Heiko Gaßner1, Philipp Sanders1, Alisa Dietrich1, Franz Marxreiter1, Bjoern M Eskofier2, Jürgen Winkler1, Jochen Klucken1,3,4. 1. Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany. 2. Machine Learning and Data Analytics Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany. 3. Medical Valley - Digital Health Application Center GmbH, Bamberg, Germany. 4. Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.
Abstract
BACKGROUND: Gait impairments in Parkinson's disease (PD) are quantified using inertial sensors under standardized test settings in the hospital. Recent studies focused on the assessment of free-living gait in PD. However, the clinical relevance of standardized gait tests recorded at the patient's home is unclear. OBJECTIVE: To evaluate the reliability of supervised, standardized sensor-based gait outcomes at home compared to the hospital. METHODS: Patients with PD (n = 20) were rated by a trained investigator using the Unified Parkinson Disease Rating Scale (UPDRS-III). Gait tests included a standardized 4×10 m walk test and the Timed Up and Go Test (TUG). Tests were performed in the hospital (HOSPITAL) and at patients' home (HOME), and controlled for investigator, time of the day, and medication. Statistics included reliability analysis using Intra-Class correlations and Bland-Altman plots. RESULTS: UPDRS-III and TUG were comparable between HOSPITAL and HOME. PD patients' gait at HOME was slower (gait velocity Δ= -0.07±0.11 m/s, -6.1%), strides were shorter (stride length Δ= -9.2±9.4 cm; -7.3%), and shuffling of gait was more present (maximum toe-clearance Δ= -0.7±2.5 cm; -8.8%). Particularly, narrow walkways (<85 cm) resulted in a significant reduction of gait velocity at home. Reliability analysis (HOSPITAL vs. HOME) revealed excellent ICC coefficients for UPDRS-III (0.950, p < 0.000) and gait parameters (e.g., stride length: 0.898, p < 0.000; gait velocity: 0.914, p < 0.000; stance time: 0.922, p < 0.000; stride time: 0.907, p < 0.000). CONCLUSION: This pilot study underlined the clinical relevance of gait parameters by showing excellent reliability for supervised, standardized gait tests at HOSPITAL and HOME, even though gait parameters were different between test conditions.
BACKGROUND: Gait impairments in Parkinson's disease (PD) are quantified using inertial sensors under standardized test settings in the hospital. Recent studies focused on the assessment of free-living gait in PD. However, the clinical relevance of standardized gait tests recorded at the patient's home is unclear. OBJECTIVE: To evaluate the reliability of supervised, standardized sensor-based gait outcomes at home compared to the hospital. METHODS:Patients with PD (n = 20) were rated by a trained investigator using the Unified Parkinson Disease Rating Scale (UPDRS-III). Gait tests included a standardized 4×10 m walk test and the Timed Up and Go Test (TUG). Tests were performed in the hospital (HOSPITAL) and at patients' home (HOME), and controlled for investigator, time of the day, and medication. Statistics included reliability analysis using Intra-Class correlations and Bland-Altman plots. RESULTS: UPDRS-III and TUG were comparable between HOSPITAL and HOME. PDpatients' gait at HOME was slower (gait velocity Δ= -0.07±0.11 m/s, -6.1%), strides were shorter (stride length Δ= -9.2±9.4 cm; -7.3%), and shuffling of gait was more present (maximum toe-clearance Δ= -0.7±2.5 cm; -8.8%). Particularly, narrow walkways (<85 cm) resulted in a significant reduction of gait velocity at home. Reliability analysis (HOSPITAL vs. HOME) revealed excellent ICC coefficients for UPDRS-III (0.950, p < 0.000) and gait parameters (e.g., stride length: 0.898, p < 0.000; gait velocity: 0.914, p < 0.000; stance time: 0.922, p < 0.000; stride time: 0.907, p < 0.000). CONCLUSION: This pilot study underlined the clinical relevance of gait parameters by showing excellent reliability for supervised, standardized gait tests at HOSPITAL and HOME, even though gait parameters were different between test conditions.
Entities:
Keywords:
Parkinson’s disease; gait analysis; home monitoring; telemedicine; wearable sensors
Authors: Felix Kluge; Silvia Del Din; Andrea Cereatti; Heiko Gaßner; Clint Hansen; Jorunn L Helbostad; Jochen Klucken; Arne Küderle; Arne Müller; Lynn Rochester; Martin Ullrich; Bjoern M Eskofier; Claudia Mazzà Journal: PLoS One Date: 2021-08-20 Impact factor: 3.240
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