A Brain-Computer Interface for arbitrary Pick and Place Tasks
01 Feb 2019-
TL;DR: A higher-level interface in which the user has to select the location of an object on his/her computer screen, which needs to be picked up or the location where the object needs to been placed, and a 2-class SSVEP paradigm is utilized.
Abstract: The Brain-Computer Interfaces are quite useful for persons with neurodegenerative disorders. This paper presents such an interface which is useful and intuitive for arbitrary pick and place tasks. We have developed a higher-level interface in which the user has to select the location of an object on his/her computer screen, which needs to be picked up or the location where the object needs to be placed. After providing the location, the robot directly reaches to pick the object or to place the object at the selected location. To select these locations, we have utilized a 2-class SSVEP paradigm. Using the SSVEP and eye-blinks, the user is able to perform pick and place task at arbitrary locations.
References
More filters
TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
6,803 citations
"A Brain-Computer Interface for arbi..." refers background in this paper
...The Brain-Computer interfaces (BCIs)[1] are a boon for persons with neurogenerative disorders....
[...]
TL;DR: In this paper, a simple procedure is derived which determines a best rotation of a given vector set into a second vector set by minimizing the weighted sum of squared deviations, which is generalized for any given metric constraint on the transformation.
Abstract: A simple procedure is derived which determines a best rotation of a given vector set into a second vector set by minimizing the weighted sum of squared deviations. The method is generalized for any given metric constraint on the transformation.
2,843 citations
TL;DR: The discrimination between the four motor imagery tasks based on classification of single EEG trials improved when, in addition to event-related desynchronization (ERD), event- related synchronization (ERS) patterns were induced in at least one or two tasks.
1,402 citations
TL;DR: A recognition approach is proposed based on the extracted frequency features for an SSVEP-based brain computer interface (BCI) that were higher than those using a widely used fast Fourier transform (FFT)-based spectrum estimation method.
Abstract: Canonical correlation analysis (CCA) is applied to analyze the frequency components of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG). The essence of this method is to extract a narrowband frequency component of SSVEP in EEG. A recognition approach is proposed based on the extracted frequency features for an SSVEP-based brain computer interface (BCI). Recognition Results of the approach were higher than those using a widely used fast Fourier transform (FFT)-based spectrum estimation method
826 citations
"A Brain-Computer Interface for arbi..." refers background or methods in this paper
...[3] used 12 stimuli, [11] used 9 stimuli and [12] used 6 stimuli flickering at different frequencies....
[...]
...The SSVEP is the response of the brain, which is primarily detected at the visual cortex, to a visual stimulus modulated at a frequency more than 6 Hz [11]....
[...]
...SSVEP can be detected by simple Power Spectrum analysis of the EEG recorded as in [3] or by using canonical correlation analysis as in [11] and [12]....
[...]
TL;DR: A brain-computer interface that can help users to input phone numbers based on the steady-state visual evoked potential (SSVEP), which has noninvasive signal recording, little training required for use, and high information transfer rate.
Abstract: This paper presents a brain-computer interface (BCI) that can help users to input phone numbers. The system is based on the steady-state visual evoked potential (SSVEP). Twelve buttons illuminated at different rates were displayed on a computer monitor. The buttons constituted a virtual telephone keypad, representing the ten digits 0-9, BACKSPACE, and ENTER. Users could input phone number by gazing at these buttons. The frequency-coded SSVEP was used to judge which button the user desired. Eight of the thirteen subjects succeeded in ringing the mobile phone using the system. The average transfer rate over all subjects was 27.15 bits/min. The attractive features of the system are noninvasive signal recording, little training required for use, and high information transfer rate. Approaches to improve the performance of the system are discussed.
765 citations
"A Brain-Computer Interface for arbi..." refers background or methods in this paper
...[3] used 12 stimuli, [11] used 9 stimuli and [12] used 6 stimuli flickering at different frequencies....
[...]
...Motor-Imagery[2], Steady State Visually Evoked Potentials(SSVEP)[3], P-300[4], etc....
[...]
...SSVEP can be detected by simple Power Spectrum analysis of the EEG recorded as in [3] or by using canonical correlation analysis as in [11] and [12]....
[...]