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You searched for subject:(Brain computer Interface). Showing records 1 – 30 of 268 total matches.

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Washington University in St. Louis

1. Burns, Scott. The Design and Implementation of an Extensible Brain-Computer Interface.

Degree: MA, Biomedical Engineering, 2010, Washington University in St. Louis

 An implantable brain computer interface: BCI) includes tissue interface hardware, signal conditioning circuitry, analog-to-digital conversion: ADC) circuitry and some sort of computing hardware to discriminate… (more)

Subjects/Keywords: Brain-Computer Interface

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

APA (6th Edition):

Burns, S. (2010). The Design and Implementation of an Extensible Brain-Computer Interface. (Thesis). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/etd/501

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):

Burns, Scott. “The Design and Implementation of an Extensible Brain-Computer Interface.” 2010. Thesis, Washington University in St. Louis. Accessed November 19, 2019. https://openscholarship.wustl.edu/etd/501.

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

MLA Handbook (7th Edition):

Burns, Scott. “The Design and Implementation of an Extensible Brain-Computer Interface.” 2010. Web. 19 Nov 2019.

Vancouver:

Burns S. The Design and Implementation of an Extensible Brain-Computer Interface. [Internet] [Thesis]. Washington University in St. Louis; 2010. [cited 2019 Nov 19]. Available from: https://openscholarship.wustl.edu/etd/501.

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

Council of Science Editors:

Burns S. The Design and Implementation of an Extensible Brain-Computer Interface. [Thesis]. Washington University in St. Louis; 2010. Available from: https://openscholarship.wustl.edu/etd/501

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

2. Ciancibello, John. Improving Real-Time Classification Methods for an Intracortical Brain Computer Interface in Humans.

Degree: Biomedical Engineering, 2017, Brown University

 A primary goal of intracortical Brain-Computer Interface (iBCI) technology is to restore communication and independence for people with motor disabilities. The BrainGate System is an… (more)

Subjects/Keywords: Brain-Computer Interface

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

APA (6th Edition):

Ciancibello, J. (2017). Improving Real-Time Classification Methods for an Intracortical Brain Computer Interface in Humans. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:733302/

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):

Ciancibello, John. “Improving Real-Time Classification Methods for an Intracortical Brain Computer Interface in Humans.” 2017. Thesis, Brown University. Accessed November 19, 2019. https://repository.library.brown.edu/studio/item/bdr:733302/.

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

MLA Handbook (7th Edition):

Ciancibello, John. “Improving Real-Time Classification Methods for an Intracortical Brain Computer Interface in Humans.” 2017. Web. 19 Nov 2019.

Vancouver:

Ciancibello J. Improving Real-Time Classification Methods for an Intracortical Brain Computer Interface in Humans. [Internet] [Thesis]. Brown University; 2017. [cited 2019 Nov 19]. Available from: https://repository.library.brown.edu/studio/item/bdr:733302/.

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

Council of Science Editors:

Ciancibello J. Improving Real-Time Classification Methods for an Intracortical Brain Computer Interface in Humans. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:733302/

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


University of Illinois – Chicago

3. Mugler, Emily M. Investigation of Speech for Communicative Brain-Computer Interface.

Degree: 2014, University of Illinois – Chicago

 Recent successes in decoding speech from cortical signals provide hope for restoring function to those who have lost the ability to speak normally. Despite these… (more)

Subjects/Keywords: brain-computer interface; electrocorticography; speech

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APA (6th Edition):

Mugler, E. M. (2014). Investigation of Speech for Communicative Brain-Computer Interface. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/11211

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):

Mugler, Emily M. “Investigation of Speech for Communicative Brain-Computer Interface.” 2014. Thesis, University of Illinois – Chicago. Accessed November 19, 2019. http://hdl.handle.net/10027/11211.

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

MLA Handbook (7th Edition):

Mugler, Emily M. “Investigation of Speech for Communicative Brain-Computer Interface.” 2014. Web. 19 Nov 2019.

Vancouver:

Mugler EM. Investigation of Speech for Communicative Brain-Computer Interface. [Internet] [Thesis]. University of Illinois – Chicago; 2014. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10027/11211.

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

Council of Science Editors:

Mugler EM. Investigation of Speech for Communicative Brain-Computer Interface. [Thesis]. University of Illinois – Chicago; 2014. Available from: http://hdl.handle.net/10027/11211

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


University of Toronto

4. Aleem, Idris Syed. Online Environmental Control of Multiple Devices using Transcranial Doppler (TCD) Ultrasonography.

Degree: 2012, University of Toronto

Individuals with severe impairments may use brain-computer interface (BCI) technologies in order to interact with their external environment. One non-invasive brain-monitoring technology which may be… (more)

Subjects/Keywords: TCD; Brain Computer Interface; 0541

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

APA (6th Edition):

Aleem, I. S. (2012). Online Environmental Control of Multiple Devices using Transcranial Doppler (TCD) Ultrasonography. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/33315

Chicago Manual of Style (16th Edition):

Aleem, Idris Syed. “Online Environmental Control of Multiple Devices using Transcranial Doppler (TCD) Ultrasonography.” 2012. Masters Thesis, University of Toronto. Accessed November 19, 2019. http://hdl.handle.net/1807/33315.

MLA Handbook (7th Edition):

Aleem, Idris Syed. “Online Environmental Control of Multiple Devices using Transcranial Doppler (TCD) Ultrasonography.” 2012. Web. 19 Nov 2019.

Vancouver:

Aleem IS. Online Environmental Control of Multiple Devices using Transcranial Doppler (TCD) Ultrasonography. [Internet] [Masters thesis]. University of Toronto; 2012. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1807/33315.

