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Year 2020, , 35 - 46, 27.03.2020

Kutlucan Görür , Mehmet Recep Bozkurt , Muhammed Serdar Başçıl Feyzullah Temurtas

https://doi.org/10.18466/cbayarfbe.571994
Cited By: 1

Abstract

References

  • [1] Huo X., Ghovanloo M. 2012. Tongue Drive: A wireless tongue-operated means for people with severe disabilities to communicate their intentions; IEEE Comm. Magaz. 50(10):128-135.
  • [2] Andreasen Struijk L.N.S. 2006. An inductive tongue computer interface for control of computers and assistive devices. IEEE Trans. on Biomed. Engin; 53(12):2594-2597.
  • [3] Nam Y., Koo B., Cichocki A., Choi S. 2016 Glossokinetic Potentials for a tongue–machine interface. IEEE Systems, Man, & Cybernetics Magaz; 2(1): 6-13.
  • [4] Nam Y., Zhao Q., Cichocki A., Choi S. 2012. Tongue-Rudder: A Glossokinetic-Potential-Based tongue–machine interface. IEEE Trans. on Bio. Engin; 59(1): 290-299.
  • [5] Nam Y., Koo B., Cichocki A., Choi S. 2014. GOM-Face: GKP, EOG, and EMG-Based multimodal interface with application to humanoid robot control. IEEE Trans. on Biomed. Engin; 61(2):453-462.
  • [6] Tang H., Beebe D.J. 2006. An oral tactile interface for blind navigation. IEEE Trans On Neural Sys. and Rehab. Engin; 14(1):116-123.
  • [7] Bao X., Wang J., Hu J. 2009. Method of individual identification based on electroencephalogram analysis. Inter Conf on New Trends in Infor. and Ser. Sci; DOI: 10.1109/NISS.2009.44. 2009, pp.390-393.
  • [8] Gorur, K. Makine Öğrenmesi Algoritmaları Kullanılarak Glossokinetik Potansiyel Tabanlı Dil-Makine Arayüzü Tasarımı; Sakarya Üniversitesi Fen Bilimleri Enstitüsü: Doktora Tezi, Sakarya, 2019.
  • [9] Reuderink B., Poel M., Nijholt A. 2011. The impact of loss of control on movement BCIs. IEEE Trans on Neural Syst and Reha Engin; 19(6):628-637.
  • [10] Rupp, R, Rohm, M, Schneiders, M, Kreilinger, A, Müller-Putz, G.R. 2015. Functional rehabilitation of the paralyzed upper extremity after spinal cord injury by noninvasive hybrid neuroprostheses. Proceedings of the IEEE; 103(6):954-968.
  • [11] Krishnamurthy, G, Ghovanloo, M. Tongue Drive: A tongue operated magnetic sensor based wireless assistive technology for people with severe disabilities, IEEE International Symposium on Circuits and Systems, 2006, pp 5551-5554.
  • [12] Vaidyanathan, R, Chung, B, Gupta, L, Kook, H, Kota, S., West, J.D. 2007. Tongue-movement communication and control concept for hands-free human–machine interfaces. IEEE Systems, Man, & Cybernetics Magazine; 37(4):533-546.
  • [13] Vigário, R, Särelä, J, Jousmäki, V, Hämäläinen, M., Oja, E. 2000. Independent component approach to the analysis of EEG and MEG recordings. IEEE Transactions on Biomedical Engineering; 47(5):589-593.
  • [14] . Nam, Y, Bonkon, K, Choi, S. Language-related glossokinetic potentials on scalp, IEEE International conference on systems, Man, and Cybernetics, San Diego, USA, 2014, pp 1063-1067.
  • [15] Jayaram, V, Alamgir, M, Altun, Y, Schölkopf, B, GrosseWentrup, M. 2016. Transfer learning in brain-computer interfaces. IEEE Computational Intelligence Magazine; 20-31.
  • [16] Kao, J.C, Stavisky, S.D, Sussillo D, Nuyujukian, P, Shenoy K.V. 2014. Information systems opportunities in brain–machine interface decoders. Proceedings of the IEEE; 102(5):666-68.
  • [17] Cerutti, S. 2009. In the Spotlight: Biomedical signal processing. IEEE Reviews In Biomedical Enginering; 2:9-11.
  • [18] Genc, H.M, Cataltepe, Z, Pearson, T. A New PCA/ICA based feature selection method, IEEE Signal Processing and Communations Applications, Eskisehir, Turkey, 2007.
  • [19] . Gorur, K, Bozkurt M.R, Bascil M.S, Temurtas F. 2018. Glossokinetic potential based tongue–machine interface for 1-D extraction. Australasian Physical & Engineering Sciences in Medicine; 41(2):379-391.
  • [20] Gorur K, Bozkurt M.R, Bascil M.S, Temurtas F. 2018. Glossokinetic potential based tongue–machine interface for 1-D extraction using neural networks, Biocybernetics and Biomedical Engineering; 38(3):745-759.

Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses

Year 2020, , 35 - 46, 27.03.2020

Kutlucan Görür , Mehmet Recep Bozkurt , Muhammed Serdar Başçıl Feyzullah Temurtas

https://doi.org/10.18466/cbayarfbe.571994
Cited By: 1

Abstract

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The tongue-machine interface (TMI)
between the paralyzed person and computer makes possible to manage assistive
technologies. Severely disabled individuals caused by traumatic brain and
spinal cord injuries need continuous help to carry out everyday routines. The
cranial nerve is arisen directly from the brain to connect the tongue that is
one of the last affected organs in neuromuscular disorders. Besides, the tongue has highly
capable of mobility located in the oral cavity which also provides cosmetic
advantages. These crucial skills make the tongue to be an odd organ employed in
the human-machine interfaces. In this study, it was aimed to investigate 1-D
extraction and develop a novel tongue-machine interface using the glossokinetic
potential responses (GKPs). This rare used bio-signs are occurred by contacting
the buccal walls with the tip of the tongue in the oral cavity. Our study,
named as GKP-based TMI measuring the glossokinetic potential responses over the
scalp may serve paralyzed persons an unobtrusive, natural and reliable
communication channel. In this work, 8 males and 2 females, aged between 22-34
naive healthy subjects have participated. Linear discriminant analysis and
support vector machine were implemented with mean-absolute value and power
spectral density feature extraction process. Moreover independent component
analysis (ICA) and principal component analysis (PCA) were used to evaluate the
reduced dimension of the data set for GKPs in machine learning algorithms. And
the highest result was obtained as 97.03%. 

Keywords

Assistive Technologies Glossokinetic Potential Responses Independent Component Analysis Principal Component Analysis Tongue-Machine Interface

References

  • [1] Huo X., Ghovanloo M. 2012. Tongue Drive: A wireless tongue-operated means for people with severe disabilities to communicate their intentions; IEEE Comm. Magaz. 50(10):128-135.
  • [2] Andreasen Struijk L.N.S. 2006. An inductive tongue computer interface for control of computers and assistive devices. IEEE Trans. on Biomed. Engin; 53(12):2594-2597.
  • [3] Nam Y., Koo B., Cichocki A., Choi S. 2016 Glossokinetic Potentials for a tongue–machine interface. IEEE Systems, Man, & Cybernetics Magaz; 2(1): 6-13.
  • [4] Nam Y., Zhao Q., Cichocki A., Choi S. 2012. Tongue-Rudder: A Glossokinetic-Potential-Based tongue–machine interface. IEEE Trans. on Bio. Engin; 59(1): 290-299.
  • [5] Nam Y., Koo B., Cichocki A., Choi S. 2014. GOM-Face: GKP, EOG, and EMG-Based multimodal interface with application to humanoid robot control. IEEE Trans. on Biomed. Engin; 61(2):453-462.
  • [6] Tang H., Beebe D.J. 2006. An oral tactile interface for blind navigation. IEEE Trans On Neural Sys. and Rehab. Engin; 14(1):116-123.
  • [7] Bao X., Wang J., Hu J. 2009. Method of individual identification based on electroencephalogram analysis. Inter Conf on New Trends in Infor. and Ser. Sci; DOI: 10.1109/NISS.2009.44. 2009, pp.390-393.
  • [8] Gorur, K. Makine Öğrenmesi Algoritmaları Kullanılarak Glossokinetik Potansiyel Tabanlı Dil-Makine Arayüzü Tasarımı; Sakarya Üniversitesi Fen Bilimleri Enstitüsü: Doktora Tezi, Sakarya, 2019.
  • [9] Reuderink B., Poel M., Nijholt A. 2011. The impact of loss of control on movement BCIs. IEEE Trans on Neural Syst and Reha Engin; 19(6):628-637.
  • [10] Rupp, R, Rohm, M, Schneiders, M, Kreilinger, A, Müller-Putz, G.R. 2015. Functional rehabilitation of the paralyzed upper extremity after spinal cord injury by noninvasive hybrid neuroprostheses. Proceedings of the IEEE; 103(6):954-968.
  • [11] Krishnamurthy, G, Ghovanloo, M. Tongue Drive: A tongue operated magnetic sensor based wireless assistive technology for people with severe disabilities, IEEE International Symposium on Circuits and Systems, 2006, pp 5551-5554.
  • [12] Vaidyanathan, R, Chung, B, Gupta, L, Kook, H, Kota, S., West, J.D. 2007. Tongue-movement communication and control concept for hands-free human–machine interfaces. IEEE Systems, Man, & Cybernetics Magazine; 37(4):533-546.
  • [13] Vigário, R, Särelä, J, Jousmäki, V, Hämäläinen, M., Oja, E. 2000. Independent component approach to the analysis of EEG and MEG recordings. IEEE Transactions on Biomedical Engineering; 47(5):589-593.
  • [14] . Nam, Y, Bonkon, K, Choi, S. Language-related glossokinetic potentials on scalp, IEEE International conference on systems, Man, and Cybernetics, San Diego, USA, 2014, pp 1063-1067.
  • [15] Jayaram, V, Alamgir, M, Altun, Y, Schölkopf, B, GrosseWentrup, M. 2016. Transfer learning in brain-computer interfaces. IEEE Computational Intelligence Magazine; 20-31.
  • [16] Kao, J.C, Stavisky, S.D, Sussillo D, Nuyujukian, P, Shenoy K.V. 2014. Information systems opportunities in brain–machine interface decoders. Proceedings of the IEEE; 102(5):666-68.
  • [17] Cerutti, S. 2009. In the Spotlight: Biomedical signal processing. IEEE Reviews In Biomedical Enginering; 2:9-11.
  • [18] Genc, H.M, Cataltepe, Z, Pearson, T. A New PCA/ICA based feature selection method, IEEE Signal Processing and Communations Applications, Eskisehir, Turkey, 2007.
  • [19] . Gorur, K, Bozkurt M.R, Bascil M.S, Temurtas F. 2018. Glossokinetic potential based tongue–machine interface for 1-D extraction. Australasian Physical & Engineering Sciences in Medicine; 41(2):379-391.
  • [20] Gorur K, Bozkurt M.R, Bascil M.S, Temurtas F. 2018. Glossokinetic potential based tongue–machine interface for 1-D extraction using neural networks, Biocybernetics and Biomedical Engineering; 38(3):745-759.
There are 20 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Kutlucan Görür 0000-0003-3578-0150

