A Wearable Device-Based System: The Potential Role in Real-time and Remote EEG Monitoring
,
Abstract
Purpose: In recent years, the Electroencephalography (EEG)-based Brain-Computer Interface (BCI) appli-cation has been growing rapidly and has emerged as a technology with high translational potential since it allows disabled people to translate human intentions into control signals and to interact with the external environment without any kinesthetic movement. Individuals with significant health problems can benefit from this technology to improve their independence and facilitate participation in activities, thus improving general well-being and preventing impairments. The rapid advances in technology have led to optimal innovation in the context of wearable health monitoring and remote control solutions. Many wearable devices for capturing EEG signals in daily life have recently been released on the market. Our paper aims to present a wearable de-vice-based system for real-time and remote EEG monitoring, to describe the proposed system modules and the signal processing algorithms, to explore the functionalities of this wearable EEG solution, and to suggest its potential application for daily brain data recordings in the home en-vironment.
Materials and Methods: The validity of the Emotiv Epoc+ device in the continuous and real-time EEG signals acquisition and monitoring was demonstrated by means of preliminary test measurements during a resting state paradigm performed by a healthy control subject.
Results: Our findings confirmed the Epoc+ reliability for event-related brain potential research and in measuring acceptable spectral EEG data.
Conclusion: The described approach, focusing on the emerging area of remote monitoring sensors and wearable device applications, might be leveraged to measure complex health outcomes in non-specialist and remote settings.
1- Emma M. Smith et al., "Assistive Technology Use and Provision During COVID-19: Results From a Rapid Global Survey." International Journal of Health Policy and Management, Vol. 11 (No. 6), pp. 747-56, (2022).
2- Arrigo Palumbo, Vera Gramigna, Barbara Calabrese, and Nicola Ielpo, "Motor-Imagery EEG-Based BCIs in Wheelchair Movement and Control: A Systematic Literature Review." Sensors, Vol. 21 (No. 18), p. 6285, (2021).
3- A. Lau-Zhu, M. P. H. Lau, and G. McLoughlin, "Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges." (in eng), Dev Cogn Neurosci, Vol. 36, p. 100635, Apr. (2019).
4- Lun-De Liao et al., "Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors." Journal of NeuroEngineering and Rehabilitation, Vol. 9 (No. 1), p. 5, 2012/01/28 (2012).
5- Alfred Lim, Wai Chia, and Siew Chin, A mobile driver safety system: Analysis of single-channel EEG on drowsiness detection. (2015).
6- B. Byrom, M. McCarthy, P. Schueler, and W. Muehlhausen, "Brain Monitoring Devices in Neuroscience Clinical Research: The Potential of Remote Monitoring Using Sensors, Wearables, and Mobile Devices." (in eng), Clin Pharmacol Ther, Vol. 104 (No. 1), pp. 59-71, Jul. (2018).
7- Qing Zhang et al., "A real-time wireless wearable electroencephalography system based on Support Vector Machine for encephalopathy daily monitoring." International Journal of Distributed Sensor Networks, Vol. 14 (No. 5), p. 1550147718779562, (2018).
8- Alexander J. Casson, "Wearable EEG and beyond." Biomedical Engineering Letters, Vol. 9 (No. 1), pp. 53-71, 2019/02/01 (2019).
9- N. A. Badcock et al., "Validation of the Emotiv EPOC EEG system for research quality auditory event-related potentials in children." (in eng), Peer J, Vol. 3, p. e907, (2015).
10- N. A. Badcock, P. Mousikou, Y. Mahajan, P. de Lissa, J. Thie, and G. McArthur, "Validation of the Emotiv EPOC(®) EEG gaming system for measuring research quality auditory ERPs." (in eng), PeerJ, Vol. 1, p. e38, (2013).
11- M. Duvinage, T. Castermans, M. Petieau, T. Hoellinger, G. Cheron, and T. Dutoit, "Performance of the Emotiv Epoc headset for P300-based applications." (in eng), Biomed Eng Online, Vol. 12p. 56, Jun 25 (2013).
12- Edmund Wascher, Holger Heppner, and Sven Hoffmann, "Towards the measurement of event-related EEG activity in real-life working environments." International journal of psychophysiology: official journal of the International Organization of Psychophysiology, Vol. 91, pp. 3-9, (2014).