Council of Science Editors:

Aleem IS. Online Environmental Control of Multiple Devices using Transcranial Doppler (TCD) Ultrasonography. [Masters Thesis]. University of Toronto; 2012. Available from: http://hdl.handle.net/1807/33315


University of Missouri – Kansas City

5. Gottemukkula, Vikas. Application of Wrapper Methods to Non-Invasive Brain-State Detection: An Opto-Electric Approach .

Degree: 2011, University of Missouri – Kansas City

 Using a classification guided feature selection (wrapper method) in conjunction with a new performance metric, I present a solution to multi-class subject invariant Brain Computer(more)

Subjects/Keywords: Wrapper method; Brain Computer Interface

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

APA (6th Edition):

Gottemukkula, V. (2011). Application of Wrapper Methods to Non-Invasive Brain-State Detection: An Opto-Electric Approach . (Thesis). University of Missouri – Kansas City. Retrieved from http://hdl.handle.net/10355/9594

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):

Gottemukkula, Vikas. “Application of Wrapper Methods to Non-Invasive Brain-State Detection: An Opto-Electric Approach .” 2011. Thesis, University of Missouri – Kansas City. Accessed November 19, 2019. http://hdl.handle.net/10355/9594.

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

MLA Handbook (7th Edition):

Gottemukkula, Vikas. “Application of Wrapper Methods to Non-Invasive Brain-State Detection: An Opto-Electric Approach .” 2011. Web. 19 Nov 2019.

Vancouver:

Gottemukkula V. Application of Wrapper Methods to Non-Invasive Brain-State Detection: An Opto-Electric Approach . [Internet] [Thesis]. University of Missouri – Kansas City; 2011. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10355/9594.

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

Council of Science Editors:

Gottemukkula V. Application of Wrapper Methods to Non-Invasive Brain-State Detection: An Opto-Electric Approach . [Thesis]. University of Missouri – Kansas City; 2011. Available from: http://hdl.handle.net/10355/9594

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


Colorado State University

6. Alzahrani, Saleh Ibrahim. Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A.

Degree: PhD, Bioengineering, 2019, Colorado State University

 The electroencephalogram (EEG) is broadly used for diagnosis of brain diseases and research of brain activities. Although the EEG provides a good temporal resolution, it… (more)

Subjects/Keywords: EEG; Brain-computer interface; TCRE

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APA (6th Edition):

Alzahrani, S. I. (2019). Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/195380

Chicago Manual of Style (16th Edition):

Alzahrani, Saleh Ibrahim. “Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A.” 2019. Doctoral Dissertation, Colorado State University. Accessed November 19, 2019. http://hdl.handle.net/10217/195380.

MLA Handbook (7th Edition):

Alzahrani, Saleh Ibrahim. “Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A.” 2019. Web. 19 Nov 2019.

Vancouver:

Alzahrani SI. Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10217/195380.

Council of Science Editors:

Alzahrani SI. Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195380

7. Yang, Yuan. Analyse de signaux EEG pour des applications grand-public des interfaces cerveau-machine : EEG signal analysis for brain-computer interfaces for large public applications.

Degree: Docteur es, Signal et images, 2013, Paris, ENST

Les interfaces cerveau-machine (ICM) utilisent les signaux émis par le cerveau pour contrôler des machines ainsi que des appareils (claviers, voitures, neuro-prothèses). Après plusieurs décennies… (more)

Subjects/Keywords: Interface cerveau-machine; Brain-computer interface

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APA (6th Edition):

Yang, Y. (2013). Analyse de signaux EEG pour des applications grand-public des interfaces cerveau-machine : EEG signal analysis for brain-computer interfaces for large public applications. (Doctoral Dissertation). Paris, ENST. Retrieved from http://www.theses.fr/2013ENST0043

Chicago Manual of Style (16th Edition):

Yang, Yuan. “Analyse de signaux EEG pour des applications grand-public des interfaces cerveau-machine : EEG signal analysis for brain-computer interfaces for large public applications.” 2013. Doctoral Dissertation, Paris, ENST. Accessed November 19, 2019. http://www.theses.fr/2013ENST0043.

MLA Handbook (7th Edition):

Yang, Yuan. “Analyse de signaux EEG pour des applications grand-public des interfaces cerveau-machine : EEG signal analysis for brain-computer interfaces for large public applications.” 2013. Web. 19 Nov 2019.

Vancouver:

Yang Y. Analyse de signaux EEG pour des applications grand-public des interfaces cerveau-machine : EEG signal analysis for brain-computer interfaces for large public applications. [Internet] [Doctoral dissertation]. Paris, ENST; 2013. [cited 2019 Nov 19]. Available from: http://www.theses.fr/2013ENST0043.

Council of Science Editors:

Yang Y. Analyse de signaux EEG pour des applications grand-public des interfaces cerveau-machine : EEG signal analysis for brain-computer interfaces for large public applications. [Doctoral Dissertation]. Paris, ENST; 2013. Available from: http://www.theses.fr/2013ENST0043


Texas A&M University

8. Cheng, Yu-Che. A Hybrid Brain-computer Interface for Intelligent Prosthetics.

Degree: 2014, Texas A&M University

 Over the past few decades, many researcher have shown that human can use brain signals to communicate with computers or machines by using brain-computer interfaces… (more)

Subjects/Keywords: Eye tracking; EEG; Brain-computer interface

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APA (6th Edition):

Cheng, Y. (2014). A Hybrid Brain-computer Interface for Intelligent Prosthetics. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153806

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):

Cheng, Yu-Che. “A Hybrid Brain-computer Interface for Intelligent Prosthetics.” 2014. Thesis, Texas A&M University. Accessed November 19, 2019. http://hdl.handle.net/1969.1/153806.

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

MLA Handbook (7th Edition):

Cheng, Yu-Che. “A Hybrid Brain-computer Interface for Intelligent Prosthetics.” 2014. Web. 19 Nov 2019.

Vancouver:

Cheng Y. A Hybrid Brain-computer Interface for Intelligent Prosthetics. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1969.1/153806.

