms. Indeed, this was a game changer for our projects. We now feel so confident with the tool and its ease of use that we are planning to give it to external participants in their daily living environments, says professor Vanhatalo.

Exhibitor Data Sheet