In this study, we demonstrated the use of low-cost portable electroencephalography (EEG) as a method for prehospital stroke diagnosis. We used a portable EEG system to record data from 25 participants, 16 had acute ischemic stroke events, and compared the results to age-matched controls that included stroke mimics. Delta/alpha ratio (DAR), (delta + theta)/(alpha + beta) ratio (DBATR) and pairwise-derived Brain Symmetry Index (pdBSI) were investigated, as well as head movement using the on-board accelerometer and gyroscope. We then used machine learning to distinguish between different subgroups. DAR and DBATR increased in ischemic stroke patients with increasing stroke severity (p = 0.0021, partial η2 = 0.293; p = 0.01, partial η2 = 0.234). Also, pdBSI decreased in low frequencies and increased in high frequencies in patients who had a stroke (p = 0.036, partial η2 = 0.177). Using classification trees, we were able to distinguish moderate to severe stroke patients and from minor stroke and controls, with a 63% sensitivity, 86% specificity and accuracy of 76%. There are significant differences in DAR, DBATR, and pdBSI between patients with ischemic stroke when compared to controls, and these effects scale with severity. We have shown the utility of a low-cost portable EEG system to aid in patient triage and diagnosis as an early detection tool.

Objective In this pilot study, we investigated using portable electroencephalography (EEG) as a potential prehospital stroke diagnostic method. Methods We used a portable EEG system to record data from 25 participants, 16 had acute ischemic stroke events, and compared the results of age-matched controls that included stroke mimics. Delta/alpha ratio (DAR), (delta+theta)/(alpha+beta) ratio (DBATR) and pairwise-derived Brain Symmetry Index (pdBSI) were investigated, as well as accelerometer and gyroscope trends. We then made classification trees using TreeBagger to distinguish between different subgroups. Results DAR and DBATR showed an increase in ischemic stroke patients that correlates with stroke severity (p<0.01). pdBSI decreased in low frequencies and increased in high frequencies in patients who had a stroke (p<0.05). All quantitative EEG measures were significant between stroke patients and controls. Using classification trees, we were able to distinguish between subgroups of stroke patients and controls. Conclusions There are significant differences in DAR, DBATR, and pdBSI between patients with ischemic stroke when compared to controls; results relate to severity. Significance With significant differences between patients with strokes and controls, we have shown the feasibility and utility for the Muse EEG system to aid in patient triage and diagnosis as an early detection tool.

Accurate and timely prehospital stroke diagnosis and detection of large vessel occlusion (LVO) are essential to ensure stroke patients are transported to hospitals that offer emergent reperfusion therapies. However, symptom based prehospital stroke scales often fail to identify LVO. Thus, a need exists for cost-effective and portable diagnostic tools, such as portable electroencephalography (EEG) to improve the accuracy of prehospital stroke diagnosis. Hypotheses: 1) Quantitative EEG measures will differ between LVO and non-LVO stroke patients, particularly in regards to brain slowing (ratio of low to high frequency oscillatory brain power) and brain asymmetry (ratio between oscillations in the affected and unaffected hemisphere) 2) Combining EEG with prehospital stroke scales will improve the accuracy of LVO detection. We enrolled patients with acute suspected stroke on presentation to an emergency department at a comprehensive stroke centre. Patients were rapidly evaluated with the Los Angeles Motor Scale followed by a 3-minute resting-state EEG recording using a modified Muse EEG headband (InteraXon). The LVO diagnosis and the extent of cerebral blood flow abnormalities were determined from CT angiography and CT perfusion imaging performed in close temporal proximity to the EEG recording. The study enrolled 74 patients (n= 8 LVO, n=66 non-LVO, including stroke mimics). Initial analysis suggests that LVO patients have trends towards brain slowing, as measured by the delta alpha ratio (LVO: mean = 1.21, SEM = 0.03; non-LVO: mean = 1.19, SEM = 0.01; p-value = 0.34). Additionally, LVO patients showed a trend towards increased brain asymmetry from 6-8 Hz, suggesting physiological differences between hemispheres specific to the theta frequency (LVO: mean = 0.02, SEM = 0.006; non-LVO: mean = 0.01, SEM = 0.002; p-value = 0.13). Quantitative measures will be assessed using classification trees to determine which combination of EEG and clinical features is most predictive of LVO. In conclusion, acute differences in brain activity between LVO and non-LVO patients can be detected with portable EEG, which when combined with clinical stroke scales, have the potential to improve the diagnosis and triage of suspected stroke patients in a prehospital setting.

Introduction: Persistent neurovascular uncoupling may be associated with poor outcome in patients with ischemic stroke after successful recanalization. Quantitative electroencephalography (EEG) can be used to assess neuronal function. We assessed relation between degree of recanalization post-endovascular thrombectomy (EVT), quantitative EEG based parameters and severity of neurological deficits. Methods: Patients with acute ischemic stroke with large vessel occlusion in anterior circulation were enrolled. EEG was recorded using a modified Muse headband (InteraXon) before, immediately after and at 24 hours post-EVT. Pairwise-derived brain symmetry index (pdBSI) and delta-to-alpha ratio (DAR) were computed using Fitting Oscillation & one-over F (FOOOF) MATLAB wrapper. Results: A total of six patients with mean age 73.6±11.6 years and baseline median (IQR) NIHSS of 13.5 (11-15) were included. Expanded thrombolysis in cerebral infarction (eTICI) scores were 2b67 in one, 2c in two and 3 in three cases. Baseline EEG was recorded at 75 minutes (60-100) from arrival, second at 255 minutes (90-420) after recanalization and third at 28.5 hours (27-31) after recanalization. Four patients with improvement in NIHSS of >10 had 46.6±31.7% change in pdBSI at 24 h. One patient with NIHSS <10 improvement had -25.3% change in pdBSI. One patient with low baseline NIHSS (9) had 90.9% change in pdBSI. There was linear correlation between baseline infarct volume on perfusion studies and change in pdBSI at 24 h (r=0.86, p<0.0001, Figure 1). There was no difference in the DAR in the ipsilateral hemisphere pre-EVT, immediately post-EVT (p=0.6) and 24 h post-EVT (p=0.8). Conclusion: Preliminary data suggest return of neuronal function and clinical recovery may lag after successful recanalization, due to persistent neurovascular uncoupling. Higher baseline infarct volume may predict lower pdBSI change. Portable EEG may help characterise this novel treatment target.

NOVEL ODDBALL PARADIGM IN VIRTUAL REALITY 1 Electroencephalography (EEG) research is typically conducted in controlled laboratory settings. This limits the generalizability to real-world situations. Virtual reality (VR) sits as a transitional tool that provides tight experimental control with more realistic stimuli. To test the validity of using VR for eventrelated potential (ERP) research, we used a well-established paradigm, the oddball task. Standard stimuli were presented 80% of the time and target stimuli which were responded to, presented 20% of the time.For our first study we compared traditional to VR stimulus presentation using standard visual and auditory oddball tasks. We found that ERPs collected using VR head mounted displays and typical monitors were comparable on measures of latency, amplitude, and spectral composition. In a second study we implemented a novel depth-based oddball task. We demonstrated that typical oddball ERPs elicited by presentation of near and far stimuli. Interestingly, we observed significant differences in early ERPs components between near and far stimuli, even after controlling for the effects of the oddball task.Current results suggest that VR can serve as a valid means of stimulus presentation in novel or otherwise inaccessible environments for EEG experimentation. We demonstrated the capability of the depth-based oddball to reliably elicit P3 responses, and find an interaction between the depth at which objects are presented and early ERP response. Further research is warranted to better explain this relationship of depth on the ERP components.