13- R. Maskeliunas, R. Damasevicius, I. Martisius, and M. Vasiljevas, "Consumer-grade EEG devices: are they usable for control tasks?" (in eng), PeerJ, Vol. 4, p. e1746, (2016).
14- Olave E. Krigolson, Chad C. Williams, Angela Norton, Cameron D. Hassall, and Francisco L. Colino, "Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research." (in English), Frontiers in Neuroscience, Methods Vol. 112017-March-10 (2017).
15- Jonathan W. P. Kuziek, Axita Shienh, and Kyle E. Mathewson, "Transitioning EEG experiments away from the laboratory using a Raspberry Pi 2." Journal of Neuroscience Methods, Vol. 277, pp. 75-82, 2017/02/01/ (2017).
16- Ekaterina Kutafina, Alexander Brenner, Yannic Titgemeyer, Rainer Surges, and Stephan Jonas, "Comparison of mobile and clinical EEG sensors through resting state simultaneous data collection." PeerJ, Vol. 8, p. e8969, 2020/05/01 (2020).
17- Mai Thuong Duong and Thi Hanh Phuc Nong, "Building an EEG-based BCI systems for Remote Device Control using CNN network " American Journal of Engineering Research, Researche Paper Vol. 10 (No. 6), pp. 123-30, (2021).
18- A. Biondi et al., "Remote and Long-Term Self-Monitoring of Electroencephalographic and Noninvasive Measurable Variables at Home in Patients With Epilepsy (EEG@HOME): Protocol for an Observational Study." (in eng), JMIR Res Protoc, Vol. 10 (No. 3), p. e25309, Mar. 19 (2021).
19- Cedric Cannard, Tracy Brandmeyer, Helané Wahbeh, and Arnaud Delorme, "Chapter 16 - Self-health monitoring and wearable neurotechnologies." in Handbook of Clinical Neurology, Vol. 168, Nick F. Ramsey and José del R. Millán, Eds.: Elsevier, (2020), pp. 207-32.
20- Christoph M. Michel, Micah M. Murray, Göran Lantz, Sara Gonzalez, Laurent Spinelli, and Rolando Grave de Peralta, "EEG source imaging." Clinical Neurophysiology, Vol. 115 (No. 10), pp. 2195-222, 2004/10/01/ (2004).
21- H. Jasper H, "The ten twenty electrode system of the international federation." Electroencephalography and Clinical Neurophysiology, Vol. 10, pp. 371-75, 1958 (1958).
22- G. H. Klem, H. O. Lüders, H. H. Jasper, and C. Elger, "The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology." (in eng), Electroencephalogr Clin Neurophysiol Suppl, Vol. 52, pp. 3-6, (1999).
23- Paul L. Nunez and Ramesh Srinivasan, Electric Fields of the Brain: The neurophysics of EEG. Oxford University Press, (2006).
24- Andrzej Cichocki and Saeid Sanei, "EEG/MEG Signal Processing." Comput. Intell. Neurosci., Vol. 2007/ (2007).
25- SIMpLE Project. Available online: https://biomedical.arrigopalumbo.com/progetto-simple/ (accessed on 7 August 2021).
26- Arrigo Palumbo et al., "SIMpLE: A Mobile Cloud-Based System for Health Monitoring of People with ALS." Sensors, Vol. 21 (No. 21), p. 7239, (2021).
27- A. Palumbo, B. Calabrese, N. Ielpo, A. Demeco, A. Ammendolia, and D. Corchiola, "Cloud-based biomedical system for remote monitoring of ALS patients." in 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), (2020), pp. 1469-76.
28- Emotiv Epoc+. Available online: https://www.emotiv.com/epoc/ (accessed on 13 February 2022).
29- EmotivPro. Available online: https://emotiv.gitbook.io/emotivpro-v2-0/ (accessed on 13 February 2022).
30- Yannic Titgemeyer et al., "Can commercially available wearable EEG devices be used for diagnostic purposes? An explorative pilot study." Epilepsy & Behavior, Vol. 103, p. 106507, 2020/02/01/ (2020).
