Berlin Brain–Computer Interface—The HCI communication channel for discovery

The investigation of innovative Human–Computer Interfaces (HCI) provides a challenge for future interaction research and development. Brain–Computer Interfaces (BCIs) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as amyotrophic lateral sclerosis (ALS) or complete paralysis of all extremities due to high spinal cord injury. Beyond medical applications, a BCI conjunction with exciting multimedia applications, e.g., a dexterity discovery, could define a new level of control possibilities also for healthy customers decoding information directly from the user's brain, as reflected in EEG signals which are recorded non-invasively from the scalp.This contribution introduces the Berlin Brain–Computer Interface (BBCI) and presents set-ups where the user is provided with intuitive control strategies in plausible interactive bio-feedback applications. Yet at its beginning, BBCI thus adds a new dimension in HCI research by offering the user an additional and independent communication channel based on brain activity only. Successful experiments already yielded inspiring proofs-of-concept. A diversity of interactive application models, say computer games, and their specific intuitive control strategies are now open for BCI research aiming at a further speed up of user adaptation and increase of learning success and transfer bit rates.BBCI is a complex distributed software system that can be run on several communicating computers responsible for (i) the signal acquisition, (ii) the data processing and (iii) the feedback application. Developing a BCI system, special attention must be paid to the design of the feedback application that serves as the HCI unit. This should provide the user with the information about her/his brain activity in a way that is intuitively intelligible. Exciting discovery applications qualify perfectly for this role. However, most of these applications incorporate control strategies that are developed especially for the control with haptic devices, e.g., joystick, keyboard or mouse. Therefore, novel control strategies should be developed for this purpose that (i) allow the user to incorporate additional information for the control of animated objects and (ii) do not frustrate the user in the case of a misclassification of the decoded brain signal.BCIs are able to decode different information types from the user's brain activity, such as sensory perception or motor intentions and imaginations, movement preparations, levels of stress, workload or task-related idling. All of these diverse brain signals can be incorporated in an exciting discovery scenario. Modern HCI research and development technologies can provide BCI researchers with the know-how about interactive feedback applications and corresponding control strategies.     

非侵入式脑—机接口编解码技术研究进展

脑—机接口（brain-computer interface,BCI）系统通过采集、分析大脑信号,将其转换为输出指令,从而跨越外周神经系统,实现由大脑信号对外部设备的直接控制,进而用于替代、修复、增强、补充或改善中枢神经系统的正常输出。非侵入式脑—机接口由于具有安全性以及便携性等优点,得到了广泛关注和持续研究。研究人员对脑信号编码方法的不断探索扩展了BCI系统的应用场景和适用范围。同时,脑信号解码方法的不断研发极大地克服了脑电信号信噪比低的缺点,提高了系统性能,这都为构建高性能脑—机接口系统奠定了基础。本文综述了非侵入式脑—机接口编解码技术以及系统应用的最新研究进展,展望其未来发展前景,以期促进BCI系统的深入研究与广泛应用。     

Brain-Computer Interfaces: Where Human and Machine Meet

For a long time, researchers have been working on a marriage of human and machine that sounds like something out of science fiction: a brain-computer interface. BCIs read electrical signals or other manifestations of brain activity and translate them into a digital form that computers can understand, process, and convert into actions of some kind, such as moving a cursor or turning on a TV. Several academic and corporate researchers are now working to commercialize the technology, while other projects are taking innovative approaches to BCIs that could create interesting products or services in the not-too-distant future. The technology holds great promise for people who can't use their arms or hands normally because they have had spinal cord injuries or suffer from conditions such as amyotrophic lateral sclerosis (ALS) or cerebral palsy. BCI could help them control computers, wheelchairs, televisions, or other devices with brain activity     

