The primary objective of AutoActive is to realize tools, methods and algorithms that allow extraction of reliable and useful information on human activity from heterogeneous sensor data.
In order to work towards this objective, AutoActive has the following secondary objectives:
- Sensor technology: To enable synchronisation, filtering, calibration and collection of raw sensor data from a wide range of wireless sensors.
- Software platform: To realize a framework for dynamic, research-based modelling, storage, presentation, and on-demand access of human activity measurement data.
- Data interpretation: To develop methods to use experiments, simulations and the analysis framework to develop sensor fusion algorithms optimised for specific applications, user groups or individuals.
- Case studies: To develop and verify data interpretation solutions through case studies selected to address key challenges of heterogeneous sensor analysis. Case topics: 1) disease monitoring, 2) exercise performance
- Innovate and publish. To publish results, educate 1 PhD and 2 Post Docs candidates, and generate profit and innovation for the benefit of Norwegian companies, public organizations and society at large.
- WP1: Sensor, Technology – Victor Gonzales, SINTEF
- WP2: Software Platform – Anders Liverud, SINTEF
- WP3: Data Interpretation - Andeas Austeng, UiO
- WP4: Case - Exercise Performance - Øyvind Sandbakk, NTNU Senter for toppidrett
- WP5: Case - Disease Management - Elisabeth Gulowsen Celius , OUS
- WP6: Project and Impact Management - Trine M. Seeberg, SINTEF