| P50 | author | Andrzej Cichocki | Q29387078 |
| P2093 | author name string | Yan Chen | |
| | Fei Wang | |
| | Yuanqing Li | |
| | Pengmin Qin | |
| | Haiyun Huang | |
| | Yanbin He | |
| | Qiuyou Xie | |
| | Ronghao Yu | |
| | Xiaoxiao Ni | |
| | Jiahui Pan | |
| P2860 | cites work | Detecting awareness in the vegetative state | Q28262523 |
| | Detection of response to command using voluntary control of breathing in disorders of consciousness. | Q30370499 |
| | Dissociations between behavioural and functional magnetic resonance imaging-based evaluations of cognitive function after brain injury | Q30498254 |
| | Preservation of electroencephalographic organization in patients with impaired consciousness and imaging-based evidence of command-following | Q30626228 |
| | BCI Competition 2003--Data set IIb: support vector machines for the P300 speller paradigm | Q30937824 |
| | Brain-computer interfaces for patients with disorders of consciousness. | Q31126499 |
| | Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines | Q31149852 |
| | From unresponsive wakefulness to minimally conscious PLUS and functional locked-in syndromes: recent advances in our understanding of disorders of consciousness | Q33933165 |
| | Willful modulation of brain activity in disorders of consciousness | Q34096737 |
| | An independent SSVEP-based brain-computer interface in locked-in syndrome. | Q51084774 |
| | Subliminal visual oddball stimuli evoke a P300 component. | Q52142626 |
| | Cognitive Motor Dissociation Following Severe Brain Injuries. | Q52147546 |
| | Emotion-Related Consciousness Detection in Patients With Disorders of Consciousness Through an EEG-Based BCI System. | Q55017439 |
| | Assessing Command-Following and Communication With Vibro-Tactile P300 Brain-Computer Interface Tools in Patients With Unresponsive Wakefulness Syndrome | Q60041077 |
| | Functional ‘unlocking’: bedside detection of covert awareness after severe brain damage | Q60041080 |
| | The JFK Coma Recovery Scale-Revised: measurement characteristics and diagnostic utility | Q81159757 |
| | Bedside detection of awareness in the vegetative state | Q84071982 |
| | Characterization of EEG signals revealing covert cognition in the injured brain | Q88120672 |
| | Detection of Brain Activation in Unresponsive Patients with Acute Brain Injury | Q93047251 |
| | Bedside detection of awareness in the vegetative state: a cohort study | Q34232051 |
| | Brain-computer interfacing in disorders of consciousness | Q34285718 |
| | Does the 'P300' speller depend on eye gaze? | Q34356361 |
| | The vegetative and minimally conscious states: current knowledge and remaining questions | Q34387758 |
| | Detecting awareness after severe brain injury | Q35006963 |
| | Brain response to thermal stimulation predicts outcome of patients with chronic disorders of consciousness | Q35483120 |
| | Prediction of Consciousness Recovery in Coma after Traumatic Brain Injury by Disorder of Consciousness Scale (DOCS). | Q36631050 |
| | A review of classification algorithms for EEG-based brain-computer interfaces. | Q36780462 |
| | Brain-computer interfaces for communication with nonresponsive patients | Q38049294 |
| | Disorders of consciousness after acquired brain injury: the state of the science | Q38182339 |
| | "Look at my classifier's result": Disentangling unresponsive from (minimally) conscious patients | Q38675447 |
| | EEG epileptiform abnormalities at admission to a rehabilitation department predict the risk of seizures in disorders of consciousness following a coma. | Q40925670 |
| | Probing command following in patients with disorders of consciousness using a brain-computer interface | Q44078957 |
| | Discrimination between control and idle states in asynchronous SSVEP-based brain switches: a pseudo-key-based approach | Q44249702 |
| | Protocol Design Challenges in the Detection of Awareness in Aware Subjects Using EEG Signals. | Q45949590 |
| | Voluntary brain processing in disorders of consciousness. | Q46253163 |
| | Survival and consciousness recovery are better in the minimally conscious state than in the vegetative state. | Q47960945 |
| | How are different neural networks related to consciousness? | Q47984988 |
| | Evaluation of induced and evoked changes in EEG during selective attention to verbal stimuli. | Q47997568 |
| | GABAA receptor deficits predict recovery in patients with disorders of consciousness: A preliminary multimodal [(11) C]Flumazenil PET and fMRI study | Q48017428 |
| | BCI demographics: how many (and what kinds of) people can use an SSVEP BCI? | Q48341158 |
| | BCI in patients with disorders of consciousness: clinical perspectives | Q48362901 |
| | How many people are able to control a P300-based brain-computer interface (BCI)? | Q48396880 |
| | Visual modifications on the P300 speller BCI paradigm | Q48522820 |
| | EEG predictors of outcome in patients with disorders of consciousness admitted for intensive rehabilitation. | Q48529894 |
| | Gaze-independent brain-computer interfaces based on covert attention and feature attention | Q48859891 |
| | The auditory P300-based single-switch brain-computer interface: paradigm transition from healthy subjects to minimally conscious patients | Q48969080 |
| | Predict recovery of consciousness in post-acute severe brain injury: the role of EEG reactivity. | Q49065018 |
| P275 | copyright license | Creative Commons Attribution-NonCommercial 4.0 International | Q34179348 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P921 | main subject | brain–computer interface | Q897410 |
| P577 | publication date | 2020-02-26 | |
| P1433 | published in | Brain | Q897386 |
| P1476 | title | Prognosis for patients with cognitive motor dissociation identified by brain-computer interface | |