Brain–computer interfaces and dualism: a problem of brain,mind, and body

The brain–computer interface (BCI) has made remarkable progress in the bridging the divide between the brain and the external environment to assist persons with severe disabilities caused by brain impairments. There is also continuing philosophical interest in BCIs which emerges from thoughtful reflection on computers, machines, and artificial intelligence. This article seeks to apply BCI perspectives to examine, challenge, and work towards a possible resolution to a persistent problem in the mind–body relationship, namely dualism. The original humanitarian goals of BCIs and the technological inventiveness result in BCIs being surprisingly useful. We begin from the neurologically impaired person, the problems encountered, and some pioneering responses from computers and machines. Secondly, the interface of mind and brain is explored via two points of clarification: direct and indirect BCIs, and the nature of thoughts. Thirdly, dualism is beset by mind–body interaction difficulties and is further questioned by the phenomena of intentions, interactions, and technology. Fourthly, animal minds and robots are explored in BCI settings again with relevance for dualism. After a brief look at other BCIs, we conclude by outlining a future BCI philosophy of brain and mind, which might appear ominous and could be possible.     

Brain–Computer Interfaces for Multimodal Interaction: A Survey and Principles

For decades, brain–computer interfaces (BCIs) have been used for restoring the communication and mobility of disabled people through applications such as spellers, web browsers, and wheelchair controls. In parallel to advances in computational intelligence and the production of consumer BCI products, BCIs have recently started to be considered as alternative modalities in human–computer interaction (HCI). One of the popular topics in HCI is multimodal interaction (MMI), which deals with combining multiple modalities in order to provide powerful, flexible, adaptable, and natural interfaces. This article discusses the situation of BCI as a modality within MMI research. State-of-the-art, real-time multimodal BCI applications are surveyed in order to demonstrate how BCI can be helpful as a modality in MMI. It is shown that multimodal use of BCIs can improve error handling, task performance, and user experience and that they can broaden the user spectrum. The techniques for employing BCI in MMI are described, and the experimental and technical challenges with some guidelines to overcome these are shown. Issues in input fusion, output fission, integration architectures, and data collection are covered.     

Classification of primitive shapes using brain–computer interfaces

Brain–computer interfaces (BCIs) are recent developments in alternative technologies of user interaction. The purpose of this paper is to explore the potential of BCIs as user interfaces for CAD systems. The paper describes experiments and algorithms that use the BCI to distinguish between primitive shapes that are imagined by a user. Users wear an electroencephalogram (EEG) headset and imagine the shape of a cube, sphere, cylinder, pyramid or a cone. The EEG headset collects brain activity from 14 locations on the scalp. The data is analyzed with independent component analysis (ICA) and the Hilbert–Huang Transform (HHT). The features of interest are the marginal spectra of different frequency bands (theta, alpha, beta and gamma bands) calculated from the Hilbert spectrum of each independent component. The Mann–Whitney U-test is then applied to rank the EEG electrode channels by relevance in five pair-wise classifications. The features from the highest ranking independent components form the final feature vector which is then used to train a linear discriminant classifier. Results show that this classifier can discriminate between the five basic primitive objects with an average accuracy of about 44.6% (compared to naïve classification rate of 20%) over ten subjects (accuracy range of 36%–54%). The accuracy classification changes to 39.9% when both visual and verbal cues are used. The repeatability of the feature extraction and classification was checked by conducting the experiment on 10 different days with the same participants. This shows that the BCI holds promise in creating geometric shapes in CAD systems and could be used as a novel means of user interaction.     

The networked home: an analysis of current developments and future trends

The paper examines the concept of the networked home as both a social institution and a technological construction. While the concept of networks is not new to family studies, the new technologies of information and communication are requiring us to look at the home as an intersection point of sociology and technology. Fundamental to our analysis is the concept of home as living space that unfolds into a collection of multiple centers – home as activity center, entertainment center, work center, information center, communication center, learning center and shopping center. In our analysis, the living space is subdivided structurally into social, physical and technological spaces in which the centers are embedded as organic elements. The integration of the centers with the living space model is fundamental to understanding the home as a networked home. Electronic Publication     

