Human–Machine Interface for Wheelchair Control Using sEMG Signals

Abstract

AbstractElectromyogram (EMG) signal is the electrical activity that is generated by alpha motor neurons in response to the impulse from the brain. EMG is divided into two types: surface EMG and intramuscular EMG. Surface EMG signals provide information about the intensity of muscle activation. EMG signals are used to make myoelectric control system-powered upper-limb prostheses, and electric-powered wheelchairs are the major applications of the myoelectric control system. Tremendous growth has been seen in human–machine interface (HMI) wheelchairs over the last few decades. The manual wheelchair that can be moved by pushing the wheels with hands is replaced by Joystick and a voice-controlled wheelchair. However, even with the advances in technology elderly and paralyzed people have difficulties in intuitive control and navigation of wheelchairs. Therefore, a smart wheelchair based on surface EMG signals and an accelerometer are proposed. The signals from EMG sensors act as input signals which get processed by Arduino Uno, and the output signal based on detected hand gesture is wirelessly transmitted. Proper training is performed to determine the threshold value for each gesture identification. The RF receiver sends the received signal to Arduino mega to process the signal, and Arduino mega sends a command to motor drive to move the wheelchair. The smart wheelchair is controlled in left, right, forward and backward directions. The ultrasonic sensor is being used in the wheelchair to detect obstacles. The hardware design is properly tested and validated; thereby smart wheelchair is cost-effective, easy to use, and safety is ensured.KeywordsEMGGesture recognitionWheel chair controlRF transmitter and receiverArduino