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http://elartu.tntu.edu.ua/handle/lib/36651
Назва: | The methods of biosignals processing and their implementation in the structure of the system of impaired human communicative function compensation |
Автори: | Яворська, Євгенія Богданівна Дозорська, Оксана Федорівна Дозорський, Василь Григорович Паньків, Ірина Михайлівна Капаціла, Юрій Богданович Кубашок, Андрій |
Приналежність: | ТНТУ |
Бібліографічний опис: | Oksana Dozorska, Vasil Dozorskyi, Evhenia Yavorska, Yuriy Kapatsila, Iryna Pankiv, Andriy Kubashok. The methods of biosignals processing and their implementation in the structure of the system of impaired human communicative function compensation // ADVANCED APPLIED ENERGY and INFORMATION TECHNOLOGIES 2021. Proceedings of the International Conference (Ternopil, 15-17 of December 2021.) / Ministry of Education and Science of Ukraine, Ternopil Ivan Puluj National Technical Universtiy [and other.]. – Ternopil : TNTU, Zhytomyr : «Publishing house “Book-Druk”» LLC, 2021. – 222 c. |
Bibliographic description: | Oksana Dozorska, Vasil Dozorskyi, Evhenia Yavorska, Yuriy Kapatsila, Iryna Pankiv, Andriy Kubashok. The methods of biosignals processing and their implementation in the structure of the system of impaired human communicative function compensation // ADVANCED APPLIED ENERGY and INFORMATION TECHNOLOGIES 2021. Proceedings of the International Conference (Ternopil, 15-17 of December 2021.) / Ministry of Education and Science of Ukraine, Ternopil Ivan Puluj National Technical Universtiy [and other.]. – Ternopil : TNTU, Zhytomyr : «Publishing house “Book-Druk”» LLC, 2021. – 222 c. |
Дата публікації: | гру-2021 |
Дата подання: | 2021 |
Дата внесення: | 21-гру-2021 |
Видавництво: | TNTU, Zhytomyr : «Publishing house “Book-Druk”» LLC, 2021 |
Країна (код): | UA |
Місце видання, проведення: | ТНТУ |
Теми: | human communicative function compensation system processing methods spectral-correlation analysis electrodes block of biosignals selection |
Діапазон сторінок: | 151-157 |
Короткий огляд (реферат): | The methods of biosignals processing and structure of the system of impaired human communicative function compensation are proposed. The methods of biosignals processing are based on the application of spectralcorrelation analysis methods using the sliding window method and include preparatory and main stages. The sequence of steps of biosignals processing at the preparatory and main stages is substantiated. Also technical parameters and features of practical realization of constituent elements of the system of impaired human communicative function compensation are offered. The principle of operation of the system is based on the parallel selection and processing of electroencephalographic and electromyographic signals. At the same time the features of electrode constructions for selection of electroencephalographic signals, which are widespread today, as well as possible artifacts that will arise in the process of selection of these signals are analyzed. The design of electrodes for registration of electroencephalographic and electromyographic signals is proposed, the selection and processing of which is the basis of the method of indirect compensation of the impaired communicative function, which is realized by this system. A variant of realization of the functional diagram of the block of biosignals selection is proposed. The proposed design of the system of impaired human communicative function compensation can be manufactured using 3D printing technology, which will reduce its cost. |
URI (Уніфікований ідентифікатор ресурсу): | http://elartu.tntu.edu.ua/handle/lib/36651 |
ISBN: | 978-617-8079-60-4 |
Власник авторського права: | Яворська Є.Б., 2021 О.Ф. Дозорська, 2021 Дозорський В.Г., 2021 Паньків І.М., 2021 Капаціла Ю.Б., 2021 Кубашок А.В., 2021 |
Перелік літератури: | 1. Brigham, K., Vijaya Kumar B.V.K. (2010). Imagined Speech Classification with EEG Signals for Silent Communication: A Preliminary Investigation into Synthetic Telepathy. Bioinformatics and Biomedical Engineering, Proceedings of the 4th International Conference. Chengdu, China. 2. Porbadnigk, A., Wester, M., Schultz, T. (2009). EEG-Based Speech Recognition: Impact of Temporal Effects. Bio-inspired Systems and Signal, Processing, Proceedings of the 2nd International Conference. Porto. Portugal. 3. Meltzner, G.S., Heaton, J.T., Deng, Y., De Luca, G., Roy, S.H., Joshua, C. Kline. (2017). Silent Speech Recognition as an Alternative Communication Device for Persons with Laryngectomy. IEEE/ACM Trans Audio Speech Lang Process, Proceedings of the Conference. 4. Herff, C., Schultz, T. (2016). Automatic speech recognition from neural signals: A focused review. Frontiers in Neuroscience, 10, 1-7. 5. Wand, M., Schmidhuber, J. (2016). Deep Neural Network Frontend for Continuous EMG-based Speech Recognition. International Speech Communication Association (Interspeech), Proceedings of the 17th Annual Conference. San Francisco, USA. 6. Jorgensen, C., Lee, D.D., Agabon, S. (2003). Sub Auditory Speech Recognition Based on EMG/EPG Signals. Neural Networks, Proceedings of the International Joint Conference. 7. Khan, M., Jahan, M. (2016). Sub-vocal speech pattern recognition of Hindi alphabet with surface electromyography signal. Perspectives in Science, 8, 558-560. 8. Gonzalez, J.A., Cheah, L.A., Gilbert, J.M., Bai, J., Ell, S.R., Green, P.D., Moore, R.K. (2016). A silent speech system based on permanent magnet articulography and direct synthesis. Computer Speech & Language, 67–87. 9. Xueqian, J., Li, J., Du, Y. (2008). Unvoiced Speech Recognition Based on One-Channel Facial Myoelectric Signal. Intelligent Control and Automation, Proceedings of the Sixth World Congress. Dalian, China. 10. Sannykov, V. (2008). Syloj mysli. Populiarnaia mekhanika, 6(68), 72-75. (in Russian). 11. Dozorska, O. (2018). The mathematical model of electroenсephalographic and electromyographic signals for the task of human communicative function restoration. Scientific jornal of the Ternopil National Technical University, 92(4), 126–132. 12. Nykytyuk, V., Dozorskyi, V., Dozorska, O. (2018). Detection of biomedical signals disruption using a sliding window. Scientific jornal of the Ternopil National Technical University, 91(3), 125–133. |
Тип вмісту: | Conference Abstract |
Розташовується у зібраннях: | Наукові публікації працівників кафедри біотехнічних систем |
Файли цього матеріалу:
Файл | Опис | Розмір | Формат | |
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ICAAEIT-2021_proceedings.pdf | 21,53 MB | Adobe PDF | Переглянути/відкрити |
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