Direction control and speed control combined model of motor-imagery based brain-actuated vehicle

Yin, Guodong; Gong, Lei

doi:10.23919/chicc.2017.8027685

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Engineering : This is the second highest research area in this SLR, with 24 articles and 9 companies. Eight articles used Emotiv equipment [ 5 , 44 , 45 , 46 , 47 , 48 , 49 , 50 ], five articles used g.Tec equipment [ 51 , 52 , 53 , 54 , 55 ], three articles used Brain Products equipment [ 56 , 57 , 58 ], two articles used Compumedics Neuroscan equipment [ 59 , 60 ], and two articles used NeuroSky equipment [ 61 , 62 ]. For the equipment for Cognionics Inc. [ 63 ], Electrical Geodesics Inc. [ 64 ], Neuroelectrics [ 65 ], and Advanced Brain Monitoring [ 66 ], one article each used their equipment.…”

Section: Resultsmentioning

confidence: 99%

“…The outdoor applications include helping security teams explore opponent areas for safety and security [ 50 , 276 ]. Other innovations using the BCI technology influence researchers to use BCIs as a part of daily life, such as controlling vehicles for assistance in remote driving [ 49 ]. With this approach, BCIs can help in programming vehicles for self driving whenever the vehicle detects that the driver feels drowsy or tired.…”

Section: Discussionmentioning

confidence: 99%

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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: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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

Jamil

Belkacem

Ouhbi

et al. 2021

Sensors

View full text Add to dashboard Cite

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Brain–Computer Interfaces for Mobility Assistance: A Comparative Analysis of EEG-Based Classification Models for Brain-Controlled Wheelchairs

Muhammad Kabeer,

Megalingam,

Sakthiprasad

2024

Smart Innovation, Systems and Technologies

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Functional Mapping of the Brain for Brain–Computer Interfacing: A Review

et al. 2023

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Brain–computer interfacing has been applied in a range of domains including rehabilitation, neuro-prosthetics, and neurofeedback. Neuroimaging techniques provide insight into the structural and functional aspects of the brain. There is a need to identify, map and understand the various structural areas of the brain together with their functionally active roles for the accurate and efficient design of a brain–computer interface. In this review, the functionally active areas of the brain are reviewed by analyzing the research available in the literature on brain–computer interfacing in conjunction with neuroimaging experiments. This review first provides an overview of various approaches of brain–computer interfacing and basic components in the BCI system and then discuss active functional areas of the brain being utilized in non-invasive brain–computer interfacing performed with hemodynamic signals and electrophysiological recording-based signals. This paper also discusses various challenges and limitations in BCI becoming accessible to a novice user, including security issues in the BCI system, effective ways to overcome those issues, and design implementations.

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Direction control and speed control combined model of motor-imagery based brain-actuated vehicle

Cited by 4 publications

References 16 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 Interfaces for Mobility Assistance: A Comparative Analysis of EEG-Based Classification Models for Brain-Controlled Wheelchairs

Functional Mapping of the Brain for Brain–Computer Interfacing: A Review

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