Joseph W. Burns

Sleep stage dynamics in fibromyalgia patients and controls.

OBJECTIVE To determine whether previously described sleep stage dynamics, reflecting the mean duration of specific sleep stages, may have clinical utility in a sample of patients with fibromyalgia syndrome (FMS) and controls. METHODS Women with FMS (n=15, screened to exclude other sleep disorders) and age-matched women in good health (n=15) were studied with nocturnal polysomnography, multiple sleep latency tests, 2-week pain diaries, and a measure of current pain intensity. RESULTS The FMS subjects, in comparison to controls, did not show differences in several common polysomnographic measures, except for increased numbers of stage shifts (126+/-27 vs. 107+/-22, p=.042). Mean durations for episodes of total sleep, stage 1 sleep, stage 3/4 sleep, and rapid eye movement sleep failed to distinguish FMS and control subjects (Wilcoxon rank sum tests, p>.10 for each), but those for stage 2 sleep were shorter in the FMS subjects (p=.006), possibly because transitions to stage 3/4 sleep occurred more quickly (p=.036). Shorter stage 2 sleep durations predicted higher pain diary scores (Spearman rho=-.56, p=.0014) and current pain intensity (rho=-.71, p<0.0001). CONCLUSIONS Sleep stage dynamic, and, more specifically, shorter durations of sleep stage 2 periods, distinguish FMS and control female subjects and may predict pain levels experienced in FMS. Analysis of the lengths of individual sleep stages, in addition to the usual sleep stage amounts and percentages listed in standard polysomnogram reports, may have clinical utility.

Parametric reconstruction of internal building structures via canonical scattering mechanisms

In this paper, we describe a model-based, non-linear reconstruction method for mapping internal building structures using through-wall radar data. We based the model on canonical geometry constructs that are commonly used in construction practices. These constructs are then formulated as sets of simple scattering mechanisms, which can be estimated from the data. Our non-linear approach employs an iterative, conditional estimation method as a function of the intervening structures between the sensor and the object under consideration. Specific associations of scattering mechanisms are then used to re-create various building structures such as walls, doors, stairs, etc. We discuss some examples of estimating specific scattering mechanisms and a model-based reasoning approach for assembling them to reconstruct the interior structure of a building.

Limited short-term prognostic utility of cerebral NIRS during neonatal therapeutic hypothermia

Objective: We evaluated the utility of amplitude-integrated EEG (aEEG) and regional oxygen saturation (rSO2) measured using near-infrared spectroscopy (NIRS) for short-term outcome prediction in neonates with hypoxic ischemic encephalopathy (HIE) treated with therapeutic hypothermia. Methods: Neonates with HIE were monitored with dual-channel aEEG, bilateral cerebral NIRS, and systemic NIRS throughout cooling and rewarming. The short-term outcome measure was a composite of neurologic examination and brain MRI scores at 7 to 10 days. Multiple regression models were developed to assess NIRS and aEEG recorded during the 6 hours before rewarming and the 6-hour rewarming period as predictors of short-term outcome. Results: Twenty-one infants, mean gestational age 38.8 ± 1.6 weeks, median 10-minute Apgar score 4 (range 0–8), and mean initial pH 6.92 ± 0.19, were enrolled. Before rewarming, the most parsimonious model included 4 parameters (adjusted R2 = 0.59; p = 0.006): lower values of systemic rSO2 variability (p = 0.004), aEEG bandwidth variability (p = 0.019), and mean aEEG upper margin (p = 0.006), combined with higher mean aEEG bandwidth (worse discontinuity; p = 0.013), predicted worse short-term outcome. During rewarming, lower systemic rSO2 variability (p = 0.007) and depressed aEEG lower margin (p = 0.034) were associated with worse outcome (model-adjusted R2 = 0.49; p = 0.005). Cerebral NIRS data did not contribute to either model. Conclusions: During day 3 of cooling and during rewarming, loss of physiologic variability (by systemic NIRS) and invariant, discontinuous aEEG patterns predict poor short-term outcome in neonates with HIE. These parameters, but not cerebral NIRS, may be useful to identify infants suitable for studies of adjuvant neuroprotective therapies or modification of the duration of cooling and/or rewarming.

Respiratory cycle-related EEG changes: response to CPAP.

