Brain-computer interfaces for hci and games

We study the research themes and the state-of-the-art of brain-computer interaction. Brain-computer interface research has seen much progress in the medical domain, for example for prosthesis control or as biofeedback therapy for the treatment of neurological disorders. Here, however, we look at brain-computer interaction especially as it applies to research in Human-Computer Interaction (HCI). Through this workshop and continuing discussions, we aim to define research approaches and applications that apply to disabled and able-bodied users across a variety of real-world usage scenarios. Entertainment and game design is one of the application areas that will be considered

Anticipatory models of human movements and dynamics: the roadmap of the AnDy project

International audienceFuture robots will need more and more anticipation capabilities, to properly react to human actions and provide efficient collaboration. To achieve this goal, we need new technologies that not only estimate the motion of the humans, but that fully describe the whole-body dynamics of the interaction and that can also predict its outcome. These hardware and software technologies are the goal of the European project AnDy. In this paper, we describe the roadmap of AnDy, which leverages existing technologies to endow robots with the ability to control physical collaboration through intentional interaction. To achieve this goal, AnDy relies on three technological and scientific breakthroughs. First, AnDy will innovate the way of measuring human whole-body motions by developing the wearable AnDySuit, which tracks motions and records forces. Second, AnDy will develop the AnDyModel, which combines ergonomic models with cognitive predictive models of human dynamic behavior in collaborative tasks, learned from data acquired with the AnDySuit. Third, AnDy will propose AnDyControl, an innovative technology for assisting humans through pre-dictive physical control, based on AnDyModel. By measuring and modeling human whole-body dynamics, AnDy will provide robots with a new level of awareness about human intentions and ergonomy. By incorporating this awareness on-line in the robot's controllers, AnDy paves the way for novel applications of physical human-robot collaboration in manufacturing, health-care, and assisted living

A Blueprint for Real-Time Functional Mapping via Human Intracranial Recordings

International audienceBACKGROUND: The surgical treatment of patients with intractable epilepsy is preceded by a pre-surgical evaluation period during which intracranial EEG recordings are performed to identify the epileptogenic network and provide a functional map of eloquent cerebral areas that need to be spared to minimize the risk of post-operative deficits. A growing body of research based on such invasive recordings indicates that cortical oscillations at various frequencies, especially in the gamma range (40 to 150 Hz), can provide efficient markers of task-related neural network activity. PRINCIPAL FINDINGS: Here we introduce a novel real-time investigation framework for mapping human brain functions based on online visualization of the spectral power of the ongoing intracranial activity. The results obtained with the first two implanted epilepsy patients who used the proposed online system illustrate its feasibility and utility both for clinical applications, as a complementary tool to electrical stimulation for presurgical mapping purposes, and for basic research, as an exploratory tool used to detect correlations between behavior and oscillatory power modulations. Furthermore, our findings suggest a putative role for high gamma oscillations in higher-order auditory processing involved in speech and music perception. CONCLUSION/SIGNIFICANCE: The proposed real-time setup is a promising tool for presurgical mapping, the investigation of functional brain dynamics, and possibly for neurofeedback training and brain computer interfaces

Brain-Computer Interfaces: Revolutionizing Human-Computer Interaction

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

The extraction of neural information from the surface EMG for the control of upper-limb prostheses

Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards