Zacytuj

M. Rashid et al., “Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review,” Frontiers in Neurorobotics, vol. 14. Frontiers Media S.A., Jun. 03, 2020, doi: 10.3389/fnbot.2020.00025; Search in Google Scholar

S. Natarajan, M. Karthikeyan, K. Rakesh, R. Balaji, and S. Babuk, “International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Brainwave-Controlled System for Home automation and Password Authentication; Search in Google Scholar

C. Author, Z. Anwar, H. Yanti, N. Apriola Susanto, A. Rachma, and V. Damayanti, “Online Mindfulness-Based Cognitive Therapy: Interventions to Increase Resilience of the Covid-19 Patients Through Cyberpsichology Approach,” Rev. Iberoam. Psicol. del Ejerc. y el Deport., vol. 17, no. 3, p. 3, 2022; Search in Google Scholar

X. Gu et al., “EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications,” Jan. 2020; Search in Google Scholar

R. Raj, S. Deb, and P. Bhattacharya, “Brain Computer Interfaced Single Key Omni Directional Pointing and Command System: A Screen Pointing Interface for Differently-abled Person,” in Procedia Computer Science, 2018, vol. 133, pp. 161–168, DOI: 10.1016/j.procs.2018.07.020. Search in Google Scholar

V. Raghav Varada, D. Moolchandani, and A. Rohit, “Measuring and Processing the Brain’s EEG Signals with Visual Feedback for Human Machine Interface,” Int. J. Sci. Eng. Res., vol. 4, no. 1, 2013; Search in Google Scholar

A. T. Infantes, F. A. Hurtado, F. S. Vera, and J. E. M. Guirao, “Mindfulness in Health Education: From Physical to Virtual Presence during the Pandemic, an Anthropological Study in Spain,” Sustain., vol. 14, no. 5, Mar. 2022, DOI: 10.3390/su14052547; Search in Google Scholar

B. Ülker, M. B. Tabakcioǧlu, H. Çizmeci, and D. Ayberkin, “Relations of attention and meditation level with learning in engineering education,” in Proceedings of the 9th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2017, Dec. 2017, vol. 2017-January, pp. 1-4, doi: 10.1109/ECAI.2017.8166407; Search in Google Scholar

A. Al Ozairi, D. Alsaeed, E. Al-Ozairi, M. Irshad, R. S. Crane, and A. Almoula, “Effectiveness of virtual mindfulness-based interventions on perceived anxiety and depression of physicians during the COVID-19 pandemic: A pre-post experimental study,” Front. Psychiatry, vol. 13, Jan. 2023, DOI: 10.3389/fpsyt.2022.1089147; Search in Google Scholar

A. Ali, R. Afridi, T. A. Soomro, S. A. Khan, M. Y. A. Khan, and B. S. Chowdhry, “A Single-Channel Wireless EEG Headset Enabled Neural Activities Analysis for Mental Healthcare Applications,” Wirel. Pers. Commun., vol. 125, no. 4, pp. 3699–3713, Aug. 2022, DOI: 10.1007/s11277-022-09731-w; Search in Google Scholar

T. Lomas, I. Ivtzan, and C. H. Y. Fu, “A systematic review of the neurophysiology of mindfulness on EEG oscillations,” Neurosci. Biobehav. Rev., vol. 57, pp. 401–410, Oct. 2015, doi: 10.1016/J.NEUBIOREV.2015.09.018. Search in Google Scholar

P. Arias-Cabarcos, T. Habrich, K. Becker, C. Becker, and T. Strufe, “Inexpensive brainwave authentication: New techniques and insights on user acceptance,” Proc. 30th USENIX Secur. Symp., no. 1, pp. 55–72, 2021; Search in Google Scholar

N. van Atteveldt, T. W. P. Janssen, and I. Davidesco, “Measuring Brain Waves in the Classroom,” Front. Young Minds, vol. 8, no. August 2020, doi: 10.3389/frym.2020.00096; Search in Google Scholar

