Human Communication Technology. Группа авторов

Читать онлайн книгу.

Human Communication Technology - Группа авторов


Скачать книгу
13,583.32 ± 24.17 3 11,156.19 ± 23.36 0.95 ± 0.02 11,157.14 ± 23.38 4 8,117.19 ± 21.29 0.97 ± 0.02 8,118.18 ± 21.31 5 7,912.86 ± 13.23 0.91 ± 0.02 7,913.77 ± 13.25
Test Speed reference latency Network latency Total latency
1 4,061.42 ± 17.32 0.99 ± 0.02 4,062.41 ± 17.34
2 5,282.33 ± 16.96 1.00 ± 0.02 5,283.33 ± 16.98
3 6,106.19 ± 42.46 0.97 ± 0.02 6,107.16 ± 82.94
4 7,217.19 ± 19.56 0.91 ± 0.02 7,218.10 ± 19.58
5 7,997.36 ± 13.23 0.98 ± 0.02 7,998.34 ± 13.25

      1. Schmitt, S.E., Pargeon, K., Frechette, E.S., Hirsch, L.J., Dalmau, J., Friedman, D., Extreme delta brush: A unique EEG pattern in adults with anti-NMDA receptor encephalitis. Neurology, 79, 11, 1094–1100, 2012.

      2. Sudharsan, R.R., Deny, J., Kumaran, E.M., Geege, A.S., An Analysis of Different Biopotential Electrodes Used for Electromyography. 12, 1, 1–7, 2020.

      3. Stanski, D.R., Pharmacodynamic modeling of anesthetic EEG drug effects. Annu. Rev. Pharmacol. Toxicol., 32, 1, 423–447, 1992.

      4. Gillin, J.C., Duncan, W., Pettigrew, K.D., Frankel, B.L., Snyder, F., Successful separation of depressed, normal, and insomniac subjects by EEG sleep data. Arch. Gen. Psychiatry, 36, 1, 85–90, 1979.

      5. Adler, G., Brassen, S., Jajcevic, A., EEG coherence in Alzheimer’s dementia. J. Neural Transm., 110, 9, 1051–1058, 2003.

      6. Sudharsan, R.R. and Deny, J., Field Programmable Gate Array (FPGA)-Based Fast and Low-Pass Finite Impulse Response (FIR) Filter, in: Intelligent Computing and Innovation on Data Science, pp. 199–206, 2020.

      7. Alvarez, L.A., Moshé, S.L., Belman, A.L., Maytal, J., Resnick, T.J., Keilson, M., EEG and brain death determination in children. Neurology, 38, 2, 227, 1988.

      8. Friedberg, J., Shock treatment, brain damage, and memory loss: A neurological perspective. Am. J. Psychiatry, 134, 9, 1010–1014, 1977.

      9. Waldert, S., Invasive vs. non-invasive neuronal signals for brain–machine interfaces: Will one prevail? Front. Neurosci., 10, 1–4, 2016.

      10. Burchiel, K.J., McCartney, S., Lee, A., Raslan, A.M., Accuracy of deep brain stimulation electrode placement using intraoperative computed tomography without microelectrode recording. J. Neurosurg., 119, 2, 301–306, 2013.

      11. Deny, J. and Sudharsan, R.R., Block Rearrangements and TSVs for a Standard Cell 3D IC Placement, in: Intelligent Computing and Innovation on Data Science, pp. 207–214, 2020.

      13. Onal, C. et al., Complications of invasive subdural grid monitoring in children with epilepsy. J. Neurosurg., 98, 5, 1017–1026, 2003.

      14. Ball, T., Kern, M., Mutschler, I., Aertsen, A., Schulze-Bonhage, A., Signal quality of simultaneously recorded invasive and non-invasive EEG. Neuroimage, 46, 3, 708–716, 2009.

      15. Pinegger, A., Wriessnegger, S.C., Faller, J., Müller-Putz, G.R., Evaluation of different EEG acquisition systems concerning their suitability for building a brain–computer interface: Case studies. Front. Neurosci., 10, 441, 2016.

      16. Alotaiby, T., El-Samie, F.E.A., Alshebeili, S.A., Ahmad, I., A review of channel selection algorithms for EEG signal processing. EURASIP J. Adv. Signal Process., 2015, 1, 66, 2015.

      17. Hidalgo-Muñoz, A.R., López, M.M., Santos, I.M., Vázquez-Marrufo, M., Lang, E.W., Tomé, A.M., Affective valence detection from EEG signals using wrapper methods. Emotion and Attention Recognition Based on Biological Signals and Images, 12, p. 23, 2017.

      18. Dash, M. and Liu, H., Feature selection for classification. Intell. Data Anal., 1, 131–156, 1997.

      19. Liu, H. and Yu, L., Toward integrating feature selection algorithms for classification and clustering. IEEE Trans. Knowl. Data Eng., 17, 491–502, 2005.

      20. Klimesch, W., EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Res. Rev., 29, 23, 169–195, 1999.

      21. Woehrle, H., Krell, M.M., Straube, S., Kim, S.K., Kirchner, E.A., Kirchner, F., An adaptive spatial filter for user-independent single trial detection of event-related potentials. IEEE Trans. Biomed. Eng., 62, 7, 1696–1705, 2015.

      22. Norcia, A.M., Appelbaum, L.G., Ales, J.M., Cottereau,


Скачать книгу