31- P. de Lissa, S. Sörensen, N. Badcock, J. Thie, and G. McArthur, "Measuring the face-sensitive N170 with a gaming EEG system: A validation study." (in eng), J Neurosci Methods, Vol. 253, pp. 47-54, Sep. 30 (2015).
32- Kirill Stytsenko, Evaldas Jablonskis, and Cosima Prahm, "Evaluation of consumer EEG device Emotiv EPOC." (2011).
33- Jijun Tong, Peng Zhang, Ran Xiao, and Lei Ding, "The portable P300 dialing system based on tablet and Emotiv Epoc headset." (in eng), Annu Int Conf IEEE Eng Med Biol Soc, Vol. 2015, pp. 566-9, Aug. (2015).
34- C. Ashby, A. Bhatia, F. Tenore, and J. Vogelstein, "Low-cost electroencephalogram (EEG) based authentication." in 2011 5th International IEEE/EMBS Conference on Neural Engineering, (2011), pp. 442-45.
35- Bongjae Choi and Sungho Jo, "A Low-Cost EEG System-Based Hybrid Brain-Computer Interface for Humanoid Robot Navigation and Recognition." PLOS ONE, Vol. 8 (No. 9), p. e74583, (2013).
36- Y. Wang, Z. Wang, W. Clifford, C. Markham, T. E. Ward, and C. Deegan, "Validation of low-cost wireless EEG system for measuring event-related potentials." in 2018 29th Irish Signals and Systems Conference (ISSC), (2018), pp. 1-6.
37- g.tec. “g.USBamp EEG amplifier”. Available: https://www.gtec.at/product-configurator/g-usbamp/ .
38- Didar Dadebayev, Wei Wei Goh, and Ee Xion 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), pp. 4385-401, 2022/07/01/ (2022).
39- N. S. Williams, G. M. McArthur, B. de Wit, G. Ibrahim, and N. A. Badcock, "A validation of Emotiv EPOC Flex saline for EEG and ERP research." (in eng), PeerJ, Vol. 8, p. e9713, (2020).
40- A. Delorme and S. Makeig, "EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis." (in eng), J Neurosci Methods, Vol. 134 (No. 1), pp. 9-21, Mar. 15 (2004).
41- R. Oostenveld, P. Fries, E. Maris, and J. M. Schoffelen, "FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data." (in eng), Comput Intell Neurosci, Vol. 2011, p. 156869, (2011).
42- Sarah Blum, Nadine S. J. Jacobsen, Martin G. Bleichner, and Stefan Debener, "A Riemannian Modification of Artifact Subspace Reconstruction for EEG Artifact Handling." (in English), Frontiers in Human Neuroscience, Original Research Vol. 132019-April-26 (2019).
43- C. Y. Chang, S. H. Hsu, L. Pion-Tonachini, and T. P. Jung, "Evaluation of Artifact Subspace Reconstruction for Automatic Artifact Components Removal in Multi-Channel EEG Recordings." (in eng), IEEE Trans Biomed Eng, Vol. 67 (No. 4), pp. 1114-21, Apr (2020).
44- Cleaning Raw EEG Data. Available online: https://github.com/sccn/clean_rawdata. (accessed on 30 March 2023).
45- EEGLAB extensions and plugins. https://sccn.ucsd.edu/wiki/EEGLAB_Extensions. (accessed on 30 March 2023).
46- A. Palumbo et al., "An Embedded System for EEG Acquisition and Processing for Brain Computer Interface Applications." in Wearable and Autonomous Biomedical Devices and Systems for Smart Environment: Issues and Characterization, Aimé Lay-Ekuakille and Subhas Chandra Mukhopadhyay, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, (2010), pp. 137-54.
47- Arrigo Palumbo, Nicola Ielpo, and Barbara Calabrese, "An FPGA-Embedded Brain-Computer Interface System to Support Individual Autonomy in Locked-In Individuals." Sensors, Vol. 22 (No. 1), p. 318, (2022).
48- Arrigo Palumbo, Patrizia Vizza, Barbara Calabrese, and Nicola Ielpo, "Biopotential Signal Monitoring Systems in Rehabilitation: A Review." Sensors, Vol. 21 (No. 21), p. 7172, (2021).
