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You searched for subject:(brain machine interface). Showing records 1 – 30 of 127 total matches.

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University of Minnesota

1. Gupta, Rahul. On motor learning and force fields: encoding and decoding.

Degree: PhD, Biomedical Engineering, 2010, University of Minnesota

 The control of motor behavior is essential for us to interact with our environment. We possess an almost infinite variety of motor behaviors and acquire… (more)

Subjects/Keywords: Brain machine interface; Biomedical Engineering

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APA (6th Edition):

Gupta, R. (2010). On motor learning and force fields: encoding and decoding. (Doctoral Dissertation). University of Minnesota. Retrieved from http://purl.umn.edu/98382

Chicago Manual of Style (16th Edition):

Gupta, Rahul. “On motor learning and force fields: encoding and decoding.” 2010. Doctoral Dissertation, University of Minnesota. Accessed January 22, 2020. http://purl.umn.edu/98382.

MLA Handbook (7th Edition):

Gupta, Rahul. “On motor learning and force fields: encoding and decoding.” 2010. Web. 22 Jan 2020.

Vancouver:

Gupta R. On motor learning and force fields: encoding and decoding. [Internet] [Doctoral dissertation]. University of Minnesota; 2010. [cited 2020 Jan 22]. Available from: http://purl.umn.edu/98382.

Council of Science Editors:

Gupta R. On motor learning and force fields: encoding and decoding. [Doctoral Dissertation]. University of Minnesota; 2010. Available from: http://purl.umn.edu/98382

2. 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 January 22, 2020. 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. 22 Jan 2020.

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 2020 Jan 22]. 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


University of Illinois – Chicago

3. Gandhi, Devang. Assessment of PGA coated Polyimide Microelectrode as a Flexible, Implantable Neural Interface for CNS.

Degree: 2012, University of Illinois – Chicago

 Neuroprosthetic devices have been suggested as part of a Brain Machine Interface (BMI) intended to restore functionality in humans affected with various sensory or motor… (more)

Subjects/Keywords: Brain; Brain Machine Interface; microelectrode; Implantable Devices

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APA (6th Edition):

Gandhi, D. (2012). Assessment of PGA coated Polyimide Microelectrode as a Flexible, Implantable Neural Interface for CNS. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/8650

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):

Gandhi, Devang. “Assessment of PGA coated Polyimide Microelectrode as a Flexible, Implantable Neural Interface for CNS.” 2012. Thesis, University of Illinois – Chicago. Accessed January 22, 2020. http://hdl.handle.net/10027/8650.

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

MLA Handbook (7th Edition):

Gandhi, Devang. “Assessment of PGA coated Polyimide Microelectrode as a Flexible, Implantable Neural Interface for CNS.” 2012. Web. 22 Jan 2020.

Vancouver:

Gandhi D. Assessment of PGA coated Polyimide Microelectrode as a Flexible, Implantable Neural Interface for CNS. [Internet] [Thesis]. University of Illinois – Chicago; 2012. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/10027/8650.

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

Council of Science Editors:

Gandhi D. Assessment of PGA coated Polyimide Microelectrode as a Flexible, Implantable Neural Interface for CNS. [Thesis]. University of Illinois – Chicago; 2012. Available from: http://hdl.handle.net/10027/8650

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


Rochester Institute of Technology

4. 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 January 22, 2020. 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. 22 Jan 2020.

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 2020 Jan 22]. 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 New South Wales

5. Firth, Josiah. Towards a new generation of brain–machine interface: an electro-optic approach.

Degree: Electrical Engineering & Telecommunications, 2018, University of New South Wales

 This thesis presents an investigation into the design and fabrication of an electro-optic device for transducing small biological voltage signals into the optical domain using… (more)

Subjects/Keywords: Optrode; Brain-machine interface; Liquid crystal

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APA (6th Edition):

Firth, J. (2018). Towards a new generation of brain–machine interface: an electro-optic approach. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/60922 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:54291/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Firth, Josiah. “Towards a new generation of brain–machine interface: an electro-optic approach.” 2018. Doctoral Dissertation, University of New South Wales. Accessed January 22, 2020. http://handle.unsw.edu.au/1959.4/60922 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:54291/SOURCE02?view=true.

MLA Handbook (7th Edition):

Firth, Josiah. “Towards a new generation of brain–machine interface: an electro-optic approach.” 2018. Web. 22 Jan 2020.

Vancouver:

Firth J. Towards a new generation of brain–machine interface: an electro-optic approach. [Internet] [Doctoral dissertation]. University of New South Wales; 2018. [cited 2020 Jan 22]. Available from: http://handle.unsw.edu.au/1959.4/60922 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:54291/SOURCE02?view=true.

