Validity of an algorithm for determining sleep/wake states using a new actigraph

Background

This study aimed to develop an algorithm for determining sleep/wake states by using chronological data on the amount of physical activity (activity intensity) measured with the FS-750 actigraph, a device that can be worn at the waist, allows for its data to be downloaded at home, and is suitable for use in both sleep research and remote sleep medicine.

Methods

Participants were 34 healthy young adults randomly assigned to two groups, A (n =17) and B (n =17), who underwent an 8-hour polysomnography (PSG) in the laboratory environment. Simultaneous activity data were obtained using the FS-750 attached at the front waist. Sleep/wake state and activity intensity were calculated every 2 minutes (1 epoch). To determine the central epoch of the sleep/wake states (x), a five-variable linear model was developed using the activity intensity of Group A for five epochs (x_-2, x_-1, x, x₊₁, x₊₂; 10 minutes). The optimal coefficients were calculated using discriminant analysis. The agreement rate of the developed algorithm was then retested with Group B, and its validity was examined.

Results

The overall agreement rates for group A and group B calculated using the sleep/wake score algorithm developed were 84.7% and 85.4%, respectively. Mean sensitivity (agreement rate for sleep state) was 88.3% and 90.0% and mean specificity (agreement rate for wakeful state) was 66.0% and 64.9%, respectively. These results confirmed comparable agreement rates between the two groups. Furthermore, when applying an estimation rule developed for the sleep parameters measured by the FS-750, no differences were found in the average values between the calculated scores and PSG results, and we also observed a correlation between the two sets of results. Thus, the validity of these evaluation indices based on measurements from the FS-750 is confirmed.

Conclusions

The developed algorithm could determine sleep/wake states from activity intensity data obtained with the FS-750 with sensitivity and specificity equivalent to that determined with conventional actigraphs. The FS-750, which is smaller, less expensive, and able to take measurements over longer periods than conventional devices, is a promising tool for advancing sleep studies at home and in remote sleep medicine.     

Automatic Detection of Whole Night Snoring Events Using Non-Contact Microphone

Objective

Although awareness of sleep disorders is increasing, limited information is available on whole night detection of snoring. Our study aimed to develop and validate a robust, high performance, and sensitive whole-night snore detector based on non-contact technology.

Design

Sounds during polysomnography (PSG) were recorded using a directional condenser microphone placed 1 m above the bed. An AdaBoost classifier was trained and validated on manually labeled snoring and non-snoring acoustic events.

Patients

Sixty-seven subjects (age 52.5±13.5 years, BMI 30.8±4.7 kg/m², m/f 40/27) referred for PSG for obstructive sleep apnea diagnoses were prospectively and consecutively recruited. Twenty-five subjects were used for the design study; the validation study was blindly performed on the remaining forty-two subjects.

Measurements and Results

To train the proposed sound detector, >76,600 acoustic episodes collected in the design study were manually classified by three scorers into snore and non-snore episodes (e.g., bedding noise, coughing, environmental). A feature selection process was applied to select the most discriminative features extracted from time and spectral domains. The average snore/non-snore detection rate (accuracy) for the design group was 98.4% based on a ten-fold cross-validation technique. When tested on the validation group, the average detection rate was 98.2% with sensitivity of 98.0% (snore as a snore) and specificity of 98.3% (noise as noise).

Conclusions

Audio-based features extracted from time and spectral domains can accurately discriminate between snore and non-snore acoustic events. This audio analysis approach enables detection and analysis of snoring sounds from a full night in order to produce quantified measures for objective follow-up of patients.     

A validation study of Fitbit Charge 2™ compared with polysomnography in adults

We evaluated the performance of a consumer multi-sensory wristband (Fitbit Charge 2?), against polysomnography (PSG) in measuring sleep/wake state and sleep stage composition in healthy adults.

In-lab PSG and Fitbit Charge 2? data were obtained from a single overnight recording at the SRI Human Sleep Research Laboratory in 44 adults (19—61 years; 26 women; 25 Caucasian). Participants were screened to be free from mental and medical conditions. Presence of sleep disorders was evaluated with clinical PSG. PSG findings indicated periodic limb movement of sleep (PLMS, > 15/h) in nine participants, who were analyzed separately from the main group (n = 35). PSG and Fitbit Charge 2? sleep data were compared using paired t-tests, Bland–Altman plots, and epoch-by-epoch (EBE) analysis.

