A Kinematic Information Acquisition Model That Uses Digital Signals from an Inertial and Magnetic Motion Capture System

This paper presents a model that enables the transformation of digital signals generated by an inertial and magnetic motion capture system into kinematic information. First, the operation and data generated by the used inertial and magnetic system are described. Subsequently, the five stages of the...

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Published in:Sensors (Basel, Switzerland) Switzerland), 2022-06, Vol.22 (13), p.4898
Main Authors: Alarcón-Aldana, Andrea Catherine, Callejas-Cuervo, Mauro, Bastos-Filho, Teodiano, Bó, Antônio Padilha Lanari
Format: Article
Language:English
Subjects:
articular amplitude
Biomechanical Phenomena
Biomechanics
Data processing
Elbow Joint
Forearm
inertial magnetic sensors
Kinematics
Magnetic Phenomena
Methods
Motion capture
Pronation
Range of Motion, Articular
Rehabilitation
Sensors
Signal processing
Supination
upper limb
Virtual environments
Virtual worlds
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cited_by cdi_FETCH-LOGICAL-c508t-d5aac5f4bd9c1c4b79e345881e4927e8470ed4f338393920b03d14c1031847d13
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container_issue 13
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container_title Sensors (Basel, Switzerland)
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creator Alarcón-Aldana, Andrea Catherine
Callejas-Cuervo, Mauro
Bastos-Filho, Teodiano
Bó, Antônio Padilha Lanari
description This paper presents a model that enables the transformation of digital signals generated by an inertial and magnetic motion capture system into kinematic information. First, the operation and data generated by the used inertial and magnetic system are described. Subsequently, the five stages of the proposed model are described, concluding with its implementation in a virtual environment to display the kinematic information. Finally, the applied tests are presented to evaluate the performance of the model through the execution of four exercises on the upper limb: flexion and extension of the elbow, and pronation and supination of the forearm. The results show a mean squared error of 3.82° in elbow flexion-extension movements and 3.46° in forearm pronation-supination movements. The results were obtained by comparing the inertial and magnetic system versus an optical motion capture system, allowing for the identification of the usability and functionality of the proposed model.
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subjects articular amplitude
Biomechanical Phenomena
Biomechanics
Data processing
Elbow Joint
Forearm
inertial magnetic sensors
Kinematics
Magnetic Phenomena
Methods
Motion capture
Pronation
Range of Motion, Articular
Rehabilitation
Sensors
Signal processing
Supination
upper limb
Virtual environments
Virtual worlds
title A Kinematic Information Acquisition Model That Uses Digital Signals from an Inertial and Magnetic Motion Capture System
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