Council of Science Editors:

Firth J. Towards a new generation of brain–machine interface: an electro-optic approach. [Doctoral Dissertation]. University of New South Wales; 2018. Available from: http://handle.unsw.edu.au/1959.4/60922 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:54291/SOURCE02?view=true


Université de Grenoble

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

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 January 22, 2020. 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. 22 Jan 2020.

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 2020 Jan 22]. 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 Kansas

7. Guggenmos, David. Driving Functional Behavioral Recovery Using Activity-Dependent Stimulation.

Degree: PhD, Molecular & Integrative Physiology, 2012, University of Kansas

 The purpose of this project was to determine if artificially linking spared motor and sensory areas following a cortical lesion would lead to increased behavioral… (more)

Subjects/Keywords: Physiology; Bmi; Brain-machine-brain interface; Cortical plasticity; Motor cortex

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APA (6th Edition):

Guggenmos, D. (2012). Driving Functional Behavioral Recovery Using Activity-Dependent Stimulation. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/14839

Chicago Manual of Style (16th Edition):

Guggenmos, David. “Driving Functional Behavioral Recovery Using Activity-Dependent Stimulation.” 2012. Doctoral Dissertation, University of Kansas. Accessed January 22, 2020. http://hdl.handle.net/1808/14839.

MLA Handbook (7th Edition):

Guggenmos, David. “Driving Functional Behavioral Recovery Using Activity-Dependent Stimulation.” 2012. Web. 22 Jan 2020.

Vancouver:

Guggenmos D. Driving Functional Behavioral Recovery Using Activity-Dependent Stimulation. [Internet] [Doctoral dissertation]. University of Kansas; 2012. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/1808/14839.

Council of Science Editors:

Guggenmos D. Driving Functional Behavioral Recovery Using Activity-Dependent Stimulation. [Doctoral Dissertation]. University of Kansas; 2012. Available from: http://hdl.handle.net/1808/14839

8. Giovanini, Renato de Macedo [UNESP]. SSVEP-EEG signal pattern recognition system for real-time brain-computer interfaces applications.

Degree: 2017, Universidade Estadual Paulista

There are, nowadays, about 110 million people in the world who live with some type of severe motor disability. Specifically in Brazil, about 2.2% of… (more)

Subjects/Keywords: Pattern recognition; Machine learning; Brain-machine interface; Brain-computer interface; Python; Raspberry Pi; Open-source; Reconhecimento de padrões; Aprendizado de máquina; Interface cérebro-máquina; Interface cérebro-computador

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APA (6th Edition):

Giovanini, R. d. M. [. (2017). SSVEP-EEG signal pattern recognition system for real-time brain-computer interfaces applications. (Thesis). Universidade Estadual Paulista. Retrieved from http://hdl.handle.net/11449/151710

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):

Giovanini, Renato de Macedo [UNESP]. “SSVEP-EEG signal pattern recognition system for real-time brain-computer interfaces applications.” 2017. Thesis, Universidade Estadual Paulista. Accessed January 22, 2020. http://hdl.handle.net/11449/151710.

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

MLA Handbook (7th Edition):

Giovanini, Renato de Macedo [UNESP]. “SSVEP-EEG signal pattern recognition system for real-time brain-computer interfaces applications.” 2017. Web. 22 Jan 2020.

Vancouver:

Giovanini RdM[. SSVEP-EEG signal pattern recognition system for real-time brain-computer interfaces applications. [Internet] [Thesis]. Universidade Estadual Paulista; 2017. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/11449/151710.

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

Council of Science Editors:

Giovanini RdM[. SSVEP-EEG signal pattern recognition system for real-time brain-computer interfaces applications. [Thesis]. Universidade Estadual Paulista; 2017. Available from: http://hdl.handle.net/11449/151710

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


University of Illinois – Urbana-Champaign

9. Osuagwu, Onyeama E. Brain-machine interface coupled cognitive sensory fusion with a Kohonen and reservoir computing scheme.

Degree: PhD, Electrical & Computer Engineering, 2015, University of Illinois – Urbana-Champaign

 Artificial Intelligence (AI) has been a source of great intrigue and has spawned many questions regarding the human condition and the core of what it… (more)

Subjects/Keywords: Artificial Intelligence; Robotics; Neural Networks; Natural Language Acquisition; Brain-Machine Interface

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APA (6th Edition):

Osuagwu, O. E. (2015). Brain-machine interface coupled cognitive sensory fusion with a Kohonen and reservoir computing scheme. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/89230

Chicago Manual of Style (16th Edition):

Osuagwu, Onyeama E. “Brain-machine interface coupled cognitive sensory fusion with a Kohonen and reservoir computing scheme.” 2015. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed January 22, 2020. http://hdl.handle.net/2142/89230.

MLA Handbook (7th Edition):

Osuagwu, Onyeama E. “Brain-machine interface coupled cognitive sensory fusion with a Kohonen and reservoir computing scheme.” 2015. Web. 22 Jan 2020.