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

Council of Science Editors:

Cheng Y. A Hybrid Brain-computer Interface for Intelligent Prosthetics. [Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153806

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


University of California – Berkeley

9. Secundo, Lavi. Analysis of Neural Activity in Human Motor Cortex - towards Brain Machine Interface System.

Degree: Neuroscience, 2010, University of California – Berkeley

 The discovery of directional tuned neurons in the primary motor cortex has advanced motor research in several domains. For instance, in the area of brain(more)

Subjects/Keywords: Nanoscience; brain computer interface; ECOG; motor control

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APA (6th Edition):

Secundo, L. (2010). Analysis of Neural Activity in Human Motor Cortex - towards Brain Machine Interface System. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/93k279tk

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):

Secundo, Lavi. “Analysis of Neural Activity in Human Motor Cortex - towards Brain Machine Interface System.” 2010. Thesis, University of California – Berkeley. Accessed November 19, 2019. http://www.escholarship.org/uc/item/93k279tk.

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

MLA Handbook (7th Edition):

Secundo, Lavi. “Analysis of Neural Activity in Human Motor Cortex - towards Brain Machine Interface System.” 2010. Web. 19 Nov 2019.

Vancouver:

Secundo L. Analysis of Neural Activity in Human Motor Cortex - towards Brain Machine Interface System. [Internet] [Thesis]. University of California – Berkeley; 2010. [cited 2019 Nov 19]. Available from: http://www.escholarship.org/uc/item/93k279tk.

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

Council of Science Editors:

Secundo L. Analysis of Neural Activity in Human Motor Cortex - towards Brain Machine Interface System. [Thesis]. University of California – Berkeley; 2010. Available from: http://www.escholarship.org/uc/item/93k279tk

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


East Tennessee State University

10. Jones, Marissa R. Faces, Locations, and Tools: A Proposed Two-Stimulus P300 Brain Computer Interface.

Degree: MA, Psychology, 2017, East Tennessee State University

Brain Computer Interface (BCI) technology can be important for those unable to communicate due loss of muscle control. The P300 Speller allows communication at… (more)

Subjects/Keywords: EEG; Brain-Computer Interface; Cognitive Psychology

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APA (6th Edition):

Jones, M. R. (2017). Faces, Locations, and Tools: A Proposed Two-Stimulus P300 Brain Computer Interface. (Masters Thesis). East Tennessee State University. Retrieved from https://dc.etsu.edu/etd/3268

Chicago Manual of Style (16th Edition):

Jones, Marissa R. “Faces, Locations, and Tools: A Proposed Two-Stimulus P300 Brain Computer Interface.” 2017. Masters Thesis, East Tennessee State University. Accessed November 19, 2019. https://dc.etsu.edu/etd/3268.

MLA Handbook (7th Edition):

Jones, Marissa R. “Faces, Locations, and Tools: A Proposed Two-Stimulus P300 Brain Computer Interface.” 2017. Web. 19 Nov 2019.

Vancouver:

Jones MR. Faces, Locations, and Tools: A Proposed Two-Stimulus P300 Brain Computer Interface. [Internet] [Masters thesis]. East Tennessee State University; 2017. [cited 2019 Nov 19]. Available from: https://dc.etsu.edu/etd/3268.

Council of Science Editors:

Jones MR. Faces, Locations, and Tools: A Proposed Two-Stimulus P300 Brain Computer Interface. [Masters Thesis]. East Tennessee State University; 2017. Available from: https://dc.etsu.edu/etd/3268


University of Minnesota

11. Suma, Daniel. Ballistic Finger Imagery for Asynchronous BCI Control.

Degree: MS, Biomedical Engineering, 2017, University of Minnesota

 In this work a novel paradigm and algorithm are developed in order to decode ballistic finger imagery of both the left and right index fingers… (more)

Subjects/Keywords: Asynchronous Control; Brain Computer Interface; EEG; Imagery

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APA (6th Edition):

Suma, D. (2017). Ballistic Finger Imagery for Asynchronous BCI Control. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/202110

Chicago Manual of Style (16th Edition):

Suma, Daniel. “Ballistic Finger Imagery for Asynchronous BCI Control.” 2017. Masters Thesis, University of Minnesota. Accessed November 19, 2019. http://hdl.handle.net/11299/202110.

MLA Handbook (7th Edition):

Suma, Daniel. “Ballistic Finger Imagery for Asynchronous BCI Control.” 2017. Web. 19 Nov 2019.

Vancouver:

Suma D. Ballistic Finger Imagery for Asynchronous BCI Control. [Internet] [Masters thesis]. University of Minnesota; 2017. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/11299/202110.

Council of Science Editors:

Suma D. Ballistic Finger Imagery for Asynchronous BCI Control. [Masters Thesis]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/202110


University of Toronto

12. Myrden, Andrew. Detecting and Classifying Cognitive Activity Based on Changes in Cerebral Blood Flow Velocity.

Degree: 2011, University of Toronto

Individuals with severe physical impairments have a reduced ability to communicate through movement and speech. We investigated transcranial Doppler ultrasound as a potential measurement modality… (more)

Subjects/Keywords: brain-computer interface; transcranial doppler; 0541

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

APA (6th Edition):

Myrden, A. (2011). Detecting and Classifying Cognitive Activity Based on Changes in Cerebral Blood Flow Velocity. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/31352

Chicago Manual of Style (16th Edition):

Myrden, Andrew. “Detecting and Classifying Cognitive Activity Based on Changes in Cerebral Blood Flow Velocity.” 2011. Masters Thesis, University of Toronto. Accessed November 19, 2019. http://hdl.handle.net/1807/31352.

MLA Handbook (7th Edition):

Myrden, Andrew. “Detecting and Classifying Cognitive Activity Based on Changes in Cerebral Blood Flow Velocity.” 2011. Web. 19 Nov 2019.

