A Method to Extend Functionality of Pointer Input Devices
We describe a general method for extending any pointer input device with an arbitrary set of commands. The proposed interface can be trained by the user to recognize certain cursor movement patterns and interpret them as special input events. Methods for extraction and recognition of such patterns are general enough to work with low-precision pointing devices, and they can be adjusted to provide computer access for people with disabilities. The core of the system is a trainable classifier, in the current implementation an artificial neural network. The architecture of the neural network automatically adjusts according to complexity of the classification task. The system demonstrated good accuracy and responsiveness during extensive experiments. Some tests included a severely motion-impaired individual.
KeywordsArtificial Neural Network Hide Node Input Device Interarrival Time Pointer Input
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