EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots

@article{Tariq2018EEGBasedBC,
  title={EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots},
  author={Madiha Tariq and Pavel M. Trivailo and Milan Simic},
  journal={Frontiers in Human Neuroscience},
  year={2018},
  volume={12}
}
Over recent years, brain-computer interface (BCI) has emerged as an alternative communication system between the human brain and an output device. Deciphered intents, after detecting electrical signals from the human scalp, are translated into control commands used to operate external devices, computer displays and virtual objects in the real-time. BCI provides an augmentative communication by creating a muscle-free channel between the brain and the output devices, primarily for subjects having… 

Figures from this paper

Real-Time EEG–EMG Human–Machine Interface-Based Control System for a Lower-Limb Exoskeleton

TLDR
This article presents a rehabilitation technique based on a lower-limb exoskeleton integrated with a human–machine interface (HMI), and shows how the combined use of multimodal signals can improve the accuracy, performance, and reliability of HMI.

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review

TLDR
A systematic review of the state of the art and opportunities in the development of BCIs for the rehabilitation of upper and lower limbs of the human body found that using EEG signals, and user feedback offer benefits including cost, effectiveness, better training, user motivation and there is a need to continue developing interfaces that are accessible to users, and that integrate feedback techniques.

Developing a Motor Imagery-Based Real-Time Asynchronous Hybrid BCI Controller for a Lower-Limb Exoskeleton

TLDR
The developed BCI controller can potentially be benefit people with neurological disorders who may have difficulties operating manual control and investigate the feasibility of the controller under a practical scenario including stand-up, gait-forward, and sit-down.

EEG-Based EMG Estimation of Shoulder Joint for the Power Augmentation System of Upper Limbs

TLDR
The shoulder’s power can be augmented by estimated virtual EMG signals for the people wearing an EMG-based power augmentation exoskeleton robot, demonstrating the feasibility and potential of using EEG signals to provide power augmented through BMI technology.

A Practical EEG-Based Human-Machine Interface to Online Control an Upper-Limb Assist Robot

TLDR
An efficient control method based on P300, a special EEG component, which has great potential for helping paralyzed people easily control an assist robot to do numbers of things is proposed.

A Survey in Implementation and Applications of Electroencephalograph (EEG)-Based Brain-Computer Interface

TLDR
A simple and easy analysis of each technique and its respective benefits and drawbacks, including signal acquisition, signal pre-processing, feature classification and classification are shown.

Identification of Lower-Limb Motor Tasks via Brain–Computer Interfaces: A Topical Overview

TLDR
This study conducted a topical overview of specialized papers covering lower-limb motor task identification through PR-based BCI/EEG signal analysis systems to find the most relevant papers on the subject.

Brain-controlled cycling system for rehabilitation following paraplegia with delay-time prediction

TLDR
An ergometric cycling wheelchair, with a brain–machine interface (BMI), that can force the legs to move by including normal stepping speeds and quick responses and be designed to accommodate the expected delay between the intentional onset and physical movement, to achieve rehabilitation effects for each participant.

Brain–Computer Interfaces for Spinal Cord Injury Rehabilitation

TLDR
This chapter will discuss the current potential of BCIs for SCI rehabilitation, as well as what areas of this field need to be improved in the future.
...

References

SHOWING 1-10 OF 157 REFERENCES

Decoding Sensorimotor Rhythms during Robotic-Assisted Treadmill Walking for Brain Computer Interface (BCI) Applications

TLDR
The results demonstrate the feasibility of BCI-based robotic-assisted training devices for gait rehabilitation in stroke patients using spectral EEG patterns related to robot-assisted active and passive walking.

Towards a non-invasive brain-machine interface system to restore gait function in humans

TLDR
The results show the feasibility of developing non-invasive neural interfaces for volitional control of devices aimed at restoring human gait function and support the possibility of decoding human bipedal locomotion with EEG.

Brain-Computer Interface Controlled Functional Electrical Stimulation System for Ankle Movement

TLDR
This study suggests that the integration of a noninvasive BCI with a lower-extremity FES system is feasible and may offer a novel and effective therapy in the neuro-rehabilitation of individuals with lower extremity paralysis due to neurological injuries.

An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand

TLDR
A novel brain/neural-computer interaction (BNCI) system that integrates electroencephalography (EEG) and electrooculography (EOG) to improve control of assistive robotics in daily life environments is introduced and suggests that hybrid BNCI systems can achieve substantially better control over assistive devices, e.g., a hand exoskeleton, than systems using brain signals alone.

Brain-machine interfaces for controlling lower-limb powered robotic systems.

TLDR
It is concluded that lower-body powered exoskeletons with automated gait intention detection based on BMIs open new possibilities in the assistance and rehabilitation fields, although the current performance, clinical benefits and several key challenging issues indicate that additional research and development is required to deploy these systems in the clinic and at home.

Toward Brain-Actuated Humanoid Robots: Asynchronous Direct Control Using an EEG-Based BCI

TLDR
The experimental results showed that the subjects successfully controlled the humanoid robot in the indoor maze and reached the goal by using the proposed asynchronous EEG-based active BCI system.

From Spinal Central Pattern Generators to Cortical Network: Integrated BCI for Walking Rehabilitation

TLDR
Different approaches to the use of electroencephalogram, upper limb electromyogram, or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs) are critically investigated.

Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms

TLDR
The work indicates that the sensorimotor-rhythm-based noninvasive BCI has the potential to provide communication and control capabilities as an alternative to physiological motor pathways.

EEG-Based Brain–Computer Interfaces for Communication and Rehabilitation of People with Motor Impairment: A Novel Approach of the 21st Century

TLDR
This work reviews the research on non-invasive, electroencephalography (EEG)-based BCI systems for communication and rehabilitation and focuses on the approaches intended to help severely paralyzed and locked-in patients regain communication using three different BCI modalities: slow cortical potentials, sensorimotor rhythms and P300 potentials.

Brain-computer interface controlled robotic gait orthosis

TLDR
These results provide preliminary evidence that restoring brain-controlled ambulation after SCI is feasible and may justify the future development of BCI-controlled lower extremity prostheses for free overground walking for those with complete motor SCI.
...