Patients with spinal cord injuries (SCIs) can have extremely restricted movement and independent transport functionality. Brain computer interfaces (BCIs) o er the potential to enable robotic wheelchair control through the monitoring and categorisation of brain activity signals. This enables users to control the wheelchair through the use of prede ned thought patterns. However, the process of continually executing commands can be tiring, and errors could have potentially dangerous consequences. Shared control interfaces aim to address these issues by inserting an intelligent com- puter interface between the user's brain activity signal commands and the output actuated by the wheelchair. The computer should be able to appraise both user commands and the surrounding environment to compute appropriate wheelchair behaviour. Information regarding the surrounding environment can be either collected from sensors attached to the chair, or be made available through stored map data. The Bioengineering Department at the University of Strathclyde has developed a virtual reality (VR) model of an electric wheelchair that can be used to navigate in a virtual environment. The VR wheelchair can be used as a platform to develop and test the wheelchair's performance. A shared control system has been developed which is able to perform several desirable functions, however can be augmented and improved upon through further research and development. This project involves reviewing the current system and upgrading or adding new func- tionality as required. In addition, both pre-existing and additional functionality has been documented and quantized. Furthermore, new maps have been developed to facilitate in the testing of the system. The major outcomes of this project include implementing signi cant improvements 2 and testing facilities into the shared control system, and providing documentation to allow continual development.

An immersive virtual reality electric-powered wheelchair simulator, controlled by a Brain-Computer Interface (BCI) has been developed at the University of Strathclyde. However, fine manoeuvring is difficult due to the limited number of commands that can be given through the BCI. This project aims to incorporate shared control between the user and an intelligent wheelchair controller to provide a better driving experience, while ensuring the safety of the user. A shared control strategy was developed to provide three types of assisting behaviours - Obstacle Avoidance, Collision Avoidance and Wall Following. Reactive navigation strategies were devised with the help of user input from the keypad and information about the environment provided by sonar sensors, infra-red sensors and velocity levels obtained from ground truth. Respecting the importance of user autonomy, as re-iterated in the literature, the user has the power to override the assisting behaviour provided, except in the case of a risk of collision. The shared control technique was evaluated with the help of five healthy volunteers who performed numerous wheelchair driving tasks in manual and shared control modes in the wheelchair simulator. They rated their driving experience using NASA Task Load Index (TLX) scales. In order to study the effectiveness of the shared control behaviours, a secondary task was used to simulate a state of suppressed ability in the able-bodied people. Average workload scores were calculated for all the tasks and revealed that while workload was decreased in the case of shared control for Wall Following behaviour, it was the opposite for Obstacle Avoidance. The inferences made from the NASA-TLX assessment procedure and the observations made during the experiments have provided a useful insight into the limitations of the system and scope for improvement.

Brain-computer interfaces (BCIs) are devices that enable people to communicate via thought alone. Brain signals can be directly translated into messages or commands. Until recently, these devices were used primarily to help people who could not move. However, BCIs are now becoming practical tools for a wide variety of people, in many different situations. What will BCIs in the future be like? Who will use them, and why? This book, written by many of the top BCI researchers and developers, reviews the latest progress in the different components of BCIs. Chapters also discuss practical issues in an emerging BCI enabled community. The book is intended both for professionals and for interested laypeople who are not experts in BCI research.

This volume summarizes the ethical, social and cultural contexts of interfacing brains and computers. It is intended for the interdisciplinary community of BCI stakeholders. Insofar, engineers, neuroscientists, psychologists, physicians, care-givers and also users and their relatives are concerned. For about the last twenty years brain-computer-interfaces (BCIs) have been investigated with increasing intensity and have in principle shown their potential to be useful tools in diagnostics, rehabilitation and assistive technology. The central promise of BCI technology is enabling severely impaired people in mobility, grasping, communication, and entertainment. Successful applications are for instance communication devices enabling locked-in patients in staying in contact with their environment, or prostheses enabling paralysed people in reaching and grasping. In addition to this, it serves as an introduction to the whole field of BCI for any interested reader.