Vancouver:

Osuagwu OE. Brain-machine interface coupled cognitive sensory fusion with a Kohonen and reservoir computing scheme. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2015. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/2142/89230.

Council of Science Editors:

Osuagwu OE. Brain-machine interface coupled cognitive sensory fusion with a Kohonen and reservoir computing scheme. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/89230


Purdue University

10. Regele, Oliver Brian. The Perceptual Salience of Amplitude Modulated Cortical Stimulation: Peak Equivalence or RMS Equivalence?.

Degree: MSin Biomedical Engineering, Biomedical Engineering, 2013, Purdue University

  Intracortical microstimulation (ICMS) is a method of electrically stimulating the primary motor, visual, somatosensory and auditory cortices in the brain. The goal is to… (more)

Subjects/Keywords: auditory cortex; brain machine interface; intracortical microstimulation; neuroprosthetics; Biomedical

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APA (6th Edition):

Regele, O. B. (2013). The Perceptual Salience of Amplitude Modulated Cortical Stimulation: Peak Equivalence or RMS Equivalence?. (Thesis). Purdue University. Retrieved from http://docs.lib.purdue.edu/open_access_theses/66

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):

Regele, Oliver Brian. “The Perceptual Salience of Amplitude Modulated Cortical Stimulation: Peak Equivalence or RMS Equivalence?.” 2013. Thesis, Purdue University. Accessed January 22, 2020. http://docs.lib.purdue.edu/open_access_theses/66.

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

MLA Handbook (7th Edition):

Regele, Oliver Brian. “The Perceptual Salience of Amplitude Modulated Cortical Stimulation: Peak Equivalence or RMS Equivalence?.” 2013. Web. 22 Jan 2020.

Vancouver:

Regele OB. The Perceptual Salience of Amplitude Modulated Cortical Stimulation: Peak Equivalence or RMS Equivalence?. [Internet] [Thesis]. Purdue University; 2013. [cited 2020 Jan 22]. Available from: http://docs.lib.purdue.edu/open_access_theses/66.

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

Council of Science Editors:

Regele OB. The Perceptual Salience of Amplitude Modulated Cortical Stimulation: Peak Equivalence or RMS Equivalence?. [Thesis]. Purdue University; 2013. Available from: http://docs.lib.purdue.edu/open_access_theses/66

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


University of California – Berkeley

11. So, Kelvin. Changes in neural activity during brain-machine interface control: from information encoding and connectivity to local field potentials.

Degree: Electrical Engineering & Computer Sciences, 2013, University of California – Berkeley

Brain-machine interfaces (BMIs) are an emerging field of research that seeks to interface the brain directly with prosthetic devices. Researchers have exhibited compelling proof-of-concept experiments… (more)

Subjects/Keywords: Electrical engineering; Neurosciences; brain-machine interface; neural engineering; signal processing

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APA (6th Edition):

So, K. (2013). Changes in neural activity during brain-machine interface control: from information encoding and connectivity to local field potentials. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/1tn846g9

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):

So, Kelvin. “Changes in neural activity during brain-machine interface control: from information encoding and connectivity to local field potentials.” 2013. Thesis, University of California – Berkeley. Accessed January 22, 2020. http://www.escholarship.org/uc/item/1tn846g9.

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

MLA Handbook (7th Edition):

So, Kelvin. “Changes in neural activity during brain-machine interface control: from information encoding and connectivity to local field potentials.” 2013. Web. 22 Jan 2020.

Vancouver:

So K. Changes in neural activity during brain-machine interface control: from information encoding and connectivity to local field potentials. [Internet] [Thesis]. University of California – Berkeley; 2013. [cited 2020 Jan 22]. Available from: http://www.escholarship.org/uc/item/1tn846g9.

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

Council of Science Editors:

So K. Changes in neural activity during brain-machine interface control: from information encoding and connectivity to local field potentials. [Thesis]. University of California – Berkeley; 2013. Available from: http://www.escholarship.org/uc/item/1tn846g9

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


University of California – Berkeley

12. Moorman, Helene. Representation and control in closed-loop brain-machine interface systems.

Degree: Neuroscience, 2015, University of California – Berkeley

Brain-machine interface (BMI) systems attempt to restore motor function lost due to injury or neurodegenerative disease by bypassing natural motor pathways and allowing direct neural… (more)

Subjects/Keywords: Neurosciences; brain-machine interface; motor control; motor learning; prosthetics; redundant control

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APA (6th Edition):

Moorman, H. (2015). Representation and control in closed-loop brain-machine interface systems. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/3x1645gm

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):

Moorman, Helene. “Representation and control in closed-loop brain-machine interface systems.” 2015. Thesis, University of California – Berkeley. Accessed January 22, 2020. http://www.escholarship.org/uc/item/3x1645gm.