49- N. Ielpo et al., "EMG-Miner: Automatic Acquisition and Processing of Electromyographic Signals: First Experimentation in a Clinical Context for Gait Disorders Evaluation." in 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, (2014), pp. 441-46.
50- Mahsa Soufineyestani, Dale Dowling, and Arshia Khan, "Electroencephalography (EEG) Technology Applications and Available Devices." Applied Sciences, Vol. 10 (No. 21), p. 7453, (2020).
51- Rodrigo Ramele, Ana Julia Villar, and Juan Miguel Santos, "Report: EPOC Emotiv EEG Basics." arXiv preprint arXiv:2206.09051, (2022).
2- Arrigo Palumbo, Vera Gramigna, Barbara Calabrese, and Nicola Ielpo, "Motor-Imagery EEG-Based BCIs in Wheelchair Movement and Control: A Systematic Literature Review." Sensors, Vol. 21 (No. 18), p. 6285, (2021).
3- A. Lau-Zhu, M. P. H. Lau, and G. McLoughlin, "Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges." (in eng), Dev Cogn Neurosci, Vol. 36, p. 100635, Apr. (2019).
4- Lun-De Liao et al., "Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors." Journal of NeuroEngineering and Rehabilitation, Vol. 9 (No. 1), p. 5, 2012/01/28 (2012).
5- Alfred Lim, Wai Chia, and Siew Chin, A mobile driver safety system: Analysis of single-channel EEG on drowsiness detection. (2015).
6- B. Byrom, M. McCarthy, P. Schueler, and W. Muehlhausen, "Brain Monitoring Devices in Neuroscience Clinical Research: The Potential of Remote Monitoring Using Sensors, Wearables, and Mobile Devices." (in eng), Clin Pharmacol Ther, Vol. 104 (No. 1), pp. 59-71, Jul. (2018).
7- Qing Zhang et al., "A real-time wireless wearable electroencephalography system based on Support Vector Machine for encephalopathy daily monitoring." International Journal of Distributed Sensor Networks, Vol. 14 (No. 5), p. 1550147718779562, (2018).
8- Alexander J. Casson, "Wearable EEG and beyond." Biomedical Engineering Letters, Vol. 9 (No. 1), pp. 53-71, 2019/02/01 (2019).
9- N. A. Badcock et al., "Validation of the Emotiv EPOC EEG system for research quality auditory event-related potentials in children." (in eng), Peer J, Vol. 3, p. e907, (2015).
10- N. A. Badcock, P. Mousikou, Y. Mahajan, P. de Lissa, J. Thie, and G. McArthur, "Validation of the Emotiv EPOC(®) EEG gaming system for measuring research quality auditory ERPs." (in eng), PeerJ, Vol. 1, p. e38, (2013).
11- M. Duvinage, T. Castermans, M. Petieau, T. Hoellinger, G. Cheron, and T. Dutoit, "Performance of the Emotiv Epoc headset for P300-based applications." (in eng), Biomed Eng Online, Vol. 12p. 56, Jun 25 (2013).
12- Edmund Wascher, Holger Heppner, and Sven Hoffmann, "Towards the measurement of event-related EEG activity in real-life working environments." International journal of psychophysiology: official journal of the International Organization of Psychophysiology, Vol. 91, pp. 3-9, (2014).
13- R. Maskeliunas, R. Damasevicius, I. Martisius, and M. Vasiljevas, "Consumer-grade EEG devices: are they usable for control tasks?" (in eng), PeerJ, Vol. 4, p. e1746, (2016).
14- Olave E. Krigolson, Chad C. Williams, Angela Norton, Cameron D. Hassall, and Francisco L. Colino, "Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research." (in English), Frontiers in Neuroscience, Methods Vol. 112017-March-10 (2017).
15- Jonathan W. P. Kuziek, Axita Shienh, and Kyle E. Mathewson, "Transitioning EEG experiments away from the laboratory using a Raspberry Pi 2." Journal of Neuroscience Methods, Vol. 277, pp. 75-82, 2017/02/01/ (2017).
16- Ekaterina Kutafina, Alexander Brenner, Yannic Titgemeyer, Rainer Surges, and Stephan Jonas, "Comparison of mobile and clinical EEG sensors through resting state simultaneous data collection." PeerJ, Vol. 8, p. e8969, 2020/05/01 (2020).
