Sistema de monitoreo muscular basado en EMG con retroalimentación multisensorial e integración a plataforma web para terapias de rehabilitación remota en tiempo real.
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Date
2025
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Publisher
Universidad de Concepción
Abstract
Este proyecto tiene como objetivo desarrollar un sistema portátil de monitoreo muscular, con retroalimentación multisensorial y una plataforma web de supervisión remota, orientado a facilitar terapias de rehabilitación a distancia para personas con movilidad reducida o limitaciones que dificulten su acceso a centros de ejercitación con especialistas. El sistema desarrollado integra un sensor de electromiografía (EMG), complementado con un acelerómetro. Las señales obtenidas son sometidas a un proceso de filtrado digital, utilizando técnicas como el filtro de Media Móvil Exponencial (EMA) y el filtro Notch, con el fin de mejorar la calidad de las señales registradas. Posteriormente, los datos procesados son transmitidos de manera inalámbrica a través de conexión Wi-Fi hacia una plataforma web, la cual permite a profesionales de la salud configurar rutinas de ejercicio personalizadas según los requerimientos de cada paciente, y visualizar la realización de ejercicios de fuerza y movimiento en tiempo real. Una característica distintiva del sistema es la retroalimentación multisensorial háptica, visual y auditiva, diseñada para guiar al paciente durante la realización de los ejercicios y prevenir lesiones derivadas de sobreesfuerzo muscular. Como resultado, se logró desarrollar un sistema funcional, con un diseño compacto y ligero, con dimensiones de 79 x 49 x 26 mm y un peso de 437 gramos. El análisis energético estimó una autonomía de aproximadamente 3 horas bajo condiciones de ejercicio controladas, lo que resulta suficiente para realizar múltiples sesiones de ejercicio por cada carga de la batería. En cuanto al procesamiento de señales, se comprobó la efectividad del filtro EMA con un factor α = 0.5, logrando un suavizado adecuado de la señal EMG rectificada sin perdida significativa de información. El presente trabajo constituye las bases de un sistema con potencial para aplicaciones reales, siendo el siguiente paso su validación clínica.
This project aims to develop a portable muscle monitoring system with multisensory feedback and a remote supervision web platform, intended to facilitate distance rehabilitation therapies for people with reduced mobility or limitations that hinder their access to specialized exercise centers. The developed system integrates an electromyography (EMG) sensor, complemented by an accelerometer. The acquired signals undergo a digital filtering process using techniques such as an Exponential Moving Average (EMA) filter and a Notch filter to improve the quality of the recorded signals. Subsequently, the processed data is transmitted wirelessly via a Wi-Fi connection to a web platform. This platform allows healthcare professionals to configure personalized exercise routines according to each patient's requirements and visualize the execution of strength and movement exercises in real time. A distinctive feature of the system is its haptic, visual, and auditory multisensory feedback, designed to guide the patient during exercise execution and prevent injuries derived from muscle overexertion. As a result, a functional system was successfully developed, featuring a compact and lightweight design with dimensions of 79 x 49 x 26 mm and a weight of 437 grams. The energy analysis estimated an autonomy of approximately 3 hours under controlled exercise conditions, which is sufficient to conduct multiple exercise sessions on a single battery charge. Regarding signal processing, the effectiveness of the EMA filter with a smoothing factor of α = 0.5 was verified, achieving adequate smoothing of the rectified EMG signal without significant loss of information. This work establishes the foundation for a system with potential for real-world applications, with the next step being its clinical validation.
This project aims to develop a portable muscle monitoring system with multisensory feedback and a remote supervision web platform, intended to facilitate distance rehabilitation therapies for people with reduced mobility or limitations that hinder their access to specialized exercise centers. The developed system integrates an electromyography (EMG) sensor, complemented by an accelerometer. The acquired signals undergo a digital filtering process using techniques such as an Exponential Moving Average (EMA) filter and a Notch filter to improve the quality of the recorded signals. Subsequently, the processed data is transmitted wirelessly via a Wi-Fi connection to a web platform. This platform allows healthcare professionals to configure personalized exercise routines according to each patient's requirements and visualize the execution of strength and movement exercises in real time. A distinctive feature of the system is its haptic, visual, and auditory multisensory feedback, designed to guide the patient during exercise execution and prevent injuries derived from muscle overexertion. As a result, a functional system was successfully developed, featuring a compact and lightweight design with dimensions of 79 x 49 x 26 mm and a weight of 437 grams. The energy analysis estimated an autonomy of approximately 3 hours under controlled exercise conditions, which is sufficient to conduct multiple exercise sessions on a single battery charge. Regarding signal processing, the effectiveness of the EMA filter with a smoothing factor of α = 0.5 was verified, achieving adequate smoothing of the rectified EMG signal without significant loss of information. This work establishes the foundation for a system with potential for real-world applications, with the next step being its clinical validation.
Description
Tesis presentada para optar al título de Ingeniero/a Civil Biomédico/a.
Keywords
Electromiografía, Músculos, Monitoreo fisiológico, Rehabilitación, Personas con discapacidad