Description:Field of Invention
The present invention pertains to controlling thrust in neurotechnology by brain signal in the wheel chair for healthcare system development.
Background of the Invention
The different technological developments and innovation in various scientific domains originates the background for the development of such creative idea of wheelchair control using brain signal. It has been stock from very long of research in neuropsychology/neuroscience especially in reaching out to the brain signals and their different application in machine-human connectivity. Development in various neuroimaging approaches, like functional magnetic resonance (fMRI), electroencephalography (EEG), advance X-ray imaging, have develops and provided perceptions into exploring brain movement and its activity.At the same time, developments in assistive and robotics technology have provided the proper path in the development of leading-edge technology mobility devices, and wheelchair is one of them. Engineers and many researchers have been digging ways to connect such innovative technologies to provide more responsive and intuitive systems for personalized caring who is having serious physical disabilities or some physical issues by birth.The invention also gains attention and inspiration for the growing demand of the market for proper solution to physical challenge people and with different disabilities. Focusing on improving independence and quality of lifestyle, the wheelchair with brain control innovation objective is to address the personal challenges and need faced by different uses with confined mobility, ultimately give rise them to explore their environments with higher dignity and freedom. Using only the capability of motor it is quite difficult to make a control over wheelchair using standard control device. The main objective is to focus and to make sure that the user can process as intended. Optimal concentration model performance analysis is important so, that every user can control the entire movement of wheelchair easily. The analysis conducted for the visible mode as well as invisible mode and EEG signal has been utilized using average features and signal peak with FFT and follow the attention sensing channel [R. Tomar, R. R. Abu Hassan et. al., Analysis of optimal Brainware concentration model for wheelchair input interface, IEEE Int. symp. on robotics and intelligent sensor, 99. 336-341, 2015]. Headset using BCI (brain-computer interfaced) used to control the wheelchair with electric setup. This complete setup in form of wheelchair will help the disabled people who cannot have any movement in his/her leg or hands and have an issue of cerebromedullospinal. Facial expression is used to map and the movement/motion of the wheelchair. Movement around the face muscle can be closely observed using EEG signal which is attached with the motion of wheelchair. Preprocessing of signal was done to minimize the artefacts and all the feature are taken out using FFT and this will help to achieve an accuracy of 97.6% [F Ansari, S Dodia et. al., Brain computer interface for wheelchair control operations: An approach based on FFT and on-line sequential extreme learning machine, Clinical Epidemiology and Global Health, pp. 274-278, Elsevier, 2019]. Human brainwave integrated wheelchair was designed to provide support to a disabled people. The main aim of this invention is to improve the overall performance of wheelchair using BCI system relies on the personalized brain attention. Mind wave has been deployed to gather the attention utility to the movement of wheelchair. Movement of eyeblink change the movement of wheelchair in backward, forward, right, and left. Stop function was achieved using the movement of eyebrow. This complete system was designed to help and support paralyzed person using integrated brainwave and attention value [N. Sahat, A. Alias et. al. Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient, Bulletin of Electrical and informatics, Vol. 10, pp. 3022-3041, 2021].
Description of Prior Art
Prior art in the field of brain-controlled wheelchairs includes various approaches and technologies aimed at improving mobility and independence for individuals with severe physical disabilities. CN108646726A reveals the control of wheelchair and the method with the integration of voice relies on brainwave. Brainwave accession being done by filtering process, further converted to control signal to control the action and moment of wheelchair using feature extraction and some modulation approach. To control the overall wheelchair system it requires voice module, travelling motors, processor module, obstacle identification module, road map module etc. And to detect the brainwave it requires machine control gadgets and brainwave acquisition. Terminal gadgets consist of server and mobile phones to establish a communication. The invention activates user wheelchair which passes through brainwave then to the voice module for controlling wheelchair action so, that wheelchair user can be identified and converted it into voice messages. Road condition and barrier identification are processed by wheelchair functioning which is reported, to improve the intelligence, reliability, control, and safety.
US0095383 reveals the control of wheelchair following intelligent approach based on self-driving and BCI technology. The complete method follow the different steps to achieve the control which includes: gathering present/current images using webcams to perform obstacles identification, acquiring participants destination and locations for path strategy as per the current obstacle observations, performing automatic localization of wheelchair, choosing a destination by a participant using BCI, follow the strategy as per current location of wheelchair from initial point and the destination is chosen by the user at last point in integration with the waypoints and updated position of wheelchair with optimal path is now feedback to the PID tracking algorithm, evaluating a linear velocity and angular velocity using this algorithm. Generated signal now sent to the PID controller which convert this odometry data using encoders into linear and angular velocities as feedback for motion control and control the driving of chair to the destination in real-time. The intelligent system greatly helps and relives the mental pressure of a user and may adapt as per variations in the environment and betters the self-care ability of user for long-run. Overall, prior art in the field of brain-controlled wheelchairs encompasses a range of approaches and technologies, each with its own advantages and limitations. Continued research and development in this area aim to further refine these systems and make them more accessible and effective for users with severe physical disabilities.