17- Mai Thuong Duong and Thi Hanh Phuc Nong, "Building an EEG-based BCI systems for Remote Device Control using CNN network " American Journal of Engineering Research, Researche Paper Vol. 10 (No. 6), pp. 123-30, (2021).
18- A. Biondi et al., "Remote and Long-Term Self-Monitoring of Electroencephalographic and Noninvasive Measurable Variables at Home in Patients With Epilepsy (EEG@HOME): Protocol for an Observational Study." (in eng), JMIR Res Protoc, Vol. 10 (No. 3), p. e25309, Mar. 19 (2021).
19- Cedric Cannard, Tracy Brandmeyer, Helané Wahbeh, and Arnaud Delorme, "Chapter 16 - Self-health monitoring and wearable neurotechnologies." in Handbook of Clinical Neurology, Vol. 168, Nick F. Ramsey and José del R. Millán, Eds.: Elsevier, (2020), pp. 207-32.
20- Christoph M. Michel, Micah M. Murray, Göran Lantz, Sara Gonzalez, Laurent Spinelli, and Rolando Grave de Peralta, "EEG source imaging." Clinical Neurophysiology, Vol. 115 (No. 10), pp. 2195-222, 2004/10/01/ (2004).
21- H. Jasper H, "The ten twenty electrode system of the international federation." Electroencephalography and Clinical Neurophysiology, Vol. 10, pp. 371-75, 1958 (1958).
22- G. H. Klem, H. O. Lüders, H. H. Jasper, and C. Elger, "The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology." (in eng), Electroencephalogr Clin Neurophysiol Suppl, Vol. 52, pp. 3-6, (1999).
23- Paul L. Nunez and Ramesh Srinivasan, Electric Fields of the Brain: The neurophysics of EEG. Oxford University Press, (2006).
24- Andrzej Cichocki and Saeid Sanei, "EEG/MEG Signal Processing." Comput. Intell. Neurosci., Vol. 2007/ (2007).
25- SIMpLE Project. Available online: https://biomedical.arrigopalumbo.com/progetto-simple/ (accessed on 7 August 2021).
26- Arrigo Palumbo et al., "SIMpLE: A Mobile Cloud-Based System for Health Monitoring of People with ALS." Sensors, Vol. 21 (No. 21), p. 7239, (2021).
27- A. Palumbo, B. Calabrese, N. Ielpo, A. Demeco, A. Ammendolia, and D. Corchiola, "Cloud-based biomedical system for remote monitoring of ALS patients." in 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), (2020), pp. 1469-76.
28- Emotiv Epoc+. Available online: https://www.emotiv.com/epoc/ (accessed on 13 February 2022).
29- EmotivPro. Available online: https://emotiv.gitbook.io/emotivpro-v2-0/ (accessed on 13 February 2022).
30- Yannic Titgemeyer et al., "Can commercially available wearable EEG devices be used for diagnostic purposes? An explorative pilot study." Epilepsy & Behavior, Vol. 103, p. 106507, 2020/02/01/ (2020).
31- P. de Lissa, S. Sörensen, N. Badcock, J. Thie, and G. McArthur, "Measuring the face-sensitive N170 with a gaming EEG system: A validation study." (in eng), J Neurosci Methods, Vol. 253, pp. 47-54, Sep. 30 (2015).
32- Kirill Stytsenko, Evaldas Jablonskis, and Cosima Prahm, "Evaluation of consumer EEG device Emotiv EPOC." (2011).
33- Jijun Tong, Peng Zhang, Ran Xiao, and Lei Ding, "The portable P300 dialing system based on tablet and Emotiv Epoc headset." (in eng), Annu Int Conf IEEE Eng Med Biol Soc, Vol. 2015, pp. 566-9, Aug. (2015).
34- C. Ashby, A. Bhatia, F. Tenore, and J. Vogelstein, "Low-cost electroencephalogram (EEG) based authentication." in 2011 5th International IEEE/EMBS Conference on Neural Engineering, (2011), pp. 442-45.
35- Bongjae Choi and Sungho Jo, "A Low-Cost EEG System-Based Hybrid Brain-Computer Interface for Humanoid Robot Navigation and Recognition." PLOS ONE, Vol. 8 (No. 9), p. e74583, (2013).
