Keystroke recognition for virtual keyboard

The progress in the field of human-computer interaction with hand held electronic devices, such as, personal digital assistants (PDAs) and mobile phones searches for new interaction techniques. Proximity sensing extends the concept of computer-human interaction beyond actual physical contact with a...

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Bibliographic Details
Main Authors: Mantyjarvi, J., Koivumaki, J., Vuori, P.
Format: Conference Proceeding
Language:English
Subjects:
Application software
Fingers
Infrared detectors
Keyboards
Mobile handsets
Pattern recognition
Personal digital assistants
Transceivers
Transmitters
User interfaces
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Summary:The progress in the field of human-computer interaction with hand held electronic devices, such as, personal digital assistants (PDAs) and mobile phones searches for new interaction techniques. Proximity sensing extends the concept of computer-human interaction beyond actual physical contact with a device. In this paper, a virtual keyboard implementation is presented and keystroke recognition experiments with the keyboard utilizing proximity measurements are described. An infrared (IR) transceiver array is used for detecting the proximity of a finger. Keystroke recognition accuracy is examined with k-nearest neighbor (k-NN) classifier while a multilayer perceptron (MLP) classifier is designed for online implementation. Experiments and results of keystroke classification are presented for both classifiers. The recognition accuracy, which is between 78% and 99% for k-NN classifier and between 69% and 96% for MLP classifier, depends mainly on the location of a specific key on the keyboard area.
DOI:10.1109/ICME.2002.1035630