Vancouver:

Myrden A. Detecting and Classifying Cognitive Activity Based on Changes in Cerebral Blood Flow Velocity. [Internet] [Masters thesis]. University of Toronto; 2011. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1807/31352.

Council of Science Editors:

Myrden A. Detecting and Classifying Cognitive Activity Based on Changes in Cerebral Blood Flow Velocity. [Masters Thesis]. University of Toronto; 2011. Available from: http://hdl.handle.net/1807/31352


University of Illinois – Urbana-Champaign

13. Froeter, Paul. Biocompatible silicon nitride thin films for self-rolled-up microtube technologies: guiding neurons.

Degree: MS, 1200, 2015, University of Illinois – Urbana-Champaign

 This thesis presents the evolution and optimization of a self-rolled-up membrane (s-RUM) that is not only insulating, but transparent and biocompatible, allowing it to be… (more)

Subjects/Keywords: self-assembled; thin film; brain computer interface

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APA (6th Edition):

Froeter, P. (2015). Biocompatible silicon nitride thin films for self-rolled-up microtube technologies: guiding neurons. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/73027

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):

Froeter, Paul. “Biocompatible silicon nitride thin films for self-rolled-up microtube technologies: guiding neurons.” 2015. Thesis, University of Illinois – Urbana-Champaign. Accessed November 19, 2019. http://hdl.handle.net/2142/73027.

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

MLA Handbook (7th Edition):

Froeter, Paul. “Biocompatible silicon nitride thin films for self-rolled-up microtube technologies: guiding neurons.” 2015. Web. 19 Nov 2019.

Vancouver:

Froeter P. Biocompatible silicon nitride thin films for self-rolled-up microtube technologies: guiding neurons. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2015. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/2142/73027.

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

Council of Science Editors:

Froeter P. Biocompatible silicon nitride thin films for self-rolled-up microtube technologies: guiding neurons. [Thesis]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/73027

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


Rochester Institute of Technology

14. Cinar, Eyup. A Study of recent classification algorithms and a novel approach for biosignal data classification.

Degree: Microelectronic Engineering, 2010, Rochester Institute of Technology

 Analyzing and understanding human biosignals have been important research areas that have many practical applications in everyday life. For example, Brain Computer Interface is a… (more)

Subjects/Keywords: Brain computer interface; Machine learning; Robotics

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APA (6th Edition):

Cinar, E. (2010). A Study of recent classification algorithms and a novel approach for biosignal data classification. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/7137

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):

Cinar, Eyup. “A Study of recent classification algorithms and a novel approach for biosignal data classification.” 2010. Thesis, Rochester Institute of Technology. Accessed November 19, 2019. https://scholarworks.rit.edu/theses/7137.

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

MLA Handbook (7th Edition):

Cinar, Eyup. “A Study of recent classification algorithms and a novel approach for biosignal data classification.” 2010. Web. 19 Nov 2019.

Vancouver:

Cinar E. A Study of recent classification algorithms and a novel approach for biosignal data classification. [Internet] [Thesis]. Rochester Institute of Technology; 2010. [cited 2019 Nov 19]. Available from: https://scholarworks.rit.edu/theses/7137.

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

Council of Science Editors:

Cinar E. A Study of recent classification algorithms and a novel approach for biosignal data classification. [Thesis]. Rochester Institute of Technology; 2010. Available from: https://scholarworks.rit.edu/theses/7137

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


University of Adelaide

15. Yang, Ruiting. Signal processing for a brain computer interface.

Degree: 2010, University of Adelaide

Brain computer interface (BCI) systems measure brain signal and translate it into control commands in an attempt to mimic specific human thinking activities. In recent… (more)

Subjects/Keywords: Brain computer interface; BCI; EEG; Classifier

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APA (6th Edition):

Yang, R. (2010). Signal processing for a brain computer interface. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/60004

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):

Yang, Ruiting. “Signal processing for a brain computer interface.” 2010. Thesis, University of Adelaide. Accessed November 19, 2019. http://hdl.handle.net/2440/60004.

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

MLA Handbook (7th Edition):

Yang, Ruiting. “Signal processing for a brain computer interface.” 2010. Web. 19 Nov 2019.

Vancouver:

Yang R. Signal processing for a brain computer interface. [Internet] [Thesis]. University of Adelaide; 2010. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/2440/60004.

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

Council of Science Editors:

Yang R. Signal processing for a brain computer interface. [Thesis]. University of Adelaide; 2010. Available from: http://hdl.handle.net/2440/60004

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


University of Toronto

16. Lu, Jie. Development and Evaluation of an Online Transcranial Doppler Ultrasonographic Brain-computer Interface for Communication.

Degree: 2013, University of Toronto

We investigated an emerging brain-computer interface (BCI) modality, namely, transcranial Doppler ultrasonography (TCD), which measures cerebral blood flow velocity. We hypothesized that a bilateral TCD-driven… (more)

Subjects/Keywords: Brain computer interface; Transcranial Doppler ultrasound; 0541

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

APA (6th Edition):

Lu, J. (2013). Development and Evaluation of an Online Transcranial Doppler Ultrasonographic Brain-computer Interface for Communication. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/43093

Chicago Manual of Style (16th Edition):

Lu, Jie. “Development and Evaluation of an Online Transcranial Doppler Ultrasonographic Brain-computer Interface for Communication.” 2013. Masters Thesis, University of Toronto. Accessed November 19, 2019. http://hdl.handle.net/1807/43093.

MLA Handbook (7th Edition):

Lu, Jie. “Development and Evaluation of an Online Transcranial Doppler Ultrasonographic Brain-computer Interface for Communication.” 2013. Web. 19 Nov 2019.

Vancouver:

Lu J. Development and Evaluation of an Online Transcranial Doppler Ultrasonographic Brain-computer Interface for Communication. [Internet] [Masters thesis]. University of Toronto; 2013. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1807/43093.

