Daniel J. Levendowski

Real-Time Analysis of EEG Indexes of Alertness, Cognition, and Memory Acquired With a Wireless EEG Headset

The integration of brain monitoring into the man-machine interface holds great promise for real-time assessment of operator status and intelligent allocation of tasks between machines and humans. This article presents an integrated hardware and software solution for acquisition and real-time analysis of the electroencephalogram (EEG) to monitor indexes of alertness, cognition, and memory. Three experimental paradigms were evaluated in a total of 45 participants to identify EEG indexes associated with changes in cognitive workload: the Warship Commander Task (WCT), a simulated navy command and control environment that allowed workload levels to be systematically manipulated; a cognitive task with three levels of difficulty and consistent sensory inputs and motor outputs; and a multisession image learning and recognition memory test. Across tasks and participants, specific changes in the EEG were identified that were reliably associated with levels of cognitive workload. The EEG indexes were also shown to change as a function of training on the WCT and the learning and memory task. Future applications of the system to augment cognition in military and industrial environments are discussed.

Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model

A great deal of research over the last century has focused on drowsiness/alertness detection, as fatigue-related physical and cognitive impairments pose a serious risk to public health and safety. Available drowsiness/alertness detection solutions are unsatisfactory for a number of reasons: (1) lack of generalizability, (2) failure to address individual variability in generalized models, and/or (3) lack of a portable, un-tethered application. The current study aimed to address these issues, and determine if an individualized electroencephalography (EEG) based algorithm could be defined to track performance decrements associated with sleep loss, as this is the first step in developing a field deployable drowsiness/alertness detection system. The results indicated that an EEG-based algorithm, individualized using a series of brief identification tasks, was able to effectively track performance decrements associated with sleep deprivation. Future development will address the need for the algorithm to predict performance decrements due to sleep loss, and provide field applicability.

Assessment of the test–retest reliability of laboratory polysomnography

Statement of the problemWhen conducting a treatment intervention study, it is assumed that a level of reliability can be obtained from the measurement tool such that the outcome can be reasonably assessed.Purpose of studyInvestigate the reliability of laboratory polysomnography, the gold standard for assessment of treatment outcomes for obstructive sleep apnea, at a 1-month interval.Materials and MethodsIn a clinical trial of 118 patients recruited to assess the effects of a pharmaceutical treatment intervention, a subset of 20 patients designated as placebo controls completed two polysomnography studies, one at baseline and one at least one month later.ResultsThe correlation between the overall Apnea/Hypopnea indices from the two polysomnography (PSG) studies was poor (ru2009=u20090.44) and the results were biased, with a mean increase of seven events per hour on nightxa02. Twenty-five percent of the subjects had an increase greater than 20 events/hour on nightxa02 and only 45% of participants had a night-to-night difference of ≤5 events/hour. The correlation between overall apnea indexes for nightsxa01 and 2 (ru2009=u20090.61) was improved, compared to the overall apnea/hypopnea indexes. The correlation in sleep efficiency across the two nights was relatively week (ru2009=u20090.52) but significant. The correlations between nightsxa01 and 2 for the percentage of time supine (ru2009=u20090.70) and the supine apnea–hypopnea index (AHI) (ru2009=u20090.69) were similar and highly significant. The correlation for the non-supine AHI was only 0.25ConclusionsIn this study, the reliability of a single-night PSG in measuring treatment outcome was compromised as a result of the large night-to-night variability of subjects’ obstructive sleep apnea (OSA). Studies employing the AHI as an outcome need to be adequately powered with respect to the inherent night-to-night variability in the measurement. When assessing treatment intervention outcomes, there may be benefit from the acquisition and averaging of multiple nights of data in order to mitigate the inherent night-to-night variability of OSA and improve the accuracy of the outcome assessment.

