Neurasense / (Record no. 603364)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02203nam a22001817a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | 0 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621.382,FAR |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Farid, Syed Hammad |
| 245 ## - TITLE STATEMENT | |
| Title | Neurasense / |
| Statement of responsibility, etc. | Syed Hammad Farid, Abdul Muhaymin, Muhammad Usman Tariq, Zain Ul Abdeen Abbasi. (TCC-31 / BETE-56) |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | MCS, NUST |
| Name of producer, publisher, distributor, manufacturer | Rawalpindi 2023 |
| Date of production, publication, distribution, manufacture, or copyright notice | Rawalpindi 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 51 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | The 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | UG EE Project |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) | |
| Topical term or geographic name as entry element | TCC-31 / BETE-56 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervisor Imran Javaid |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Thesis |
| Withdrawn status | Permanent Location | Current Location | Shelving location | Date acquired | Full call number | Barcode | Koha item type |
|---|---|---|---|---|---|---|---|
| Military College of Signals (MCS) | Military College of Signals (MCS) | Thesis | 10/07/2023 | 621.382,FAR | MCSPTC-448 | Project Report |