Council of Science Editors:

Lu J. Development and Evaluation of an Online Transcranial Doppler Ultrasonographic Brain-computer Interface for Communication. [Masters Thesis]. University of Toronto; 2013. Available from: http://hdl.handle.net/1807/43093


Northeastern University

17. Luo, Rui. Implementation of a shared control system for brain-controlled wheelchair navigation.

Degree: MS, Department of Electrical and Computer Engineering, 2018, Northeastern University

 Individuals with physical disabilities continue to rely on electric wheelchairs and personalized human-machine interfaces for their mobility. Even though the problem is well-studied in literature,… (more)

Subjects/Keywords: brain computer interface; navigation; shared control; wheelchair

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

APA (6th Edition):

Luo, R. (2018). Implementation of a shared control system for brain-controlled wheelchair navigation. (Masters Thesis). Northeastern University. Retrieved from http://hdl.handle.net/2047/D20292435

Chicago Manual of Style (16th Edition):

Luo, Rui. “Implementation of a shared control system for brain-controlled wheelchair navigation.” 2018. Masters Thesis, Northeastern University. Accessed November 19, 2019. http://hdl.handle.net/2047/D20292435.

MLA Handbook (7th Edition):

Luo, Rui. “Implementation of a shared control system for brain-controlled wheelchair navigation.” 2018. Web. 19 Nov 2019.

Vancouver:

Luo R. Implementation of a shared control system for brain-controlled wheelchair navigation. [Internet] [Masters thesis]. Northeastern University; 2018. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/2047/D20292435.

Council of Science Editors:

Luo R. Implementation of a shared control system for brain-controlled wheelchair navigation. [Masters Thesis]. Northeastern University; 2018. Available from: http://hdl.handle.net/2047/D20292435


Virginia Tech

18. Nagabushan, Naresh. Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications.

Degree: MS, Electrical and Computer Engineering, 2019, Virginia Tech

Brain-Computer Interfaces (BCIs) that rely on motor imagery currently allow subjects to control quad-copters, robotic arms, and computer cursors. Recent advancements have been made possible… (more)

Subjects/Keywords: Brain-Computer-Interface; iEEG; EEG; Classification

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

APA (6th Edition):

Nagabushan, N. (2019). Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/90183

Chicago Manual of Style (16th Edition):

Nagabushan, Naresh. “Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications.” 2019. Masters Thesis, Virginia Tech. Accessed November 19, 2019. http://hdl.handle.net/10919/90183.

MLA Handbook (7th Edition):

Nagabushan, Naresh. “Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications.” 2019. Web. 19 Nov 2019.

Vancouver:

Nagabushan N. Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10919/90183.

Council of Science Editors:

Nagabushan N. Analyzing and Classifying Neural Dynamics from Intracranial Electroencephalography Signals in Brain-Computer Interface Applications. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/90183


Université de Grenoble

19. Barachant, Alexandre. Commande robuste d'un effecteur par une interface cerveau machine EEG asynchrone : Robust control of an actuator by EEG based asynchronous BCI.

Degree: Docteur es, Signal, image, paroles, télécoms, 2012, Université de Grenoble

Cette thèse a pour but le développement d’une Interface cerveau-machine (ICM) à partir de la mesure EEG,permettant à l’utilisateur de communiquer avec un dispositif externe… (more)

Subjects/Keywords: Interface cerveau machine; EEG; ICM; Brain computer interface; EEG; BCI; 620

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APA (6th Edition):

Barachant, A. (2012). Commande robuste d'un effecteur par une interface cerveau machine EEG asynchrone : Robust control of an actuator by EEG based asynchronous BCI. (Doctoral Dissertation). Université de Grenoble. Retrieved from http://www.theses.fr/2012GRENT112

Chicago Manual of Style (16th Edition):

Barachant, Alexandre. “Commande robuste d'un effecteur par une interface cerveau machine EEG asynchrone : Robust control of an actuator by EEG based asynchronous BCI.” 2012. Doctoral Dissertation, Université de Grenoble. Accessed November 19, 2019. http://www.theses.fr/2012GRENT112.

MLA Handbook (7th Edition):

Barachant, Alexandre. “Commande robuste d'un effecteur par une interface cerveau machine EEG asynchrone : Robust control of an actuator by EEG based asynchronous BCI.” 2012. Web. 19 Nov 2019.

Vancouver:

Barachant A. Commande robuste d'un effecteur par une interface cerveau machine EEG asynchrone : Robust control of an actuator by EEG based asynchronous BCI. [Internet] [Doctoral dissertation]. Université de Grenoble; 2012. [cited 2019 Nov 19]. Available from: http://www.theses.fr/2012GRENT112.

Council of Science Editors:

Barachant A. Commande robuste d'un effecteur par une interface cerveau machine EEG asynchrone : Robust control of an actuator by EEG based asynchronous BCI. [Doctoral Dissertation]. Université de Grenoble; 2012. Available from: http://www.theses.fr/2012GRENT112


University of California – San Francisco

20. Muller, Leah. Electrocorticography-based neurotechnology development: Recording from and effectively stimulating the human brain.

Degree: Bioengineering, 2017, University of California – San Francisco

 Neural devices have great potential to improve the treatment of neuropsychiatric, sensorimotor, and epileptiform disorders in humans. Recently, focus has been appropriately directed toward enabling… (more)

Subjects/Keywords: Biomedical engineering; brain computer interface; brain machine interface; direct electrical stimulation; electrocorticography; microelectrocorticography; neural engineering

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APA (6th Edition):

Muller, L. (2017). Electrocorticography-based neurotechnology development: Recording from and effectively stimulating the human brain. (Thesis). University of California – San Francisco. Retrieved from http://www.escholarship.org/uc/item/2g21d9wp

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):

Muller, Leah. “Electrocorticography-based neurotechnology development: Recording from and effectively stimulating the human brain.” 2017. Thesis, University of California – San Francisco. Accessed November 19, 2019. http://www.escholarship.org/uc/item/2g21d9wp.

