Keystroke recognition for virtual keyboard

Jani Mantyjarvi, Jussi Koivumaki, Petri Vuori

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

32 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings - 2002 IEEE International Conference on Multimedia and Expo, ICME 2002
PublisherIEEE Institute of Electrical and Electronic Engineers
Number of pages4
ISBN (Print)0-7803-7304-9
Publication statusPublished - 1 Jan 2002
MoE publication typeA4 Article in a conference publication
Event2002 IEEE International Conference on Multimedia and Expo, ICME 2002 - Lausanne, Switzerland
Duration: 26 Aug 200229 Aug 2002


Conference2002 IEEE International Conference on Multimedia and Expo, ICME 2002


Dive into the research topics of 'Keystroke recognition for virtual keyboard'. Together they form a unique fingerprint.

Cite this