STUDY OBJECTIVES Respiratory cycle-related EEG changes (RCREC) quantify statistically significant synchrony between respiratory cycles and EEG spectral power, vary to some extent with work of breathing, and may help to predict sleepiness in patients with obstructive sleep apnea. This study was designed to assess the acute response of RCREC to relief of upper airway obstruction by positive airway pressure (PAP). DESIGN Comparison of RCREC between baseline diagnostic polysomnograms and PAP titration studies. SETTING Accredited academic sleep disorders center. PATIENTS Fifty adults referred for suspected sleep disordered breathing. INTERVENTIONS For each recording, the RCREC in specific physiologic EEG frequency ranges were computed as previously described for the last 3 h of sleep not occupied by apneic events. RESULTS The sample included 27 women; mean age was 47 ± 11 (SD) years; and median respiratory disturbance index at baseline was 24 (inter-quartile range 15-43). Decrements in RCREC, from baseline to PAP titration, reached 43%, 24%, 14%, 22%, and 31% for delta (P = 0.0004), theta (P = 0.01), alpha (P = 0.10), sigma (P = 0.08), and beta (P = 0.01) EEG frequency ranges, respectively. Within each specific sleep stage, these reductions from baseline to PAP studies in synchrony between EEG power and respiratory cycles still reached significance (P < 0.05) for one or more EEG frequency ranges and for all frequency ranges during REM sleep. CONCLUSIONS RCREC tends to diminish acutely with alleviation of upper airway obstruction by PAP. These data in combination with previous observations support the hypothesis that RCREC reflect numerous, subtle, brief, but consequential inspiratory microarousals.

Quantitative sleep stage analyses as a window to neonatal neurologic function

Objective: To test the hypothesis that neonatal sleep physiology reflects cerebral dysfunction, we compared neurologic examination scores to the proportions of recorded sleep/wake states, sleep depth, and sleep fragmentation in critically ill neonates. Methods: Newborn infants (≥35 weeks gestation) who required intensive care and were at risk for seizures were monitored with 8- to 12-hour polysomnograms (PSGs). For each infant, the distribution of sleep-wake states, entropy of the sequence of state transitions, and delta power from the EEG portion of the PSG were quantified. Standardized neurologic examination (Thompson) scores were calculated. Results: Twenty-eight infants participated (mean gestational age 39.0 ± 1.6 weeks). An increased fraction of quiet sleep correlated with worse neurologic examination scores (Spearman rho = 0.54, p = 0.003), but the proportion of active sleep did not (p > 0.1). Higher state entropy corresponded to better examination scores (rho = −0.43, p = 0.023). Decreased delta power during quiet sleep, but not the power at other frequencies, was also associated with worse examination scores (rho = −0.48, p = 0.009). These findings retained significance after adjustment for gestational age or postmenstrual age at the time of the PSG. Sleep stage transition probabilities were also related to examination scores. Conclusions: Among critically ill neonates at risk for CNS dysfunction, several features of recorded sleep—including analyses of sleep stages, depth, and fragmentation—showed associations with neurologic examination scores. Quantitative PSG analyses may add useful objective information to the traditional neurologic assessment of critically ill neonates.

The face of sleepiness: improvement in appearance after treatment of sleep apnea.

STUDY OBJECTIVES Anecdote but no formal evidence suggests that facial appearance improves after hypersomnolent patients with obstructive sleep apnea are treated. We investigated whether masked volunteer raters can identify post- rather than pre-treatment images as looking more alert, and whether impressions are predicted by any objective changes on highly precise 3-dimensional digital photogrammetry. METHODS Participants included 20 adults with obstructive sleep apnea on polysomnography and excessive sleepiness on Epworth Sleepiness Scales. Photogrammetry was performed before and after ≥ 2 months of adherent use of positive airway pressure. Twenty-two raters then assessed pre- and post-treatment facial images, paired side-by-side in random order. RESULTS Subjects included 14 men and 6 women, with mean age 45 ± 11 (SD) years and mean baseline apnea/hypopnea index of 26 ± 21. The 22 raters twice as often identified post-treatment rather than pre-treatment images to look more alert (p = 0.0053), more youthful (p = 0.026), more attractive (p = 0.0068), and more likely to reflect the treated state (p = 0.015). Photogrammetry documented post-treatment decreases in forehead surface volume and decreased infraorbital and cheek redness, but no narrowing of the interpalpebral fissure. Decreased deep NREM sleep at baseline, and pre- to post-treatment decrements in facial redness showed promise as predictors of improved subjective ratings for alertness. CONCLUSIONS Patients with obstructive sleep apnea are perceived to appear more alert, more youthful, and more attractive after adherent use of positive airway pressure. Objective changes in facial surface volume and color were identified. Post-treatment decrements in redness may inform subjective impressions of improved alertness.

Engineering better sleep

Sleep medicine is a growing field with multidisciplinary origins in physiological monitoring techniques, on which it still largely depends. Collaborations between engineers and sleep specialists offer substantial opportunities to improve on current approaches to diagnosis and assessment of patients with sleep problems. Such collaborations could also prove key to improved fundamental understanding of the pathophysiology that underlies sleep disorders and their adverse impact on the brain, cardiovascular system, and optimal health.

