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Sleeve for Knee Angle Monitoring: An IMU-POF Sensor Fusion System

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Vargas Valencia, Laura Susana
Schneider, Felipe B. A.
Leal Junior, Arnaldo G.
Caicedo Rodríguez, Pablo
Sierra Arévalo, Wilson A.
Rodríguez Cheu, Luis E.
Bastos Filho, Teodiano
Frizera Neto, Anselmo
Abstract (Spanish)
El ángulo de flexión-extensión de la rodilla es una variable importante que debe ser monitoreada en diversos escenarios clínicos, por ejemplo, durante la evaluación de rehabilitación física. El propósito de este trabajo es desarrollar y validar un sensor sistema de fusión basado en una rodillera para el seguimiento de fisioterapia. El sistema consiste en fusionar datos de dos unidades de medición inercial (IMU) y una curvatura de fibra óptica de polímero (POF) basada en variación de intensidad sensor que utiliza un multiplicativo extendido basado en cuaterniones Filtro Kalman (MEKF). El método de fusión de datos propuesto. No tiene magnetómetro y aborda las incertidumbres de los sensores mediante intervalos de confiabilidad definidos durante la marcha. Doce participantes sanos realizaron pruebas de caminata utilizando nuestro sistema de rodillera y los resultados fueron validados frente a un sistema de captura de movimiento estándar de oro. Además, se realiza una comparación con otros tres cálculos del ángulo de la rodilla. métodos, que se basan exclusivamente en IMU, se llevó a cabo afuera. El sistema propuesto presentó mejor desempeño (media RMSE < 3,3◦, coeficientes LFM, a1 = 0,99 ± 0,04, a0 = 0,70 ± 2,29, R2 = 0,98 ± 0,01 y ρC > 0,99) en comparación con los demás métodos evaluados. Resultados experimentales demostrar la usabilidad y viabilidad de nuestro sistema para estimar el movimiento de la rodilla con alta precisión, repetibilidad y reproducibilidad. Este sistema portátil puede ser adecuado para Evaluación del movimiento en laboratorios de rehabilitación en futuros estudios.
Abstract (English)
—The knee flexion-extension angle is an important variable to be monitored in various clinical scenarios, for example, during physical rehabilitation assessment. The purpose of this work is to develop and validate a sensor fusion system based on a knee sleeve for monitoring of physical therapy. The system consists of merging data from two inertial measurement units (IMUs) and an intensityvariation based Polymer Optical Fiber (POF) curvature sensor using a quaternion-based Multiplicative Extended Kalman Filter (MEKF). The proposed data fusion method is magnetometer-free and deals with sensors’ uncertainties through reliability intervals defined during gait. Walking trials were performed by twelve healthy participants using our knee sleeve system and results were validated against a gold standard motion capture system. Additionally, a comparison with other three knee angle estimation methods, which are exclusively based on IMUs, was carried out. The proposed system presented better performance (mean RMSE < 3.3◦, LFM coefficients, a1 = 0.99 ± 0.04, a0 = 0.70 ± 2.29, R2 = 0.98 ± 0.01 and ρC > 0.99) when compared to the other evaluated methods. Experimental results demonstrate the usability and feasibility of our system to estimate knee motion with high accuracy, repeatability, and reproducibility. This wearable system may be suitable for motion assessment in rehabilitation labs in future studies.
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10 páginas
URI: https://repositorio.escuelaing.edu.co/handle/001/3255
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