Validity of an inertial sensor-based system for the assessment of spatio-temporal parameters in people with multiple sclerosis

Annalena Zahn; Veronika Koch; Lucas Schreff; Patrick Oschmann; Jürgen Winkler; Heiko Gaßner; Roy Müller

doi:10.3389/fneur.2023.1164001

Validity of an inertial sensor-based system for the assessment of spatio-temporal parameters in people with multiple sclerosis

Front Neurol. 2023 Apr 20:14:1164001. doi: 10.3389/fneur.2023.1164001. eCollection 2023.

Authors

Annalena Zahn^{1

2}, Veronika Koch³, Lucas Schreff^{1

4}, Patrick Oschmann¹, Jürgen Winkler², Heiko Gaßner^{2

3}, Roy Müller^{1

2

4}

Affiliations

¹ Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany.
² Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen, Erlangen, Germany.
³ Fraunhofer Institute for Integrated Circuits (IIS), Digital Health Systems, Erlangen, Germany.
⁴ Bayreuth Center of Sport Science, University of Bayreuth, Bayreuth, Germany.

Abstract

Background: Gait variability in people with multiple sclerosis (PwMS) reflects disease progression or may be used to evaluate treatment response. To date, marker-based camera systems are considered as gold standard to analyze gait impairment in PwMS. These systems might provide reliable data but are limited to a restricted laboratory setting and require knowledge, time, and cost to correctly interpret gait parameters. Inertial mobile sensors might be a user-friendly, environment- and examiner-independent alternative. The purpose of this study was to evaluate the validity of an inertial sensor-based gait analysis system in PwMS compared to a marker-based camera system.

Methods: A sample N = 39 PwMS and N = 19 healthy participants were requested to repeatedly walk a defined distance at three different self-selected walking speeds (normal, fast, slow). To measure spatio-temporal gait parameters (i.e., walking speed, stride time, stride length, the duration of the stance and swing phase as well as max toe clearance), an inertial sensor system as well as a marker-based camera system were used simultaneously.

Results: All gait parameters highly correlated between both systems (r > 0.84) with low errors. No bias was detected for stride time. Stance time was marginally overestimated (bias = -0.02 ± 0.03 s) and gait speed (bias = 0.03 ± 0.05 m/s), swing time (bias = 0.02 ± 0.02 s), stride length (0.04 ± 0.06 m), and max toe clearance (bias = 1.88 ± 2.35 cm) were slightly underestimated by the inertial sensors.

Discussion: The inertial sensor-based system captured appropriately all examined gait parameters in comparison to a gold standard marker-based camera system. Stride time presented an excellent agreement. Furthermore, stride length and velocity presented also low errors. Whereas for stance and swing time, marginally worse results were observed.

Keywords: different walking speeds; gait-parameter; multiple sclerosis (MS); three-dimensional gait analysis; walking human; wearable sensors.

Grants and funding

This work was supported in part by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project 438496663 (Mobility APP) and SFB 1483—Project-ID 442419336 (EmpkinS). The work of JW and HG were supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement 820820. This joint undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations. Further, the work of HG was supported by the Fraunhofer Internal Programs under Grant Nos. Attract 044-602140 and 044-602150. The authors further acknowledge financial support by Deutsche Forschungsgemeinschaft and Friedrich-Alexander-Universität Erlangen-Nürnberg within the funding program Open Access Publication Funding.