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

MLA Handbook (7th Edition):

Moorman, Helene. “Representation and control in closed-loop brain-machine interface systems.” 2015. Web. 22 Jan 2020.

Vancouver:

Moorman H. Representation and control in closed-loop brain-machine interface systems. [Internet] [Thesis]. University of California – Berkeley; 2015. [cited 2020 Jan 22]. Available from: http://www.escholarship.org/uc/item/3x1645gm.

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

Council of Science Editors:

Moorman H. Representation and control in closed-loop brain-machine interface systems. [Thesis]. University of California – Berkeley; 2015. Available from: http://www.escholarship.org/uc/item/3x1645gm

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


University of California – Berkeley

13. Clancy, Kelly. Using calcium imaging to understand function and learning in layer 2/3 of cerebral cortex.

Degree: Biophysics, 2014, University of California – Berkeley

 Sensory information is encoded with sparse spiking in rodent sensory cortex, but the organization and functional basis of this sparse code is not well understood.… (more)

Subjects/Keywords: Neurosciences; brain machine interface; calcium imaging; somatosensory cortex; sparse coding

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APA (6th Edition):

Clancy, K. (2014). Using calcium imaging to understand function and learning in layer 2/3 of cerebral cortex. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/3dn3388c

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):

Clancy, Kelly. “Using calcium imaging to understand function and learning in layer 2/3 of cerebral cortex.” 2014. Thesis, University of California – Berkeley. Accessed January 22, 2020. http://www.escholarship.org/uc/item/3dn3388c.

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

MLA Handbook (7th Edition):

Clancy, Kelly. “Using calcium imaging to understand function and learning in layer 2/3 of cerebral cortex.” 2014. Web. 22 Jan 2020.

Vancouver:

Clancy K. Using calcium imaging to understand function and learning in layer 2/3 of cerebral cortex. [Internet] [Thesis]. University of California – Berkeley; 2014. [cited 2020 Jan 22]. Available from: http://www.escholarship.org/uc/item/3dn3388c.

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

Council of Science Editors:

Clancy K. Using calcium imaging to understand function and learning in layer 2/3 of cerebral cortex. [Thesis]. University of California – Berkeley; 2014. Available from: http://www.escholarship.org/uc/item/3dn3388c

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


Washington University in St. Louis

14. 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 January 22, 2020. 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. 22 Jan 2020.

Vancouver:

Liu Y. Decoding Brain Activation from Ipsilateral Cortex using ECoG Signals in Humans. [Internet] [Thesis]. Washington University in St. Louis; 2011. [cited 2020 Jan 22]. 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


University of Houston

15. Tisa, Tamanna Afrin. Development of Multi-Electrode Neural Probe on Optical Fiber Substrate for Brain-Machine Interfaces.

Degree: Electrical and Computer Engineering, Department of, 2018, University of Houston

Brain-machine interfaces (BMIs) aim to restore communication and control of prosthetic devices to individuals with neurological injury or disease, by recording the neural activity, and… (more)

Subjects/Keywords: Brain-machine interface; optical fiber; optogenetics; lithography; neural probe

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APA (6th Edition):

Tisa, T. A. (2018). Development of Multi-Electrode Neural Probe on Optical Fiber Substrate for Brain-Machine Interfaces. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3430

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):

Tisa, Tamanna Afrin. “Development of Multi-Electrode Neural Probe on Optical Fiber Substrate for Brain-Machine Interfaces.” 2018. Thesis, University of Houston. Accessed January 22, 2020. http://hdl.handle.net/10657/3430.

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

MLA Handbook (7th Edition):

Tisa, Tamanna Afrin. “Development of Multi-Electrode Neural Probe on Optical Fiber Substrate for Brain-Machine Interfaces.” 2018. Web. 22 Jan 2020.

Vancouver:

Tisa TA. Development of Multi-Electrode Neural Probe on Optical Fiber Substrate for Brain-Machine Interfaces. [Internet] [Thesis]. University of Houston; 2018. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/10657/3430.

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

Council of Science Editors:

Tisa TA. Development of Multi-Electrode Neural Probe on Optical Fiber Substrate for Brain-Machine Interfaces. [Thesis]. University of Houston; 2018. Available from: http://hdl.handle.net/10657/3430

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


ETH Zürich

16. Kassraian Fard, Pegah. Multivariate Analysis Methods in Cognitive Neuroimaging: Applications in Basic and Clinical Research.

