PROBABILISTIC WORKPSACE SCAN MODES OF A ROBOT MANIPULATOR COMMANDED BY EEG SIGNALS

2008 ◽  
Keyword(s):  
Robot Manipulator ◽  
Eeg Signals ◽  
Scan Modes

scholarly journals Probabilistic scan mode of a robot manipulator workspace using EEG signals. Part II

2007 ◽  
Vol 90 ◽  
pp. 012096
Author(s):  
Fernando A Auat Cheeín ◽  
Fernando di Sciascio ◽  
Teodiano Freire Bastos ◽  
Ricardo Carelli
Keyword(s):  
Robot Manipulator ◽  
Eeg Signals

scholarly journals Probabilistic scan mode of a robot manipulator workspace using EEG signals. Part I

2007 ◽  
Vol 90 ◽  
pp. 012095
Author(s):  
Fernando A Auat Cheeín ◽  
Fernando di Sciascio ◽  
Teodiano Freire Bastos ◽  
Ricardo Carelli
Keyword(s):  
Robot Manipulator ◽  
Eeg Signals

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

NEUROFUZZY CONTROL STRUCTURE FOR A ROBOT MANIPULATOR

2006 ◽  
Vol 2 (1) ◽  
pp. 19-31
Author(s):  
Turki Y. Abdalla ◽  
Ammar A. Abdulhmeed
Keyword(s):  
Control Structure ◽  
Robot Manipulator ◽  
Neurofuzzy Control

Dynamics of space elastic robot-manipulator

1997 ◽  
Vol 3 (3-4) ◽  
pp. 90-95
Author(s):  
V.I. Gouliaev ◽  
◽  
T.V. Zavrazhina ◽  
Keyword(s):  
Robot Manipulator

NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

2019 ◽  
pp. 139-145
Author(s):  
Selma Büyükgöze
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Electrode Placement ◽  
Eeg Signals ◽  
Non Invasive ◽  
Brain Signals ◽  
Brain States ◽  
The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

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