Kaasa solution, a Movesense development partner from Germany, is publishing Data Collector 2.0 for recording Movesense raw data. Data Collector 2.0 is a powerful iOS solution that not only records Movesense data but also manages data collecting in projects where data is collected in several locations and multiple people.
Read more Movesense Motion Sensors Helping Companies Build Wearables for Various Fields
“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 Kaasa CEO Nico Kaartinen.
The new Data Collector connects quickly to up to five sensors and records their data to synchronized files, reports Movesense. The app includes a number of innovative features that makes data collection easy and reliable and makes sure that the recorded data is stored systematically:
One of the innovative features of the app is sharing of sensor settings. When collecting data for research projects, prototypes, AI algorithms, and other purposes, it is essential that the sensor settings are kept identical across all sensors, locations and users in a project. Kaasa Data Collector 2.0 makes storing and sharing sensor settings within a project very fast and easy. This becomes even easier when using Movesense smart connectors.
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, says professor Sampsa Vanhatalo, leading researcher at BABA center, Helsinki Children’s Hospital.
Read more Microsoft Patents Multidimensional Heart Rate Sensor that Delivers Accurate Data on Wearables
“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, adds professor Vanhatalo, who’s also one of the first users of Data Collecto
