I created GGIR in 2013 as a generic solution to handle and analyse the data collected with modern accelerometers. GGIR facilitates: data reading, data quality assessment, generation of basic descriptive reports about a person’s movement, sleep detection and the detection bouts of time spent in acceleration ranges while allowing for short gaps in behaviour.Learn more
Key GGIR features
Open source software
Process and analyse multi-day data
"Being able to access Vincent’s expertise and support through his consultancy service is very important to us. He has developed bespoke accelerometer data processing options that can be applied at scale, enabling us to get more from our datasets and advancing our research."
Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
"The Private Training provided us with the information and resources necessary to confidently use GGIR. Drs. van Hees and Migueles provided opportunity for questions and feedback that allowed us to make adaptations specific to our research projects. They were accessible, transparent, and helpful!"
AdventHealth Research Institute - Neuroscience Orlando, Florida, USA
"Accelerometer data are an amazing source of information, but how to extract this information? How to detect sleep, derive time in activity levels, create fragmentation indices, extract time-series for functional data analysis…? Vincent found solutions for all of them while working collaboratively with me and my team. A very good experience!"
Université de Paris, Inserm U1153, France; University College London, UK
"We are very excited to collaborate with Dr. Vincent van Hees in analyzing the accelerometry data of our large German National Cohort (NAKO). Vincent has an outstanding ability to develop and apply scientific software and algorithms to process movement data. It is a great pleasure to work with him!"
Dept. of Epidemiology and Preventive Medicine, University of Regensburg, Germany