PAMM:一种面向基于内存共享的域间通信的优化模型

云计算平台和虚拟化技术的结合为虚拟机域间通信带来了新的需求,基于内存共享的域间通信可以提高运行在同一物理机上的虚拟机间的通信效率。但是,基于内存共享的域间过程中产生的上下文状态切换限制了其优化能力。引入一种新的内存共享模型PAMM,即通过添加一个管理模块对内存共享过程中所传递的内存页进行聚合管理,减少申请超级调用的次数,以达到减少状态切换的目的。实验表明,PAMM能够提升基于内存共享的域间通信的通信效率。     

Brain–computer interfacing: more than the sum of its parts

The performance of non-invasive electroencephalogram-based (EEG) brain–computer interfaces (BCIs) has improved significantly in recent years. However, remaining challenges include the non-stationarity and the low signal-to-noise ratio of the EEG, which limit the bandwidth and hence the available applications. Optimization of both individual components of BCIs and the interrelationship between them is crucial to enhance bandwidth. In other words, neuroscientific knowledge and machine learning need to be optimized by considering concepts from human–computer interaction research and usability. In this paper, we present results of ongoing relevant research in our lab that addresses several important issues for BCIs based on the detection of transient changes in oscillatory EEG activity. First, we report on the long-term stability and robustness of detection of oscillatory EEG components modulated by distinct mental tasks, and show that the use of mental task pairs “mental subtraction versus motor imagery” achieves robust and reliable performance (Cohen’s κ > 0.6) in seven out of nine subjects over a period of 4 days. Second, we report on restricted Boltzmann machines (RBMs) as promising tools for the recognition of oscillatory EEG patterns. In an off-line BCI simulation we computed average peak accuracies, averaged over ten subjects, of 80.8 ± 7.2 %. Third, we present the basic framework of the context-aware hybrid Graz-BCI that allows interacting with the massive multiplayer online role playing game World of Warcraft. We show how a more integrated design approach that considers all components of BCIs, their interrelationships, other input signals and contextual information can increase interaction efficacy.     

Activity-based design

In many types of activities, communicative and material activities are so intertwined that the one cannot be understood without taking the other into account. This is true of maritime and hospital work that are used as examples in the paper. The spatial context of the activity is also important: what you can do depends upon where you are. Finally, human and automatic machinery alternate in filling certain roles in the activity: sometime the officer maintains the course, sometimes the autopilot. Such activities require us to rethink the traditional oppositions between communication and instrumental actions, between human and non-human participants, and between an activity and its spatio-temporal context. The advent of pervasive technologies, where active or passive systems become embedded in our working and living spaces, from where they offer their services to us, puts the need to reconsider these basic oppositions high on the research agenda. This paper presents a consistent framework called habitats for understanding communicative and material activities and their interplay, for understanding how activities can be associated to physical surroundings, and for understanding how humans and automatic machinery can replace one another in an activity. It also gives an example of how to use the framework for design.     

Abidirectional brain-computer interface for effective epilepsy control

Brain-computer interfaces （BCIs） can provide direct bidirectional communication between the brain and a machine. Recently, the BCI technique has been used in seizure control. UsuMly, a closed-loop system based on BCI is set up which delivers a therapic electrical stimulus only in response to seizure onsets. In this way, the side effects of neurostimulation can be greatly reduced. In this paper, a new BCI-based responsive stimulation system is proposed. With an efficient morphology-based seizure detector, seizure events can be identified in the early stages which trigger electrical stimulations to be sent to the cortex of the brain. The proposed system was tested on rats with penicillin-induced epileptic seizures. Online experiments show that 83% of the seizures could be detected successfully with a short average time delay of 3.11 s. With the therapy of the BCI-based seizure control system, most seizures were suppressed within 10 s. Compared with the control group, the average seizure duration was reduced by 30.7%. Therefore, the proposed system can control epileptic seizures effectively and has potential in clinical applications.     