36- Y. Wang, Z. Wang, W. Clifford, C. Markham, T. E. Ward, and C. Deegan, "Validation of low-cost wireless EEG system for measuring event-related potentials." in 2018 29th Irish Signals and Systems Conference (ISSC), (2018), pp. 1-6.
37- g.tec. “g.USBamp EEG amplifier”. Available: https://www.gtec.at/product-configurator/g-usbamp/ .
38- Didar Dadebayev, Wei Wei Goh, and Ee Xion 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), pp. 4385-401, 2022/07/01/ (2022).
39- N. S. Williams, G. M. McArthur, B. de Wit, G. Ibrahim, and N. A. Badcock, "A validation of Emotiv EPOC Flex saline for EEG and ERP research." (in eng), PeerJ, Vol. 8, p. e9713, (2020).
40- A. Delorme and S. Makeig, "EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis." (in eng), J Neurosci Methods, Vol. 134 (No. 1), pp. 9-21, Mar. 15 (2004).
41- R. Oostenveld, P. Fries, E. Maris, and J. M. Schoffelen, "FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data." (in eng), Comput Intell Neurosci, Vol. 2011, p. 156869, (2011).
42- Sarah Blum, Nadine S. J. Jacobsen, Martin G. Bleichner, and Stefan Debener, "A Riemannian Modification of Artifact Subspace Reconstruction for EEG Artifact Handling." (in English), Frontiers in Human Neuroscience, Original Research Vol. 132019-April-26 (2019).
43- C. Y. Chang, S. H. Hsu, L. Pion-Tonachini, and T. P. Jung, "Evaluation of Artifact Subspace Reconstruction for Automatic Artifact Components Removal in Multi-Channel EEG Recordings." (in eng), IEEE Trans Biomed Eng, Vol. 67 (No. 4), pp. 1114-21, Apr (2020).
44- Cleaning Raw EEG Data. Available online: https://github.com/sccn/clean_rawdata. (accessed on 30 March 2023).
45- EEGLAB extensions and plugins. https://sccn.ucsd.edu/wiki/EEGLAB_Extensions. (accessed on 30 March 2023).
46- A. Palumbo et al., "An Embedded System for EEG Acquisition and Processing for Brain Computer Interface Applications." in Wearable and Autonomous Biomedical Devices and Systems for Smart Environment: Issues and Characterization, Aimé Lay-Ekuakille and Subhas Chandra Mukhopadhyay, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, (2010), pp. 137-54.
47- Arrigo Palumbo, Nicola Ielpo, and Barbara Calabrese, "An FPGA-Embedded Brain-Computer Interface System to Support Individual Autonomy in Locked-In Individuals." Sensors, Vol. 22 (No. 1), p. 318, (2022).
48- Arrigo Palumbo, Patrizia Vizza, Barbara Calabrese, and Nicola Ielpo, "Biopotential Signal Monitoring Systems in Rehabilitation: A Review." Sensors, Vol. 21 (No. 21), p. 7172, (2021).
49- N. Ielpo et al., "EMG-Miner: Automatic Acquisition and Processing of Electromyographic Signals: First Experimentation in a Clinical Context for Gait Disorders Evaluation." in 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, (2014), pp. 441-46.
50- Mahsa Soufineyestani, Dale Dowling, and Arshia Khan, "Electroencephalography (EEG) Technology Applications and Available Devices." Applied Sciences, Vol. 10 (No. 21), p. 7453, (2020).
51- Rodrigo Ramele, Ana Julia Villar, and Juan Miguel Santos, "Report: EPOC Emotiv EEG Basics." arXiv preprint arXiv:2206.09051, (2022).
| Files | ||
| Issue | Vol 11 No 3 (2024) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/fbt.v11i3.15882 | |
| Keywords | ||
| Wearable Electroencephalography Consumer-Grade Electroencephalography Devices Signals Processing Remote Monitoring | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Palumbo A, Gramigna V, Calabrese B, Ielpo N, Demeco A. A Wearable Device-Based System: The Potential Role in Real-time and Remote EEG Monitoring. Frontiers Biomed Technol. 2024;11(3):375-388.