In the main group, Fitbit Charge 2? showed 0.96 sensitivity (accuracy to detect sleep), 0.61 specificity (accuracy to detect wake), 0.81 accuracy in detecting N1+N2 sleep (“light sleep”), 0.49 accuracy in detecting N3 sleep (“deep sleep”), and 0.74 accuracy in detecting rapid-eye-movement (REM) sleep. Fitbit Charge 2? significantly (p < 0.05) overestimated PSG TST by 9 min, N1+N2 sleep by 34 min, and underestimated PSG SOL by 4 min and N3 sleep by 24 min. PSG and Fitbit Charge 2? outcomes did not differ for WASO and time spent in REM sleep. No more than two participants fell outside the Bland–Altman agreement limits for all sleep measures. Fitbit Charge 2? correctly identified 82% of PSG-defined non-REM–REM sleep cycles across the night. Similar outcomes were found for the PLMS group.

Fitbit Charge 2? shows promise in detecting sleep-wake states and sleep stage composition relative to gold standard PSG, particularly in the estimation of REM sleep, but with limitations in N3 detection. Fitbit Charge 2? accuracy and reliability need to be further investigated in different settings (at-home, multiple nights) and in different populations in which sleep composition is known to vary (adolescents, elderly, patients with sleep disorders).     

Assessing Sleep Disturbance in Low Back Pain: The Validity of Portable Instruments

Although portable instruments have been used in the assessment of sleep disturbance for patients with low back pain (LBP), the accuracy of the instruments in detecting sleep/wake episodes for this population is unknown. This study investigated the criterion validity of two portable instruments (Armband and Actiwatch) for assessing sleep disturbance in patients with LBP. 50 patients with LBP performed simultaneous overnight sleep recordings in a university sleep laboratory. All 50 participants were assessed by Polysomnography (PSG) and the Armband and a subgroup of 33 participants wore an Actiwatch. Criterion validity was determined by calculating epoch-by-epoch agreement, sensitivity, specificity and prevalence and bias- adjusted kappa (PABAK) for sleep versus wake between each instrument and PSG. The relationship between PSG and the two instruments was assessed using intraclass correlation coefficients (ICC 2, 1). The study participants showed symptoms of sub-threshold insomnia (mean ISI = 13.2, 95% CI = 6.36) and poor sleep quality (mean PSQI = 9.20, 95% CI = 4.27). Observed agreement with PSG was 85% and 88% for the Armband and Actiwatch. Sensitivity was 0.90 for both instruments and specificity was 0.54 and 0.67 and PABAK of 0.69 and 0.77 for the Armband and Actiwatch respectively. The ICC (95%CI) was 0.76 (0.61 to 0.86) and 0.80 (0.46 to 0.92) for total sleep time, 0.52 (0.29 to 0.70) and 0.55 (0.14 to 0.77) for sleep efficiency, 0.64 (0.45 to 0.78) and 0.52 (0.23 to 0.73) for wake after sleep onset and 0.13 (−0.15 to 0.39) and 0.33 (−0.05 to 0.63) for sleep onset latency, for the Armband and Actiwatch, respectively. The findings showed that both instruments have varied criterion validity across the sleep parameters from excellent validity for measures of total sleep time, good validity for measures of sleep efficiency and wake after onset to poor validity for sleep onset latency.     

Untreated Sleep-Disordered Breathing: Links to Aging-Related Decline in Sleep-Dependent Memory Consolidation

Background

Increasing age is associated with a decline in cognition and motor skills, while at the same time exacerbating one''s risk of developing obstructive sleep apnea (OSA). OSA-related cognitive deficits are highly prevalent and can affect various memory systems including overnight memory consolidation on a motor sequence task.Thus, the aim of our study was to examine the effect of aging on sleep-dependent motor memory consolidation in patients with and without OSA.

Methods

We studied 44 patients (19–68 years) who had been referred by a physician for a baseline polysomnography (PSG) evaluation. Based on their PSG, patients were assigned either to the OSA group (AHI>5/h), or control (Non-OSA) group (AHI<5/h).All subjects performed the Psychomotor Vigilance Task (PVT) and the Motor Sequence Learning Task (MST) in the evening and again in the morning after their PSG.

