The bionic hand movement using myo sensor and neural networks
One part of human body in which very useful in this life is a hand. This life will be disrupted if one or both of these hands do not work, due to disability or amputation. One of the contributions that help this condition is the bionic hand. This study have developed a bionic hand that consist of six servo motors to drive the fingers movement. Myo sensor is used in this bionic hand, it is located in the forearm. It has been used to record the muscle signals. Feature extraction of the muscle signal was formulated by using root mean square (rms) Kind of the bionic hand movement was found by identifying the movement signal pattern using back propagation through the artificial neural network. The output data obtained from back propagation was processed by microcontroller and transmitted to the servo motors for getting a movement of the bionic hand. Based on experimental data, five kinds of movement were tested in this system, average of recognition for each movement: handful accuracy movement 65% pointing fingers 75% wave in 100% wave out 75% and spread 100% Testing for the whole movements (five kinds) were performed with the average error 17%
2016 International Conference on Knowledge Creation and Intelligent Computing (KCIC)