Correlative Postural Gait Descriptor to Discriminate Parkinsonian Findings in a Markerless Analysis

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dc.creatorPortilla, Jean
dc.creatorRangel Pieschacon, Edgar
dc.creatorBacca, Odair
dc.creatorRamírez, Paula C.
dc.creatorGuayacán, Luis
dc.creatorMartínez Carrillo, Fabio
dc.date2026-02-12
dc.descriptionParkinson's disease (PD) is one of the most prevalent neurodegenerative disorders worldwide, with over 10 million cases reported globally. Currently, gait analysis is crucial for quantifying motor abnormalities, and most methods rely on physical markers, which alter patients' natural movements and have limitations in explaining spatiotemporal relationships of the joints. This study aimed to implement a markerless methodology that reconstructs gait postures and encodes spatiotemporal joint information as covariance descriptors, which are then used to discriminate between subjects with Parkinson's disease and healthy controls. The methodology consisted of a study of covariance encoding of postures and joint trajectories to identify potential coordination patterns that aid in PD classification. The results obtained in a population of 30 subjects, recorded in a total of 240 videos, approved by the Scientific Research Ethics Committee of Universidad Industrial de Santander (CEINCI), showed an average PD classification accuracy of 75% and an AUC of 74%. In conclusion, the correlation descriptors demonstrated the potential to discriminate between subjects with PD and healthy controls and to encode coordination patterns. Furthermore, the visual correlation maps show differences between the two groups, which can further support routine clinical analysis.en-US
dc.descriptionLa enfermedad de Parkinson (EP) es uno de los trastornos neurodegenerativos más prevalentes en todo el mundo, con más de 10 millones de casos reportados a nivel mundial. Hoy en día, el análisis de la marcha es crucial para cuantificar anomalías motoras y en gran parte se basan en marcadores físicos, alterando los gestos naturales de los pacientes, con limitaciones para explicar las relaciones articulares espaciotemporales. Este trabajo tuvo como objetivo implementar una metodología sin marcadores físicos que recupera posturas de locomoción de la marcha y codificar información articular espaciotemporal como descriptores de covarianza, que se utilizan además para obtener discriminación entre sujetos con Parkinson y sujetos de control. La metodología empleada consistió en un estudio de codificación de covarianzas de posturas y trayectorias articulares para explicar posibles patrones de coordinación que benefician la clasificación de la EP. Los resultados obtenidos en una población de 30 sujetos, grabados en un total de 240 videos, avalado por el comité de ética en investigación científica de la Universidad Industrial de Santander (CEINCI), el enfoque propuesto fueron una clasificación de precisión de EP promedio del 75 % y un AUC del 74 %. Finalmente se concluye que los descriptores correlativos evidenciaron la capacidad potencial de discriminar sujetos con EP y codificar patrones de coordinación. Además, los mapas correlativos visuales muestran diferencias entre poblaciones, lo que puede respaldar aún más el análisis de rutina clínica.es-ES
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dc.identifierhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/3432
dc.identifier10.22430/22565337.3432
dc.languageeng
dc.publisherInstituto Tecnológico Metropolitano (ITM)en-US
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/3432/3941
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/3432/4103
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dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/3432/4118
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dc.rightsCopyright (c) 2026 TecnoLógicasen-US
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0en-US
dc.sourceTecnoLógicas; Vol. 29 No. 65 (2026); e3432en-US
dc.sourceTecnoLógicas; Vol. 29 Núm. 65 (2026); e3432es-ES
dc.source2256-5337
dc.source0123-7799
dc.subjectmatrices de correlaciónes-ES
dc.subjectmatrices de covarianzaes-ES
dc.subjectanálisis de la marchaes-ES
dc.subjectcaptura de movimientoes-ES
dc.subjectenfermedad de Parkinsones-ES
dc.subjectcorrelation matricesen-US
dc.subjectcovariance matricesen-US
dc.subjectgait analysisen-US
dc.subjectmotion captureen-US
dc.subjectParkinson diseaseen-US
dc.titleCorrelative Postural Gait Descriptor to Discriminate Parkinsonian Findings in a Markerless Analysisen-US
dc.titleAnálisis de patrones parkinsonianos de la marcha usando descriptores correlativos a partir de mecanismos sin marcadoreses-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeResearch Papersen-US
dc.typeArtículos de investigaciónes-ES

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