International Journal of Science, Engineering and TechnologyAuthors: Mr. Yash Bansod, Prof. Ranjana Shende
Abstract: People with disabilities in their mobility are a large population worldwide who have a need for intuitive and reliable assistive technologies. In these settings, the human machine interaction is a very interesting approach through electromyography (emg) signals, which are naturally produced during voluntary muscle movement. This work explains the design of a low-cost robotic mobility vehicle for a muscle signal controlled assistive prototype, which is able to independently process forearm emg signals of both arms. Two muscle bioamp candy sensors record the signal from the user's forearm and then the signal is filtered by a 4th order butterworth band pass filter from 74.5hz to 149.5hz, followed by a moving average envelope detector. Using an arduino uno microcontroller and l298n motor driver, a threshold-based decision layer is used to convert the envelope values into motor direction control. In addition to motion control, the system includes an ultrasonic sensor for detecting obstacles near the driver and two infrared sensors to detect the edges of the surfaces where the driver is standing, to send this information to a safety interlock that can override the motor control system when dangerous conditions are detected. Three subjects were tested, and consistent and reliable directionality was achieved in all intended modes of movement. The integrated safety architecture proved successful for avoiding unwanted motion in the event of an obstacle or edge detection, thus confirming the multi-sensor system approach for low-cost assistive mobility systems.
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