The database constists of data from 18 healthy subjects who performed walking and running. The participants performed walking and running and standing in an outdoor environment on varying surfaces and performed a small circuit around the building. All subjects gave written informed consent. Details on the subject population is given in .
Data was acquired using two IMU sensors laterally attached to the left ankle. Data from 3D accelerometer and gyroscope were recorded. The data was annotated by hand using a camera reference.
Please cite this publication when using the data set:
 Martindale C., Hönig F., Strohmann C., Eskofier B.. Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models, Sensors 2017, 17(10), 2328; doi:10.3390/s17102328.
Smart_annotation_dataset.zip, please contact email@example.com in case of questions or urgent queries.
This work was in part supported by the FAUEmerging Fields Initiative (EFIMoves). Bjoern Eskofier gratefully acknowledges the support of the German Research Foundation (DFG) within the framework of the Heisenberg professorship program (Grant Number ES 434/8-1). All authors acknowledge support by Deutsche Forschungsgemeinschaft and Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) within the funding programme Open Access Publishing.