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

MLA Handbook (7th Edition):

Muller, Leah. “Electrocorticography-based neurotechnology development: Recording from and effectively stimulating the human brain.” 2017. Web. 19 Nov 2019.

Vancouver:

Muller L. Electrocorticography-based neurotechnology development: Recording from and effectively stimulating the human brain. [Internet] [Thesis]. University of California – San Francisco; 2017. [cited 2019 Nov 19]. Available from: http://www.escholarship.org/uc/item/2g21d9wp.

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

Council of Science Editors:

Muller L. Electrocorticography-based neurotechnology development: Recording from and effectively stimulating the human brain. [Thesis]. University of California – San Francisco; 2017. Available from: http://www.escholarship.org/uc/item/2g21d9wp

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


University of Southern California

21. Ryu, Taiyoung. Maum: exploring immersive gameplay with emerging user interface devices.

Degree: MFA, Interactive Media, 2010, University of Southern California

 This paper explores how new user interface devices can change conventional gameplay, and contribute to immersive user experiences. The game, “Maum” is an experimental game… (more)

Subjects/Keywords: human-computer interaction; brain-computer interface; physical interface; artistic games; experimental games; surrealism

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APA (6th Edition):

Ryu, T. (2010). Maum: exploring immersive gameplay with emerging user interface devices. (Thesis). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/331031/rec/3977

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):

Ryu, Taiyoung. “Maum: exploring immersive gameplay with emerging user interface devices.” 2010. Thesis, University of Southern California. Accessed November 19, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/331031/rec/3977.

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

MLA Handbook (7th Edition):

Ryu, Taiyoung. “Maum: exploring immersive gameplay with emerging user interface devices.” 2010. Web. 19 Nov 2019.

Vancouver:

Ryu T. Maum: exploring immersive gameplay with emerging user interface devices. [Internet] [Thesis]. University of Southern California; 2010. [cited 2019 Nov 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/331031/rec/3977.

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

Council of Science Editors:

Ryu T. Maum: exploring immersive gameplay with emerging user interface devices. [Thesis]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/331031/rec/3977

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


University of Stirling

22. Adair, Jason. Improving the generalisability of brain computer interface applications via machine learning and search-based heuristics.

Degree: PhD, 2018, University of Stirling

Brain Computer Interfaces (BCI) are a domain of hardware/software in which a user can interact with a machine without the need for motor activity, communicating… (more)

Subjects/Keywords: Machine Learning; BCI; Brain Computer Interface; Mutual Information; Iterated Local Search; Transfer Learning; Genetic Algorithms; Evolutionary Search; Heuristics; Brain-Machine Interface; Brain-computer Interface; Computer science – Mathematics

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

APA (6th Edition):

Adair, J. (2018). Improving the generalisability of brain computer interface applications via machine learning and search-based heuristics. (Doctoral Dissertation). University of Stirling. Retrieved from http://hdl.handle.net/1893/29577

Chicago Manual of Style (16th Edition):

Adair, Jason. “Improving the generalisability of brain computer interface applications via machine learning and search-based heuristics.” 2018. Doctoral Dissertation, University of Stirling. Accessed November 19, 2019. http://hdl.handle.net/1893/29577.

MLA Handbook (7th Edition):

Adair, Jason. “Improving the generalisability of brain computer interface applications via machine learning and search-based heuristics.” 2018. Web. 19 Nov 2019.

Vancouver:

Adair J. Improving the generalisability of brain computer interface applications via machine learning and search-based heuristics. [Internet] [Doctoral dissertation]. University of Stirling; 2018. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/1893/29577.

Council of Science Editors:

Adair J. Improving the generalisability of brain computer interface applications via machine learning and search-based heuristics. [Doctoral Dissertation]. University of Stirling; 2018. Available from: http://hdl.handle.net/1893/29577


Washington University in St. Louis

23. Liu, Yuzong. Decoding Brain Activation from Ipsilateral Cortex using ECoG Signals in Humans.

Degree: MA, Computer Science and Engineering, 2011, Washington University in St. Louis

 Today, learning from the brain is the most challenging issue in many areas. Neural scientists, computer scientists, and engineers are collaborating in this broad research… (more)

Subjects/Keywords: Computer Science; Machine Learning, Brain Computer Interface, ECoG Signal, Ipsilateral

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APA (6th Edition):

Liu, Y. (2011). Decoding Brain Activation from Ipsilateral Cortex using ECoG Signals in Humans. (Thesis). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/etd/513

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):

Liu, Yuzong. “Decoding Brain Activation from Ipsilateral Cortex using ECoG Signals in Humans.” 2011. Thesis, Washington University in St. Louis. Accessed November 19, 2019. https://openscholarship.wustl.edu/etd/513.

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

MLA Handbook (7th Edition):

Liu, Yuzong. “Decoding Brain Activation from Ipsilateral Cortex using ECoG Signals in Humans.” 2011. Web. 19 Nov 2019.

Vancouver:

Liu Y. Decoding Brain Activation from Ipsilateral Cortex using ECoG Signals in Humans. [Internet] [Thesis]. Washington University in St. Louis; 2011. [cited 2019 Nov 19]. Available from: https://openscholarship.wustl.edu/etd/513.