Treatment outcomes of mandibular advancement devices in positional and nonpositional OSA patients

OBJECTIVEnThe aim of the study was to investigate treatment outcome of mandibular advancement devices (MADs) for positional and nonpositional obstructive sleep apnea (OSA).nnnSTUDY DESIGNnForty-two positional (supine apnea-hypopnea index [AHI] > or = 2 times lateral AHI) and 30 nonpositional (supine AHI < 2 times lateral AHI) OSA patients performed 2-nights of sleep study before and after insertion of MADs.nnnRESULTSnThe decreases in apnea severity based on a reduction in the overall and supine AHI values after MADs therapy were significantly greater for the positional OSA than nonpositional OSA group. A multiple linear regression analysis showed that decrease in overall AHI was significantly associated with being in the positional group (standardized coefficient = 0.505). Age, body mass index, gender, and time in supine position during sleep did not show significant associations with decrease in overall AHI after MAD therapy.nnnCONCLUSIONnOur data suggest that MADs are more effective in positional OSA than nonpositional OSA patients.

The impact of obstructive sleep apnea variability measured in-lab versus in-home on sample size calculations

Background When conducting a treatment intervention, it is assumed that variability associated with measurement of the disease can be controlled sufficiently to reasonably assess the outcome. In this study we investigate the variability of Apnea-Hypopnea Index obtained by polysomnography and by in-home portable recording in untreated mild to moderate obstructive sleep apnea (OSA) patients at a four- to six-month interval. Methods Thirty-seven adult patients serving as placebo controls underwent a baseline polysomnography and in-home sleep study followed by a second set of studies under the same conditions. The polysomnography studies were acquired and scored at three independent American Academy of Sleep Medicine accredited sleep laboratories. The in-home studies were acquired by the patient and scored using validated auto-scoring algorithms. The initial in-home study was conducted on average two months prior to the first polysomnography, the follow-up polysomnography and in-home studies were conducted approximately five to six months after the initial polysomnography. Results When comparing the test-retest Apnea-hypopnea Index (AHI) and apnea index (AI), the in-home results were more highly correlated (r = 0.65 and 0.68) than the comparable PSG results (r = 0.56 and 0.58). The in-home results provided approximately 50% less test-retest variability than the comparable polysomnography AHI and AI values. Both the overall polysomnography AHI and AI showed a substantial bias toward increased severity upon retest (8 and 6 events/hr respectively) while the in-home bias was essentially zero. The in-home percentage of time supine showed a better correlation compared to polysomnography (r = 0.72 vs. 0.43). Patients biased toward more time supine during the initial polysomnography; no trends in time supine for in-home studies were noted. Conclusion Night-to-night variability in sleep-disordered breathing can be a confounding factor in assessing treatment outcomes. The sample size of this study was small given the night-to-night variability in OSA and limited understanding of polysomnography reliability. We found that in-home studies provided a repeated measure of sleep disordered breathing less variable then polysomnography. Investigators using polysomnography to assess treatment outcomes should factor in the increased variability and bias toward increased AHI values upon retest to ensure the study is adequately powered.

Assessment of a neck-based treatment and monitoring device for positional obstructive sleep apnea.

STUDY OBJECTIVESnA majority of patients diagnosed with obstructive sleep apnea are position dependent whereby they are at least twice as severe when sleeping supine (POSA). This study evaluated the accuracy and efficacy of a neck-worn device designed to limit supine sleep. The study included nightly measurements of snoring, sleep/wake, time supine, and the frequency and duration of feedback to monitor compliance.nnnMETHODSnThirty patients between ages 18 and 75 years, BMI ≤ 35 with an overall apnea-hypopnea index (AHI) ≥ 5 and an overall AHI ≥ 1.5 times the non-supine AHI, and an Epworth score ≥ 5 were prospectively studied. Subjective reports and polysomnography were used to assess efficacy resulting from 4 weeks of in-home supine-avoidance therapy and to measure device accuracy. From 363 polysomnography reports, 209 provided sufficient positional data to estimate one sites prevalence of positional OSA.nnnRESULTSnIn 83% of participants exhibiting > 50% reduction in overall AHI, the mean and median reductions were 69% and 79%. Significant reductions in the overall and supine AHI, apnea index, percent time SpO2 < 90%, and snoring contributed to significant improvements in stage N1 and N2 sleep, reductions in cortical arousals and awakenings, and improved depression scores. Supine position was under-detected by > 5% in 3% of cases. Sleep efficiency by neck actigraphy was within 10% of polysomnography in 87% of the studies when position feedback was delivered. The prevalence of POSA was consistently > 70% when the overall AHI was < 60.nnnCONCLUSIONSnThe neck position therapy device is accurate and effective in restricting supine sleep, improving AHI, sleep architecture and continuity, and monitoring treatment outcomes.

Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters

OBJECTIVESnElectroencephalography (EEG) assessment in research and clinical studies is limited by the patient burden of multiple electrodes and the time needed to manually score records. The objective of our study was to investigate the accuracy of an automated sleep-staging algorithm which is based on a single bipolar EEG signal.nnnMETHODSnThree raters each manually scored the polysomnographic (PSG) records from 44 patients referred for sleep evaluation. Twenty-one PSG records were scored by Rechtschaffen and Kales (R&K) criteria (group 1) and 23 PSGs were scored by American Academy of Sleep Medicine (AASM) 2007 criteria (group 2). Majority agreement was present in 98.4% of epochs and was used for comparison to automated scoring from a single EEG lead derived from the left and right electrooculogram.nnnRESULTSnThe κ coefficients for interrater manual scoring ranged from 0.46 to 0.89. The κ coefficient for the auto algorithm vs manual scoring by rater ranged from 0.42 to 0.63 and was 0.61 (group 1, κ=0.61 and group 2, κ=0.62) for majority agreement for all studies. The mean positive percent agreement across subjects and stages was 72.6%, approximately 80% for stages wake (78.3%), stage 2 sleep (N2) (80.9%), and stage 3 sleep (N3) (78.1%); the percentage slightly decreased to 73.2% for rapid eye movement (REM) sleep and dropped to 31.9% for stage 1 sleep (N1). Differences in agreement were observed based on raters, obstructive sleep apnea (OSA) severity, medications, and signal quality.nnnCONCLUSIONSnOur study demonstrated that automated scoring of sleep obtained from a single-channel of forehead EEG results in agreement to majority manual scoring are similar to results obtained from studies of manual interrater agreement. The benefit in assessing auto-staging accuracy with consensus agreement across multiple raters is most apparent in patients with OSA; additionally, assessing auto-staging accuracy limited disagreements in patients on medications and in those with compromised signal quality.

Prevalence of probable obstructive sleep apnea risk and severity in a population of dental patients

Obstructive sleep apnea is a commonly undiagnosed chronic disease. While dentists represent an important resource for identifying people at risk for primary snoring and sleep apnea, less than 50% of dentists are capable of identifying the common signs and symptoms of sleep disordered breathing. The aim of this study is to assess the prevalence of probable obstructive sleep apnea/sleep disordered breathing and symptoms associated with this condition in a population of dental patients using a validated questionnaire and software that could be administered in a dental office. A retrospective analysis conducted at two dental practices using questionnaire responses obtained from 175 men and 156 women, and sleep study data obtained in the patient’s homes from 75 men and 30 women with a portable recorder. Forty-six percent of the men and 19% of the women reported snoring frequently or always. Of the 67% of the men and 28% of the women identified as having a high pre-test probability (high risk) of having at least mild sleep apnea, over 33% of the men and 6% of the women surveyed were predicted to have moderate or severe sleep apnea. In a subgroup of 105 patients classified at high risk who completed an overnight sleep study, 96% had an apnea hypopnea index (AHI) greater than five events per hour. Seventy percent of those predicted to have moderate or severe OSA by questionnaire had an AHI greater than 20. All patients previously diagnosed with sleep apnea were correctly classified at high risk by ARES questionnaire. There was a high concordance between the predicted OSA risk and the degree of sleep disordered breathing. The high prevalence of undiagnosed sleep apnea in dental patients suggests that dentists could provide a valuable service to their patients by incorporating sleep apnea screening and treatment into their practice. Those who practice sedation dentistry should consider additional precautions when managing patients with risk of sleep apnea.

