Research Areas

Haptic Virtual Environments (HAVEs)

Haptic virtual environments (HAVEs) are haptically-mediated virtual worlds that interface the user via the sense of touch. They allow the user to feel his/her manipulation of a 3D object, for example, when probing it for its material properties (e.g., feel its roughness and weight) and verifying that an action is completed (e.g., feel the force exerted on a 3D snap button). Haptic interfaces enable the users to synergistically integrate information from their senses to make for richer sensorial experience. Finally, a networked HAVE can provide new ways for remote users to work together by supporting collaborative physical efforts such as moving a 3D desk jointly.

Despite these advantages, HAVEs still warrant further consideration to achieve a higher degree of realism and make a big impact in most fields. First, there has been a general lack of understanding of issues related to multimodal user interaction. Another contributing factor is the HAVE software development tools that do not address interaction at a high level and do not provide functionality specific to application domains. These two factors, in combination with other factors (e.g., technology, cost, etc.), have been hypothesized to be partly responsible for slowing the development and wide acceptance of HAVE applications.

Brain-Computer Interface (BCI)

How can we help people with severe motor disabilities (e.g., an amyotrophic lateral sclerosis (ALS) patient who is completely motor paralyzed, but still has intact sensory and cognitive brain functions) interact with the external environment? This solution can be enabled by detecting specific features of their brain activities (i.e., intents/thoughts) and translating them into physical commands which control the output devices. Brain-Computer Interface (BCI ) is a novel and promising communication channel for these physically disable people (e.g., people who are locked-in such as brainstem stroke, severe polyneuropathy, severe cerebral palsy, etc.).

HCI lab has taken the initiative to invest in research and development of the technology of brain-computer interface, including 1) noninvasive methods to monitor and obtain brain signals (e.g., electroencephalography, EEG), 2) effective signal processing methods that extract signal features (e.g., spatial and temporal filter, etc.), 3) innovative algorithms that translate these features into device commands (e.g., linear and non-linear classifiers, neural networks, etc.), and 4) the development and evaluation of potential applications (e.g., the selection of targets, letters, or icons, etc.). How would you feel if you can turn off the annoying alarm disturbing you early in the morning without even moving a single muscle of yours, but by just thinking to stop it?

Cognitive Ergonomics and usability engineering

Cognitive ergonomics focuses on the fit between human cognitive abilities and limitations and the machine, task, environment, etc. Cognitive ergonomics aim to enhance performance of cognitive tasks by means of several interventions, including:

  • user-centered design of human-computer interaction (HCI);
  • design of information technology systems that support cognitive tasks (e.g., cognitive artifacts);
  • development of training programs;
  • work redesign to manage cognitive workload and increase human reliability.

Adaptive and Intelligent Human-Computer Interaction

As the amount of information available to use grows exponentially, much attention has been paid to intelligent assistance to filter and coherently organize unrelated and scattered information, and finally help people respond effectively. Such rapid growth of the agent technology applications has generated a need for methods to systematically design interactions between human users and agents. When agents are used to support the delegated information processing on behalf of the human user, one major challenge is to identify the appropriate form of interaction between agents and the human user. However, few attempts have been made to understand and improve agent-assisted collaboration in team operations.

Ubiquitous Computing

As the cost of RFID tags drops, they are used for an increasing number of physical objects in the world. For example, cases of item-level tagging, i.e., attaching RFID tags to individual sales items, are emerging in the retail arena. Item-level tagging creates exciting opportunities to design applications for so-called “Internet of things.” However, there are serious privacy concerns about unobtrusive monitoring using ubiquitous RFID tags. There is a need for tools that support people to control their privacy boundaries and protect their privacy according to their needs.