Voice controlled Smart Electric-Powered wheelchair based on Artificial Neural Network

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Mohammed Hussein Jabardi

Abstract

Electric Powered Wheelchair (EPW) used by people with disabilities, who cannot move or with a limited ability to move. The traditional technique that used to control the powered wheelchair can be a challenging and stressful operation. Therefore, there is a demand to find alternative ways to perform this process. In that, the voice recognition is a natural form of pointing that can use to replace the joystick whilst still allowing for similar control. Neural network one of the effective ways to recognize the speech commands, because of its ability to grant a trainable powered wheelchair controller with a convenient way, ease of use and attractiveness. In this situation, the neural networks are providing a trainable system for each person irrespectively of his disability.
Smart Electric-Powered Wheelchair (SEPW) is an electric-powered wheelchair based on Artificial Neural Networks (ANN) Technique can recognize the voice commands and replace the traditional control of powered wheelchairs with intelligent technology. So, a neural network for the feed-forward Multi-layer perceptron has been trained to recognize isolated spoken words (commands), such as ‘right, ‘left,' ‘stop' and so on. Initially, the design of the system's network started with one hidden layer using five neurons (according to [1] formula). During the training process, the number of hidden neurons has been increased to keep the mean square error (MSE) of the system minimum as possible. Furthermore, the system structure is designed based on a Multi Layers Perceptron (MLP) neural system for five output neurons, which represent the powered wheelchair's commands

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