Smart Wheelchair with Voice Control for Physically Challenged People

A wheel chair is a mechanically operated device that allows the user to move about independently. This minimizes the user's personal effort and force required to move the wheelchair wheels. Furthermore, it allows visually or physically handicapped people to go from one location to another. Voice commands and button controls can be used to operate wheelchairs. In recent years, there has been a lot of interest in smart wheelchairs. These gadgets are very handy while traveling from one location to another. The devices can also be utilized in nursing homes where the elderly have difficulties moving about. For individuals who have lost their mobility, the gadgets are a godsend. Different types of smart wheelchairs have been created in the past, but new generations of wheelchairs are being developed and utilized that incorporate the use of artificial intelligence and therefore leave the user with a little to tamper with. The project also intends to develop a comparable wheel chair that has some intelligence and so assists the user in his or her mobility.

A Novel IOT Based Smart Wheelchair Design for Cerebral Palsy Patients

Several patients face Cerebral Palsy. Such debilitating diseases impede motor control and make it difficult for them to operate traditional electric wheelchairs. Existing models of smart wheelchairs accommodate these issues to a certain extent but fail to deliver a solution for patients to use the wheelchairs completely autonomously. This paper proposes a novel model for a cost-effective smart wheelchair that takes simple gestures as input for movement, along with several quality-of-life and assistive modules such as vitals monitoring and voice memo support for patients suffering from memory loss, along with obstacle detection to ensure complete safety of the patient regardless of the terrain. The paper discusses the various modules present in the wheelchair, elaborates upon the algorithm used for input detection and calculation, and finally, the implementation of each module. Lastly, the paper enlists comparisons between existing smart wheelchair models and the proposed model and lists out its strengths, weaknesses and states its findings from the proposed system's results.

Further Improvement of Customized Vibration Generator for Machine–Human Feedbacks with the Help of Resonant Networks

Modern industrial, household and other equipment include sophisticated power mechanisms and complicated control solutions and require tighter human–machine–human interaction, forming the structures known as cyber–physical–human systems. Their significant parts are human–machine command links and machine–human feedbacks. Such systems are found in medicine, for example, in orthopedics, where they are important for operation and functional abilities of orthopedic devices—smart wheelchairs, verticalizers, prosthesis, rehabilitation units, etc. The mentioned feedbacks may be implemented based on the haptic perceptions that require vibration actuators. In orthopedics, such actuators can also be used for diagnostic purposes. This research brings forward the idea of the use of resonant operation of the driver of vibration actuator. The corresponding driver has been built and experimentally tested. It has been found that (1) the point of maximal current is actually defined by the resonant frequency, (2) change of the capacitance allows shifting of the point of maximal current output and (3) damping factors make the above-described effect less obvious. Further development of the proposed idea requires a comprehensive comparison of four-quadrant and two-quadrant schemes in this application and development of a real-time programmable capacitor pack consisting of several binary weighted capacitors and a commutating circuit, which is installable to these schemes.

Assistive Robot for Mobility Enhancement of Impaired Students for Barrier-Free Education: A Proof of Concept

Smart wheelchairs are in the category of assistive robots, which interact physically and/or non-physically with people with physical disabilities to extend their autonomy. Smart wheelchairs are assistive robots that enhance mobility, and can be especially useful for improving access to university premises. This paper proposes a smart wheelchair that can be integrated with an academic management system to enable students who have serious leg problems and cannot walk on their own to reach any academic building or room on a university campus autonomously. The proposed smart wheelchair receives information from the academic management system about the spaces on campus, the lesson schedule, the office hours of lecturers, and so on. Students can select the desired task from the user interface. The smart wheelchair can then guide the student autonomously to the desired point of interest, while planning the best barrier-free route inside the campus/building and, simultaneously, avoiding fixed and moving obstacles. The assistive robot has localization and navigation capabilities, which allow students to move about campus freely and autonomously, and benefit from a barrier-free education.

AI-based smart and intelligent wheelchair

The differently abled and/or old-aged people require assistance for their movement. Generally, such assistant providing tool is wheelchair. Normal wheelchairs are manually operated and heavy to move adding burden to the suffered. Hence, automated wheelchairs that are equipped with sensors and a data processing unit constitute a special class of wheeled mobile robots, termed as “smart wheelchairs” in general. In the existing system, the wheelchair movement that is controlled by joystick uses buttons to start and stop the wheel. This is difficult for the differently abled to press the required button with precision. Although there are smart wheelchairs with gesture control, it lacks accuracy in the calculation of the location. The proposed system uses artificial intelligence for its working and proves to be a unique combination of wheelchair and health monitoring system. The wheelchair can be accessed both in manual and automatic modes. In the manual mode, the wheel is controlled using joystick whereas in the automated mode, MPU6050 sensor and accelerometer is used to control the direction by gesture. SPO2 sensor attached to the wheelchair is used to collect the health parameters. Thus, enabling the self-dependency of the person. Further, deep learning analysis of the data from the sensors and the wheelchair usage pattern is compared with the dataset to determine the stress level. The signal from the sensors is monitored and the vitals data is updated in the ThingSpeak website via Bluetooth module serving as a digital health chart.

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers

The last decade observed a significant research effort directed towards maneuverability and safety of mobile robots such as smart wheelchairs. The conventional electric wheelchair can be equipped with motorized omnidirectional wheels and several sensors serving as inputs for the controller to achieve smooth, safe, and reliable maneuverability. This work uses the decentralized algorithm to control the motion of omnidirectional wheelchairs. In the body frame of the omnidirectional wheeled wheelchair there are three separated independent components of motion including rotational motion, horizontal motion, and vertical motion, which can be controlled separately. So, each component can have its different sub-controller with a minimum tracking error. The present work aims to enhance the mobility of wheelchair users by utilizing an application to control the motion of their attained/unattained smart wheelchairs, especially in narrow places and at hard detours such as 90˚ corners and U-turns, which improves the quality of life of disabled users by facilitating their wheelchairs’ maneuverability. Two approaches of artificial intelligent-based controllers (PD-Fuzzy-P and GA-PID controllers) are designed to optimally enhance the maneuverability of the system. MATLAB software is used to simulate the system and calculate the Mean Error (ME) and Mean Square Error (MSE) for various scenarios in both approaches, the results showed that the PD-Fuzzy-P controller has a faster convergence in trajectory tracking than the GA-PID controller. Therefore, the proposed system can find its application in many areas including transporting locomotor-based disabled individuals and geriatric people as well as automated guided vehicles.

Wheelchair Neuro Fuzzy Control and Tracking System Based on Voice Recognition

Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.