Automatic Movement Segmentation of Exoskeleton Data
Lisa Gutzeit, Marc Tabie, Elsa Andrea Kirchner
In Conference Proceedings of the 3rd International Mobile Brain/Body Imaging Conference, (MoBI-2018), 11.7.-14.7.2018, Berlin, TU Berlin DepositOnce, pages 62-63, Jul/2018.
We present a method to automatically segment manipulation movement demonstrated with an
exoskeleton into distinct action units. The automatic segmentation of movement plays an important
role in applications such as robotic learning from demonstration , as well as in braincomputer
interfaces when labels for machine learning methods are needed, e.g. for movement
prediction . The presented segmentation method is motivated by the hypothesis that human
movement is composed of simple building blocks which can be combined to complex behavior
. In manipulation movements, these building blocks are characterized by a bell-shaped
velocity profile of the hand . We use this to segment human movement trajectories of manipulation
tasks into movement building blocks.