Technology Development for Unblessed People using BCI: A Survey

Kaur, Mandeep; Ahmed, Pervaiz K.; Rafiq, M. Qasim

doi:10.5120/4920-7142

Cited by 15 publications

(7 citation statements)

References 32 publications

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“…A relevant number of BCI systems have been designed to improve the quality of life of people with diseases (Kaur et al, 2012). In these cases BCI is used to perform a direct and precise control of prosthetic devices, wheelchairs (Carrino et al, 2012) and computers.…”

Section: Bci For Serious Gamesmentioning

confidence: 99%

A Serious Game Application using EEG-based Brain Computer Interface

Perales¹,

Amengual²

2013

Proceedings of the International Congress on Neurotechnology, Electronics and Informatics

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Serious games have demonstrated their effectiveness as a therapeutic resource to deal with motor, sensory and cognitive disabilities. In this article we consider Brain Computer Interfaces (BCI) as a new interaction mechanism that could be used in serious games to improve their rehabilitation activity thanks to the ability of neurofeedback to stimulate the cortical plasticity. We present the brief state-of-the-art of BCI serious games and the factors to be considered in order to develop this particular kind of software that could be highly complex and require experts with different knowledge and skills. We propose a new approach based on the detection of focus features in the game activity. We introduce a system able to assess the Alpha band variations in particular game tasks. Our initial target users are children with cerebral palsy and motor disabilities. The system is currently under evaluation with control users before to be operated with the target users in rehabilitation centers.

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Section: Bci For Serious Gamesmentioning

confidence: 99%

A Serious Game Application using EEG-based Brain Computer Interface

Perales¹,

Amengual²

2013

Proceedings of the International Congress on Neurotechnology, Electronics and Informatics

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“…EEG and fMRI belong to the non-invasive BCI systems, and intracortical recording and ECoG are the two invasive modalities mainly used in BCI research [ 7 ] (p. 6285). This research focused on the non-invasive EEG-based BCIs that have been realized using a variety of paradigms, including steady-state visual evoked potential (SSVEP), P300, rapid serial visual presentation (RSVP), movement-related potentials (MRPs), motor imagery [ 8 , 9 , 10 ], etc. These paradigms can be identified in two groups: endogenous and exogenous.…”

Section: Introductionmentioning

confidence: 99%

An Electric Wheelchair Manipulating System Using SSVEP-Based BCI System

Chen

Liu

et al. 2022

Biosensors

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Most people with motor disabilities use a joystick to control an electric wheelchair. However, those who suffer from multiple sclerosis or amyotrophic lateral sclerosis may require other methods to control an electric wheelchair. This study implements an electroencephalography (EEG)-based brain–computer interface (BCI) system and a steady-state visual evoked potential (SSVEP) to manipulate an electric wheelchair. While operating the human–machine interface, three types of SSVEP scenarios involving a real-time virtual stimulus are displayed on a monitor or mixed reality (MR) goggles to produce the EEG signals. Canonical correlation analysis (CCA) is used to classify the EEG signals into the corresponding class of command and the information transfer rate (ITR) is used to determine the effect. The experimental results show that the proposed SSVEP stimulus generates the EEG signals because of the high classification accuracy of CCA. This is used to control an electric wheelchair along a specific path. Simultaneous localization and mapping (SLAM) is the mapping method that is available in the robotic operating software (ROS) platform that is used for the wheelchair system for this study.

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“…The ultimate goal of many researchers is to develop a BCI system that is robust and portable enough to meet the daily communication and social interaction needs of severely disabled individuals. An EEG-based BCI system comprises of five consecutive modules: The Signal Acquisition, Signal Processing, Feature Extraction, Classification and Command Generation modules [6].…”

Section: Introductionmentioning

confidence: 99%

Brain controlled multiagent aerial vehicles system

Borgul¹,

Bazylev²

2013

2013 18th International Conference on Methods &Amp; Models in Automation &Amp; Robotics (MMAR)

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This paper describes designed control system for group of quadcopters with connection to the brain-computer interface. Quadcopter can be controlled mentally. Electroencephalogram signals are used as control commands. The system is able to keep formation during the movement on the optimal trajectory for the fastest exploration of locality. The application provides both manual and full-automatic control with streaming video capturing. Realized system may be used by disabled people for drug delivery and observation of neighborhood or by the operators in industry as well as in exploration of locality in case of technogenic accident and catastrophe, elemental calamity.

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Technology Development for Unblessed People using BCI: A Survey

Cited by 15 publications

References 32 publications

A Serious Game Application using EEG-based Brain Computer Interface

A Serious Game Application using EEG-based Brain Computer Interface

An Electric Wheelchair Manipulating System Using SSVEP-Based BCI System

Brain controlled multiagent aerial vehicles system

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