CLASSIFICATION OF GAIT ANOMALIES BY USING SPACE-TIME PARAMETERS OBTAINED WITH POSE ESTIMATION

STALIN BENENAULA; MILTON DAMIAN TRELLES; LUIS EDUARDO GARZA-CASTANONLUIS ISMAEL MINCHALA

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CLASSIFICATION OF GAIT ANOMALIES BY USING SPACE-TIME PARAMETERS OBTAINED WITH POSE ESTIMATION

机译：CLASSIFICATION OF GAIT ANOMALIES BY USING SPACE-TIME PARAMETERS OBTAINED WITH POSE ESTIMATION

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Identifying anomalies in people suffering from gait disorders is typically performed by invasive methods, which implies attaching equipment to the human body. For instance, electromyography, as well as the use of body markers, are tools used to evaluate pathological gaits. This work presents a non-invasive system for analyzing and classifying normal, hemiparetic, and paraparetic gaits. To this end, we combine computer vision algorithms and artificial intelligence to generate space-time parameters related to the lower limbs' movement. The proposed methodology consists of capturing RGB images of volunteers that perform several cycles of the normal, hemiparetic, and paraparetic gaits. Pose estimation models process these images, and intelligent classifiers, based on convolution-al neural networks (CNN) and support vector machine (SVM), and process skeleton gait energy image (SGEI) to achieve characterization and classification of gait, respectively. From the three gait patterns, it is obtained of stride length, cadence, stride width, stride time, gait speed, and angles of the body's lower extremities. Experimental results show high efficiency in the gait pattern classification, with efficiencies up to 98.57.

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《International journal of innovative computing, information and control》 |2022年第6期|1913-1927|共15页
作者
STALIN BENENAULA; MILTON DAMIAN TRELLES; LUIS EDUARDO GARZA-CASTANONLUIS ISMAEL MINCHALA;
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Department of Electrical, Electronics and Telecommunications Engineering Universidad de Cuenca Ave. 12 de Abril y Agustin Cueva, Cuenca 010101, Ecuador;

School of Engineering and Sciences Tecnologico de Monterrey Av. Eugenio Garza Sada 2501 Col. Tecnologico C.P. 64700, Monterrey, Nuevo Leon, Mexico;

Department of Electrical, Electronics and Telecommunications Engineering Universidad de Cuenca Ave. 12 de Abril y Agustin Cueva, Cuenca 010101, Ecuador, School of Engineering and Sciences Tecnologico de Monterrey Av. Eugenio Garza Sada 2501 Col. Tecnologi;

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正文语种英语
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Artificial intelligence; Classification; Gait anomalies; Image processing;

CLASSIFICATION OF GAIT ANOMALIES BY USING SPACE-TIME PARAMETERS OBTAINED WITH POSE ESTIMATION

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