Name: Gait event detection based on EMG signals (en Inglés)
SKU: 57704685
Price: 55.56 USD
Availability: InStock
Author: Nazmi, Nurhazimah ; Abdul Rahman, Mohd Azizi
ISBN: 9786202920940

portada Gait event detection based on EMG signals (en Inglés)

Gait event detection based on EMG signals (en Inglés)

Formato

Libro Físico

Autor

Mohd Azizi Abdul Rahman

Nurhazimah Nazmi

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

22.9x15.2x0.4 cm

Peso

0.10 kg.

ISBN13

9786202920940

Categorías

Ingeniería electrónica

Gait event detection based on EMG signals (en Inglés)

Mohd Azizi Abdul Rahman (Autor) · Nurhazimah Nazmi (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Gait event detection based on EMG signals (en Inglés)"

Exposure to physical therapy in rehabilitation shows a major interest in recent years for foot drop prevention by using ankle foot devices (AFO). In classifying the stance and swing phases, electromyography (EMG) signals were used to assist in utilising the AFO. Even though this approach has successfully controlled the actuator, classification model of EMG signals during stance and swing phases have not yet been discovered. Thus, a model to classify the stance and swing phases of EMG signals was proposed in this study. A model was developed by extracting the features using time domain (TD) and feeding it into artificial neural network (ANN) classifier. It was observed that Levenberg-Marquardt training algorithm of ANN with five TD features performed better than other features with an average percentage of classification accuracy of 87.4%. The outcome of this study could enhance the development of AFO and implementations in real time application were suggested for future applications.