P300 BCI based planning behavior selection network for humanoid robot control

Yun, Sung-Jae; Lee, Myeong-Chun; Cho, Sung-Bae

doi:10.1109/icnc.2013.6818000

Cited by 6 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several BCI techniques are used in controlling telepresence robots [16][17][18][19][20]. It shows that choosing the proper paradigm is an essential step in the design of BCI's telepresence sensorimotor rhythm (SMR) system [21][22][23][24].…”

Section: Brain-signal Based Controllingmentioning

confidence: 99%

Telepresence Robots and Controlling Techniques in Healthcare System

Naseer¹,

Khan²,

Nawaz³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

In this era of post-COVID-19, humans are psychologically restricted to interact less with other humans. According to the world health organization (WHO), there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide. Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment. Investigations were done to overcome the remedy, and the researcher developed different techniques and recommended solutions. Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans. It played a vital role in this perspective to help humans to perform daily routine tasks. Healthcare workers can use telepresence robots to interact with patients who visit the healthcare center for initial diagnosis for better healthcare system performance without direct interaction. The presented paper aims to compare different telepresence robots and their different controlling techniques to perform the needful in the respective scenario of healthcare environments. This paper comprehensively analyzes and reviews the applications of presented techniques to control different telepresence robots. However, our feature-wise analysis also points to specific technical, appropriate, and ethical challenges that remain to be solved. The proposed investigation summarizes the need for further multifaceted research on the design and impact of a telepresence robot for healthcare centers, building on new perceptions during the COVID-19 pandemic.

show abstract

Section: Brain-signal Based Controllingmentioning

confidence: 99%

Telepresence Robots and Controlling Techniques in Healthcare System

Naseer¹,

Khan²,

Nawaz³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Generally combinations of a signal used by Hybrid BCI include a mix of Electromyography [ 44 ] (EMG) + Electroencephalography (EEG), Event-Related Desynchronization (ERD) along with Steady State Visual Evoked Potential (SSVEP), Near-Infrared Spectroscopy (NIRS) along with EEG, ERD along with P300 etc [ 45 , 46 ]. Table 1 lists the description of the major signals and methods discussed above [ 47 , 48 , 49 ].…”

Section: Preliminary Knowledgementioning

confidence: 99%

Brain-Computer Interface-Based Humanoid Control: A Review

Chamola

Vineet

Nayyar

et al. 2020

Sensors

View full text Add to dashboard Cite

A Brain-Computer Interface (BCI) acts as a communication mechanism using brain signals to control external devices. The generation of such signals is sometimes independent of the nervous system, such as in Passive BCI. This is majorly beneficial for those who have severe motor disabilities. Traditional BCI systems have been dependent only on brain signals recorded using Electroencephalography (EEG) and have used a rule-based translation algorithm to generate control commands. However, the recent use of multi-sensor data fusion and machine learning-based translation algorithms has improved the accuracy of such systems. This paper discusses various BCI applications such as tele-presence, grasping of objects, navigation, etc. that use multi-sensor fusion and machine learning to control a humanoid robot to perform a desired task. The paper also includes a review of the methods and system design used in the discussed applications.

show abstract

“…Several BCI methods have been used in human telepresence studies [16]- [20]. These studies have shown that the choice of an appropriate paradigm is an essential step in designing the telepresence system.…”

Section: Numerous Studies Have Demonstrated Successful Outcomes In Comentioning

confidence: 99%

Design and Optimization of a BCI-Driven Telepresence Robot Through Programming by Demonstration

et al. 2019

View full text Add to dashboard Cite

Improving the life quality of people with severe motor paralysis has a significant impact on restoring their functional independence to perform activities of daily living (ADL). Telepresence is a subfield of the robotic-assisted route, where human plays the role of an operator, sending high-level instructions to an assistive robot while receiving sensory feedback. However, for severely motor-impaired people, conventional interaction modalities may not be suitable due to their complete paralysis. Thus, designing alternative ways of interaction such as Brain-Computer Interfaces (BCI) is essential for a telepresence capability. We propose a novel framework that integrates a BCI system and a humanoid robot to develop a brain-controlled telepresence system with multimodal control features. In particular, the low-level control is executed by Programming by Demonstration (PbD) models, and the higher-level cognitive commands are produced by a BCI system to perform vital ADLs. The presented system is based on real-time decoding of attentionmodulated neural responses elicited in the brain electroencephalographic signals and generating multiple control commands. As a result, the system allows a user to interact with a humanoid robot while receiving auditory and visual feedback from the robot's sensors. We validated our system across ten subjects in a realistic scenario. The experimental results show the feasibility of the approach in the design of a telepresence robot with high BCI decoding performances. INDEX TERMS Brain-Computer interfaces, telepresence, programming by demonstration, EEG, eventrelated potentials, humanoid robots.

show abstract

P300 BCI based planning behavior selection network for humanoid robot control

Cited by 6 publications

References 12 publications

Telepresence Robots and Controlling Techniques in Healthcare System

Telepresence Robots and Controlling Techniques in Healthcare System

Brain-Computer Interface-Based Humanoid Control: A Review

Design and Optimization of a BCI-Driven Telepresence Robot Through Programming by Demonstration

Contact Info

Product

Resources

About