Brain Computer Interfaced Single Key Omni Directional Pointing and Command System: a Screen Pointing Interface for Differently-abled Person

Raj, Rahul; Deb, Suman; Bhattacharya, Prabir

doi:10.1016/j.procs.2018.07.020

Cited by 10 publications

(11 citation statements)

References 9 publications

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“…g.Tec equipment was used in 54 articles for the EEG method , 33 articles used Emotiv equipment , and 24 articles used Compumedics Neuroscan equipment . Further, 16 articles used Brain Products equipment [191][192][193][194][195][196][197][198][199][200][201][202][203][204][205][206], 13 articles used NeuroSky equipment [207][208][209][210][211][212][213][214][215][216][217][218][219], and Neuroelectrics [220][221][222][223][224][225][226][227] and OpenBCI [228][229][230][231][232][233][234][235] equipment were used in eight articles each. Moreover, seven articles used Biosemi equipment [236][237]…”

Section: Rq1: What Are the Publication Trends Based On Eeg Equipment?mentioning

confidence: 99%

Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: A Systematic Literature Review

Jamil

Belkacem

Ouhbi

et al. 2021

Sensors

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Humans interact with computers through various devices. Such interactions may not require any physical movement, thus aiding people with severe motor disabilities in communicating with external devices. The brain–computer interface (BCI) has turned into a field involving new elements for assistive and rehabilitative technologies. This systematic literature review (SLR) aims to help BCI investigator and investors to decide which devices to select or which studies to support based on the current market examination. This examination of noninvasive EEG devices is based on published BCI studies in different research areas. In this SLR, the research area of noninvasive BCIs using electroencephalography (EEG) was analyzed by examining the types of equipment used for assistive, adaptive, and rehabilitative BCIs. For this SLR, candidate studies were selected from the IEEE digital library, PubMed, Scopus, and ScienceDirect. The inclusion criteria (IC) were limited to studies focusing on applications and devices of the BCI technology. The data used herein were selected using IC and exclusion criteria to ensure quality assessment. The selected articles were divided into four main research areas: education, engineering, entertainment, and medicine. Overall, 238 papers were selected based on IC. Moreover, 28 companies were identified that developed wired and wireless equipment as means of BCI assistive technology. The findings of this review indicate that the implications of using BCIs for assistive, adaptive, and rehabilitative technologies are encouraging for people with severe motor disabilities and healthy people. With an increasing number of healthy people using BCIs, other research areas, such as the motivation of players when participating in games or the security of soldiers when observing certain areas, can be studied and collaborated using the BCI technology. However, such BCI systems must be simple (wearable), convenient (sensor fabrics and self-adjusting abilities), and inexpensive.

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Section: Rq1: What Are the Publication Trends Based On Eeg Equipment?mentioning

confidence: 99%

Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: A Systematic Literature Review

Jamil

Belkacem

Ouhbi

et al. 2021

Sensors

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“…This experiment uses two types of virtual keyboards, QWERTY type as described previously, ABC type consists of alphabets and two control characters defined as Delete and Space. The keyboard has 30 cells; each alphabet occupies one cell character and two cells for each control button [17]. In this study, two types of keyboard use square pointers.…”

Section: Second Experimentsmentioning

confidence: 99%

“…The research conducted by [17] develops a BCI based keyboard with long-term potential for areas such as learning, training, brain stimulation and other clinical purposes. That study presents an average accuracy improvement of all the users from a 40% error rate in the first round to a 10.5% error rate in the fourth round of the trials.…”

Section: Introductionmentioning

confidence: 99%

Brain computer interface based smart keyboard using neurosky mindwave headset

Salih

Abdal

2020

TELKOMNIKA

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In the last decade, numerous researches in the field of electro-encephalography (EEG) and brain-computer-interface (BCI) have been accomplished. BCI has been developed to aid disabled/partially disabled people to efficiently communicate with the community. This paper presents a control tool using the Neurosky Mindwave headset, which detects brainwaves (voluntary blinks and attention) to form a braincomputer interface (BCI) by receiving the system signals from the frontal lobe. This paper proposed an alternative computer input device for those disabled people (who are physically challenged) rather than the conventional one. The work suggested to use two virtual keyboard designs. The conducted experiment revealed a significant result in developing user printing skills on PCs. Encouraging results (1.55-1.8 word per minute (WPM)) were obtained in this research in comparison to other studies.

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“…Considering the large increase in the use of these brain wave capture devices, today there are many companies that are dedicated to manufacturing them to meet the needs of customers and, especially, to be able to carry this type of technology over to researchers and video game lovers. Some of the best known portable electroencephalogram devices on the market are: NeuroSky's MindSet which has a dry electrode located in position FP1, according to the International 10-20 system, and has a sample rate of 512 Hz [14], Muse that has 4 electrodes located on the front (F7, F8, FP1, FP2) and has a sampling rate of 256 Hz [15] and Emotiv Epoc that has 14 channels (AF3, AF4, F3, F4, FC5, FC6, F7, F8, T7, T8, P7, P8, O1, O2) for the acquisition of EEG signals, is capable of capturing 128 or 256 samples per second, has an internal frequency of 2048Hz and additionally has a gyroscope for two-dimensional control [16].…”

Section: Introductionmentioning

confidence: 99%

Advances in the mental control of a robotic hand

2020

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Introduction: The present article is the product of the research "Advances in the mental control of a robotic hand", developed at the University of Pamplona in the year 2019. Problem: Currently one of the main problems presented by robotic hand prostheses is the way in which the user indicates the movements to be performed. Given this, the best results have been obtained using invasive systems. Objective: The main objective of the system is to allow a person to control the movements and / or gestures of a robotic hand using their thoughts, in such a way that the control is as natural and precise as possible. Methodology: Use is made of a non-invasive, low-cost brain-computer interface (BCI) for the generation of control system references. Results: The performance of the system is directly subject to the user's ability to recreate actions or movements in their mind; the more defined your thinking, the better the control response. Conclusion: Mind control represents a new challenge for users, but as it is used, it becomes a more natural and precise control method, offering great control possibilities to people who make daily use of robotic hand prostheses. Originality: Through this research, an alternative is formulated for the control of hand prostheses, which does not require invasive systems and has the advantage of being low cost. Limitations: Frustration, stress and external noise are factors that directly affect the performance of the system.

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Brain Computer Interfaced Single Key Omni Directional Pointing and Command System: a Screen Pointing Interface for Differently-abled Person

Cited by 10 publications

References 9 publications

Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: A Systematic Literature Review

Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: A Systematic Literature Review

Brain computer interface based smart keyboard using neurosky mindwave headset

Advances in the mental control of a robotic hand

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