NCT03827187 Awareness Detection and Communication in Disorders of Consciousness

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This trial targets 30 participants in total. It began in 2022-02-08 with a primary completion date of 2026-08.

Brief Summary

STUDY OVERVIEW Brain injury can result in a loss of consciousness or awareness, to varying degrees. Some injuries are mild and cause relatively minor changes in consciousness. However, in severe cases a person can be left in a state where they are "awake" but unaware, which is called unresponsive wakefulness syndrome (UWS, previously known as a vegetative state). Up to 43% of patients with a UWS diagnosis, regain some conscious awareness, and are then reclassified as minimally conscious after further assessment by clinical experts. Many of those in the minimally conscious state (MCS) and all with unresponsive wakefulness syndrome (UWS) are incapable of providing any, or consistent, overt motor responses and therefore, in some cases, existing measures of consciousness are not able to provide an accurate assessment. Furthermore, patients with locked-in syndrome (LIS), which is not a disorder of consciousness as patients are wholly aware, also, struggle to produce overt motor responses due to paralysis and anarthria, leading to long delays in accurate diagnoses using current measures to determine levels of consciousness and awareness. There is evidence that LIS patients, and a subset of patients with prolonged disorders of consciousness (DoC), can imagine movement (such as imagining lifting a heavy weight with their right arm) when given instructions presented either auditorily or visually - and the pattern of brain activity that they produce when imagining these movements, can be recorded using a method known as electroencephalography (or EEG). With these findings, the investigators have gathered evidence that EEG-based bedside detection of conscious awareness is possible using Brain- Computer Interface (BCI) technology - whereby a computer programme translates information from the users EEG-recorded patterns of activity, to computer commands that allow the user to interact via a user interface. The BCI system for the current study employs three possible imagined movement combinations for a two-class movement classification; left- vs right-arm, right-arm vs feet, and left-arm vs feet. Participants are trained, using real-time feedback on their performance, to use one of these combinations of imagined movement to respond to 'yes' or 'no' answer questions in the Q\&A sessions, by imagining one movement for 'yes' and the other for 'no'. A single combination of movements is chosen for each participant at the outset, and this participant-specific combination is used throughout their sessions. The study comprises three phases. The assessment Phase I (sessions 1-2) is to determine if the patient can imagine movements and produce detectable modulation in sensorimotor rhythms and thus is responding to instructions. Phase II (sessions 3-6) involves motor-imagery (MI) -BCI training with neurofeedback to facilitate learning of brain activity modulation; Phase III (sessions 7-10) assesses patients' MI-BCI response to closed questions, categorized to assess biographical, numerical, logical, and situational awareness. The present study augments the evidence of the efficacy for EEG-based BCI technology as an objective movement-independent diagnostic tool for the assessment of, and distinction between, PDoC and LIS patients.

Eligibility Criteria

Study 1 - Initial assessment/screening Inclusion Criteria: * Disorder of consciousness or low awareness state diagnosis ranging from unclear diagnosis in low awareness states, vegetative state and minimally conscious diagnosis. Those with locked in syndrome / completed locked in syndrome resulting from injury or disease e.g., motor neuron disease who do not have health problems that would preclude them from participating may be assessed but considered as a separate cohort to those with low awareness states. * acute, post-acute patients where appropriate Exclusion Criteria: * Participants with brain related diseases or illnesses (e.g., progressive neurological condition or uncontrolled epilepsy) or suffer from pain (these may adversely affect the brain data produced) and are deemed to be unsuitable for the trials by clinical teams. * Current consumption of medications that cause excessive fatigue or adversely affect cognitive functioning * Where English is not the individual's first language * Participant with excessive uncontrollable arm or head movement or teeth grinding as EEG signal quality will be degraded significantly. Study 2 - BCI training Inclusion Criteria: \- Those identified in study 1 to have a level of awareness based on observed appropriate brain activations and/or those who have known awareness but are target groups for movement independent assistive devices and technologies controlled using a brain-computer interface. Exclusion Criteria: \- Participants who have shown no active brain responses in study 1 where the difference between baseline

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