Though many paradigms have been developed to study multitasking using eye tracking, most traditional applications of eye tracking are not used in real time, but instead to augment training or simply to observe optimal strategies. As eye tracking methods become more popular, they have been applied in the field of human-computer interaction and usability, as well as human-robot interaction. Recent real-time eye tracking assistance systems have focused on specific domains such as training, evaluation, or basic hypothesis testing in areas such as medical imaging, security, and aviation.
EyeFrame successfully addresses the need for domain-general multitasking assistance. EyeFrame allows the user to program sensory cues on a screen display which direct the user’s attention to neglected areas of the screen. These neglected areas are determined from real-time attention data gathered by an input device, such as a mouse or an eye tracker. EyeFrame is an assistive system for managing multiple visual tasks, which is domain-general, transparent, intuitive, non-interfering, non-command, improves control (without replacing direct control), and adaptively extrapolates to a variety of circumstances.
TECHNOLOGY DESCRIPTION
ADVANTAGES
• Provides real-time sensory feedback to improve multi-tasking
• Delegates short-term working memory to computer, reducing repeated decisions by user by one per second
• Domain-general, so may be used in diverse applications and settings (e.g. computer screen, dashboard, windshield)
• Accepts variety of input devices: mouse, eye tracker, touch screen, keyboard
PRODUCT OPPORTUNITIES
• Medical imaging analysis
• Aircraft and motor vehicle operation
• Training software
• Surveillance
ABOUT THE INVENTOR
Dr. Siegelmann, a recognized expert in Complex Systems and Neural Networks, focuses on theoretical computational neuroscience, computation in and modeling of natural systems and their application to intelligent systems. Of particular research interest are intelligence vis-a-vis adaptive memory, advanced models of cognition, and evolving, intelligent interfaces for robotics and other intelligent systems. Her studies often involve multi-scale modeling and system level analysis of major disorders such as cancer. The creator of a new field of computer science, Super-Turing computation, Dr. Siegelmann is applying the theory to biological systems and exploring them in connection with a new generation of analog computer.
AVAILABILITY:
Available for Licensing and/or Sponsored Research
DOCKET:
UMA 16-040
PATENT STATUS:
Patent Pending
NON-CONFIDENTIAL INVENTION DISCLOSURE
LEAD INVENTOR:
Hava Siegelmann, Ph.D.
CONTACT: