This blog post explains what technological differences in the Fibion device provide it considerably better starting point for accurate energy expenditure estimation than other devices on the market (be it consumer or research device). Moreover, we show the same in numbers based on a validation study.
We get asked often how Fibion can detect different activity types just with a device you wear in your pocket. We tell that it is based on a neural networks analysis that takes into consideration magnitude, frequency band and patterns of acceleration in three-dimensional space. Well, that doesn’t help too much if you don’t have mathematics and physics as a hobby, so here is a blog post that explains why Fibion detects different physical activities much more accurately than other physical activity sensors.
Fibion Inc. is proud to announce a new R&D collaboration with Shanghai Jiao Tong University (SJTU). SJTU is one of the top three universities in China and it has established a new top research center this year, called Exercise, Health and Technology Center (EHT) (http://eht.sjtu.edu.cn/). The Head of the new research center Professor Sulin Cheng is excited about the collaboration...
Olli Tikkanen defends his doctoral dissertation
Date: October 1, 2014, at 12:00 PM
Location: Seminaarinmäki, L 303, University of Jyväskylä, Finland
Mr Olli Tikkanen, M.Sc., defends his doctoral dissertation in Science of Coaching and Fitness titled "Physiological loading during normal daily life and exercise assessed with electromyography ". The opponent is Professor Hans Savelberg (Maastricht University, The Netherlands) and the custos is Professor Taija Juutinen...