Event Abstract

Quantification of refined temporal gait parameters in Parkinson’s disease using an accelerometer-based ambulatory system

  • 1 Human Movement Analysis Laboratory, University of Liège, Belgium
  • 2 Department of Electrical Engineering and Computer Science, University of Liège, Belgium
  • 3 GIGA-Cyclotron Research Center In Vivo Imaging, University of Liege, Belgium
  • 4 Department of Neurology, University Hospital Liège, Belgium

Objective: To apply for the first time in Parkinson’s disease (PD) a newly developed and validated signal-processing algorithm aimed at quantifying the variability, symmetry, and regularity of refined temporal gait parameters during comfortable walking using an ambulatory accelerometer-based foot-mounted system. Methods: We recorded 47 seconds long gait data from 14 PD patients ((mean±std) age = 67.8 ± 10.8 years, Unified PD Rating Scale score obtained on medication (Part III) = 27.8 ± 11.6, Hoehn & Yahr stage = 2.0 ± 0.6) and 14 age-matched controls (age = 68.2 ± 10.2 years) using 4 accelerometers attached to the regular shoes of each participant [1][2]. Participants walked in straight lines at their self-selected/usual speed outside a controlled laboratory. Data processing and analyses included the following chronological steps. First, we extracted stride-by-stride left/right heel strike (HS), toe strike (TS), toe-off (TO), maximum heel clearance (MHC), and maximum toe clearance (MTC) timings. Second, using these timings, we computed the mean/coefficient of variation (CV) of durations of (1) left/right stride (Sr), stance (Sa), swing (Sw), and double-support (DS) phases, and (2) left/right HS to TS (HS2TS), TS to TO (TS2TO), TO to MHC (TO2MHC), MTC to HS (MTC2HS) sub-phases [3]. We also calculated symmetry and regularity ratios, and phase/sub-phase durations as percentages of Sr. Results: Compared with controls, PD patients showed significantly decreased mean value of HS2TO and increased variability of several gait phase/sub-phase durations (Table 1). Conclusions: This accelerometer-based algorithm is able to quantify disturbances in gait phase/sub-phase durations during comfortable walking in PD patients. This opens new perspectives for gait analyses in PD patients with/without freezing of gait in their ecological environment.

Figure 1


The authors would like to thank all the participants who accepted to participate as volunteers to the walking tests of the present study.


[1] Boutaayamou M, Schwartz C, Stamatakis J, Denoël V, Maquet D, Forthomme B, Croisier J-L, Macq B, Verly J, Garraux G, and Brüls O, “Development and validation of an accelerometer‒based method for quantifying gait events.” In Medical Engineering and Physics, 37(2), 226–232, 2015. https://doi.org/10.1016/j.medengphy.2015.01.001 http://www.sciencedirect.com/science/article/pii/S135045331500003X [2] Boutaayamou M, Denoël V, Brüls O, Demonceau M, Maquet D, Forthomme B, Croisier J-L, Schwartz C, Verly J, and Garraux G, “Algorithm for temporal gait analysis using wireless foot-mounted accelerometers.” In Biomedical Engineering Systems and Technologies, Communications in Computer and Information Science, 690:236–254, Springer, 2017. https://doi.org/10.1007/978-3-319-54717-6_14 [3] Boutaayamou M, Gillain S, Schwartz C, Denoël V, Petermans J, Croisier J-L, Forthomme B, Verly J, Brüls O, and Garraux G, "Validated assessment of gait sub-phase durations in older adults using an accelerometer-based ambulatory system.” In 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSIGNALS, pp. 248-255, 20-22 January, Madeira, Portugal, 2018. http://www.scitepress.org/Papers/2018/67162/67162.pdf [4] Boutaayamou M, Gillain S, Schwartz C, Brüls O, Denoël V, Petermans J, Forthomme B, Croisier J-L, Verly J, and Garraux G, “Validated extraction of refined temporal gait parameters using foot-worn accelerometers in dual task walking condition of older adults.” In International Conference on Movement (Brain, Body, Cognition), Harvard University’s School of Medicine, Boston Massachusetts, USA, 27-29 July, 2018. http://hdl.handle.net/2268/221150

Keywords: Gait, accelerometer, Signal processing, Algorithms, Heel strike, Toe strike, Toe-off, maximum heel clearance, maximum toe clearance, Parkinson's disease

Conference: Belgian Brain Congress 2018 — Belgian Brain Council, LIEGE, Belgium, 19 Oct - 19 Oct, 2018.

Presentation Type: e-posters


Citation: Boutaayamou M, Depierreux F, Parmentier E, Schwartz C, Brüls O, Verly JG and Garraux G (2019). Quantification of refined temporal gait parameters in Parkinson’s disease using an accelerometer-based ambulatory system. Front. Neurosci. Conference Abstract: Belgian Brain Congress 2018 — Belgian Brain Council. doi: 10.3389/conf.fnins.2018.95.00071

Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.

The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.

Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.

For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.

Received: 29 Aug 2018; Published Online: 17 Jan 2019.

* Correspondence: PhD. Mohamed Boutaayamou, Human Movement Analysis Laboratory, University of Liège, Liège, Belgium, mboutaayamou@uliege.be