J
Jason Tyler Griffin
Researcher at BlackBerry Limited
Publications - 424
Citations - 11379
Jason Tyler Griffin is an academic researcher from BlackBerry Limited. The author has contributed to research in topics: Mobile device & Keypad. The author has an hindex of 55, co-authored 424 publications receiving 11379 citations.
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Patent
Hand-held electronic device with a keyboard optimized for use with the thumbs
TL;DR: In this article, a hand-held electronic device with a keyboard optimized for use with the thumbs is described, where the angles at which keys on either side of the keyboard are placed are complimentary.
Patent
Electronic device and method of displaying information in response to a gesture
Mihal Lazaridis,Daniel Tobias Rydenhag,Donald James Lindsay,Alistair Hamilton,Robert Simon Lessing,Jason Tyler Griffin,Joseph Eytan Benedek,Todd Andrew Wood +7 more
TL;DR: In this article, a gesture is detected on the touch-sensitive display, which gesture indicates a request to display information associated with a second application without opening the second application, and at least part of the information from the first application is displayed without opening it.
Patent
Portable electronic device including tactile touch-sensitive input device and method of protecting same
TL;DR: In this article, an actuating arrangement including a piezoelectric actuator for selectively receiving an applied voltage to apply a force to the touch-sensitive input assembly is presented.
Patent
Hand-held electronic device with auxiliary input device
Jason Tyler Griffin,John A. Holmes,Mihal Lazaridis,Herb Little,Harry R. Major,Craig A. Dunk,Michael Brown,Jerome Lang +7 more
TL;DR: In this article, a hand-held electronic device with a keyboard, a thumbwheel, display and associated software is optimized for use of the device with the thumbs, where the keys on the device keyboard are optimally shaped and configured for thumb-based input.
Patent
Text input system for a mobile electronic device and methods thereof
TL;DR: In this article, the location of a user's touch on the touch interface is detected and more than one letter may be identified based on the location, and predictive text software is used to determine which of the identified letters the user intended to select.