Searched for: author%3A%22Kok%2C+M.%22
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Skog, Isaac (author), Hendeby, Gustaf (author), Kok, M. (author)
A framework for tightly integrated motion mode classification and state estimation in motion-constrained inertial navigation systems is presented. The framework uses a jump Markov model to describe the navigation system's motion mode and navigation state dynamics with a single model. A bank of Kalman filters is then used for joint inference...
conference paper 2023
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Blok, Janneke (author), Poggensee, K. (author), Lemus Perez, D.S. (author), Kok, M. (author), Pangalila, Robert F. (author), Vallery, H. (author), Deferme, Jolien (author), Toussaint-Duyster, Leontien (author), Horemans, H.L.D. (author)
Trunk motor control is essential for the proper functioning of the upper extremities and is an important predictor of gait capacity in children with delayed development. Early diagnosis and intervention could increase the trunk motor capabilities in later life, but current tools used to assess the level of trunk motor control are largely...
conference paper 2022
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Wahlstrom, Johan (author), Kok, M. (author)
The last years have seen a growing body of literature on data-driven pedestrian inertial navigation. However, despite this, it is still unclear how to efficiently combine classical models and other a priori information with existing machine learning frameworks. In this paper, we first categorize existing approaches to data-driven pedestrian...
journal article 2022