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

Council of Science Editors:

Liu Y. Decoding Brain Activation from Ipsilateral Cortex using ECoG Signals in Humans. [Thesis]. Washington University in St. Louis; 2011. Available from: https://openscholarship.wustl.edu/etd/513

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

24. Dangi, Siddharth. Closed-loop decoder adaptation algorithms for brain-machine interface systems.

Degree: Electrical Engineering & Computer Sciences, 2015, University of California – Berkeley

Brain-machine interfaces (BMIs) aim to assist patients suffering from neurological injuries and disease by enabling them to use their own neural activity to control external… (more)

Subjects/Keywords: Electrical engineering; Computer science; Neurosciences; BCI; BMI; brain-computer interface; brain-machine interface; CLDA; closed-loop decoder adaptation

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APA (6th Edition):

Dangi, S. (2015). Closed-loop decoder adaptation algorithms for brain-machine interface systems. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/5xx451th

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):

Dangi, Siddharth. “Closed-loop decoder adaptation algorithms for brain-machine interface systems.” 2015. Thesis, University of California – Berkeley. Accessed November 19, 2019. http://www.escholarship.org/uc/item/5xx451th.

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

MLA Handbook (7th Edition):

Dangi, Siddharth. “Closed-loop decoder adaptation algorithms for brain-machine interface systems.” 2015. Web. 19 Nov 2019.

Vancouver:

Dangi S. Closed-loop decoder adaptation algorithms for brain-machine interface systems. [Internet] [Thesis]. University of California – Berkeley; 2015. [cited 2019 Nov 19]. Available from: http://www.escholarship.org/uc/item/5xx451th.

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

Council of Science Editors:

Dangi S. Closed-loop decoder adaptation algorithms for brain-machine interface systems. [Thesis]. University of California – Berkeley; 2015. Available from: http://www.escholarship.org/uc/item/5xx451th

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


Duke University

25. Li, Zheng. Non-Linear Adaptive Bayesian Filtering for Brain Machine Interfaces .

Degree: 2010, Duke University

Brain-machine interfaces (BMI) are systems which connect brains directly to machines or computers for communication. BMI-controlled prosthetic devices use algorithms to decode neuronal recordings… (more)

Subjects/Keywords: Computer Science; Engineering, Biomedical; adaptive filtering; brain-computer interface; brain-machine interface; Kalman filtering; neuroprosthetic; spike-sorting

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APA (6th Edition):

Li, Z. (2010). Non-Linear Adaptive Bayesian Filtering for Brain Machine Interfaces . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/2363

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):

Li, Zheng. “Non-Linear Adaptive Bayesian Filtering for Brain Machine Interfaces .” 2010. Thesis, Duke University. Accessed November 19, 2019. http://hdl.handle.net/10161/2363.

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

MLA Handbook (7th Edition):

Li, Zheng. “Non-Linear Adaptive Bayesian Filtering for Brain Machine Interfaces .” 2010. Web. 19 Nov 2019.

Vancouver:

Li Z. Non-Linear Adaptive Bayesian Filtering for Brain Machine Interfaces . [Internet] [Thesis]. Duke University; 2010. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/10161/2363.

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

Council of Science Editors:

Li Z. Non-Linear Adaptive Bayesian Filtering for Brain Machine Interfaces . [Thesis]. Duke University; 2010. Available from: http://hdl.handle.net/10161/2363

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


University of California – San Diego

26. Wei, Chun-Shu. Towards Brain Decoding for Real-World Drowsiness Detection.

Degree: Bioengineering, 2017, University of California – San Diego

 A brain-computer interface (BCI) allows human to communicate with a computer by thoughts. Recent advances in brain decoding have shown the capability of BCIs in… (more)

Subjects/Keywords: Bioengineering; Brain-computer interface; Brain decoding; Drowsiness; EEG; Non-hair-bearing EEG; Transfer learning

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APA (6th Edition):

Wei, C. (2017). Towards Brain Decoding for Real-World Drowsiness Detection. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/6zg154xw

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):

Wei, Chun-Shu. “Towards Brain Decoding for Real-World Drowsiness Detection.” 2017. Thesis, University of California – San Diego. Accessed November 19, 2019. http://www.escholarship.org/uc/item/6zg154xw.

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

MLA Handbook (7th Edition):

Wei, Chun-Shu. “Towards Brain Decoding for Real-World Drowsiness Detection.” 2017. Web. 19 Nov 2019.

Vancouver:

Wei C. Towards Brain Decoding for Real-World Drowsiness Detection. [Internet] [Thesis]. University of California – San Diego; 2017. [cited 2019 Nov 19]. Available from: http://www.escholarship.org/uc/item/6zg154xw.

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

Council of Science Editors:

Wei C. Towards Brain Decoding for Real-World Drowsiness Detection. [Thesis]. University of California – San Diego; 2017. Available from: http://www.escholarship.org/uc/item/6zg154xw

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


Carnegie Mellon University

27. Clanton, Samuel T. Brain-Computer Interface Control of an Anthropomorphic Robotic Arm.

Degree: 2011, Carnegie Mellon University

 This thesis describes a brain-computer interface (BCI) system that was developed to allow direct cortical control of 7 active degrees of freedom in a robotic… (more)

Subjects/Keywords: Brain-computer interface; BCI; brain-machine interface; neuroprosthesis; motor control; robot; shared control; virtual fixture; impedance; compliance; Robotics

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APA (6th Edition):

Clanton, S. T. (2011). Brain-Computer Interface Control of an Anthropomorphic Robotic Arm. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/170

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):

Clanton, Samuel T. “Brain-Computer Interface Control of an Anthropomorphic Robotic Arm.” 2011. Thesis, Carnegie Mellon University. Accessed November 19, 2019. http://repository.cmu.edu/dissertations/170.

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

MLA Handbook (7th Edition):

Clanton, Samuel T. “Brain-Computer Interface Control of an Anthropomorphic Robotic Arm.” 2011. Web. 19 Nov 2019.

Vancouver:

Clanton ST. Brain-Computer Interface Control of an Anthropomorphic Robotic Arm. [Internet] [Thesis]. Carnegie Mellon University; 2011. [cited 2019 Nov 19]. Available from: http://repository.cmu.edu/dissertations/170.

