Control of a humanoid robot by a noninvasive brain–computer interface in humans

By Christian Bell, Pradeep Shenoy, Rawichote Chalodhorn, Rajesh P. N. Rao. Journal of Neural Engineering, 2008

403 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/69bf3d446cb406bb0d0e0d039935f55387552d3b

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

A comprehensive review of EEG-based brain–computer interface paradigms (2019, positive): “Bell et al [103] increased the information transfer rate (ITR) to 24 bits min − 1 for a four-choice classification problem relying on the fact that P300 has a robust response to multiple trials.”
Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. (2017, neutral): “These include spelling devices (10, 71, 101, 117, 132, 438, 559, 608, 619, 672, 876, 882), speech generators (190, 326, 549), BMIs for control of a humanoid robot (55, 103, 120, 138, 301), telepresence systems (130, 223, 804), BMI-controlled wheelchairs (121, LEBEDEV AND NICOLELIS”
Progress in Brain Computer Interface: Challenges and Opportunities (2019, methodology): “cluding brain fingerprinting for lie detection [5], detecting drowsiness for improving human working performances [6], controlling virtual reality [7] and video games [8], and driving humanoid robots [9], [10], [11]. Figure 1 shows the increasing number of publications on BCI in various application ”
Artifact Removal in Physiological Signals—Practices and Possibilities (2012, background): “Other uses of EEG include the detection of sleep/drowsiness levels [19], [20], [21], cognitive workload [20], [22] and in brain–computer interfaces (BCI) [23], [24], [25], [26] all of which have applications in a personal healthcare domain.”
P300 brain computer interface: current challenges and emerging trends (2012, background): “Another recent paper described a P300 BCI to control a mobile robot (Bell et al., 2008) or to control a wheelchair (Iturrate et al., 2009).”
Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges (2010, methodology): “A similar P300 approach has been followed to control a humanoid robot [9].”
Brain-Computer Interfaces: A Gentle Introduction (2009, background): “These stimuli are usually letters, but can be symbols that represent other goals, such as controlling a cursor, robot arm, or mobile robot [15, 16].”