O. Alshear, T. Hava, and K. Üniversitesi, “Brain Wave Sensors for Every Body Rbotic View project,” 2016, doi: 10.13140/RG.2.2.22223.69280; Search in Google Scholar

R. Rastogi, “Bharati Vidyapeeth’s Institute of Computer Applications and Management, A Novel Approach for Residential Society Maintenance Problem for Better Human Life View project Audio Visual EMG & GSR Biofeedback Analysis for Effect of Spiritual Techniques View project,” Accessed: Apr. 12, 2023; Search in Google Scholar

G. J. Siegel, B. W. Agranoff, R. W. Albers, S. K. Fisher, and M. D. Uhler, “Basic Neurochemistry,” Basic Neurochem. Mol. Cell. Med. Asp., pp. 1–13, 1999, Accessed: Apr. 12, 2023; Search in Google Scholar

G. Li and W. Y. Chung, “A context-aware EEG headset system for early detection of driver drowsiness,” Sensors, vol. 15, no. 8, pp. 20873-20893, Aug. 2015, DOI: 10.3390/s150820873; Search in Google Scholar

M. Tajdini, V. Sokolov, I. Kuzminykh, S. Shiaeles, and B. Ghita, “Wireless sensors for brain activity - A survey,” Electronics (Switzerland), vol. 9, no. 12. MDPI, pp. 1–26, Dec. 01, 2020, doi: 10.3390/electronics9122092; Search in Google Scholar

J. S. Poulsen, J. Kļonovs, and C. K. Petersen, “Title: Development of a Mobile EEG-Based Feature Extraction and Classification System for Biometric Authentication,” 2011; Search in Google Scholar

Z. Koudelková and M. Strmiska, “Introduction to the identification of brain waves based on their frequency,” MATEC Web Conf., vol. 210, pp. 1-4, 2018, DOI: 10.1051/matecconf/201821005012; Search in Google Scholar

N. K. Gajjar, “Electroencephalogram: Control Devices with Mind-Waves,” Int. J. Sci. Dev. Res., vol. 3, no. 10, 2018; Search in Google Scholar

NeuroSky website and product Information available at https://neurosky.com/biosensors/eeg-sensor/; Search in Google Scholar

Mindrove website and product information accesibile at https://mindrove.com/arc/; Search in Google Scholar

Brainaccess device can be accesed at the following website: https://www.brainaccess.ai/wp-content/uploads/downloads/UserManualHALO.pdf; Search in Google Scholar

Bitbrain headband was accessed at the following website: https://www.bitbrain.com/neurotechnology-products/semi-dry-eeg/versatile-eeg; Search in Google Scholar

OpenBCI - Ultracortex was accesed at https://shop.openbci.com/products/ultracortex-mark-iv?variant=43568404110; Search in Google Scholar

John LaRocco, Minh Dong Le, Dong-Guk Paeng,” A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection”, Front. Neuroinform., Vol. 14, 2020; Search in Google Scholar

NeurotechJP, Consumer BCI Review: 5 EEG Headsets for Developers, 08.05.2022, accesed online at https://neurotechjp.com/blog/5-bci-gadget-reviews/; Search in Google Scholar

Didar Dadebayev, Wei Wei Goh, Ee Xioh Tan, “EEG-based emotion recognition: Review of commercial EEG devices and machine learning techniques”, Journal of King Saud University - Computer and Information Sciences, Vol. 34, No. 7, 2022, pp. 4385-4401; Search in Google Scholar

Melida Racz, Erick Noboa, and others,” PlatypOUs-A Mobile Robot Platform and Demonstration Tool Supporting STEM Education”, Sensors 2022, 22(6) 2284; Search in Google Scholar

K. Jalab, J. Csipor and others,” EEG sensor system development consisting of solid polyvinyl alcohol-glycerol-NaCl contact gel and 3D-printed, silver-coated polylactic acid electrode for potential brain–computer interface use”, MaterialsToday - Chemistry, Vol. 26, 2022. Search in Google Scholar