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

Mohamed Boutaayamou1, 2*, Frédérique Depierreux3, 4, Eric Parmentier3, 4, Cédric Schwartz1, Olivier Brüls1, Jacques G. Verly2 and Gaëtan Garraux3, 4
  • 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
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Acknowledgements

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

References

[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

Topic: NOVEL STRATEGIES FOR NEUROLOGICAL AND MENTAL DISORDERS: SCIENTIFIC BASIS AND VALUE FOR PATIENT-CENTERED CARE

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

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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