Degree: 2018, ETH Zürich

 Multivariate decoding methods have revolutionized cognitive neuroimaging in recent years by enabling the extraction of spatially distributed neuronal responses not accessible to traditionally used univariate… (more)

Subjects/Keywords: Multivariate pattern analysis; fMRI; Somatosensation; Brain computer interface (BCI); Machine Learning

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APA (6th Edition):

Kassraian Fard, P. (2018). Multivariate Analysis Methods in Cognitive Neuroimaging: Applications in Basic and Clinical Research. (Doctoral Dissertation). ETH Zürich. Retrieved from http://hdl.handle.net/20.500.11850/271893

Chicago Manual of Style (16th Edition):

Kassraian Fard, Pegah. “Multivariate Analysis Methods in Cognitive Neuroimaging: Applications in Basic and Clinical Research.” 2018. Doctoral Dissertation, ETH Zürich. Accessed January 22, 2020. http://hdl.handle.net/20.500.11850/271893.

MLA Handbook (7th Edition):

Kassraian Fard, Pegah. “Multivariate Analysis Methods in Cognitive Neuroimaging: Applications in Basic and Clinical Research.” 2018. Web. 22 Jan 2020.

Vancouver:

Kassraian Fard P. Multivariate Analysis Methods in Cognitive Neuroimaging: Applications in Basic and Clinical Research. [Internet] [Doctoral dissertation]. ETH Zürich; 2018. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/20.500.11850/271893.

Council of Science Editors:

Kassraian Fard P. Multivariate Analysis Methods in Cognitive Neuroimaging: Applications in Basic and Clinical Research. [Doctoral Dissertation]. ETH Zürich; 2018. Available from: http://hdl.handle.net/20.500.11850/271893


University of Houston

17. Agashe, Harshavardhan A. Noninvasive Neuroprosthetic Control of Grasping by Amputees.

Degree: Electrical and Computer Engineering, Department of, 2014, University of Houston

 Smooth coordination and fine temporal control of muscles by the brain allows us to effortlessly pre-shape our hand to grasp different objects. Correlates of motor… (more)

Subjects/Keywords: brain-machine interface; electroencephalography; EEG; upper limb; neuroprosthetic

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

APA (6th Edition):

Agashe, H. A. (2014). Noninvasive Neuroprosthetic Control of Grasping by Amputees. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/1663

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):

Agashe, Harshavardhan A. “Noninvasive Neuroprosthetic Control of Grasping by Amputees.” 2014. Thesis, University of Houston. Accessed January 22, 2020. http://hdl.handle.net/10657/1663.

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

MLA Handbook (7th Edition):

Agashe, Harshavardhan A. “Noninvasive Neuroprosthetic Control of Grasping by Amputees.” 2014. Web. 22 Jan 2020.

Vancouver:

Agashe HA. Noninvasive Neuroprosthetic Control of Grasping by Amputees. [Internet] [Thesis]. University of Houston; 2014. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/10657/1663.

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

Council of Science Editors:

Agashe HA. Noninvasive Neuroprosthetic Control of Grasping by Amputees. [Thesis]. University of Houston; 2014. Available from: http://hdl.handle.net/10657/1663

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


University of Toronto

18. Palikarova, Stella. The Informational Body: A Sociomedical Theory of Disability and the Ethics of the Brain-Machine Interface (BMI).

Degree: 2016, University of Toronto

Cybernetic and bionic technologies hold great emancipatory potential for people with disabilities. Yet, scientists and disability scholars are polarized in their views on developing biotechnologies.… (more)

Subjects/Keywords: brain-machine interface; disability; ethics; heuristics; information; sociomedical; 0723

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APA (6th Edition):

Palikarova, S. (2016). The Informational Body: A Sociomedical Theory of Disability and the Ethics of the Brain-Machine Interface (BMI). (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/92629

Chicago Manual of Style (16th Edition):

Palikarova, Stella. “The Informational Body: A Sociomedical Theory of Disability and the Ethics of the Brain-Machine Interface (BMI).” 2016. Masters Thesis, University of Toronto. Accessed January 22, 2020. http://hdl.handle.net/1807/92629.

MLA Handbook (7th Edition):

Palikarova, Stella. “The Informational Body: A Sociomedical Theory of Disability and the Ethics of the Brain-Machine Interface (BMI).” 2016. Web. 22 Jan 2020.

Vancouver:

Palikarova S. The Informational Body: A Sociomedical Theory of Disability and the Ethics of the Brain-Machine Interface (BMI). [Internet] [Masters thesis]. University of Toronto; 2016. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/1807/92629.

Council of Science Editors:

Palikarova S. The Informational Body: A Sociomedical Theory of Disability and the Ethics of the Brain-Machine Interface (BMI). [Masters Thesis]. University of Toronto; 2016. Available from: http://hdl.handle.net/1807/92629


Duke University

19. Hanson, Timothy Lars. Technology for Brain-Machine Interfaces .

Degree: 2012, Duke University

Brain-machine interfaces (BMIs) use recordings from the nervous system to extract volitional and motor parameters for controlling external actuators, such as prosthetics, thereby bypassing… (more)

Subjects/Keywords: Electrical engineering; Biomedical engineering; brain machine interface; microstimulation; recording; wireless

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

APA (6th Edition):

Hanson, T. L. (2012). Technology for Brain-Machine Interfaces . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/5404

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):

Hanson, Timothy Lars. “Technology for Brain-Machine Interfaces .” 2012. Thesis, Duke University. Accessed January 22, 2020. http://hdl.handle.net/10161/5404.

