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Journal on Multimodal User Interfaces
Erschienen in: Journal on Multimodal User Interfaces 4/2015

01.12.2015 | Original Paper

Control of word processing environment using myoelectric signals

verfasst von: Antonín Pošusta, Adam J. Sporka, Ondřej Poláček, Šimon Rudolf, Jakub Otáhal

Erschienen in: Journal on Multimodal User Interfaces | Ausgabe 4/2015

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Abstract

This paper shows how myoelectric signals (EMG) can be used to generate control signals for further use in human–machine interfaces. Our custom-built portable USB device is able to capture multi-channel highspeed surface EMG signals from muscles and its software counterpart is capable to control common PC interface including ordinary text editors such as MS Word. At the time of the study the system utilized three parallel EMG channels to control user interfaces. The interaction was based on series of 1-of-N selections which specify rows and columns in on-screen keyboards. The selection was performed by quantification of selected muscle activity of the user. The system was further tested by a disabled person who provided input during a participatory design session. Our study has demonstrated that the system and the user interface can be used for effective text input and editing also in disabled people.
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Fußnoten
1
Thalmic Labs’ Myo is an example of commercially developed human interface device (HID) based on the EMG detection targeted on users with no disabilities to control their computer via gestures.
 
2
For instance Thalmic Labs’ Myo alpha version main purpose was to detect a set of discrete gestures rather than to provide a continuous stream of measurements at the time of the study. Current version offers 200 Hz data output.
 
3
The system allows up to 20 kHz.
 
Literatur
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Felzer T, Nordmann R (2006) Alternative text entry using different input methods. In: Proceedings of the 8th international ACM SIGACCESS conference on computers and accessibility, Assets ’06. ACM, New York, pp 10–17
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Pošusta A, Poláček O, Sporka A, Flek T, Otáhal J (2013) Text entry methods controlled by myoelectric signals. Bull Appl Mech 9:23–30
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Sporka AJ, Felzer T, Kurniawan SH, Poláček O, Haiduk P, MacKenzie IS (2011) Chanti: Predictive text entry using non-verbal vocal input. In: Proceedings of the SIGCHI conference on human factors in computing systems, CHI’11. ACM, New York, pp 2463–2472. doi:10.​1145/​1978942.​1979302
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Metadaten
Titel
Control of word processing environment using myoelectric signals
verfasst von
Antonín Pošusta
Adam J. Sporka
Ondřej Poláček
Šimon Rudolf
Jakub Otáhal
Publikationsdatum
01.12.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal on Multimodal User Interfaces / Ausgabe 4/2015
Print ISSN: 1783-7677
Elektronische ISSN: 1783-8738
DOI
https://doi.org/10.1007/s12193-015-0200-9

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