Real-time assessment of daytime sleepiness in drivers with multiple sclerosis

Devos, Hannes; Alissa, Nesreen; Lynch, Sharon G.; Sadeghi, Maryam; Akinwuntan, Abiodun Emmanuel; Siengsukon, Catherine

doi:10.1016/j.msard.2020.102607

Cited by 11 publications

(10 citation statements)

References 39 publications

(45 reference statements)

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“…Most studies included small to moderate sample sizes: on-road studies ranged from 30 ( 13 *2 ) to 218 ( 43 ) PwMS (mean: 65 PwMS included per study), while driving simulator studies ranged from 11 ( 36 ) to 38 ( 39 *3 , 40 *3 ) PwMS (mean: 25 PwMS included per study). The age of the PwMS ranged between 35.6 years (mean, SD 8.3) ( 17 ) and 55 years (median, Q1–3: 50–59) ( 35 ). Most PwMS had relapsing-remitting MS (n = 439), 25 were classified as SPMS, 29 had PPMS, and 13 were reported as unknown.…”

Section: Resultsmentioning

confidence: 99%

Driving ability and predictors for driving performance in Multiple Sclerosis: A systematic review

et al. 2022

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ObjectiveTo provide an overview of the evidence on driving ability in persons with multiple sclerosis (PwMS), specifically to (i) study the impact of MS impairment on driving ability and (ii) evaluate predictors for driving performance in MS.MethodsTo identify relevant studies, different electronic databases were screened in accordance with PRISMA guidelines; this includes reference lists of review articles, primary studies, and trial registers for protocols. Furthermore, experts in the field were contacted. Two reviewers independently screened titles, abstracts, and full-texts to identify relevant articles targeting driving in people with MS that investigated driving-related issues with a formal driving assessment (defined as either an on-road driving assessment; or naturalistic driving in a car equipped with video cameras to record the driving; or a driving simulator with a steering wheel, a brake pedal, and an accelerator).ResultsTwenty-four publications, with 15 unique samples (n = 806 PwMS), were identified. To assess driving ability, on-road tests (14 papers) and driving simulators (10 papers) were used. All studies showed moderate to high study quality in the CASP assessment. About 6 to 38% of PwMS failed the on-road tests, showing difficulties in different areas of driving. Similarly, PwMS showed several problems in driving simulations. Cognitive and visual impairment appeared to most impact driving ability, but the evidence was insufficient and inconsistent.ConclusionThere is an urgent need for more research and standardized guidelines for clinicians as one in five PwMS might not be able to drive safely. On-road tests may be the gold standard in assessing driving ability, but on-road protocols are heterogeneous and not infallible. Driving simulators assess driving ability in a standardized way, but without standardized routes and driving outcomes, comparability between studies is difficult. Different aspects, such as cognitive impairment or vision problems, impact driving ability negatively and should be taken into consideration when making decisions about recommending driving cessation.Systematic review registrationIdentifier [10.17605/OSF.IO/WTG9J].

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Section: Resultsmentioning

confidence: 99%

Driving ability and predictors for driving performance in Multiple Sclerosis: A systematic review

et al. 2022

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“…We did not find any significant association of EDS with age, sex, interocular RNFL, interocular GCL, ON, or reported physical disability in patients with MS, which is congruous with what has been reported in the literature. 33 There was slight seasonality of the patient-reported outcome, which coincides with degree of sun exposure in the southern United States. During the summer there is generally greater photic exposure relative to the winter.…”

Section: Discussionmentioning

confidence: 87%

“…Circadian rhythm disorders have been posited as a potential explanation of EDS in patients with MS. There is preliminary evidence to support this claim, 6,15 but the true prevalence of circadian rhythm dysfunction, and its contribution to EDS in MS remain unclear.…”

Section: Introductionmentioning

confidence: 99%

Disease associations of excessive daytime sleepiness in multiple sclerosis: A prospective study

Sguigna

Toranian

Tardo

et al. 2023

Multiple Sclerosis Journal - Experimental, Translational and Cl

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Background Excessive daytime sleepiness (EDS) in multiple sclerosis (MS) can be a significant source of disability. Despite this, its prevalence as a patient-reported outcome in this condition has not been well established, and its causes are not well understood. Methods We prospectively assessed EDS as part of an observational study for patients referred for diagnostic neuro-ophthalmological testing. EDS was evaluated by the Epworth Sleepiness Scale (ESS), and visual data were also collected as part of a research protocol. Analysis with patient data was performed following the exclusion of patients with known primary sleep disorders. Results A total of 69 patients with MS were included in the analysis. The mean ESS was 6.5 with a SD of 4.3. ESS ≥ 10 was present in 23% of the cohort even in the presence of minimal mean neurological disability (Patient Determined Disease Steps (PDDS) = 1.5). The ESS score was not associated with age, sex, disease-related disability, retinal nerve fiber layer (RNFL), or optic neuritis (ON), but displayed an association with visual dysfunction. Conclusions There is an increased prevalence of EDS in MS. The increased values of the ESS are not explained by other sleep disorders, suggesting separate mechanisms. Further study of the underlying mechanisms is warranted.

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“…PERCLOS is a measure of drowsiness that is defined as the proportion of time in a minute that eyes are at least 80 percent closed 33 . For higher PERCLOS values, where the eyes are mostly closed for longer periods of time than for lower PERCLOS values, subjects exhibit strong correlation with a common sign of drowsiness in driving which is lane deviation in the road 33,40 . To calculate this measure, a one-minute sliding window with a 30 seconds overlap between every two consecutive windows has been applied to the eyelid signal.…”

Section: Methodsmentioning

confidence: 99%

Driver drowsiness estimation using EEG signals with a dynamical encoder–decoder modeling framework

Arefnezhad

Hamet

Eichberger

et al. 2022

Sci Rep

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Drowsiness is a leading cause of accidents on the road as it negatively affects the driver’s ability to safely operate a vehicle. Neural activity recorded by EEG electrodes is a widely used physiological correlate of driver drowsiness. This paper presents a novel dynamical modeling solution to estimate the instantaneous level of the driver drowsiness using EEG signals, where the PERcentage of eyelid CLOSure (PERCLOS) is employed as the ground truth of driver drowsiness. Applying our proposed modeling framework, we find neural features present in EEG data that encode PERCLOS. In the decoding phase, we use a Bayesian filtering solution to estimate the PERCLOS level over time. A data set that comprises 18 driving tests, conducted by 13 drivers, has been used to investigate the performance of the proposed framework. The modeling performance in estimation of PERCLOS provides robust and repeatable results in tests with manual and automated driving modes by an average RMSE of 0.117 (at a PERCLOS range of 0 to 1) and average High Probability Density percentage of 62.5%. We further hypothesized that there are biomarkers that encode the PERCLOS across different driving tests and participants. Using this solution, we identified possible biomarkers such as Theta and Delta powers. Results show that about 73% and 66% of the Theta and Delta powers which are selected as biomarkers are increasing as PERCLOS grows during the driving test. We argue that the proposed method is a robust and reliable solution to estimate drowsiness in real-time which opens the door in utilizing EEG-based measures in driver drowsiness detection systems.

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Real-time assessment of daytime sleepiness in drivers with multiple sclerosis

Cited by 11 publications

References 39 publications

Driving ability and predictors for driving performance in Multiple Sclerosis: A systematic review

Driving ability and predictors for driving performance in Multiple Sclerosis: A systematic review

Disease associations of excessive daytime sleepiness in multiple sclerosis: A prospective study

Driver drowsiness estimation using EEG signals with a dynamical encoder–decoder modeling framework

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