Electromyography Based Translator of the Polish Sign Language

Noemi Kowalewska; Przemysław Łagodziński; Marcin Grzegorzek

doi:10.1007/978-3-030-23762-2_9

Electromyography Based Translator of the Polish Sign Language

Noemi Kowalewska^*, Przemysław Łagodziński, Marcin Grzegorzek

^*Corresponding author for this work

Institute of Medical Informatics

Abstract

Difficult problem is to facilitate the communication of a deaf person who communicates using sign language with a person who does not know such a way of conversation. A solution to problem may be to analyze hands movement in real time into written or spoken language. To achieve this, the experiment uses machine learning, which is used to recognize words in hand movements. It is also investigated what sensor combinations such as gyroscope, accelerometer, electromyograph give the best results. This work analyzes only a small part of all sign language words, but shows that much can be achieved by analyzing the hand movement itself. The project classified 18 words and with the proposed approach satisfactory results were obtained showing performance of 91%. It also presents problems that may arise when classifying the whole language.

Original language	English
Title of host publication	ITIB 2019: Information Technology in Biomedicine
Editors	Ewa Pietka, Pawel Badura, Jacek Kawa, Wojciech Wieclawek
Number of pages	10
Publisher	Springer, Cham
Publication date	26.06.2019
Pages	93-102
ISBN (Print)	978-3-030-23761-5
ISBN (Electronic)	978-3-030-23762-2
DOIs	https://doi.org/10.1007/978-3-030-23762-2_9
Publication status	Published - 26.06.2019
Event	7th International Conference on Information Technology in Biomedicine - Kamień Śląski, Poland Duration: 18.06.2019 → 20.06.2019 Conference number: 229749

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10.1007/978-3-030-23762-2_9

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title = "Electromyography Based Translator of the Polish Sign Language",

abstract = "Difficult problem is to facilitate the communication of a deaf person who communicates using sign language with a person who does not know such a way of conversation. A solution to problem may be to analyze hands movement in real time into written or spoken language. To achieve this, the experiment uses machine learning, which is used to recognize words in hand movements. It is also investigated what sensor combinations such as gyroscope, accelerometer, electromyograph give the best results. This work analyzes only a small part of all sign language words, but shows that much can be achieved by analyzing the hand movement itself. The project classified 18 words and with the proposed approach satisfactory results were obtained showing performance of 91%. It also presents problems that may arise when classifying the whole language.",

author = "Noemi Kowalewska and Przemys{\l}aw {\L}agodzi{\'n}ski and Marcin Grzegorzek",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 7th International Conference on Information Technology in Biomedicine<br/>, ITIB 2019 ; Conference date: 18-06-2019 Through 20-06-2019",

year = "2019",

month = jun,

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doi = "10.1007/978-3-030-23762-2_9",

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pages = "93--102",

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booktitle = "ITIB 2019: Information Technology in Biomedicine",

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Kowalewska, N, Łagodziński, P & Grzegorzek, M 2019, Electromyography Based Translator of the Polish Sign Language. in E Pietka, P Badura, J Kawa & W Wieclawek (eds), ITIB 2019: Information Technology in Biomedicine. Advances in Intelligent Systems and Computing, Springer, Cham, pp. 93-102, 7th International Conference on Information Technology in Biomedicine
, Kamień Śląski, Poland, 18.06.19. https://doi.org/10.1007/978-3-030-23762-2_9

Electromyography Based Translator of the Polish Sign Language. / Kowalewska, Noemi; Łagodziński, Przemysław; Grzegorzek, Marcin.
ITIB 2019: Information Technology in Biomedicine. ed. / Ewa Pietka; Pawel Badura; Jacek Kawa; Wojciech Wieclawek. Springer, Cham, 2019. p. 93-102 (Advances in Intelligent Systems and Computing).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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T1 - Electromyography Based Translator of the Polish Sign Language

AU - Kowalewska, Noemi

AU - Łagodziński, Przemysław

AU - Grzegorzek, Marcin

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N2 - Difficult problem is to facilitate the communication of a deaf person who communicates using sign language with a person who does not know such a way of conversation. A solution to problem may be to analyze hands movement in real time into written or spoken language. To achieve this, the experiment uses machine learning, which is used to recognize words in hand movements. It is also investigated what sensor combinations such as gyroscope, accelerometer, electromyograph give the best results. This work analyzes only a small part of all sign language words, but shows that much can be achieved by analyzing the hand movement itself. The project classified 18 words and with the proposed approach satisfactory results were obtained showing performance of 91%. It also presents problems that may arise when classifying the whole language.

AB - Difficult problem is to facilitate the communication of a deaf person who communicates using sign language with a person who does not know such a way of conversation. A solution to problem may be to analyze hands movement in real time into written or spoken language. To achieve this, the experiment uses machine learning, which is used to recognize words in hand movements. It is also investigated what sensor combinations such as gyroscope, accelerometer, electromyograph give the best results. This work analyzes only a small part of all sign language words, but shows that much can be achieved by analyzing the hand movement itself. The project classified 18 words and with the proposed approach satisfactory results were obtained showing performance of 91%. It also presents problems that may arise when classifying the whole language.

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A2 - Pietka, Ewa

A2 - Badura, Pawel

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PB - Springer, Cham

T2 - 7th International Conference on Information Technology in Biomedicine<br/>

Y2 - 18 June 2019 through 20 June 2019

ER -

Electromyography Based Translator of the Polish Sign Language

Abstract

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