Gait changes measure HSP progression

Evidence established in large study

Mobile digital gait measurements in this large study of 55 people with HSP over more than six years has established that changes in gait are meaningful measures of HSP progression.

Martin Regensburger

The changes in gait were correlated with clinical measures such as score on the Spastic Paraplegia Rating Scale (SPRS) and participant reported factors such as fear of falling and quality of life.

The potential exists for development of these mobile digital gait measurements into a biomarker of disease status and progression suitable for use in clinical trials, which is something badly needed and currently lacking.

Heiko Gassner


Progressive spasticity and gait impairment are the functional hallmarks of hereditary spastic paraplegia (HSP) but due to inter-individual variability, longitudinal studies on its progression are scarce.

We investigated the progression of gait deficits via mobile digital measurements in conjunction with clinical and patient-reported outcome parameters. Our cohort included adult HSP patients (n = 55) with up to 77 months of follow-up.

Gait speed showed a significant association with SPRS progression. Changes in stride time and gait variability correlated to fear of falling and quality of life, providing evidence that gait parameters are meaningful measures of HSP progression.

SOURCE:  Ann Clin Transl Neurol. 2023 Jan 9. doi: 10.1002/acn3.51725. Online ahead of print. PMID: 36622133 © 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.

Mobile digital gait analysis objectively measures progression in hereditary spastic paraplegia

Evelyn Loris  1 Malte Ollenschläger  1   2 Teresa Greinwalder  1 Björn Eskofier  2 Jürgen Winkler  1   3 Heiko Gaßner  1   4 Martin Regensburger  1   3

1. Department of Molecular Neurology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.

2. Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.

3. Center for Rare Diseases Erlangen (ZSEER), Universitätsklinikum Erlangen, Erlangen, Germany.

4. Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, 91058, Erlangen, Germany.

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