Adaptive manuals as assistive technology to support and train people with acquired brain injury in their daily life activities

Assistive technologies and ubiquitous computing can be related since both try to help people in their lives. This common objective motivated us to develop and evaluate a system that puts ubiquitous computing technologies into the rehabilitation process of people with acquired brain injury. Thus, in this paper, we present and evaluate a system that shows adaptive manuals for daily-life activities for people with acquired brain injury. This first evaluation allowed us to validate our approach and also to extract valuable information about these systems as well as environmental factors that may affect the patients.     

Scan of the Issue

In recent years, there have been rapid advances in sensor, sensor-on-a-chip, MEMS and wireless communication technologies. Now. massively distributed sensor networks are capable of linking people and the physical world together, providing platforms for information to be collected, shared, and processed in unprecedented ways. It is commonly recognized that sensor network research will lead to smart sentient spaces for our home and environment, work and leisure. It can help us to fight against disasters, protect us from hazards, and strengthen our defense. For the past few years, sensor networks research     

The Berlin Brain-Computer Interface (BBCI) – towards a new communication channel for online control in gaming applications

The investigation of innovative Human-Computer Interfaces (HCI) provides a challenge for future multimedia research and development. Brain-Computer Interfaces (BCI) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as Amyotrophic Lateral Sclerosis (ALS) or spinal cord injury. Beyond medical applications, a BCI conjunction with exciting multimedia applications, e.g., a dexterity game, could define a new level of control possibilities also for healthy customers decoding information directly from the user’s brain, as reflected in electroencephalographic (EEG) signals which are recorded non-invasively from user’s scalp. This contribution introduces the Berlin Brain–Computer Interface (BBCI) and presents setups where the user is provided with intuitive control strategies in plausible gaming applications that use biofeedback. Yet at its beginning, BBCI thus adds a new dimension in multimedia research by offering the user an additional and independent communication channel based on brain activity only. First successful experiments already yielded inspiring proofs-of-concept. A diversity of multimedia application models, say computer games, and their specific intuitive control strategies, as well as various Virtual Reality (VR) scenarios are now open for BCI research aiming at a further speed up of user adaptation and increase of learning success and transfer bit rates.

How In-Home Technologies Mediate Caregiving Relationships in Later Life

In-home technologies can support older adults' activities of daily living, provide physical safety and security, and connect elders to family and friends. They facilitate aging in place while reducing caregiver burden. One of older adults' primary concerns about in-home technologies is their potential to reduce human contact, particularly from cherished caregivers. In this exploratory in situ study, we provided an ecosystem of networked monitoring technologies to six older adults and their caregivers. We analyzed the amount and content of communication between them. The amount of noncomputer-mediated communication did not decrease through the 6-week study. The content of communication coalesced into four themes: communication about the technologies, communication facilitated by technologies, intrusiveness of technologies, and fun and playfulness with the technologies. Results suggest that in-home technologies, designed with sensitivity to older adults' primary motivations, have the potential to shape and tailor important relationships in later life.     

An overview of multi-antenna technologies for space-ground integrated networks

Multi-antenna technologies have already achieved a series of great successes in the development of information networks. For future space-ground integrated networks (SGINs), the traditional various kinds of separated information networks will converge to a whole fully connected information network to provide more flexible and reliable services on a world scale. Regarding their great successes in existing systems, multiantenna technologies will be of critical importance for the realization of SGINs and multi-antenna technologies are definitely one of the most important enabling technologies for future converged SGINs. In this article, a comprehensive overview on multi-antenna technologies is given. We first investigate multi-antenna technologies from a theoretical viewpoint. It is shown that we can understand multi-antenna technologies in a general and unified point of view. This fact has two-fold meanings. First, the research on multi-antennas can help us understand the relationships between different technologies e.g., OFDMA, CDMA, etc. On the other hand, multi-antenna technologies are easy to integrate into various information systems. Following that, we discuss in depth the potentials and challenges of the multi-antenna technologies on different platforms and in different applications case by case. More specifically, we investigate spaceborne multi-antenna technologies, airborne multi-antenna technologies, shipborne multi-antenna technologies, etc. Moreover, the combinations of multiantenna technologies with other advanced wireless technologies e.g., physical layer network coding, cooperative communication, etc., are also elaborated.     