Do Respiratory Cycle-Related EEG Changes or Arousals from Sleep Predict Neurobehavioral Deficits and Response to Adenotonsillectomy in Children?

STUDY OBJECTIVES Pediatric obstructive sleep apnea (OSA) is associated with hyperactive behavior, cognitive deficits, psychiatric morbidity, and sleepiness, but objective polysomnographic measures of OSA presence or severity among children scheduled for adenotonsillectomy have not explained why. To assess whether sleep fragmentation might explain neurobehavioral outcomes, we prospectively assessed the predictive value of standard arousals and also respiratory cycle-related EEG changes (RCREC), thought to reflect inspiratory microarousals. METHODS Washtenaw County Adenotonsillectomy Cohort II participants included children (ages 3-12 years) scheduled for adenotonsillectomy, for any clinical indication. At enrollment and again 7.2 ± 0.9 (SD) months later, children had polysomnography, a multiple sleep latency test, parent-completed behavioral rating scales, cognitive testing, and psychiatric evaluation. The RCREC were computed as previously described for delta, theta, alpha, sigma, and beta EEG frequency bands. RESULTS Participants included 133 children, 109 with OSA (apnea-hypopnea index [AHI] ≥ 1.5, mean 8.3 ± 10.6) and 24 without OSA (AHI 0.9 ± 0.3). At baseline, the arousal index and RCREC showed no consistent, significant associations with neurobehavioral morbidities, among all subjects or the 109 with OSA. At follow-up, the arousal index, RCREC, and neurobehavioral measures all tended to improve, but neither baseline measure of sleep fragmentation effectively predicted outcomes (all p > 0.05, with only scattered exceptions, among all subjects or those with OSA). CONCLUSION Sleep fragmentation, as reflected by standard arousals or by RCREC, appears unlikely to explain neurobehavioral morbidity among children who undergo adenotonsillectomy. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, ID: NCT00233194.

GPR Anomaly Detection with Robust Principal Component Analysis

This paper investigates the application of Robust Principal Component Analysis (RPCA) to ground penetrating radar as a means to improve GPR anomaly detection. The method consists of a preprocessing routine to smoothly align the ground and remove the ground response (haircut), followed by mapping to the frequency domain, applying RPCA, and then mapping the sparse component of the RPCA decomposition back to the time domain. A prescreener is then applied to the time-domain sparse component to perform anomaly detection. The emphasis of the RPCA algorithm on sparsity has the effect of significantly increasing the apparent signal-to-clutter ratio (SCR) as compared to the original data, thereby enabling improved anomaly detection. This method is compared to detrending (spatial-mean removal) and classical principal component analysis (PCA), and the RPCA-based processing is seen to provide substantial improvements in the apparent SCR over both of these alternative processing schemes. In particular, the algorithm has been applied to both field collected impulse GPR data and has shown significant improvement in terms of the ROC curve relative to detrending and PCA.

Neonatal Sleep–Wake Analyses Predict 18-month Neurodevelopmental Outcomes

Objectives The neurological examination of critically ill neonates is largely limited to reflexive behavior. The exam often ignores sleep-wake physiology that may reflect brain integrity and influence long-term outcomes. We assessed whether polysomnography and concurrent cerebral near-infrared spectroscopy (NIRS) might improve prediction of 18-month neurodevelopmental outcomes. Methods Term newborns with suspected seizures underwent standardized neurologic examinations to generate Thompson scores and had 12-hour bedside polysomnography with concurrent cerebral NIRS. For each infant, the distribution of sleep-wake stages and electroencephalogram delta power were computed. NIRS-derived fractional tissue oxygen extraction (FTOE) was calculated across sleep-wake stages. At age 18-22 months, surviving participants were evaluated with Bayley Scales of Infant Development (Bayley-III), 3rd edition. Results Twenty-nine participants completed Bayley-III. Increased newborn time in quiet sleep predicted worse 18-month cognitive and motor scores (robust regression models, adjusted r2 = 0.22, p = .007, and 0.27, .004, respectively). Decreased 0.5-2 Hz electroencephalograph (EEG) power during quiet sleep predicted worse 18-month language and motor scores (adjusted r2 = 0.25, p = .0005, and 0.33, .001, respectively). Predictive values remained significant after adjustment for neonatal Thompson scores or exposure to phenobarbital. Similarly, an attenuated difference in FTOE, between neonatal wakefulness and quiet sleep, predicted worse 18-month cognitive, language, and motor scores in adjusted analyses (each p < .05). Conclusions These prospective, longitudinal data suggest that inefficient neonatal sleep-as quantified by increased time in quiet sleep, lower electroencephalogram delta power during that stage, and muted differences in FTOE between quiet sleep and wakefulness-may improve prediction of adverse long-term outcomes for newborns with neurological dysfunction.