000			02203nam a22001817a 4500
003			NUST
040			_a0
082			_a621.382,FAR
100			_aFarid, Syed Hammad _9118410
245			_aNeurasense / _cSyed Hammad Farid, Abdul Muhaymin, Muhammad Usman Tariq, Zain Ul Abdeen Abbasi. (TCC-31 / BETE-56)
264			_aMCS, NUST _bRawalpindi 2023 _cRawalpindi 2023
300			_a51 p
505			_aThe use of assistive technology significantly raises the quality of life for people with impairments. The aim of this project is to develop an EMG-based wheelchair movement system that can assist people with physical disabilities in controlling their wheelchairs using their muscle signals. The proposed system includes surface EMG sensors that detect the electrical signals generated by the user's muscles and a microcontroller that processes and translates these signals into wheelchair commands. The system is designed to be user-friendly, efficient, and reliable, with real-time response and high accuracy. The system's performance is evaluated using various metrics, including accuracy, sensitivity, specificity, and response time. The results show that the proposed EMG-based wheelchair movement system has high accuracy and real-time response and can effectively assist people with physical disabilities in controlling their wheelchairs. EMG sensors will be positioned on the user's target muscles, together with a microcontroller to interpret the signals and a motor controller to drive the wheelchair. This project has been designed for moving a wheelchair by accumulating EMG/EEG signal from a paralyzed/disabled person. The electrode configuration is adjusted to collect muscular electrical activity. Signals are weak in nature hence need to be amplified and then digitalized to perform feature extraction. After collecting the data, the useful feature extraction from it will further send instruction to microcontroller to navigate the wheelchair movement by controlling the wheel motors. Proximity sensors will be used to avoid any collision.
650			_aUG EE Project _9118090
690			_aTCC-31 / BETE-56 _9118237
700			_a Supervisor Imran Javaid _9118411
942			_2ddc _cTHE
999			_c603364 _d603364