A recognizable surge in the field of Brain Computer Interface (BCI) research and development has emerged in the past two decades. This book is intended to provide an introduction to and summary of essentially all major aspects of BCI research and development. Its goal is to be a comprehensive, balanced, and coordinated presentation of the field's key principles, current practice, and future prospects.

Brain–Computer Interfaces Handbook: Technological and Theoretical Advances provides a tutorial and an overview of the rich and multi-faceted world of Brain–Computer Interfaces (BCIs). The authors supply readers with a contemporary presentation of fundamentals, theories, and diverse applications of BCI, creating a valuable resource for anyone involved with the improvement of people’s lives by replacing, restoring, improving, supplementing or enhancing natural output from the central nervous system. It is a useful guide for readers interested in understanding how neural bases for cognitive and sensory functions, such as seeing, hearing, and remembering, relate to real-world technologies. More precisely, this handbook details clinical, therapeutic and human-computer interfaces applications of BCI and various aspects of human cognition and behavior such as perception, affect, and action. It overviews the different methods and techniques used in acquiring and pre-processing brain signals, extracting features, and classifying users’ mental states and intentions. Various theories, models, and empirical findings regarding the ways in which the human brain interfaces with external systems and environments using BCI are also explored. The handbook concludes by engaging ethical considerations, open questions, and challenges that continue to face brain–computer interface research. Features an in-depth look at the different methods and techniques used in acquiring and pre-processing brain signals, extracting features, and classifying the user's intention Covers various theories, models, and empirical findings regarding ways in which the human brain can interface with the systems or external environments Presents applications of BCI technology to understand various aspects of human cognition and behavior such as perception, affect, action, and more Includes clinical trials and individual case studies of the experimental therapeutic applications of BCI Provides human factors and human-computer interface concerns in the design, development, and evaluation of BCIs Overall, this handbook provides a synopsis of key technological and theoretical advances that are directly applicable to brain–computer interfacing technologies and can be readily understood and applied by individuals with no formal training in BCI research and development.

A brain-computer interface (BCI) establishes a direct output channel between the human brain and external devices. BCIs infer user intent via direct measures of brain activity and thus enable communication and control without movement. This book, authored by experts in the field, provides an accessible introduction to the neurophysiological and signal-processing background required for BCI, presents state-of-the-art non-invasive and invasive approaches, gives an overview of current hardware and software solutions, and reviews the most interesting as well as new, emerging BCI applications. The book is intended not only for students and young researchers, but also for newcomers and other readers from diverse backgrounds keen to learn about this vital scientific endeavour.

Smart Wheelchairs and Brain-Computer Interfaces: Mobile Assistive Technologies combines the fields of neuroscience, rehabilitation and robotics via contributions from experts in their field to help readers develop new mobile assistive technologies. It provides information on robotics, control algorithm design for mobile robotics systems, ultrasonic and laser sensors for measurement and trajectory planning, and is ideal for researchers in BCI. A full view of this new field is presented, giving readers the current research in the field of smart wheelchairs, potential control mechanisms and human interfaces that covers mobility, particularly powered mobility, smart wheelchairs, particularly sensors, control mechanisms, and human interfaces. Presents the first book that combines BCI and mobile robotics Focuses on fundamentals and developments in assistive robotic devices which are commanded by alternative ways, such as the brain Provides an overview of the technologies that are already available to support research and the development of new products

Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI. Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services. - Provides readers with an understanding of key applications of Artificial Intelligence to Brain-Computer Interface for acquisition and modelling of non-invasive biomedical signal and image modalities for various conditions and disorders - Integrates recent advancements of Artificial Intelligence to the evaluation of large amounts of clinical data for the early detection of disorders such as Epilepsy, Alcoholism, Sleep Apnea, motor-imagery tasks classification, and others - Includes illustrative examples on how Artificial Intelligence can be applied to the Brain-Computer Interface, including a wide range of case studies in predicting and classification of neurological disorders