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

MLA Handbook (7th Edition):

Hanson, Timothy Lars. “Technology for Brain-Machine Interfaces .” 2012. Web. 22 Jan 2020.

Vancouver:

Hanson TL. Technology for Brain-Machine Interfaces . [Internet] [Thesis]. Duke University; 2012. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/10161/5404.

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

Council of Science Editors:

Hanson TL. Technology for Brain-Machine Interfaces . [Thesis]. Duke University; 2012. Available from: http://hdl.handle.net/10161/5404

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


Duke University

20. An, Je Hi. Cortical Somatosensory Neuroprosthesis for Active Tactile Exploration without Visual Feedback .

Degree: 2013, Duke University

Brain Machine Interfaces (BMI) strive to restore motor and sensory functions lost due to paralysis, amputation, and neurological diseases by interfacing brain circuitry to… (more)

Subjects/Keywords: Biomedical engineering; Neurosciences; brain machine interface; microstimulation; visual feedback

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APA (6th Edition):

An, J. H. (2013). Cortical Somatosensory Neuroprosthesis for Active Tactile Exploration without Visual Feedback . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/8208

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):

An, Je Hi. “Cortical Somatosensory Neuroprosthesis for Active Tactile Exploration without Visual Feedback .” 2013. Thesis, Duke University. Accessed January 22, 2020. http://hdl.handle.net/10161/8208.

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

MLA Handbook (7th Edition):

An, Je Hi. “Cortical Somatosensory Neuroprosthesis for Active Tactile Exploration without Visual Feedback .” 2013. Web. 22 Jan 2020.

Vancouver:

An JH. Cortical Somatosensory Neuroprosthesis for Active Tactile Exploration without Visual Feedback . [Internet] [Thesis]. Duke University; 2013. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/10161/8208.

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

Council of Science Editors:

An JH. Cortical Somatosensory Neuroprosthesis for Active Tactile Exploration without Visual Feedback . [Thesis]. Duke University; 2013. Available from: http://hdl.handle.net/10161/8208

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


Boston University

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

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 January 22, 2020. 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. 22 Jan 2020.

Vancouver:

Panko M. Developing implant technologies and evaluating brain-machine interfaces using information theory. [Internet] [Doctoral dissertation]. Boston University; 2014. [cited 2020 Jan 22]. 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


Carnegie Mellon University

22. 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 January 22, 2020. 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. 22 Jan 2020.

Vancouver:

Clanton ST. Brain-Computer Interface Control of an Anthropomorphic Robotic Arm. [Internet] [Thesis]. Carnegie Mellon University; 2011. [cited 2020 Jan 22]. 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

23. 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 January 22, 2020. 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. 22 Jan 2020.

Vancouver:

Dangi S. Closed-loop decoder adaptation algorithms for brain-machine interface systems. [Internet] [Thesis]. University of California – Berkeley; 2015. [cited 2020 Jan 22]. 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

24. 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 January 22, 2020. 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. 22 Jan 2020.

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 2020 Jan 22]. 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


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 January 22, 2020. 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. 22 Jan 2020.

Vancouver:

Li Z. Non-Linear Adaptive Bayesian Filtering for Brain Machine Interfaces . [Internet] [Thesis]. Duke University; 2010. [cited 2020 Jan 22]. 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

26. Bocquelet, Florent. Vers une interface cerveau-machine pour la restauration de la parole : Toward a brain-computer interface for speech restoration.

Degree: Docteur es, Biotechnologie, instrumentation, signal et imagerie pour la biologie, la médecine et l'environnement, 2017, Grenoble Alpes

Restorer la faculté de parler chez des personnes paralysées et aphasiques pourrait être envisagée via l’utilisation d’une interface cerveau-machine permettant de contrôler un synthétiseur de… (more)

Subjects/Keywords: Interface cerveau-Machine; Parole; Restauration; Reconnaissance formes; Bci; Synthèse parole; Brain-Computer interface; Speech; Restoration; Bci; Speech synthesis; Machine learning; 620

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APA (6th Edition):

Bocquelet, F. (2017). Vers une interface cerveau-machine pour la restauration de la parole : Toward a brain-computer interface for speech restoration. (Doctoral Dissertation). Grenoble Alpes. Retrieved from http://www.theses.fr/2017GREAS008

Chicago Manual of Style (16th Edition):

Bocquelet, Florent. “Vers une interface cerveau-machine pour la restauration de la parole : Toward a brain-computer interface for speech restoration.” 2017. Doctoral Dissertation, Grenoble Alpes. Accessed January 22, 2020. http://www.theses.fr/2017GREAS008.