In-home evaluation of efficacy and titration of a mandibular advancement device for obstructive sleep apnea.

There is increasing evidence that mandibular advancement devices (MADs) can be an effective treatment for some patients with obstructive sleep apnea, a highly prevalent chronic disease. In this study, the objectives were to objectively assess the effectiveness of MAD therapy using a limited channel recorder, and to develop a model for identifying patients who may be appropriate for MAD therapy as the initial treatment option. Thirty patients were prospectively recruited and studied at two independent dentist offices and the participants’ homes. Subjects wore the ARES Unicorder for two nights before insertion of the MAD, and again when the dentist determined that the patient had reached the titration endpoint. Self-reported measures of depression, sleepiness, and quality of life were obtained pre- and posttreatment. The reviewer was blinded to the study status while the physiological signals were being visually inspected. Significant reductions in the apnea/hypopnea index (AHI), hypoxemia measures, and snoring level were observed posttreatment. Twenty-seven of the 30 (90%) patients had a posttreatment AHI (using a 4% desaturation for hypopneas) below a clinical cut-off of 10. All but one patient (97%) exhibited at least a 50% decrease in AHI or had a posttreatment AHIu2009≤u200910. Significant differences in body mass index, weight, and neck circumference in patients with posttreatment AHIs above and below a clinical cut-off of five were identified. The linear regression used to predict the posttreatment AHI using pretreatment data resulted in an R2 of 0.68. The model correctly predicted two patients who were unable to obtain a posttreatment AHI of 10 or less. This study was designed to demonstrate two models of collaboration between a dental sleep medicine specialist and a sleep medicine physician in the monitoring of a patient treated with a MAD. The outcome data suggest that the limited channel recording system can be used as an alternative to laboratory polysomnography to reduce the cost of MAD treatment, and to improve the quality and consistency of posttreatment patient care.

EEG quantification of alertness: Methods for early identification of individuals most susceptible to sleep deprivation

Electroencephalographic (EEG) and neurocognitive measures were simultaneously acquired to quantify alertness from 24 participants during 44-hours of sleep deprivation. Performance on a three-choice vigilance task (3C-VT), paired-associate learning/memory task (PAL) and modified Maintenance of Wakefulness Test (MWT), and sleep technician-observed drowsiness (eye-closures, head-nods, EEG slowing) were quantified. The B-Alert system automatically classifies each second of EEG on an alertness/drowsiness continuum. B-Alert classifications were significantly correlated with technician-observations, visually scored EEG and performance measures. B-Alert classifications during 3C-VT, and technician observations and performance during the 3C-VT and PAL evidenced progressively increasing drowsiness as a result of sleep deprivation with a stabilizing effect observed at the batteries occurring between 0600 and 1100 suggesting a possible circadian effect similar to those reported in previous sleep deprivation studies. Participants were given an opportunity to take a 40-minute nap approximately 24-hours into the sleep deprivation portion of the study (i.e., 7 PM on Saturday). The nap was followed by a transient period of increased alertness. Approximately 8 hours after the nap, behavioral and physiological measures of drowsiness returned to levels prior to the nap. Cluster analysis was used to stratify individuals into three groups based on their level of impairment as a result of sleep deprivation. The combination of B-Alert and neuro-behavioral measures may identify individuals whose performance is most susceptible to sleep deprivation. These objective measures could be applied in an operational setting to provide a “biobehavioral assay” to determine vulnerability to sleep deprivation.