Vol.:(0123456789) 1 3 Journal of Neurology https://doi.org/10.1007/s00415-020-09725-3 ORIGINAL COMMUNICATION Gait variability as digital biomarker of disease severity in Huntington’s disease Heiko Gaßner 1  · Dennis Jensen 1  · F. Marxreiter 1  · Anja Kletsch 2  · Stefan Bohlen 2  · Robin Schubert 2  · Lisa M. Muratori 2,3  · Bjoern Eskofer 4  · Jochen Klucken 1,5,6  · Jürgen Winkler 1  · Ralf Reilmann 2,7,8  · Zacharias Kohl 1,9,10 Received: 20 September 2019 / Revised: 20 January 2020 / Accepted: 22 January 2020 © The Author(s) 2020 Abstract Background Impaired gait plays an important role for quality of life in patients with Huntington’s disease (HD). Measur- ing objective gait parameters in HD might provide an unbiased assessment of motor defcits in order to determine potential benefcial efects of future treatments. Objective To objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particu- larly, gait parameters were correlated to the Unifed Huntington’s Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC). Methods Patients with manifest HD at two German sites (n = 43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age- and gender-matched controls performed a defned gait test (4 × 10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefcient of variance (CV). Results Stride length (− 15%) and gait velocity (− 19%) were reduced, while stride (+ 7%) and stance time (+ 2%) were increased in patients with HD. However, parameters refecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest efect size) and showed strong correlations to TMS and TFC (0.416 ≤ r Sp ≤ 0.690). Objective gait variability parameters correlated with disease stage based upon TFC. Conclusions Sensor-based gait variability parameters were identifed as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and refects disease severity. Keywords Huntington’s disease · Gait analysis · Wearable sensors · Gait variability · Regularity of gait Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00415-020-09725-3) contains supplementary material, which is available to authorized users. * Zacharias Kohl Zacharias.Kohl@klinik.uni-regensburg.de 1 Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen- Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany 2 George-Huntington Institute (GHI) GmbH, Münster, Germany 3 Rehabilitation Research and Movement Performance Laboratory (RRAMP Lab), Stony Brook University, Stony Brook, NY, USA 4 Machine Learning and Data Analytics Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany 5 Medical Valley-Digital Health Application Center GmbH, Bamberg, Germany 6 Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany 7 Department of Radiology, University of Muenster, Muenster, Germany 8 Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany 9 Center for Rare Diseases Erlangen, University Hospital Erlangen, Erlangen, Germany 10 Department of Neurology, University of Regensburg, Regensburg, Germany