Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
32,439
result(s) for
"User-Computer Interface."
Sort by:
Designing with the mind in mind : simple guide to understanding user interface design guidelines
In this completely updated and revised edition of Designing with the Mind in Mind, Jeff Johnson provides you with just enough background in perceptual and cognitive psychology that user interface (UI) design guidelines make intuitive sense rather than being just a list or rules to follow.Early UI practitioners were trained in cognitive psychology.
eBook
Brave NUI world : designing natural user interfaces for touch and gesture
Brave NUI World is the first practical guide for designing touch- and gesture-based user interfaces.Written by the team from Microsoft that developed the multi-touch, multi-user Surface® tabletop product, it introduces the reader to natural user interfaces (NUI).
eBook
Human-robot interaction strategies for walker-assisted locomotion
This book presents the development of a new multimodal human-robot interface for testing and validating control strategies applied to robotic walkers for assisting human mobility and gait rehabilitation. The aim is to achieve a closer interaction between the robotic device and the individual, empowering the rehabilitation potential of such devices in clinical applications. A new multimodal human-robot interface for testing and validating control strategies applied to robotic walkers for assisting human mobility and gait rehabilitation is presented. Trends and opportunities for future advances in the field of assistive locomotion via the development of hybrid solutions based on the combination of smart walkers and biomechatronic exoskeletons are also discussed.
Book
The vicarious brain, creator of worlds
Groping around a familiar room in the dark, relearning to read after a brain injury, navigating a virtual landscape through an avatar: all are expressions of vicariance--when the brain substitutes one process or function for another. Alain Berthoz shows that this capacity allows humans to think creatively in an increasingly complex world.-- Provided by publisher.
Book
Interaction Flow Modeling Language
Interaction Flow Modeling Language describes how to apply model-driven techniques to the problem of designing the front end of software applications, i.e., the user interaction.The book introduces the reader to the novel OMG standard Interaction Flow Modeling Language (IFML).
eBook
Ensuring Digital Accessibility Through Process and Policy
Ensuring Digital Accessibility through Process and Policy provides readers with a must-have resource to digital accessibility from both a technical and policy perspective.Inaccessible digital interfaces and content often lead to forms of societal discrimination that may be illegal under various laws.
eBook
Meeting brain–computer interface user performance expectations using a deep neural network decoding framework
Brain–computer interface (BCI) neurotechnology has the potential to reduce disability associated with paralysis by translating neural activity into control of assistive devices
1
–
9
. Surveys of potential end-users have identified key BCI system features
10
–
14
, including high accuracy, minimal daily setup, rapid response times, and multifunctionality. These performance characteristics are primarily influenced by the BCI’s neural decoding algorithm
1
,
15
, which is trained to associate neural activation patterns with intended user actions. Here, we introduce a new deep neural network
16
decoding framework for BCI systems enabling discrete movements that addresses these four key performance characteristics. Using intracortical data from a participant with tetraplegia, we provide offline results demonstrating that our decoder is highly accurate, sustains this performance beyond a year without explicit daily retraining by combining it with an unsupervised updating procedure
3
,
17
–
20
, responds faster than competing methods
8
, and can increase functionality with minimal retraining by using a technique known as transfer learning
21
. We then show that our participant can use the decoder in real-time to reanimate his paralyzed forearm with functional electrical stimulation (FES), enabling accurate manipulation of three objects from the grasp and release test (GRT)
22
. These results demonstrate that deep neural network decoders can advance the clinical translation of BCI technology.
Intracortical activity data recorded over 2 years in a tetraplegic patient is used to develop an artificial intelligence algorithm that achieves fast, accurate, and stable movement decoding to reenable real-time control of the paralyzed forearm.
Journal Article