3D Motion Tracking of the Shoulder Joint with Respect to the Thorax Using MARG Sensors and Data Fusion Algorithm

• Autorzy: Barraza Madrigal José Antonio , Cantillo Negrete Jessica , Muñoz Guerrero Roberto , Contreras Rodríguez Lauro Armando , Sossa Humberto

Identyfikatory

DOI

10.1016/j.bbe.2020.04.008

• Języki publikacji: EN

Abstrakty

EN

A method for performing 3D motion tracking of the shoulder joint with respect to the thorax, using MARG sensors and a data fusion algorithm, is proposed. Two tests were done: 1) qualitative and quantitative analysis of the response of the sensors, static position and during motion, with and without the proposed data fusion algorithm; 2) motion tracking of the shoulder joint with the upper arm, the thorax, and the shoulder joint respect to the thorax. Qualitative analysis of experimental results showed that despite slight variations regarding the evaluated motion, these variations did not have repercussions on the estimated orientation. Quantitative analysis showed that the estimated orientation did not exhibit significant variations, in five minutes, such as drift errors (about 0.18 in static position and less than 1.88 during motion), variations due to noise or magnetic disturbances (RMSE less than 0.048 static position and less than 18 during motion); no singularity problems were reported. The main contributions of this research are a multisensor data fusion algorithm, which combines the complementary properties of gyroscopes, accelerometers, and magnetometers in order to estimate the 3D orientation of two body segments separately and with respect to another body segment considering the spatial relationship between them; and a method for performing 3D motion tracking of two body segments, based on the estimation of their orientation, including motion compensation. The proposed method is applicable to monitoring devices based on IMU/MARG sensors; the performance was evaluated using a customized motion analysis system.

Słowa kluczowe

EN

shoulder joint and thorax; 3D motion tracking; orientation estimation; MARG sensor; data fusion algorithm

PL

śledzenie ruchu; ocena orientacji; algorytm fuzji danych

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2020
• Tom: Vol. 40, no. 3
• Strony: 1205--1224
• Opis fizyczny: Bibliogr.51 poz., rys., tab., wykr.

Twórcy

autor

Barraza Madrigal José Antonio

• Instituto Politécnico Nacional, Escuela Superior de Ingeniería Química e Industrias Extractivas, Académia de Física, Mexico City, Mexico

autor

Cantillo Negrete Jessica

• Division of Research in Medical Engineering, Instituto Nacional de Rehabilitación, Calzada Mexico-Xochimilco Num. 289, Arenal de Guadalupe, Tlalpan, Mexico City, Mexico

autor

Muñoz Guerrero Roberto

• Center for Research and Advanced Studies of the National Polytechnic Institute, Electrical Engineering Department/ Bioelectronics Section, Mexico City, Mexico

autor

Contreras Rodríguez Lauro Armando

• Center for Research and Advanced Studies of the National Polytechnic Institute, Electrical Engineering Department/ Bioelectronics Section, Mexico City, Mexico

autor

Sossa Humberto

• Instituto Politécnico Nacional, Centro de Investigación en Computación, Laboratorio de Robótica y Mecatrónica, Mexico City, Mexico; Tecnológico de Monterrey, Unidad Guadalajara, Zapopan, Jalisco, Mexico

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).