EEG-Based Brain-Controlled Mobile Robots: A Survey

By Luzheng Bi, Xinan Fan, Yili Liu. IEEE Transactions on Human-Machine Systems, 2013

405 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/36ebbf93195c044cb8645d2202fc9be38bdf0991

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

1. Ayman Atia
2. Sarah N. Abdulkader
3. Mostafa-Sami M. Mostafa

In Cognitive Neuroscience

1. Bifta Sama Bari
2. Sabira Khatun
3. Ayman Atia
4. Ahmad Fakhri Ab. Nasir
5. M. Rashid
6. Sarah N. Abdulkader
7. Mostafa-Sami M. Mostafa
8. Rabiu Muazu Musa

In Electrical and Electronic Engineering

1. Ayman Atia
2. Sarah N. Abdulkader
3. Mostafa-Sami M. Mostafa

Citations in the corpus

• Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review (2020, background): “…that cater to specific applications, for instance, wheelchair control (Fernández-Rodríguez et al., 2016; Al-qaysi et al., 2018), BCI mobile robot (Bi et al., 2013), emotion recognition using EEG (Al-Nafjan et al., 2017), biometrics (Del Pozo-Banos et al., 2014; Alariki et al., 2018), and virtual…”
• Brain computer interfacing: Applications and challenges (2015, methodology): “They only require incorporating brain signals in order to accomplish a set of commands and no muscles intervention is needed [9,10,3].”
• A comprehensive review of EEG-based brain–computer interface paradigms (2019, neutral): “EEG signals have been used to control devices such as wheelchairs [18] and communication aid systems [19].”