202041050519 A discloses the operation of manually operated wheelchair for the amputated and paralyzed person movement which can be able to overcome the drawbacks while moving from one bed to another. Here, the proposed system did not able to solve the complete needs as its movement is possible in horizontal direction only. However, wheelchair can be utilized as a stretcher if required and this wheelchair relies on a self-support system that make it different from the others. Trackers and sliders are used for its complete movement and some screw jack is inserted to increase or decrease the height of wheelchair.
EP3884917B1 discloses the limitation of wheelchair in term of size and comfort which can be able to overcome the previous drawbacks. Wheelchair with folded feature that consist of foot step, drive wheels, seat and backrest make it unique from the others. Here, drive wheels are combined with the set frame from both side, which are adjusted for physical movement of the wheelchair. Transport handle are attached with the wheel for its movement in all directions and can be used for detachable mounting of the wheel.
Summary of the invention
In the light of the above mention drawback in the prior art, the invention of wheelchair using brain-control mechanism represents a development in convenient technology, aiming to magnify independence and mobility for individualized caring with serious physical impairment.
The specific objective of the invention is to design a wheelchair by feature of cutting-edge technologies i.e., brain-computer interface, activating users to make a control over wheelchair using brain signals. Through non-intrusive approaches like invasive techniques or EEG, implanted electrodes, through which user can navigate their surroundings with ease and higher precision. This invention addresses the specific challenges and needs of users with restricted mobility, permitting them to have a close interact with their surrounds and lead more independent lives.
Brief description of Drawings
The invention will be described in detail with reference to the exemplary embodiments shown in the figures wherein:
Figure 1. Frontal view of brain-controlled wheelchair
Figure 2. Back side view of brain-controlled wheelchair
Detailed description of the invention
The idea is based on a brain-controlled wheelchair, a ground-breaking form of mobility for people with severe physical limitations. This technique intends to give users fresh independence and movement by enabling them to control a wheelchair with their mind. A powerful Brain-Computer Interface (BCI) serves as the system's brain. The user's brain impulses are captured and analyzed by this non-invasive technology, which then transforms them into instructions that regulate the wheelchair's motion and features. The wheelchair is made to be very versatile in and of itself. It has a robust structure with built-in sensors, motors, and cutting-edge navigational systems.
The design places a high priority on safety features. To protect user security and prevent accidents, the wheelchair has built-in safety procedures, obstacle detecting systems, and emergency stop mechanisms. Additionally, a variety of users, including individuals with various degrees of physical and cognitive ability, can use the device. For anyone with mobility issues, the brain-controlled wheelchair provides a game-changing option. It enables individuals to reclaim their freedom, move around their environment more readily, and take part in daily activities more actively. Beyond personal use, it has uses in healthcare settings and rehabilitation facilities.
EEG-Based Systems: Several research studies and prototypes have utilized electroencephalography (EEG) to detect and interpret brain signals for wheelchair control. These systems typically involve users wearing EEG headsets that measure brain activity, which is then processed to command the wheelchair's movements. Invasive Brain-Computer Interfaces (BCIs): Invasive BCIs involve implanting electrodes directly into the brain, allowing for more precise control over devices such as wheelchairs. While these systems offer high levels of control, they require surgical procedures and pose certain risks, limiting their widespread adoption.
Non-Invasive BCIs: Non-invasive BCIs, such as those based on functional near-infrared spectroscopy or functional magnetic resonance imaging (fMRI), offer alternatives to EEG-based approaches. These methods typically involve measuring changes in brain activity using external sensors placed on the scalp, providing a non-invasive means of controlling wheelchairs. Hybrid Systems: Some innovations combine multiple technologies, such as EEG with eye-tracking or facial electromyography (EMG), to improve the accuracy and reliability of wheelchair control. By integrating different sensing modalities, these hybrid systems aim to enhance user experience and performance. Commercial Products: There are also commercially available brain-controlled wheelchairs and mobility devices that leverage similar technologies. These products may incorporate proprietary algorithms and user interfaces designed to optimize functionality and usability for individuals with disabilities.
In accordance to an embodiment of the disclosure, brain-controlled wheelchair comprises of various components which is shown in figure 1. Gear mechanism (4) is attached with the wheelchair for the movement of wheel in different direction. A motor driver (1) is provided to increase the level of electrical to power and to control the functioning of motor. The seat (2) was attached in the front side to provide comfortable sitting and the height of the seat adjusted using screw fitted below the seat, the comfortable arrangement of foot can be made possible by providing footstep (3) close to the front seat for proper safety of leg, the rotation can be made possible using two wheel (5) attached to both side of the wheelchair and it can able to rotate 3600. The second motor driver (6) is attached at the bottom of the wheelchair to drive the system and to control the received signal.
With reference to the figure 2 ‘wheelchair control using brain’s EEG signal’ is provided in accordance to the embodiment of the present disclosure. The Arduino board (2b) placed at the backside of the of the wheelchair on wooden panel (2c) and Arduino was provided to control all the signal transmitted by the Bluetooth devices. The backrest (2b) was provided for the proper back support to the body and to keep the spinal healthy.
EEG headband (2d) connected with onboard screen using Bluetooth which relates to motor for self-functioning. User interfacing with the wheelchair using MATLAB toll which acquire EEG data using mind wave tool and this acquisition process activates the wheel of the system for the movement in any direction. User interfacing possible to control over the wheelchair with his/her thought.