MLA Handbook (7th Edition):

Bocquelet, Florent. “Vers une interface cerveau-machine pour la restauration de la parole : Toward a brain-computer interface for speech restoration.” 2017. Web. 22 Jan 2020.

Vancouver:

Bocquelet F. Vers une interface cerveau-machine pour la restauration de la parole : Toward a brain-computer interface for speech restoration. [Internet] [Doctoral dissertation]. Grenoble Alpes; 2017. [cited 2020 Jan 22]. Available from: http://www.theses.fr/2017GREAS008.

Council of Science Editors:

Bocquelet F. Vers une interface cerveau-machine pour la restauration de la parole : Toward a brain-computer interface for speech restoration. [Doctoral Dissertation]. Grenoble Alpes; 2017. Available from: http://www.theses.fr/2017GREAS008

27. De Boutaud De Lavilléon, Gaetan. De la corrélation à la causalité : apports des interfaces cerveaux-machines sur l'étude des réactivations des cellules de lieu et des oscillations lentes du sommeil. : From correlation to causality : use of brain-machine interfaces to disentangle place cell reactivations and slow oscillations during sleep.

Degree: Docteur es, Neurosciences, 2015, Université Pierre et Marie Curie – Paris VI

La mémoire spatiale est composée d'une phase d''encodage pendant l'éveil, suivi par une phase de consolidation pendant le sommeil, au cours de laquelle les séquences… (more)

Subjects/Keywords: Mémoire; Sommeil; Interface Cerveau-Machine; Cellules de Lieu; Ondes delta; Électrophysiologie; Memory; Sleep; Brain machine interface; 612.821

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APA (6th Edition):

De Boutaud De Lavilléon, G. (2015). De la corrélation à la causalité : apports des interfaces cerveaux-machines sur l'étude des réactivations des cellules de lieu et des oscillations lentes du sommeil. : From correlation to causality : use of brain-machine interfaces to disentangle place cell reactivations and slow oscillations during sleep. (Doctoral Dissertation). Université Pierre et Marie Curie – Paris VI. Retrieved from http://www.theses.fr/2015PA066708

Chicago Manual of Style (16th Edition):

De Boutaud De Lavilléon, Gaetan. “De la corrélation à la causalité : apports des interfaces cerveaux-machines sur l'étude des réactivations des cellules de lieu et des oscillations lentes du sommeil. : From correlation to causality : use of brain-machine interfaces to disentangle place cell reactivations and slow oscillations during sleep.” 2015. Doctoral Dissertation, Université Pierre et Marie Curie – Paris VI. Accessed January 22, 2020. http://www.theses.fr/2015PA066708.

MLA Handbook (7th Edition):

De Boutaud De Lavilléon, Gaetan. “De la corrélation à la causalité : apports des interfaces cerveaux-machines sur l'étude des réactivations des cellules de lieu et des oscillations lentes du sommeil. : From correlation to causality : use of brain-machine interfaces to disentangle place cell reactivations and slow oscillations during sleep.” 2015. Web. 22 Jan 2020.

Vancouver:

De Boutaud De Lavilléon G. De la corrélation à la causalité : apports des interfaces cerveaux-machines sur l'étude des réactivations des cellules de lieu et des oscillations lentes du sommeil. : From correlation to causality : use of brain-machine interfaces to disentangle place cell reactivations and slow oscillations during sleep. [Internet] [Doctoral dissertation]. Université Pierre et Marie Curie – Paris VI; 2015. [cited 2020 Jan 22]. Available from: http://www.theses.fr/2015PA066708.

Council of Science Editors:

De Boutaud De Lavilléon G. De la corrélation à la causalité : apports des interfaces cerveaux-machines sur l'étude des réactivations des cellules de lieu et des oscillations lentes du sommeil. : From correlation to causality : use of brain-machine interfaces to disentangle place cell reactivations and slow oscillations during sleep. [Doctoral Dissertation]. Université Pierre et Marie Curie – Paris VI; 2015. Available from: http://www.theses.fr/2015PA066708


Arizona State University

28. Padmanaban, Subash. Algorithms for Neural Prosthetic Applications.

Degree: Bioengineering, 2017, Arizona State University

 In the last 15 years, there has been a significant increase in the number of motor neural prostheses used for restoring limb function lost due… (more)

Subjects/Keywords: Neurosciences; Biomedical engineering; Computer science; Brain machine interface; Feature selection; Machine learning; Neural prosthesis; Neuroscience; Peripheral nerve interface

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

APA (6th Edition):

Padmanaban, S. (2017). Algorithms for Neural Prosthetic Applications. (Doctoral Dissertation). Arizona State University. Retrieved from http://repository.asu.edu/items/44128

Chicago Manual of Style (16th Edition):

Padmanaban, Subash. “Algorithms for Neural Prosthetic Applications.” 2017. Doctoral Dissertation, Arizona State University. Accessed January 22, 2020. http://repository.asu.edu/items/44128.