Results

Despite similar learning in the evening, OSA subjects showed significantly less overnight improvement on the MST, both for immediate (OSA −2.7%±2.8% vs. controls 12.2%±3.5%; p = 0.002) and plateau improvement (OSA 4.9%±2.3% vs. controls 21.1%±4.0%; p = 0.001). Within the OSA group, there was a significant negative correlation between overnight MST improvement and age (r² = 0.3; p = 0.01), an effect that was not observed in the Non-OSA group (r² = 0.08; p = 0.23)

Conclusions

Consistent with previous research, healthy sleepers demonstrated a higher degree of sleep-dependent overnight improvement on the MST, an effect not mitigated by increasing age. However, the presence of untreated obstructive sleep apnea is associated with an aging-related cognitive deficit, otherwise not present in individuals without OSA. As other research has linked the presence of OSA to a higher likelihood of developing dementia, future studies are necessary to examine if the inhibition of memory consolidation is tied to the onset of neurodegenerative disease.     

Gender Differences in Polysomnographic Sleep in Young Healthy Sleepers

Middle‐aged and elderly populations exhibit gender differences in polysomnographic (PSG) sleep; however, whether young men and women also show such differences remains unclear. Thirty‐one young healthy sleepers (16 men and 15 women, aged 18 to 30 yr, mean±SD, 20.5±2.4 yr) completed 3 consecutive overnight sessions in a sleep laboratory, after maintaining a stable sleep‐wake cycle for 1 wk before study entry. Standard PSG sleep and self‐rated sleepiness data were collected each night. Across nights, women showed better sleep quality than men: they fell asleep faster (shorter sleep onset latency) and had better sleep efficiency, with more time asleep and less time awake (all differences showed large effect sizes, d=0.98 to 1.12). By contrast, men were sleepier than women across nights. Both men and women demonstrated poorer overall sleep quality on the first night compared with the subsequent 2 nights of study. We conclude young adult healthy sleepers show robust gender differences in PSG sleep, like older populations, with better sleep quality in women than in men. These results highlight the importance of gender in sleep and circadian rhythm research studies employing young subjects and have broader implications for women's health issues relating to these topics.     

A novel machine learning unsupervised algorithm for sleep/wake identification using actigraphy

ABSTRACT

Actigraphy is widely used in sleep studies but lacks a universal unsupervised algorithm for sleep/wake identification. An unsupervised algorithm is useful in large-scale population studies and in cases where polysomnography (PSG) is unavailable, as it does not require sleep outcome labels to train the model but utilizes information solely contained in actigraphy to learn sleep and wake characteristics and separate the two states. In this study, we proposed a machine learning unsupervised algorithm based on the Hidden Markov Model (HMM) for sleep/wake identification. The proposed algorithm is also an individualized approach that takes into account individual variabilities and analyzes each individual actigraphy profile separately to infer sleep and wake states. We used Actiwatch and PSG data from 43 individuals in the Multi-Ethnic Study of Atherosclerosis study to evaluate the method performance. Epoch-by-epoch comparisons and sleep variable comparisons were made between our algorithm, the unsupervised algorithm embedded in the Actiwatch software (AS), and the pre-trained supervised UCSD algorithm. Using PSG as the reference, the accuracy was 85.7% for HMM, 84.7% for AS, and 85.0% for UCSD. The sensitivity was 99.3%, 99.7%, and 98.9% for HMM, AS, and UCSD, respectively, and the specificity was 36.4%, 30.0%, and 31.7%, respectively. The Kappa statistic was 0.446 for HMM, 0.399 for AS, and 0.311 for UCSD, suggesting fair to moderate agreement between PSG and actigraphy. The Bland–Altman plots further show that the total sleep time, sleep latency, and sleep efficiency estimates by HMM were closer to PSG with narrower 95% limits of agreement than AS and UCSD. All three methods tend to overestimate sleep and underestimate wake compared to PSG. Our HMM approach is also able to differentiate relatively active and sedentary individuals by quantifying variabilities in activity counts: individuals with higher estimated activity variabilities tend to show more frequent sedentary behaviors. Our unsupervised data-driven HMM algorithm achieved better performance than the commonly used Actiwatch software algorithm and the pre-trained UCSD algorithm. HMM can help expand the application of actigraphy in cases where PSG is hard to acquire and supervised methods cannot be trained. In addition, the estimated HMM parameters can characterize individual activity patterns and sedentary tendencies that can be further utilized in downstream analysis.     

