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You searched for subject:(Electroencephalography methods). Showing records 1 – 8 of 8 total matches.

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RMIT University

1. Naik, G. Iterative issues of ICA, quality of separation and number of sources : a study for biosignal applications.

Degree: 2008, RMIT University

 This thesis has evaluated the use of Independent Component Analysis (ICA) on Surface Electromyography (sEMG), focusing on the biosignal applications. This research has identified and… (more)

Subjects/Keywords: Fields of Research; Electroencephalography methods

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Naik, G. (2008). Iterative issues of ICA, quality of separation and number of sources : a study for biosignal applications. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:6756

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Naik, G. “Iterative issues of ICA, quality of separation and number of sources : a study for biosignal applications.” 2008. Thesis, RMIT University. Accessed September 18, 2019. http://researchbank.rmit.edu.au/view/rmit:6756.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Naik, G. “Iterative issues of ICA, quality of separation and number of sources : a study for biosignal applications.” 2008. Web. 18 Sep 2019.

Vancouver:

Naik G. Iterative issues of ICA, quality of separation and number of sources : a study for biosignal applications. [Internet] [Thesis]. RMIT University; 2008. [cited 2019 Sep 18]. Available from: http://researchbank.rmit.edu.au/view/rmit:6756.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Naik G. Iterative issues of ICA, quality of separation and number of sources : a study for biosignal applications. [Thesis]. RMIT University; 2008. Available from: http://researchbank.rmit.edu.au/view/rmit:6756

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Alberta

2. Landals, A. Matthew. An investigation of the use of EEG phase in groupwise classification.

Degree: MSin Statistics, Department of Mathematical Sciences, 2000, University of Alberta

Subjects/Keywords: Electroencephalography – Statistical methods.; Time-series analysis.

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APA (6th Edition):

Landals, A. M. (2000). An investigation of the use of EEG phase in groupwise classification. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/sx61dp271

Chicago Manual of Style (16th Edition):

Landals, A Matthew. “An investigation of the use of EEG phase in groupwise classification.” 2000. Masters Thesis, University of Alberta. Accessed September 18, 2019. https://era.library.ualberta.ca/files/sx61dp271.

MLA Handbook (7th Edition):

Landals, A Matthew. “An investigation of the use of EEG phase in groupwise classification.” 2000. Web. 18 Sep 2019.

Vancouver:

Landals AM. An investigation of the use of EEG phase in groupwise classification. [Internet] [Masters thesis]. University of Alberta; 2000. [cited 2019 Sep 18]. Available from: https://era.library.ualberta.ca/files/sx61dp271.

Council of Science Editors:

Landals AM. An investigation of the use of EEG phase in groupwise classification. [Masters Thesis]. University of Alberta; 2000. Available from: https://era.library.ualberta.ca/files/sx61dp271

3. Jakaite, Livija. Bayesian assessment of newborn brain maturity from sleep electroencephalograms.

Degree: PhD, 2012, University of Bedfordshire

 In this thesis, we develop and test a technology for computer-assisted assessments of newborn brain maturity from sleep electroencephalogram (EEG). Brain maturation of newborns is… (more)

Subjects/Keywords: 618.92; B890 Medical Technology not elsewhere classified; newborn brain maturity; electroencephalogram; electroencephalography; Bayesian methods

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jakaite, L. (2012). Bayesian assessment of newborn brain maturity from sleep electroencephalograms. (Doctoral Dissertation). University of Bedfordshire. Retrieved from http://hdl.handle.net/10547/293806

Chicago Manual of Style (16th Edition):

Jakaite, Livija. “Bayesian assessment of newborn brain maturity from sleep electroencephalograms.” 2012. Doctoral Dissertation, University of Bedfordshire. Accessed September 18, 2019. http://hdl.handle.net/10547/293806.

MLA Handbook (7th Edition):

Jakaite, Livija. “Bayesian assessment of newborn brain maturity from sleep electroencephalograms.” 2012. Web. 18 Sep 2019.

Vancouver:

Jakaite L. Bayesian assessment of newborn brain maturity from sleep electroencephalograms. [Internet] [Doctoral dissertation]. University of Bedfordshire; 2012. [cited 2019 Sep 18]. Available from: http://hdl.handle.net/10547/293806.