Analogue evolutionary brain computer interfaces [Application Notes]

The keyboard is a device that, with its many switches, provides us with an interface that is reliable but also very unnatural. The mouse is only slightly less primitive, being an electro-mechanical transducer of musculoskeletal movement. Both have been with us for decades, yet they are unusable for people with severe musculoskeletal disorders and are themselves known causes of work-related upperlimb and back disorders, both hugely widespread problems [1], [2]. It will be a major contribution to computer interface technology one day to be able to replace mouse and keyboard with Brain-Computer Interfaces (BCIs) capable of directly interpreting the desires and intentions of computer users.     

Affective command-based control system integrating brain signals in commands control systems

Speech interaction systems are currently highly demanded for quick hands-free interactions. Conventional speech interaction systems (SISs) are trained to the user’s voice whilst most modern systems learn from interaction experience overtime. However, because speech expresses a human computer natural interaction (HCNI) with the world, SIS design must lead to interface computer system that can receive spoken information and act appropriately upon that information. In spite of significant advancements in recent years SISs, there still remain a large number of problems which must be solved in order to successfully apply the SISs in practice and also comfortably accepted by the users. Among many other problems, problems of devising and efficient modeling are considered the primary and important step in the speech recognition deployment in hands-free applications. Meanwhile, the brain–computer interfaces (BCIs) allow users to control applications by brain activity. The work presented in this paper emphasizes an improved implementation of SIS by integrating BCI in order to associate the brain signals for a list of commands as identification criteria for each specific command for controlling the wheelchair with spoken commands.     

Designing for uncertain,asymmetric control: Interaction design for brain–computer interfaces

Designing user interfaces which can cope with unconventional control properties is challenging, and conventional interface design techniques are of little help. This paper examines how interactions can be designed to explicitly take into account the uncertainty and dynamics of control inputs. In particular, the asymmetry of feedback and control channels is highlighted as a key design constraint, which is especially obvious in current non-invasive brain–computer interfaces (BCIs). Brain–computer interfaces are systems capable of decoding neural activity in real time, thereby allowing a computer application to be directly controlled by thought. BCIs, however, have totally different signal properties than most conventional interaction devices. Bandwidth is very limited and there are comparatively long and unpredictable delays. Such interfaces cannot simply be treated as unwieldy mice. In this respect they are an example of a growing field of sensor-based interfaces which have unorthodox control properties. As a concrete example, we present the text entry application “Hex-O-Spell”, controlled via motor-imagery based electroencephalography (EEG). The system utilizes the high visual display bandwidth to help compensate for the limited control signals, where the timing of the state changes encodes most of the information. We present results showing the comparatively high performance of this interface, with entry rates exceeding seven characters per minute.     

Mediating intimacy in long-distance relationships using kiss messaging

Intimate interactions between remotely located individuals are not well supported by conventional communication tools, mainly due to the lack of physical contact. Also, haptic research has not focused on the use of a kiss as a mode of interaction that maintains intimacy in long distance relationships. In this study, we designed and developed a haptic device called Kissenger (Kiss-Messenger) for this issue. Kissenger is an interactive device that provides a physical interface for transmitting a kiss between two remotely connected people. Each device is paired with another and the amount of force and shape of the kiss by the user is sensed and transmitted to another device that is replicated using actuators. Kissenger is designed to augment already existing remote communication technologies. Challenges in the design and development of the system are addressed through an iterative design process involving constant evaluation by users after each stage. The devices are evaluated through a short- and a long-term user study with remotely located couples. The results point to an initial acceptance of the device with feedback from the users on directions to improve the overall experience. This study discusses potential issues that designers should be aware of when prototyping for remote intimate interactions.