Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system
IntroductionWalking 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 p...
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2024.1449680/full |
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| author | Serena Cerfoglio Serena Cerfoglio Claudia Ferraris Luca Vismara Gianluca Amprimo Gianluca Amprimo Lorenzo Priano Lorenzo Priano Matteo Bigoni Manuela Galli Alessandro Mauro Alessandro Mauro Veronica Cimolin Veronica Cimolin |
| author_facet | Serena Cerfoglio Serena Cerfoglio Claudia Ferraris Luca Vismara Gianluca Amprimo Gianluca Amprimo Lorenzo Priano Lorenzo Priano Matteo Bigoni Manuela Galli Alessandro Mauro Alessandro Mauro Veronica Cimolin Veronica Cimolin |
| author_sort | Serena Cerfoglio |
| collection | DOAJ |
| description | IntroductionWalking 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.MethodsThe 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.ResultsThe 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.DiscussionThe results of the study suggest 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. |
| format | Article |
| id | doaj-art-8514e0064d14408fbe8638e7b959478a |
| institution | Kabale University |
| issn | 2296-4185 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj-art-8514e0064d14408fbe8638e7b959478a2024-11-25T04:27:23ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852024-11-011210.3389/fbioe.2024.14496801449680Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic systemSerena Cerfoglio0Serena Cerfoglio1Claudia Ferraris2Luca Vismara3Gianluca Amprimo4Gianluca Amprimo5Lorenzo Priano6Lorenzo Priano7Matteo Bigoni8Manuela Galli9Alessandro Mauro10Alessandro Mauro11Veronica Cimolin12Veronica Cimolin13Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDivision of Neurology and Neurorehabilitation - IRCCS Istituto Auxologico Italiano, Verbania, ItalyInstitute of Electronics, Computer and Telecommunication Engineering (IEIIT), Consiglio Nazionale delle Ricerche (CNR), Turin, ItalyDivision of Neurology and Neurorehabilitation - IRCCS Istituto Auxologico Italiano, Verbania, ItalyInstitute of Electronics, Computer and Telecommunication Engineering (IEIIT), Consiglio Nazionale delle Ricerche (CNR), Turin, ItalyDepartment of Control and Computer Engineering, Politecnico di Torino, Turin, ItalyDivision of Neurology and Neurorehabilitation - IRCCS Istituto Auxologico Italiano, Verbania, ItalyDepartment of Neurosciences, University of Turin, Turin, ItalyDivision of Neurology and Neurorehabilitation - IRCCS Istituto Auxologico Italiano, Verbania, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDivision of Neurology and Neurorehabilitation - IRCCS Istituto Auxologico Italiano, Verbania, ItalyDepartment of Neurosciences, University of Turin, Turin, ItalyDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, ItalyDivision of Neurology and Neurorehabilitation - IRCCS Istituto Auxologico Italiano, Verbania, ItalyIntroductionWalking 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.MethodsThe 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.ResultsThe 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.DiscussionThe results of the study suggest 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.https://www.frontiersin.org/articles/10.3389/fbioe.2024.1449680/fullRGB-D sensorsgait analysishemiplegiamarkerless motion analysishemiplegic individuals |
| spellingShingle | Serena Cerfoglio Serena Cerfoglio Claudia Ferraris Luca Vismara Gianluca Amprimo Gianluca Amprimo Lorenzo Priano Lorenzo Priano Matteo Bigoni Manuela Galli Alessandro Mauro Alessandro Mauro Veronica Cimolin Veronica Cimolin Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system Frontiers in Bioengineering and Biotechnology RGB-D sensors gait analysis hemiplegia markerless motion analysis hemiplegic individuals |
| title | Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system |
| title_full | Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system |
| title_fullStr | Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system |
| title_full_unstemmed | Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system |
| title_short | Estimation of gait parameters in healthy and hemiplegic individuals using Azure Kinect: a comparative study with the optoelectronic system |
| title_sort | estimation of gait parameters in healthy and hemiplegic individuals using azure kinect a comparative study with the optoelectronic system |
| topic | RGB-D sensors gait analysis hemiplegia markerless motion analysis hemiplegic individuals |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2024.1449680/full |
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