Motor-Imagery EEG-based BCIs in Wheelchairs Movement and Control: A Systematic Literature Review

Motor-Imagery EEG-Based BCIs in Wheelchair Movement and Control: A Systematic Literature Review

Sensors ◽

10.3390/s21186285 ◽

2021 ◽

Vol 21 (18) ◽

pp. 6285

Author(s):

Arrigo Palumbo ◽

Vera Gramigna ◽

Barbara Calabrese ◽

Nicola Ielpo

Keyword(s):

Motor Imagery ◽

Well Being ◽

Severe Disabilities ◽

Assistive Technologies ◽

Algorithm Analysis ◽

Features Selection ◽

Daily Lives ◽

Computer Interfaces ◽

And Performance ◽

And Control

The pandemic emergency of the coronavirus disease 2019 (COVID-19) shed light on the need for innovative aids, devices, and assistive technologies to enable people with severe disabilities to live their daily lives. EEG-based Brain-Computer Interfaces (BCIs) can lead individuals with significant health challenges to improve their independence, facilitate participation in activities, thus enhancing overall well-being and preventing impairments. This systematic review provides state-of-the-art applications of EEG-based BCIs, particularly those using motor-imagery (MI) data, to wheelchair control and movement. It presents a thorough examination of the different studies conducted since 2010, focusing on the algorithm analysis, features extraction, features selection, and classification techniques used as well as on wheelchair components and performance evaluation. The results provided in this paper could highlight the limitations of current biomedical instrumentations applied to people with severe disabilities and bring focus to innovative research topics.

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Motor-Imagery EEG-based BCIs in Wheelchairs Movement and Control: A Systematic Literature Review

10.36227/techrxiv.14916537.v1 ◽

2021 ◽

Author(s):

Arrigo Palumbo ◽

Vera Gramigna ◽

Barbara Calabrese ◽

Nicola Ielpo

Keyword(s):

Motor Imagery ◽

Well Being ◽

Severe Disabilities ◽

Assistive Technologies ◽

Algorithm Analysis ◽

Features Selection ◽

Daily Lives ◽

Computer Interfaces ◽

And Performance ◽

And Control

The pandemic emergency of the coronavirus disease 2019 (COVID-19) shed light on the need for innovative aids, devices and assistive technologies to enable people with severe disabilities to live their daily lives. EEG-based Brain-Computer Interfaces (BCIs) can lead individuals with significant health challenges to improve their independence, facilitate participation in activities, thus enhancing overall well-being and preventing impairments. This systematic review provides state-of-the-art applications of EEG-based BCIs, particularly those using motor-imagery (MI) data, to wheelchair control and movement. It presents a thorough examination of the different studies conducted since 2010, focusing on the algorithm analysis, features extraction, features selection and classification techniques used, and wheelchair components and performance evaluation. The results provided in this paper could highlight the limitations of current biomedical instrumentations applied to people with severe disabilities in the pandemic context of Covid-19 and bring focus to innovative research topics.

Download Full-text

Motor-Imagery EEG-based BCIs in Wheelchairs Movement and Control: A Systematic Literature Review

10.36227/techrxiv.14916537 ◽

2021 ◽

Author(s):

Arrigo Palumbo ◽

Vera Gramigna ◽

Barbara Calabrese ◽

Nicola Ielpo

Keyword(s):

Motor Imagery ◽

Well Being ◽

Severe Disabilities ◽

Assistive Technologies ◽

Algorithm Analysis ◽

Features Selection ◽

Daily Lives ◽

Computer Interfaces ◽

And Performance ◽

And Control

The pandemic emergency of the coronavirus disease 2019 (COVID-19) shed light on the need for innovative aids, devices and assistive technologies to enable people with severe disabilities to live their daily lives. EEG-based Brain-Computer Interfaces (BCIs) can lead individuals with significant health challenges to improve their independence, facilitate participation in activities, thus enhancing overall well-being and preventing impairments. This systematic review provides state-of-the-art applications of EEG-based BCIs, particularly those using motor-imagery (MI) data, to wheelchair control and movement. It presents a thorough examination of the different studies conducted since 2010, focusing on the algorithm analysis, features extraction, features selection and classification techniques used, and wheelchair components and performance evaluation. The results provided in this paper could highlight the limitations of current biomedical instrumentations applied to people with severe disabilities in the pandemic context of Covid-19 and bring focus to innovative research topics.

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Brain–Computer Interfaces for Human Augmentation

Brain Sciences ◽

10.3390/brainsci9020022 ◽

2019 ◽

Vol 9 (2) ◽

pp. 22 ◽

Cited By ~ 1

Author(s):

Davide Valeriani ◽

Caterina Cinel ◽

Riccardo Poli

Keyword(s):

Brain Activity ◽

Severe Disabilities ◽

Assistive Technologies ◽

Brain Computer Interfaces ◽

Computer Interfaces ◽

Control Signals ◽

Human Augmentation

The field of brain–computer interfaces (BCIs) has grown rapidly in the last few decades, allowing the development of ever faster and more reliable assistive technologies for converting brain activity into control signals for external devices for people with severe disabilities [...]