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

Council of Science Editors:

Clanton ST. Brain-Computer Interface Control of an Anthropomorphic Robotic Arm. [Thesis]. Carnegie Mellon University; 2011. Available from: http://repository.cmu.edu/dissertations/170

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


Boston University

28. Panko, Mikhail. Developing implant technologies and evaluating brain-machine interfaces using information theory.

Degree: PhD, Neuroscience, 2014, Boston University

Brain-machine interfaces (BMIs) hold promise for restoring motor functions in severely paralyzed individuals. Invasive BMIs are capable of recording signals from individual neurons and typically… (more)

Subjects/Keywords: Neurosciences; Utah array; Brain-computer interface; Brain-machine interface; Information theory; Information transfer rate; Neurotrophic electrode

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APA (6th Edition):

Panko, M. (2014). Developing implant technologies and evaluating brain-machine interfaces using information theory. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/15341

Chicago Manual of Style (16th Edition):

Panko, Mikhail. “Developing implant technologies and evaluating brain-machine interfaces using information theory.” 2014. Doctoral Dissertation, Boston University. Accessed November 19, 2019. http://hdl.handle.net/2144/15341.

MLA Handbook (7th Edition):

Panko, Mikhail. “Developing implant technologies and evaluating brain-machine interfaces using information theory.” 2014. Web. 19 Nov 2019.

Vancouver:

Panko M. Developing implant technologies and evaluating brain-machine interfaces using information theory. [Internet] [Doctoral dissertation]. Boston University; 2014. [cited 2019 Nov 19]. Available from: http://hdl.handle.net/2144/15341.

Council of Science Editors:

Panko M. Developing implant technologies and evaluating brain-machine interfaces using information theory. [Doctoral Dissertation]. Boston University; 2014. Available from: http://hdl.handle.net/2144/15341

29. Willett, Francis R. Intracortical Brain-Computer Interfaces: Modeling the Feedback Control Loop, Improving Decoder Performance, and Restoring Upper Limb Function with Muscle Stimulation.

Degree: PhD, Biomedical Engineering, 2017, Case Western Reserve University School of Graduate Studies

  Intracortical brain-computer interfaces (iBCIs) can help to restore movement and communication to people with chronic tetraplegia by recording neural activity from the motor cortex… (more)

Subjects/Keywords: Biomedical Engineering; Neurosciences; brain-computer interface; brain-machine interface; motor cortex; neural decoding; functional electrical stimulation

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APA (6th Edition):

Willett, F. R. (2017). Intracortical Brain-Computer Interfaces: Modeling the Feedback Control Loop, Improving Decoder Performance, and Restoring Upper Limb Function with Muscle Stimulation. (Doctoral Dissertation). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case149035819787053

Chicago Manual of Style (16th Edition):

Willett, Francis R. “Intracortical Brain-Computer Interfaces: Modeling the Feedback Control Loop, Improving Decoder Performance, and Restoring Upper Limb Function with Muscle Stimulation.” 2017. Doctoral Dissertation, Case Western Reserve University School of Graduate Studies. Accessed November 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case149035819787053.

MLA Handbook (7th Edition):

Willett, Francis R. “Intracortical Brain-Computer Interfaces: Modeling the Feedback Control Loop, Improving Decoder Performance, and Restoring Upper Limb Function with Muscle Stimulation.” 2017. Web. 19 Nov 2019.

Vancouver:

Willett FR. Intracortical Brain-Computer Interfaces: Modeling the Feedback Control Loop, Improving Decoder Performance, and Restoring Upper Limb Function with Muscle Stimulation. [Internet] [Doctoral dissertation]. Case Western Reserve University School of Graduate Studies; 2017. [cited 2019 Nov 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case149035819787053.

Council of Science Editors:

Willett FR. Intracortical Brain-Computer Interfaces: Modeling the Feedback Control Loop, Improving Decoder Performance, and Restoring Upper Limb Function with Muscle Stimulation. [Doctoral Dissertation]. Case Western Reserve University School of Graduate Studies; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case149035819787053


University of Minnesota

30. Doud, Alexander James. Motor imagery retraining after stroke with virtual hands: an immersive sensorimotor rhythm-based brain-computer interface.

Degree: MS, Biomedical Engineering, 2013, University of Minnesota

University of Minnesota M.S. thesis. June 2013. Major: Biomedical Engineering. Advisor: Bin He. 1 computer file (PDF); v, 34 pages.

The burden of stroke on… (more)

Subjects/Keywords: Brain-computer interface; EEG; Paralysis; Rehabilitation; Stroke; Virtual Reality

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

APA (6th Edition):

Doud, A. J. (2013). Motor imagery retraining after stroke with virtual hands: an immersive sensorimotor rhythm-based brain-computer interface. (Masters Thesis). University of Minnesota. Retrieved from http://purl.umn.edu/157410

Chicago Manual of Style (16th Edition):

Doud, Alexander James. “Motor imagery retraining after stroke with virtual hands: an immersive sensorimotor rhythm-based brain-computer interface.” 2013. Masters Thesis, University of Minnesota. Accessed November 19, 2019. http://purl.umn.edu/157410.

MLA Handbook (7th Edition):

Doud, Alexander James. “Motor imagery retraining after stroke with virtual hands: an immersive sensorimotor rhythm-based brain-computer interface.” 2013. Web. 19 Nov 2019.

Vancouver:

Doud AJ. Motor imagery retraining after stroke with virtual hands: an immersive sensorimotor rhythm-based brain-computer interface. [Internet] [Masters thesis]. University of Minnesota; 2013. [cited 2019 Nov 19]. Available from: http://purl.umn.edu/157410.

Council of Science Editors:

Doud AJ. Motor imagery retraining after stroke with virtual hands: an immersive sensorimotor rhythm-based brain-computer interface. [Masters Thesis]. University of Minnesota; 2013. Available from: http://purl.umn.edu/157410

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