Awareness Detection and Communication in Disorders of Consciousness

Stroke Clinical Trial

Official title: EEG Based Awareness Detection and Communication in Prolonged Disorders of Consciousness and Physical Disability

Status Recruiting

Clinical Trial 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.

Clinical Trial Description

PRINCIPLE RESEARCH QUESTIONS The project will address a number key principal research questions largely based on two phases to the study.

Phase/study 1

1. What percentage of disorder of consciousness patients assessed provide evidence of awareness using EEG-based BCI technology?

2. How does this differ from their clinical diagnosis/prognosis?

3. Does the EEG-based information complement or augment the clinical assessment and diagnosis process?

4. Do any of those participants who are diagnosed as being in a vegetative state (or MCS) show signs of awareness beyond the vegetative state based on the EEG-based detection of awareness protocol?

Phase/study 2

1. Is it possible to train those participants who show clear signs of awareness, as indicated by significant brain activation during the initial assessment in study 1, to produce a more prominent and/or consistent response over a number of training sessions using BCI based training and feedback protocols?

2. Can a subset of the participants use BCI technology to communicate simple responses to questions at the end of the study or is there enough evidence to suggest that with further training over a longer period that the participant may use BCI technology as an alternative or an exclusive communication channel?

3. Does neurotechnology offer any other therapeutic benefits to patients, for example, a means of technology interaction that is movement independent and engaging brain areas otherwise not engaged?

SECONDARY RESEARCH Q UESTIONS

1. Does the technology aid feedback/interpretation on assessment outcomes from consultants?

2. How might the experiment provide an opportunity for training others in the deployment of the technology in a clinical setting?

3. What types of BCI methods of feedback are best auditory/visual or both, musical or broadband noise, games or applications etc? ;

Related Conditions & MeSH terms

• Amyotrophic Lateral Sclerosis
• Consciousness Disorders
• Disorder of Consciousness
• Motor Neuron Disease
• Paralysis
• Physical Disability
• Stroke

• NCT number: NCT03827187
• Study type: Interventional
• Source: University of Ulster
• Contact: Damien Coyle, PhD
• Phone: +44 28 7167 5170
• Email: dh.coyle@ulster.ac.uk
• Status: Recruiting
• Phase: N/A
• Start date: February 8, 2022
• Completion date: August 2026