Wheelchair Control System based on Gyroscope of Wearable Tool for the Disabled

Author:

Jameel Huda Farooq,Mohammed Salim Latif,Gharghan Sadik Kamel

Abstract

Abstract A wheelchair control system based on Gyroscope of wearable tool can serve the disabled, especially in helping them move freely. The recent evolution of new technology means that unassisted, free movement has become possible. For this purpose, human–machine interface hands-free command of an electric-powered wheelchair can be achieved. In this paper, an electroencephalogram instrument, namely the EMOTIV Insight, was implemented in a human–computer interface to acquire the user’s head motion signals. The system can be operated based on the user’s head motions to carry out motion orders and control the motor of the wheelchair. The proposed system consists of an EMOTIV Insight brain-based gyroscope to sense head tilt, a DC motor driver to control wheelchair speed and directions, an eclectic-powered wheelchair, microcontroller, and laptop. We implemented the system in practice and tested it on smooth and rough surfaces in indoor/outdoor settings. The experimental results were greatly encouraging: disabled users were able to drive the wheelchair without any limitations. We obtained a significant average response time of 2 seconds. In addition, the system had accuracy, sensitivity, and specificity of 99%, 99.16%, and 98.83%, respectively.

Publisher

IOP Publishing

Subject

General Medicine

Reference35 articles.

1. Development of EOG based human machine interface control system for motorized wheelchair;Champaty,2014

2. Voice Control Module for Low Cost Local-Map Navigation Based Intelligent Wheelchair;Avutu,2017

3. Hand gesture recognition based omnidirectional wheelchair control using IMU and EMG sensors;Kundu;Journal of Intelligent & Robotic Systems,2018

4. Head movement based control system for quadriplegia patients;Qamar,2017

5. Assessment of the tongue-drive system using a computer, a smartphone, and a powered-wheelchair by people with tetraplegia;Kim;IEEE Transactions on Neural Systems and Rehabilitation Engineering,2015

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Elderly Safety and Communication: An IoT-Based Smart Glove for Fall Detection and Hand Gesture Communication;2024 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE);2024-04-25

2. Hybrid Wheelchair control method with EEG signal and facial Expression;2023 20th International Multi-Conference on Systems, Signals & Devices (SSD);2023-02-20

3. Investigation and development of hand tremor controlling device;THE FOURTH SCIENTIFIC CONFERENCE FOR ELECTRICAL ENGINEERING TECHNIQUES RESEARCH (EETR2022);2023

4. Design and implementation of experimental training board multi-medical sensors for educational purposes;THE FOURTH SCIENTIFIC CONFERENCE FOR ELECTRICAL ENGINEERING TECHNIQUES RESEARCH (EETR2022);2023

5. A review of medical wearables: materials, power sources, sensors, and manufacturing aspects of human wearable technologies;Journal of Medical Engineering & Technology;2022-07-20

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3