5,809 research outputs found
VIF: Virtual Interactive Fiction (with a twist)
Nowadays computer science can create digital worlds that deeply immerse
users; it can also process in real time brain activity to infer their inner
states. What marvels can we achieve with such technologies? Go back to
displaying text. And unfold a story that follows and molds users as never
before.Comment: Pervasive Play - CHI '16 Workshop, May 2016, San Jose, United State
GTmoPass: Two-factor Authentication on Public Displays Using Gaze-touch Passwords and Personal Mobile Devices
As public displays continue to deliver increasingly private and personalized content, there is a need to ensure that only the legitimate users can access private information in sensitive contexts. While public displays can adopt similar authentication concepts like those used on public terminals (e.g., ATMs), authentication in public is subject to a number of risks. Namely, adversaries can uncover a user's password through (1) shoulder surfing, (2) thermal attacks, or (3) smudge attacks. To address this problem we propose GTmoPass, an authentication architecture that enables Multi-factor user authentication on public displays. The first factor is a knowledge-factor: we employ a shoulder-surfing resilient multimodal scheme that combines gaze and touch input for password entry. The second factor is a possession-factor: users utilize their personal mobile devices, on which they enter the password. Credentials are securely transmitted to a server via Bluetooth beacons. We describe the implementation of GTmoPass and report on an evaluation of its usability and security, which shows that although authentication using GTmoPass is slightly slower than traditional methods, it protects against the three aforementioned threats
Co-adaptive control strategies in assistive Brain-Machine Interfaces
A large number of people with severe motor disabilities cannot access any of the
available control inputs of current assistive products, which typically rely on residual
motor functions. These patients are therefore unable to fully benefit from existent
assistive technologies, including communication interfaces and assistive robotics. In
this context, electroencephalography-based Brain-Machine Interfaces (BMIs) offer a
potential non-invasive solution to exploit a non-muscular channel for communication
and control of assistive robotic devices, such as a wheelchair, a telepresence
robot, or a neuroprosthesis. Still, non-invasive BMIs currently suffer from limitations,
such as lack of precision, robustness and comfort, which prevent their practical
implementation in assistive technologies.
The goal of this PhD research is to produce scientific and technical developments
to advance the state of the art of assistive interfaces and service robotics based on
BMI paradigms. Two main research paths to the design of effective control strategies
were considered in this project. The first one is the design of hybrid systems, based on
the combination of the BMI together with gaze control, which is a long-lasting motor
function in many paralyzed patients. Such approach allows to increase the degrees
of freedom available for the control. The second approach consists in the inclusion
of adaptive techniques into the BMI design. This allows to transform robotic tools and
devices into active assistants able to co-evolve with the user, and learn new rules of
behavior to solve tasks, rather than passively executing external commands.
Following these strategies, the contributions of this work can be categorized
based on the typology of mental signal exploited for the control. These include:
1) the use of active signals for the development and implementation of hybrid eyetracking
and BMI control policies, for both communication and control of robotic
systems; 2) the exploitation of passive mental processes to increase the adaptability
of an autonomous controller to the user\u2019s intention and psychophysiological state,
in a reinforcement learning framework; 3) the integration of brain active and passive
control signals, to achieve adaptation within the BMI architecture at the level of
feature extraction and classification
Interactive form creation: exploring the creation and manipulation of free form through the use of interactive multiple input interface
Most current CAD systems support only the two most common input devices: a mouse and a keyboard that impose a limit to the degree of interaction that a user can have with the system. However, it is not uncommon for users to work together on the same computer during a collaborative task. Beside that, people tend to use both hands to manipulate 3D objects; one hand is used to orient the object while the other hand is used to perform some operation on the object. The same things could be applied to computer modelling in the conceptual phase of the design process. A designer can rotate and position an object with one hand, and manipulate the shape [deform it] with the other hand. Accordingly, the 3D object can be easily and intuitively changed through interactive manipulation of both hands.The research investigates the manipulation and creation of free form geometries through the use of interactive interfaces with multiple input devices. First the creation of the 3D model will be discussed; several different types of models will be illustrated. Furthermore, different tools that allow the user to control the 3D model interactively will be presented. Three experiments were conducted using different interactive interfaces; two bi-manual techniques were compared with the conventional one-handed approach. Finally it will be demonstrated that the use of new and multiple input devices can offer many opportunities for form creation. The problem is that few, if any, systems make it easy for the user or the programmer to use new input devices
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