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Brain Computer Interface Controlled Voice Assistant

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.e6779.038620 ◽

2020 ◽

Vol 8 (6) ◽

pp. 2370-2377

Keyword(s):

Brain Activity ◽

Brain Computer Interface ◽

Computer Interface ◽

Project Work ◽

Daily Lives ◽

Computer Interfaces ◽

The Disabled ◽

And Performance ◽

The Brain ◽

Bci System

A brain-controlled robot using brain computer interfaces (BCIs) was explored in this project. BCIs are systems that are able to circumvent traditional communication channels (i.e. muscles and thoughts), to ensure the human brain and physical devices communicate directly and are in charge by converting various patterns of brain activity to instructions in real time. An automation can be managed with these commands. The project work seeks to build and monitor a program that can help the disabled people accomplish certain activities independently of others in their daily lives. Develop open-source EEG and brain-computer interface analysis software. The quality and performance of BCI of different EEG signals are compared. Variable signals obtained through MATLAB Processing from the Brainwave sensor. Automation modules operate by means of the BCI system. The Brain Computer Interface aims to build a fast and reliable link between a person's brain and a personal computer. The controls also use the Brain-Computer Interface for home appliances. The system will integrate with any smartphones voice assistant.

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TWO LOW-COST HUMAN COMPUTER INTERFACES FOR PEOPLE WITH SEVERE DISABILITIES

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237204000475 ◽

2004 ◽

Vol 16 (06) ◽

pp. 344-349 ◽

Cited By ~ 2

Author(s):

MU-CHUN SU ◽

YANG-HAN LEE ◽

CHENG-HUI WU ◽

SHI-YONG SU ◽

YU-XIANG ZHAO

Keyword(s):

Low Cost ◽

Severe Disabilities ◽

Disabled Persons ◽

Main Application ◽

Computer Interfaces ◽

Human Computer Interfaces ◽

The Disabled ◽

Potential Applications ◽

And Control

The object of this paper is to present a set of techniques integrated into two low-cost human computer interfaces. Although the interfaces have many potential applications, one main application is to help the disabled persons to attain or regain some degree of independent communications and control. The first interface is a voice-controlled mouse and the second one is an accelerometer-based mouse.

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Effects of smart garments on the well-being of athletes: a scoping review protocol

BMJ Open ◽

10.1136/bmjopen-2020-042127 ◽

2020 ◽

Vol 10 (11) ◽

pp. e042127

Author(s):

Abdullah Al Mahmud ◽

Tharushi Indeewari Wickramarathne ◽

Blair Kuys

Keyword(s):

Scoping Review ◽

English Language ◽

Data Extraction ◽

Well Being ◽

Wearable Electronics ◽

Daily Lives ◽

Data Extraction Form ◽

Ethical Approval ◽

Smart Garments ◽

And Performance

IntroductionWith the advancements in wearable electronics, electronically integrated smart garments started to transpire in our daily lives. Smart garment technologies are incorporated into sportswear applications to enhance the well-being and performance of athletes. Smart garments applications in the sports sector are increasing, and the variety of smart garment applications available in the literature is overwhelming. Therefore, it is essential to compare the vast array of technologies incorporated in smart garments for athletes to understand the knowledge gaps for future studies. The protocol paper aims to examine the smart garments used in the sports domain to enhance the health and well-being of athletes.Methods and analysisRelevant studies will be retrieved using predefined search terms from Scopus, Web of Science, Science Direct, PubMed and IEEE Xplore. The retrieved articles will be eliminated in two phases: title and abstract screening and full-text screening. The included articles will be primary studies published in the English language within the last 10 years. Subsequently, the included articles will be further studied to extract data using a data extraction form. The extracted data will undergo a thematic analysis. Also, quantitative analysis will be carried out using descriptive statistics.Ethics and disseminationThe results of this review will provide a comprehensive understanding of smart garment concepts used in the sports domain. The findings of this scoping review will be shared through a journal publication and a conference presentation. Ethical approval is not needed for this scoping review.Protocol registration numberDOI 10.17605/OSF.IO/34MF2 (https://osf.io/34mf2)

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Imagine That! Mental Training for Children With Developmental Coordination Disorder

Frontiers for Young Minds ◽

10.3389/frym.2021.642053 ◽

2021 ◽

Vol 9 ◽

Author(s):

Matthew W. Scott ◽

Greg Wood ◽

Paul S. Holmes ◽

Ben Marshall ◽

Jacqueline Williams ◽

...

Keyword(s):

Motor Imagery ◽

Developmental Coordination Disorder ◽

Action Observation ◽

Well Being ◽

Mental Training ◽

Brain Areas ◽

And Control ◽

Coordination Disorder ◽

The Brain ◽

Health And Well Being

Movement is important for children’s health and well-being. Most children find it easy to learn to move but children with developmental coordination disorder (DCD) find it hard. It can be tricky for them to plan and control their movements. DCD affects 1 in every 20 children. It makes important tasks difficult, like getting dressed or playing games and sports. Scientists have found that children with DCD have different activity in some brain areas compared to other children. Mental training can increase activity in these areas of the brain. One type of mental training is motor imagery, which involves imagining doing movements. Another type of mental training is action observation, which involves carefully watching how people make certain movements. These techniques can help children with DCD get better at moving. This means that doing mental training might help make life easier for children with DCD.

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