Mehmet Recep Bozkurt 0000-0003-0673-4454

Muhammed Serdar Başçıl 0000-0002-6327-854X

Feyzullah Temurtas 0000-0002-3158-4032

Publication Date March 27, 2020
Published in Issue Year 2020

Cite

APA Görür, K., Bozkurt, M. R., Başçıl, M. S., Temurtas, F. (2020). Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses. Celal Bayar University Journal of Science, 16(1), 35-46. https://doi.org/10.18466/cbayarfbe.571994
AMA Görür K, Bozkurt MR, Başçıl MS, Temurtas F. Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses. CBUJOS. March 2020;16(1):35-46. doi:10.18466/cbayarfbe.571994
Chicago Görür, Kutlucan, Mehmet Recep Bozkurt, Muhammed Serdar Başçıl, and Feyzullah Temurtas. “Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses”. Celal Bayar University Journal of Science 16, no. 1 (March 2020): 35-46. https://doi.org/10.18466/cbayarfbe.571994.
EndNote Görür K, Bozkurt MR, Başçıl MS, Temurtas F (March 1, 2020) Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses. Celal Bayar University Journal of Science 16 1 35–46.
IEEE K. Görür, M. R. Bozkurt, M. S. Başçıl, and F. Temurtas, “Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses”, CBUJOS, vol. 16, no. 1, pp. 35–46, 2020, doi: 10.18466/cbayarfbe.571994.
ISNAD Görür, Kutlucan et al. “Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses”. Celal Bayar University Journal of Science 16/1 (March 2020), 35-46. https://doi.org/10.18466/cbayarfbe.571994.
JAMA Görür K, Bozkurt MR, Başçıl MS, Temurtas F. Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses. CBUJOS. 2020;16:35–46.
MLA Görür, Kutlucan et al. “Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses”. Celal Bayar University Journal of Science, vol. 16, no. 1, 2020, pp. 35-46, doi:10.18466/cbayarfbe.571994.
Vancouver Görür K, Bozkurt MR, Başçıl MS, Temurtas F. Comparative Evaluation for PCA and ICA on Tongue-Machine Interface Using Glossokinetic Potential Responses. CBUJOS. 2020;16(1):35-46.

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