The sensor known as brain EEG sensor in form of headset is provided to establish a connection among devices and human brain using tablets and smartphone. This sensor requires only single point of contact using a dry, metal sensor on forehead and it will identify the generated brainwave function. The HC05 Bluetooth module is provided to send and receive the data from other devices and it can easily pair with microcontrollers using serial port protocol. L293-D is a motor driver which is provided and when a current carrying conductor is inserted in magnetic field and this generates a mechanical force to drive the wheel.

The adoption and learning process of brain signal acquisition that gathers the user’s brain signal into its real form execution and proper functioning. EEG is one type of process where electrical impulses were measured occurred inside the scalp. The ionic distribution of current inside the neurons generate different impulses. Measurement of generated impulses is identified by placing electrodes above the scalp. EEG is usually associated with signal which may be used to classify it as per the frequency used in this system. It is also possible to layout the various mental status of individual in the form of brainwave signal.

EEG signal first filter out all unwanted out and signal interference, then this signal is converted to brain signal or data signal, which is transmitted to the Bluetooth module, then it is transferred to the processor section which filter out the required signal using filter algorithm. Data signal consist of feature, carries out recognition in form of modulation inside the brain following discriminant analysis, finally using brain electricity data signal is changed into corresponding control signal and sent to the motor driver for its functioning.

The invention also draws inspiration from the growing demand for solutions that promote inclusivity and accessibility for people with disabilities. With a focus on enhancing independence and improving quality of life, the brain-controlled wheelchair innovation aims to address the specific needs and challenges faced by users with limited mobility, ultimately empowering them to navigate their environments with greater freedom and dignity. Simultaneously, advancements in robotics and assistive technology have facilitated the development of more sophisticated mobility devices, including wheelchairs. Researchers and engineers have been exploring ways to integrate these technologies to create more intuitive and responsive systems for individuals with severe physical disabilities.

To handle the various complex road and barrier in the travelling process, additional wheel support is provided to handle such situation. The obstacle detector used to identify the obstacle which send the signal to the processor module and that signal send to the patients to get alert of the situations and control the speed of the wheelchair. One buzzer system is also provided at the bottom of the seat to generate the alert signal whenever any obstacle found.

The overall efficiency of the brain-controlled chair can be improved by utilizing human brainwave with respect to eyebrow movement, attention value and blink identification of the human. The role brainwave is very much important to control the complete structure of wheelchair. The complete wheelchair system proves to be efficient for the physically challenged people or the patients suffering from any disability. The complete structure of invention relies on brain signal.
5 Claims & 2 figures , Claims:The following claims define the scope of the invention:
Claims:
1.An EEG brain-controlled wheelchair comprising:
a) The Arduino board (2b) attached to a wheel mounted on a control unitwith the help of wooden panel (2c).
b) A motor driver (1) is attached to the wheelchair having gear mechanism (4).
c) A Bluetooth device (5) attached with wheelchair one end of wheel chair along with footrest (3) and seat (2). A Interfacing port (2d) attached in right hand side of the wheelchair to make a connectivity with EEG band.
d) A backrest (2a) attached with the wheel chair at the backside

2. As per claim 1, the arduino board used to control the brain signal automatically, leading to better movement and improving overall quality of life.

3. As per claim 1, the motor driver enables individuals to reclaim their freedom, move around their environment more readily.

4. According to claim 1, the gear mechanics enhance mobility and independence for individuals with severe physical disabilities.

5. A per claim 1, the bluetooth module and brain sensor integrates brain-computer (EEG signal) interface technology, enabling users to control the wheel solely through their brain signals.