Council of Science Editors:

Jakaite L. Bayesian assessment of newborn brain maturity from sleep electroencephalograms. [Doctoral Dissertation]. University of Bedfordshire; 2012. Available from: http://hdl.handle.net/10547/293806


Northeastern University

4. Eftekhari Yazdi, Golnaz. Adaptive BCI-controller for dynamic systems.

Degree: MS, Department of Electrical and Computer Engineering, 2015, Northeastern University

 This thesis introduces a new approach to design an adaptive proportional controller for dynamic systems controlled by Brain Computer Interfaces (BCIs). Brain-controlled robots are being… (more)

Subjects/Keywords: adaptive controller; brain computer interface (BCI); dynamic sytem; EEG; robot; SSVEP; Adaptive control systems; Simulation methods; Brain-computer interfaces; Dynamics; Evoked potentials (Electrophysiology); Visual evoked response; Electroencephalography; Robots

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APA (6th Edition):

Eftekhari Yazdi, G. (2015). Adaptive BCI-controller for dynamic systems. (Masters Thesis). Northeastern University. Retrieved from http://hdl.handle.net/2047/D20194557

Chicago Manual of Style (16th Edition):

Eftekhari Yazdi, Golnaz. “Adaptive BCI-controller for dynamic systems.” 2015. Masters Thesis, Northeastern University. Accessed September 18, 2019. http://hdl.handle.net/2047/D20194557.

MLA Handbook (7th Edition):

Eftekhari Yazdi, Golnaz. “Adaptive BCI-controller for dynamic systems.” 2015. Web. 18 Sep 2019.

Vancouver:

Eftekhari Yazdi G. Adaptive BCI-controller for dynamic systems. [Internet] [Masters thesis]. Northeastern University; 2015. [cited 2019 Sep 18]. Available from: http://hdl.handle.net/2047/D20194557.

Council of Science Editors:

Eftekhari Yazdi G. Adaptive BCI-controller for dynamic systems. [Masters Thesis]. Northeastern University; 2015. Available from: http://hdl.handle.net/2047/D20194557


Northeastern University

5. Chang, Chun-hsiang. Radio frequency and analog CMOS integrated circuit design methods for low-power medical devices with wireless connectivity.

Degree: PhD, Department of Electrical and Computer Engineering, 2016, Northeastern University

 The ongoing improvements of complementary metal-oxide semiconductor (CMOS) technologies are enabling the integration of an increasing number of analog and digital circuits into single chips,… (more)

Subjects/Keywords: electroencephalography (EEG) front-end; linearization methods; long-term monitoring; radio frequency (RF) front-end; subthreshold biasing (weak inversion); third-order intermodulation intercept point (IIP3); Metal oxide semiconductors, Complementary; Design and construction; Amplifiers, Radio frequency; Design and construction; Radio frequency; Electroencephalography; Modulation (Electronics); Wireless communication systems in medical care

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chang, C. (2016). Radio frequency and analog CMOS integrated circuit design methods for low-power medical devices with wireless connectivity. (Doctoral Dissertation). Northeastern University. Retrieved from http://hdl.handle.net/2047/D20200179

Chicago Manual of Style (16th Edition):

Chang, Chun-hsiang. “Radio frequency and analog CMOS integrated circuit design methods for low-power medical devices with wireless connectivity.” 2016. Doctoral Dissertation, Northeastern University. Accessed September 18, 2019. http://hdl.handle.net/2047/D20200179.

MLA Handbook (7th Edition):

Chang, Chun-hsiang. “Radio frequency and analog CMOS integrated circuit design methods for low-power medical devices with wireless connectivity.” 2016. Web. 18 Sep 2019.

Vancouver:

Chang C. Radio frequency and analog CMOS integrated circuit design methods for low-power medical devices with wireless connectivity. [Internet] [Doctoral dissertation]. Northeastern University; 2016. [cited 2019 Sep 18]. Available from: http://hdl.handle.net/2047/D20200179.

Council of Science Editors:

Chang C. Radio frequency and analog CMOS integrated circuit design methods for low-power medical devices with wireless connectivity. [Doctoral Dissertation]. Northeastern University; 2016. Available from: http://hdl.handle.net/2047/D20200179


IUPUI

6. Ghane, Parisa. Silent speech recognition in EEG-based brain computer interface.

Degree: 2015, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

A Brain Computer Interface (BCI) is a hardware and software system that establishes direct communication between human brain and the… (more)

Subjects/Keywords: Brain Computer Interface; EEG; Support Vector Machine; Multi-class Classification; Speech recognition; Brain-computer interfaces  – Research  – Analysis; Electroencephalography  – Mathematical models; Support vector machines  – Research  – Analysis; Speech processing systems  – Research; Automatic speech recognition  – Research  – Analysis; Pattern recognition systems  – Statistical methods; Multimedia systems  – Research; Neural networks (Computer science)  – Research; Wavelets (Mathematics); Computer algorithms  – Research; User interfaces (Computer systems); Electrodes  – Testing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ghane, P. (2015). Silent speech recognition in EEG-based brain computer interface. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/9886 ; http://dx.doi.org/10.7912/C2B01X

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ghane, Parisa. “Silent speech recognition in EEG-based brain computer interface.” 2015. Thesis, IUPUI. Accessed September 18, 2019. http://hdl.handle.net/1805/9886 ; http://dx.doi.org/10.7912/C2B01X.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ghane, Parisa. “Silent speech recognition in EEG-based brain computer interface.” 2015. Web. 18 Sep 2019.