Sleep/wake estimation using only anterior tibialis electromyography data

ABSTRACT: BACKGROUND: In sleep efficiency monitoring system, actigraphy is the simplest and most commonly used device. However, low specificity to wakefulness of actigraphy was revealed in previous studies. In this study, we assumed that sleep/wake estimation using actigraphy and electromyography (EMG) signals would show different patterns. Furthermore, each EMG pattern in two states (sleep, wake during sleep) was analysed. Finally, we proposed two types of method for the estimation of sleep/wake patterns using only EMG signals from anterior tibialis muscles and the results were compared with PSG data. METHODS: Seven healthy subjects and five patients (2 obstructive sleep apnea, 3 periodic limb movement disorder) participated in this study. Night time polysomnography (PSG) recordings were conducted, and electrooculogram, EMG, electroencephalogram, electrocardiogram, and respiration data were collected. Time domain analysis and frequency domain analysis were applied to estimate the sleep/wake patterns. Each method was based on changes in amplitude or spectrum (total power) of anterior tibialis electromyography signals during the transition from the sleep state to the wake state. To obtain the results, leave-one-out-cross-validation technique was adopted. RESULTS: Total sleep time of the each group was about 8 hours. For healthy subjects, the mean epoch-by-epoch results between time domain analysis and PSG data were 99%, 71%, 80% and 0.64 (sensitivity, specificity, accuracy and kappa value), respectively. For frequency domain analysis, the corresponding values were 99%, 73%, 81% and 0.67, respectively. Absolute and relative differences between sleep efficiency index from PSG and our methods were 0.8 and 0.8% (for frequency domain analysis). In patients with sleep-related disorder, our proposed methods revealed the substantial agreement (kappa > 0.61) for OSA patients and moderate or fair agreement for PLMD patients. CONCLUSIONS: The results of our proposed methods were comparable to those of PSG. The time and frequency domain analyses showed the similar sleep/wake estimation performance.     

Effects of Aging on Genioglossus Motor Units in Humans

The genioglossus is a major upper airway dilator muscle thought to be important in obstructive sleep apnea pathogenesis. Aging is a risk factor for obstructive sleep apnea although the mechanisms are unclear and the effects of aging on motor unit remodeled in the genioglossus remains unknown. To assess possible changes associated with aging we compared quantitative parameters related to motor unit potential morphology derived from EMG signals in a sample of older (n = 11; >55 years) versus younger (n = 29; <55 years) adults. All data were recorded during quiet breathing with the subjects awake. Diagnostic sleep studies (Apnea Hypopnea Index) confirmed the presence or absence of obstructive sleep apnea. Genioglossus EMG signals were analyzed offline by automated software (DQEMG), which estimated a MUP template from each extracted motor unit potential train (MUPT) for both the selective concentric needle and concentric needle macro (CNMACRO) recorded EMG signals. 2074 MUPTs from 40 subjects (mean±95% CI; older AHI 19.6±9.9 events/hr versus younger AHI 30.1±6.1 events/hr) were extracted. MUPs detected in older adults were 32% longer in duration (14.7±0.5 ms versus 11.1±0.2 ms; P  =  0.05), with similar amplitudes (395.2±25.1 µV versus 394.6±13.7 µV). Amplitudes of CNMACRO MUPs detected in older adults were larger by 22% (62.7±6.5 µV versus 51.3±3.0 µV; P<0.05), with areas 24% larger (160.6±18.6 µV.ms versus 130.0±7.4 µV.ms; P<0.05) than those detected in younger adults. These results confirm that remodeled motor units are present in the genioglossus muscle of individuals above 55 years, which may have implications for OSA pathogenesis and aging related upper airway collapsibility.     

Effects of Neuromuscular Electrical Stimulation on the Masticatory Muscles and Physiologic Sleep Variables in Adults with Cerebral Palsy: A Novel Therapeutic Approach

Cerebral palsy (CP) is a term employed to define a group of non-progressive neuromotor disorders caused by damage to the immature or developing brain, with consequent limitations regarding movement and posture. CP may impair orapharygeal muscle tone, leading to a compromised chewing function and to sleep disorders (such as obstructive sleep apnea). Thirteen adults with CP underwent bilateral masseter and temporalis neuromuscular electrical stimulation (NMES) therapy. The effects on the masticatory muscles and sleep variables were evaluated using electromyography (EMG) and polysomnography (PSG), respectively, prior and after 2 months of NMES. EMG consisted of 3 tests in different positions: rest, mouth opening and maximum clenching effort (MCE). EMG values in the rest position were 100% higher than values recorded prior to therapy for all muscles analyzed (p < 0.05); mean mouth opening increased from 38.0 ± 8.0 to 44.0 ± 10.0 cm (p = 0.03). A significant difference in MCE was found only for the right masseter. PSG revealed an improved in the AHI from 7.2±7.0/h to 2.3±1.5/h (p < 0.05); total sleep time improved from 185 min to 250 min (p = 0.04) and minimun SaO2 improved from 83.6 ± 3.0 to 86.4 ± 4.0 (p = 0.04). NMES performed over a two-month period led to improvements in the electrical activity of the masticatory muscles at rest, mouth opening, isometric contraction and sleep variables, including the elimination of obstructive sleep apnea events in patients with CP.

