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ORIGINAL RESEARCH article

Front. Bioeng. Biotechnol.
Sec. Biosensors and Biomolecular Electronics
Volume 12 - 2024 | doi: 10.3389/fbioe.2024.1449680
This article is part of the Research Topic Technology aided personalized motor rehabilitation for individuals with neurological diseases View all 6 articles

Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system

Provisionally accepted
Serena Cerfoglio Serena Cerfoglio 1Claudia Ferraris Claudia Ferraris 2LUCA VISMARA LUCA VISMARA 3*Gianluca Amprimo Gianluca Amprimo 2Lorenzo Priano Lorenzo Priano 4Matteo Bigoni Matteo Bigoni 3Manuela Galli Manuela Galli 1Alessandro Mauro Alessandro Mauro 3Veronica Cimolin Veronica Cimolin 1
  • 1 Department of Electronics, Information and Bioengineering, Polytechnic University of Milan, Milan, Lombardy, Italy
  • 2 Institute of Electronics, Computer and Telecommunication Engineering, Department of Engineering, ICT and Technology for Energy and Transport, National Research Council (CNR), Turin, Piedmont, Italy
  • 3 Division of Neurology and Neurorehabilitation, Italian Auxological Institute (IRCCS), Piancavallo, Italy
  • 4 Department of Neuroscience, School of Medicine, University of Turin, Turin, Piedmont, Italy

The final, formatted version of the article will be published soon.

    Walking ability is essential for maintaining functional independence, but it can be impaired by conditions like hemiplegia resulting from a stroke event. In post-stroke populations, accurately assessing gait anomalies is crucial for rehabilitation to promote functional recovery, and to prevent falls or injuries. The aim of this study is to evaluate gait-related parameters using a solution based on a single RGB-D camera, specifically Microsoft Azure Kinect DK (MAK), on a short walkway in both healthy (n= 27) and post-stroke individuals with hemiplegia (n= 20). The spatio-temporal and center of mass (CoM) parameters estimated by this approach were compared with those obtained from a gold standard motion capture (MoCap) system for instrumented 3D gait analysis. The overall findings demonstrated high levels of accuracy (> 93%), and strong correlations (r > 0.9) between the parameters estimated by the two systems for both healthy and hemiplegic gait. In particular, some spatio-temporal parameters showed excellent agreement in both groups, while CoM displacements exhibited slightly lower correlation values in healthy individuals. This suggests that a solution based on a single optical sensor could serve as an effective intermediate tool for gait analysis, not only in clinical settings or controlled environments but also in those contexts where gold standard systems are not feasible.

    Keywords: RGB-D sensors, gait analysis, Hemiplegia, Markerless motion analysis, hemiplegic individuals

    Received: 15 Jun 2024; Accepted: 13 Nov 2024.

    Copyright: © 2024 Cerfoglio, Ferraris, VISMARA, Amprimo, Priano, Bigoni, Galli, Mauro and Cimolin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: LUCA VISMARA, Division of Neurology and Neurorehabilitation, Italian Auxological Institute (IRCCS), Piancavallo, 28824, Italy

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