Vancouver:

Ghane P. Silent speech recognition in EEG-based brain computer interface. [Internet] [Thesis]. IUPUI; 2015. [cited 2019 Sep 18]. Available from: http://hdl.handle.net/1805/9886 ; http://dx.doi.org/10.7912/C2B01X.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ghane P. Silent speech recognition in EEG-based brain computer interface. [Thesis]. IUPUI; 2015. Available from: http://hdl.handle.net/1805/9886 ; http://dx.doi.org/10.7912/C2B01X

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


IUPUI

7. Ghane, Parisa. Silent speech recognition in EEG-based brain computer interface.

Degree: 2015, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

A Brain Computer Interface (BCI) is a hardware and software system that establishes direct communication between human brain and the… (more)

Subjects/Keywords: Brain Computer Interface; EEG; Support Vector Machine; Multi-class Classification; Speech recognition; Brain-computer interfaces  – Research  – Analysis; Electroencephalography  – Mathematical models; Support vector machines  – Research  – Analysis; Speech processing systems  – Research; Automatic speech recognition  – Research  – Analysis; Pattern recognition systems  – Statistical methods; Multimedia systems  – Research; Neural networks (Computer science)  – Research; Wavelets (Mathematics); Computer algorithms  – Research; User interfaces (Computer systems); Electrodes  – Testing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ghane, P. (2015). Silent speech recognition in EEG-based brain computer interface. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/9886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ghane, Parisa. “Silent speech recognition in EEG-based brain computer interface.” 2015. Thesis, IUPUI. Accessed September 18, 2019. http://hdl.handle.net/1805/9886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ghane, Parisa. “Silent speech recognition in EEG-based brain computer interface.” 2015. Web. 18 Sep 2019.

Vancouver:

Ghane P. Silent speech recognition in EEG-based brain computer interface. [Internet] [Thesis]. IUPUI; 2015. [cited 2019 Sep 18]. Available from: http://hdl.handle.net/1805/9886.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ghane P. Silent speech recognition in EEG-based brain computer interface. [Thesis]. IUPUI; 2015. Available from: http://hdl.handle.net/1805/9886

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

8. Σπανού, Ειρήνη. Ανίχνευση παθολογίας στην επιληψία με χρήση μεθόδων υπολογισμού κλασματικής διάστασης σε ηλεκτροεγκεφαλογραφικές καταγραφές.

Degree: 2006, University of Patras

Στη συγκεκριμένη μεταπτυχιακή εργασία γίνεται ανάλυση των ηλεκτροεγκεφαλογραφικών καταγραφών επιληπτικών ασθενών με βάση την κλασματική διάσταση για τον εντοπισμό της έναρξης των επιληπτικών κρίσεων καθώς… (more)

Subjects/Keywords: Ηλεκτροεγκεφαλογράφημα (EEG); Επιληψία; Μη – γραμμική δυναμική ανάλυση; Κλασματική διάσταση; Μέθοδοι υπολογισμού κλασματικής διάστασης στο πεδίο του χρόνου; 616.853 075; Electroencephalography (EEG); Epilepsy; Non–linear dynamic analysis; Fractal dimension; Methods for the estimation of fractal dimension in time domain

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Σπανού, . (2006). Ανίχνευση παθολογίας στην επιληψία με χρήση μεθόδων υπολογισμού κλασματικής διάστασης σε ηλεκτροεγκεφαλογραφικές καταγραφές. (Masters Thesis). University of Patras. Retrieved from http://nemertes.lis.upatras.gr/jspui/handle/10889/1168

Chicago Manual of Style (16th Edition):

Σπανού, Ειρήνη. “Ανίχνευση παθολογίας στην επιληψία με χρήση μεθόδων υπολογισμού κλασματικής διάστασης σε ηλεκτροεγκεφαλογραφικές καταγραφές.” 2006. Masters Thesis, University of Patras. Accessed September 18, 2019. http://nemertes.lis.upatras.gr/jspui/handle/10889/1168.

MLA Handbook (7th Edition):

Σπανού, Ειρήνη. “Ανίχνευση παθολογίας στην επιληψία με χρήση μεθόδων υπολογισμού κλασματικής διάστασης σε ηλεκτροεγκεφαλογραφικές καταγραφές.” 2006. Web. 18 Sep 2019.

Vancouver:

Σπανού . Ανίχνευση παθολογίας στην επιληψία με χρήση μεθόδων υπολογισμού κλασματικής διάστασης σε ηλεκτροεγκεφαλογραφικές καταγραφές. [Internet] [Masters thesis]. University of Patras; 2006. [cited 2019 Sep 18]. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/1168.

Council of Science Editors:

Σπανού . Ανίχνευση παθολογίας στην επιληψία με χρήση μεθόδων υπολογισμού κλασματικής διάστασης σε ηλεκτροεγκεφαλογραφικές καταγραφές. [Masters Thesis]. University of Patras; 2006. Available from: http://nemertes.lis.upatras.gr/jspui/handle/10889/1168

.