MLA Handbook (7th Edition):

Padmanaban, Subash. “Algorithms for Neural Prosthetic Applications.” 2017. Web. 22 Jan 2020.

Vancouver:

Padmanaban S. Algorithms for Neural Prosthetic Applications. [Internet] [Doctoral dissertation]. Arizona State University; 2017. [cited 2020 Jan 22]. Available from: http://repository.asu.edu/items/44128.

Council of Science Editors:

Padmanaban S. Algorithms for Neural Prosthetic Applications. [Doctoral Dissertation]. Arizona State University; 2017. Available from: http://repository.asu.edu/items/44128


Université Catholique de Louvain

29. Delhaye, Benjamin. Design of a BMI for tetraplegic patients.

Degree: 2016, Université Catholique de Louvain

Tetraplegia is a paralysis of the four limbs, which leaves attained people without their full autonomy and freedom. Indeed, tetraplegia not only affects the movement… (more)

Subjects/Keywords: Brain-Machine Interface (BMI); Brain-Computer Interface (BCI); Neuroprosthetics; Electroencephalogram (EEG); Motor Imagery; Field-Programmable Gate Array (FPGA); Support Vector Machine (SVM); Autoregressive (AR) Model

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

APA (6th Edition):

Delhaye, B. (2016). Design of a BMI for tetraplegic patients. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:6738

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):

Delhaye, Benjamin. “Design of a BMI for tetraplegic patients.” 2016. Thesis, Université Catholique de Louvain. Accessed January 22, 2020. http://hdl.handle.net/2078.1/thesis:6738.

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

MLA Handbook (7th Edition):

Delhaye, Benjamin. “Design of a BMI for tetraplegic patients.” 2016. Web. 22 Jan 2020.

Vancouver:

Delhaye B. Design of a BMI for tetraplegic patients. [Internet] [Thesis]. Université Catholique de Louvain; 2016. [cited 2020 Jan 22]. Available from: http://hdl.handle.net/2078.1/thesis:6738.

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

Council of Science Editors:

Delhaye B. Design of a BMI for tetraplegic patients. [Thesis]. Université Catholique de Louvain; 2016. Available from: http://hdl.handle.net/2078.1/thesis:6738

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


Université de Grenoble

30. Rousseau, Sandra. Influence du retour sensoriel dans les interfaces cerveau machine EEG : étude du potentiel d'erreur : Influence of neurofeedback in brain-computer interfaces : study of the error-related potential.

Degree: Docteur es, Signal, Image, Parole et Télécoms, 2012, Université de Grenoble

Dans cette thèse nous proposons d'étudier le potentiel d'erreur et sa possible intégration dans les ICMs (Interfaces cerveau machine). Le potentiel d'erreur (ErrP) est un… (more)

Subjects/Keywords: Interface cerveau-machine; Electroencéphalogramme; Temps-réel; Brain-Computer Intrface; Electroencephalography; Real-Time; 620

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

APA (6th Edition):

Rousseau, S. (2012). Influence du retour sensoriel dans les interfaces cerveau machine EEG : étude du potentiel d'erreur : Influence of neurofeedback in brain-computer interfaces : study of the error-related potential. (Doctoral Dissertation). Université de Grenoble. Retrieved from http://www.theses.fr/2012GRENT101

Chicago Manual of Style (16th Edition):

Rousseau, Sandra. “Influence du retour sensoriel dans les interfaces cerveau machine EEG : étude du potentiel d'erreur : Influence of neurofeedback in brain-computer interfaces : study of the error-related potential.” 2012. Doctoral Dissertation, Université de Grenoble. Accessed January 22, 2020. http://www.theses.fr/2012GRENT101.

MLA Handbook (7th Edition):

Rousseau, Sandra. “Influence du retour sensoriel dans les interfaces cerveau machine EEG : étude du potentiel d'erreur : Influence of neurofeedback in brain-computer interfaces : study of the error-related potential.” 2012. Web. 22 Jan 2020.

Vancouver:

Rousseau S. Influence du retour sensoriel dans les interfaces cerveau machine EEG : étude du potentiel d'erreur : Influence of neurofeedback in brain-computer interfaces : study of the error-related potential. [Internet] [Doctoral dissertation]. Université de Grenoble; 2012. [cited 2020 Jan 22]. Available from: http://www.theses.fr/2012GRENT101.

Council of Science Editors:

Rousseau S. Influence du retour sensoriel dans les interfaces cerveau machine EEG : étude du potentiel d'erreur : Influence of neurofeedback in brain-computer interfaces : study of the error-related potential. [Doctoral Dissertation]. Université de Grenoble; 2012. Available from: http://www.theses.fr/2012GRENT101

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