The University of Sheffield
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Supplementary material for "An algorithm for accurate marker-based gait event detection in healthy and pathological populations during complex motor tasks"

posted on 2022-02-07, 22:05 authored by Tecla BonciTecla Bonci, Francesca Salis, Kirsty Scott, Lisa Alcock, Clemens Becker, Stefano Bertuletti, Ellen BuckleyEllen Buckley, Marco Caruso, Andrea Cereatti, Silvia Del Din, Eran Gazit, Clint HansenClint Hansen, Jeffrey M. Hausdorff, Walter Maetzler, Luca PalmeriniLuca Palmerini, Lynn Rochester, Lars Schwickert, basil sharrack, Ioannis VogiatzisIoannis Vogiatzis, Claudia Mazza

This repository contains supplementary material for "An algorithm for accurate marker-based gait event detection in healthy and pathological populations during complex motor tasks", Bonci T., Salis F., Scott K., Alcock L., Becker C., Bertuletti S., Buckley E., Caruso M., Cereatti A., Del Din S., Gazit E., Hansen C., M Hausdorff J.M., Maetzler W., Palmerini L., Rochester L., Schwickert L., Sharrack B., Vogiatzis I., and Mazzà C., on behalf of the Mobilise-D consortium.

Specifically, this Figshare repository contains:

1. The timing errors in ms for the gait events (initial and final contacts) as detected by the different methods evaluated in the manuscript for the three walking conditions (straight-line walking (SW), curvilinear walking (CW) and step negotiation (SN)) .

2. Matlab script for the detection of gait event using the methodology described in the manuscript. An exemplary dataset that can be used for running the provided script.

3. A READ ME document where the organization of the dataset included with the script is described.

Please consider the READ ME document to understand the structure of the dataset included in this repository.


This work was supported by the Mobilise-D project (IMI2 JU grant agreement No. 820820, this JU receives support from the European Union's Horizon 2020 and EFPIA). This study was also supported by the National Institute for Health Research (NIHR) through the Sheffield Biomedical Research Centre (BRC, grant number IS-BRC-1215-20017) and the UK Engineering and Physical Sciences Research Council (Multisim and MultiSim2 projects, grant numbers EP/K03877X/1 and EP/S032940/1, respectively).



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