Evaluation of an Open Access Markerless Motion Capture System During Gait Analysis

Alejandro Zavala; Paula A. Bejarano Mendoza; Juan Alberto Castillo Martinez; Luis A. Clementi; Ariel A. A. Braidot

doi:10.1007/978-3-031-61960-1_39

Evaluation of an Open Access Markerless Motion Capture System During Gait Analysis

Título traducido de la contribución: Evaluación de un sistema de captura de movimiento sin marcadores de acceso abierto durante el análisis de la marcha

Alejandro Zavala
, Paula A. Bejarano Mendoza
, Juan Alberto Castillo Martinez
, Luis A. Clementi
, Ariel A. A. Braidot

Producción científica: Redes de conocimiento › Actas de congreso › revisión exhaustiva

Resumen

En este estudio, se evaluaron los datos de los marcadores virtuales de la plataforma de captura de movimiento de acceso abierto OpenCap para registrar el movimiento de la marcha humana simultáneamente con un sistema de captura basado en marcadores, considerado el patrón oro. Se grabó a cuatro voluntarios, y la información cinemática de ambos sistemas se sincronizó y procesó para obtener ángulos articulares de la cadera, la rodilla y el tobillo. Los resultados mostraron una alta correlación entre los sistemas en los planos sagital y frontal, lo que sugiere una similitud en el registro del movimiento, con unas diferencias medias medias para todos los voluntarios de 5° para la cadera y 7° para la rodilla en el plano sagital, y de 3° para la cadera y 7° para la rodilla en el plano frontal. El reto más significativo de este nuevo sistema (OpenCap) es su incapacidad para estimar la rotación axial de los segmentos, por lo que no permite una evaluación fiable de la cinemática articular en el plano transversal. Los sistemas de captura de movimiento de acceso abierto son herramientas prometedoras, aunque todavía es necesario minimizar las diferencias entre los sistemas sin marcadores y los basados en marcadores. Se espera que la evolución de las aplicaciones de aprendizaje profundo en biomecánica e información cinemática, con una gran cantidad de datos, mejore la estimación de la pose y facilite el uso de sistemas de registro cinemático sin marcadores.

Título traducido de la contribución	Evaluación de un sistema de captura de movimiento sin marcadores de acceso abierto durante el análisis de la marcha
Idioma original	Inglés estadounidense
Páginas	413–427
Número de páginas	15
DOI	https://doi.org/10.1007/978-3-031-61960-1_39
Estado	Publicada - ene 1 2024

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

Áreas temáticas de ASJC Scopus

Ingeniería biomédica

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10.1007/978-3-031-61960-1_39

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title = "Evaluation of an Open Access Markerless Motion Capture System During Gait Analysis",

abstract = "In this study, data from virtual markers of the open-access motion capture platform OpenCap were evaluated to record human gait motion simultaneously with a marker-based capture system, considered the gold standard. Four volunteers were recorded, and the kinematic information from both systems was synchronized and processed to obtain joint angles of the hip, knee, and ankle. The results showed a high correlation between the systems in the sagittal and frontal planes, suggesting similarity in motion recording, with an average mean differences for all volunteers of 5° for the hip and 7° for the knee in the sagittal plane, and 3° for the hip and 7° for the knee in the frontal plane. The most significant challenge of this new system (OpenCap) is its inability to estimate the axial rotation of the segments, thus not allowing a reliable assessment of joint kinematics in the transverse plane. Open-access motion capture systems are promising tools, although it is still necessary to minimize differences between markerless and marker-based systems. The evolution of deep learning applications in biomechanics and kinematic information, with a large amount of data, is expected to improve pose estimation and facilitate the use of markerless kinematic recording systems.",

author = "Alejandro Zavala and \{Bejarano Mendoza\}, \{Paula A.\} and \{Castillo Martinez\}, \{Juan Alberto\} and Clementi, \{Luis A.\} and Braidot, \{Ariel A. A.\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.",

year = "2024",

month = jan,

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doi = "10.1007/978-3-031-61960-1\_39",

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AU - Zavala, Alejandro

AU - Bejarano Mendoza, Paula A.

AU - Castillo Martinez, Juan Alberto

AU - Clementi, Luis A.

AU - Braidot, Ariel A. A.

PY - 2024/1/1

Y1 - 2024/1/1

N2 - In this study, data from virtual markers of the open-access motion capture platform OpenCap were evaluated to record human gait motion simultaneously with a marker-based capture system, considered the gold standard. Four volunteers were recorded, and the kinematic information from both systems was synchronized and processed to obtain joint angles of the hip, knee, and ankle. The results showed a high correlation between the systems in the sagittal and frontal planes, suggesting similarity in motion recording, with an average mean differences for all volunteers of 5° for the hip and 7° for the knee in the sagittal plane, and 3° for the hip and 7° for the knee in the frontal plane. The most significant challenge of this new system (OpenCap) is its inability to estimate the axial rotation of the segments, thus not allowing a reliable assessment of joint kinematics in the transverse plane. Open-access motion capture systems are promising tools, although it is still necessary to minimize differences between markerless and marker-based systems. The evolution of deep learning applications in biomechanics and kinematic information, with a large amount of data, is expected to improve pose estimation and facilitate the use of markerless kinematic recording systems.

AB - In this study, data from virtual markers of the open-access motion capture platform OpenCap were evaluated to record human gait motion simultaneously with a marker-based capture system, considered the gold standard. Four volunteers were recorded, and the kinematic information from both systems was synchronized and processed to obtain joint angles of the hip, knee, and ankle. The results showed a high correlation between the systems in the sagittal and frontal planes, suggesting similarity in motion recording, with an average mean differences for all volunteers of 5° for the hip and 7° for the knee in the sagittal plane, and 3° for the hip and 7° for the knee in the frontal plane. The most significant challenge of this new system (OpenCap) is its inability to estimate the axial rotation of the segments, thus not allowing a reliable assessment of joint kinematics in the transverse plane. Open-access motion capture systems are promising tools, although it is still necessary to minimize differences between markerless and marker-based systems. The evolution of deep learning applications in biomechanics and kinematic information, with a large amount of data, is expected to improve pose estimation and facilitate the use of markerless kinematic recording systems.

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DO - 10.1007/978-3-031-61960-1_39

M3 - Conference proceedings

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EP - 427

ER -

Evaluation of an Open Access Markerless Motion Capture System During Gait Analysis

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