Intelligent Wheelchair

EMG (ELECTROMYOGRAPHY) SIGNAL BASED CONTROL OF AN INTELLIGENT WHEELCHAIR It is a wheelchair control by using EMG signals elicited by various hand motions. This is done by collecting surface myoelectric signals from the skin covering muscles, which contain information that can be used to recognise the neuromuscular activity. Surface electrodes are used to collect these signals in a non-invasive manner. A powered wheelchair is used for this purpose along with biometrics equipment and a laptop to interface with the user. The type of classification technique used is the multi-layer perceptron. By experimental investigaion, neural networks was sucessful in classifying different types of hand motions with an accuracy of 90.2%. The EMG data is collected by placing the eletrodes on the forearm muscles. This data is segmented for every 200 milliseconds after which feature extraction is performed using mean absolute value. The signals are fed to the artificial neural networks and are processed to attain parameters that are related to the muscles temporal activities. The resulting commands are sent to drive the wheelchair according to the user's intention. The software was tested on the intelligment wheelchair in real-time. The experimenal results confirmedthat the system is robust to different sex and environment. This method is useful for people with severe physical disabilities especially whose upper limbs are paralysed or suffer from severe spinal cord injury (SCI) or amyotrophic lateral sclerosis, as they require more sophisticated hands-free human-machine interfaces to do their daily activities by themselves.

Category:

Science & Technology

Tags:

• Intelligent Wheelchair
• Robochair
• Robotics
• Robots
• Mobile Robots
• Electromyography
• EMG
• Multi Layer Perceptron
• Spinal Cord Injury (SCI)
• Biometrics Datalink
• Wheelchair user
• Rampriya Mahendran
• sakthirampriya