Visualizing and annotating video and microsensor data from cross-country skiing using the autoactive research environment - Rindal, O. M. H.; Gløersen, Ø.; Kvåle, K.; Tjønnås, J.; Liverud, A. (9th International Congress on Science and Skiing, March 18 - 22, 2023, Saalbach-Hinterglemm, Austria, 2023)
INTRODUCTION: Wearable microsensors such as inertial movement sensors (IMUs) are revolutionizing the analysis of movement. It allows researchers to bring the lab to the field, resulting in more relevant data for the analysis of movements in sports. However, there has been a lack of tools to visualize and analyze the data. Especially, synchronizing video with recorded microsensor data, and easy annotations for machine learning purposes, have been challenging. To answer this challenge, SINTEF has developed an open-source AutoActive Research Environment (ARE) 1 consisting of an easy-to-use software with a graphical user interface, ActivityPresenter, to visualize, synchronize, annotate and organize data from sensors and cameras as well as supporting interactions with MATLAB and Python. We demonstrate this software suite by sharing a dataset to analyze and annotate sub-techniques in classical cross-country skiing as in [2]. The data and code are available at https://www.sintef.no/projectweb/autoactive/code-example/.