Design and Implementation of Wheelchair Controller Based Electroencephalogram Signal using Microcontroller

Wheelchair is a medical device that can help patients, especially for persons with physical disabilities. In this research has designed a wheelchair that can be controlled using brain wave. Mind wave device is used as a sensor to capture brain waves. Fuzzy method is used to process data from mind wave. In the design was used a modified wheelchair (original wheelchair modified with addition dc motor that can be control using microcontroller ). After processing data from mindwave using fuzzy method, then microcontroller ordered dc motor to rotate.The dc motor connected to gear of wheelchair using chain. So when the dc motor rotated the wheelchair rotated as well.  Controlling of DC motor used PID control method. Input encoder was used as feedback for PID control at each wheel.From the experimental results concentration level data of the human brain waves can be used to adjust the rate of speed of the wheelchair. The level accuracy of respons Fuzzy method ton system obtained by devide total true respons data with total tested data and the result is 85.71 %.  Wheelchairs can run at a maximum speed of 31.5 cm/s when the battery voltage is more than 24.05V. Moreover, the maximum load of wheelchair is 110 kg

MULTI-TERRAIN WHEELCHAIR MQP

Many disabled people struggle to traverse outdoor terrain without specialized equipment. To tackle the outdoors, users have to spend money, time, and sacrifice usability by using bulky assistive devices. This project was carried out by a group of four WPI students to design and construct an assistive device for a fellow student who is paralyzed from the waist down. After initial brainstorming and research, the choice was made to create a multi-terrain wheelchair. Using organizational, financial, manufacturing and design methods, the group was able to design and construct a prototype consisting of separate subsystems. This wheelchair design and prototype aims to not only assist disabled persons, but also serve as a basis for future projects to improve upon and help solve the issue

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices

Gyro-Accelerometer based Control of an Intelligent Wheelchair

This paper presents a free-hand interface to control an electric wheelchair using the head gesture for people with severe disabilities i.e. multiple sclerosis, quadriplegic patients and old age people. The patient head acceleration and rotation rate are used to control the intelligent wheelchair. The patient head gesture is detected using accelerometer and gyroscope sensors embedded on a single board MPU6050. The MEMS sensors outputs are combined using Kalman filter as sensor fusion to build a high accurate orientation sensor. The system uses an Arduino mega as microcontroller to perform data processing, sensor fusion and joystick emulation to control the intelligent wheelchair and HC-SR04 ultrasonic sensors to provide safe navigation.The wheelchair can be controlled using two modes. In the first mode, the wheelchair is controlled by the usual joystick. In the second mode, the patient uses his head motion to control the wheelchair. The principal advantage of the proposed approach is that the switching between the two control modes is soft, straightforward and transparent to the user

Power-Assist Wheelchair Attachment

This senior design project sought to combine the best characteristics of manual and power wheelchairs by creating a battery-powered attachment to propel a manual wheelchair. The primary customer needs were determined to be affordability, portability, and travel on uneven surfaces. After the initial prototype, using a hub motor proved unsuccessful, so a second design was developed that consisted of a gear reduction motor and drive wheel connected to the back of the wheelchair by a trailing arm that could be easily attached/detached from the frame. The prototype of the second design succeeded in meeting most of the project goals related to cost, off-road capability, inclines, and range. Improvements can be made by reducing the attachment weight and improving user control of the device

State-of-Science Review: SR-E29, Brain-Computer Interfaces and Cognitive Neural Prostheses

This review looks at recently developed technology that allows engineers to record signals from the brain, identify the subject’s intent, and allow the subject to control prosthetic devices or communicate with others. It explores the current status of the technology, focusing on studies aimed at developing assistive devices for human subjects. Lastly, it reviews the impressive accomplishments to date, as well as limitations of the technology that will need to be overcome to enable the development of fully practical assistive technologies