A robotic wheelchair trainer: design overview and a feasibility study

<p>Abstract</p> <p>Background</p> <p>Experiencing independent mobility is important for children with a severe movement disability, but learning to drive a powered wheelchair can be labor intensive, requiring hand-over-hand assistance from a skilled therapist.</p> <p>Methods</p> <p>To improve accessibility to training, we developed a robotic wheelchair trainer that steers itself along a course marked by a line on the floor using computer vision, haptically guiding the driver's hand in appropriate steering motions using a force feedback joystick, as the driver tries to catch a mobile robot in a game of "robot tag". This paper provides a detailed design description of the computer vision and control system. In addition, we present data from a pilot study in which we used the chair to teach children without motor impairment aged 4-9 (n = 22) to drive the wheelchair in a single training session, in order to verify that the wheelchair could enable learning by the non-impaired motor system, and to establish normative values of learning rates.</p> <p>Results and Discussion</p> <p>Training with haptic guidance from the robotic wheelchair trainer improved the steering ability of children without motor impairment significantly more than training without guidance. We also report the results of a case study with one 8-year-old child with a severe motor impairment due to cerebral palsy, who replicated the single-session training protocol that the non-disabled children participated in. This child also improved steering ability after training with guidance from the joystick by an amount even greater than the children without motor impairment.</p> <p>Conclusions</p> <p>The system not only provided a safe, fun context for automating driver's training, but also enhanced motor learning by the non-impaired motor system, presumably by demonstrating through intuitive movement and force of the joystick itself exemplary control to follow the course. The case study indicates that a child with a motor system impaired by CP can also gain a short-term benefit from driver's training with haptic guidance.</p

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

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

INTELIGENTNY WÓZEK INWALIDZKI Z NAPĘDEM ELEKTRYCZNYM: PROBLEMY I WYZWANIA W PODEJŚCIU PRODUKTOWYM

This paper focuses on intelligent assistant for power wheelchair (PW) usage in home conditions. Especially in the context of PW intelligent assistant as a consumer product. The main problematic aspects and challenges of smart PW in real application are noted. The approach to formation of system requirements and their classification is offered. The research results proposed and implemented in the ongoing Mobilis project for smart PW. Further prospects of research and development are noted. Also, it is stated that the implementation of smart PW technology opens possibilities to effective integration with new control methods (including brain-computer interfaces).Niniejszy artykuł koncentruje się na omówieniu problemów i wyzwań dotyczących nowego produktu, jakim jest Smart Power Wheelchair (SPW), czyli inteligentny asystent używany w elektrycznych wózkach inwalidzkich w warunkach domowych. Zwrócono szczególnie uwagę na ukazanie SPW jako nowego produktu konsumenckiego na rynku dóbr. Przedstawione zostały główne problematyczne aspekty i wyzwania dla SPW, które mogą pojawić się w warunkach rzeczywistych. Artykuł zawiera również propozycje dotyczące tworzenia wymagań systemowych oraz ich klasyfikacji. W kolejnej części artykułu przedstawiono wyniki badań, zrealizowanych w ramach projektu Mobilis, dzięki którym wdrożono szereg zmian w produkcie. Ponadto autorzy zapewniają o planowanych dalszych badaniach nad rozwojem produktu. Należy zwrócić uwagę, że wprowadzenie technologii SPW otwiera możliwości efektywnej integracji z nowymi metodami komunikacji (w tym z interfejsami mózg-komputer, z ang. brain-computer interfaces – BCI), z których szczególną korzyść będą miały osoby z niepełnosprawnością ruchową

Human Guide Tracking Using Combined Histogram of Oriented Gradient and Entropy Difference Minimization Algorithm for Camera Follower

Moving human is quite complicated to track since there are variations in background, texture, and lighting in an environment. This paper presents an effective method for tracking a human guide from a camera follower in both indoor and outdoor condition. This algorithm is designed to be embedded in a smart wheelchair. A conventional human detection by using Histogram of Oriented Gradient (HOG) was used at the first stage, then each detected human by HOG is utilized for tracking algorithm. The detected area from HOG is converted to grayscale image and its Entropy Difference Minimization (HOG-EDM) is calculated. The process is repeated for every frame. The entropy minimization is used as matching function in the tracking subsystem to determine the candidate of tracked object in the upcoming frame. The proposed algorithm has been proven to work well in indoor and outdoor area, even with textured background. Our testing based on self-made and public datasets shows that HOG-EDM method reaches over 80% accuracy

Multimodal interface for an intelligent wheelchair

Tese de mestrado integrado. Engenharia Informática e Computação. Universidade do Porto. Faculdade de Engenharia. 201