Trial Registration

ReBEC RBR994XFS http://www.ensaiosclinicos.gov.br     

Sleeping under the Ocean: Despite Total Isolation,Nuclear Submariners Maintain Their Sleep and Wake Patterns throughout Their Under Sea Mission

BackgroundTo assess the effects of isolation, inadequate exposure to light and specific shift work on the subjective and objective measurements of sleep and alertness of submariners.PurposeA strictly controlled randomized crossover study with the polysomnography recorded twice during the mission.MethodsSetting: Shift and night work with prolonged (70 days) social isolation from the real world (with no phone or Internet contact with families or friends during a routine mission aboard the “Téméraire” French Strategic Submarine with Ballistic Nuclear missiles (SSBN). Participants: 19 submariners working on a 24-hour shift for three days in a row schedule. Interventions: The participants attended two polysomnographic (PSG) recordings of night sleep on Day 21 (D21) and Day 51 (D51) of the 70-day patrol; urine cortisol levels were also taken after sleep, and subjective assessments of sleep, sleepiness, mood and anxiety on D21 and D51. The light and temperature on board were also recorded.ResultsPSG analyses showed that sleep did not significantly vary in length (total sleep time) or in quality between D21 and D51. The mariners reported the same subjective sleep, sleepiness, anxiety or mood (except for a slightly worse score for confusion on D51). Blood cortisol levels did not vary significantly.ConclusionsThese results show that humans living in an isolated environment for more than two months with this specific shift schedule do not suffer from any significant effects on sleep, sleepiness and confusion between D21 and D51, when they follow an organized regular shift pattern with controlled light and temperature.     

Effect of Acute Intermittent CPAP Depressurization during Sleep in Obese Patients

Background

Obstructive Sleep Apnea (OSA) describes intermittent collapse of the airway during sleep, for which continuous positive airway pressure (CPAP) is often prescribed for treatment. Prior studies suggest that discontinuation of CPAP leads to a gradual, rather than immediate return of baseline severity of OSA. The objective of this study was to determine the extent of OSA recurrence during short intervals of CPAP depressurization during sleep.

Methods

Nine obese (BMI = 40.4 ± 3.5) subjects with severe OSA (AHI = 88.9 ± 6.8) adherent to CPAP were studied during one night in the sleep laboratory. Nasal CPAP was delivered at therapeutic (11.1 ± 0.6 cm H₂0) or atmospheric pressure, in alternating fashion for 1-hour periods during the night. We compared sleep architecture and metrics of OSA during CPAP-on and CPAP-off periods.

Results

8/9 subjects tolerated CPAP withdrawal. The average AHI during CPAP-on and CPAP-off periods was 3.6 ± 0.6 and 15.8 ± 3.6 respectively (p<0.05). The average 3% ODI during CPAP-on and CPAP-off was 4.7 ± 2 and 20.4 ± 4.7 respectively (p<0.05). CPAP depressurization also induced more awake (p<0.05) and stage N1 (p<0.01) sleep, and less stage REM (p<0.05) with a trend towards decreased stage N3 (p = 0.064).

Conclusion

Acute intermittent depressurization of CPAP during sleep led to deterioration of sleep architecture but only partial re-emergence of OSA. These observations suggest carryover effects of CPAP.     

Thiol/disulfide homeostasis impaired in patients with primary Sjögren's syndrome

BackgroundPrimary Sjögren''s syndrome (pSS) is a disease associated with the overexpression of proinflammatory cytokines, and oxidative stress is one of the factors responsible for its etiopathogenesis. This study aimed to investigate the thiol/disulphide homeostasis in pSS patients.MethodsThe study included 68 pSS patients and 69 healthy controls. Thiol/disulphide homeostasis (total thiol, native thiol, and disulphide levels) was measured using the automatic spectrophotometric method developed by Erel and Neselioglu, and the results of the 2 groups were compared.ResultsThe gender and age distributions of the pSS and control groups were similar (P = 0.988 and P = 0.065). Total thiol and native thiol levels were lower in the pSS group than in the control group (470.08 ± 33.65 µmol/L vs. 528.21 ± 44.99 µmol/L, P < 0.001, and 439.14 ± 30.67 µmol/L vs. 497.56 ± 46.70 µmol/L, P < 0.001, respectively). There were no differences in disulphide levels between groups [17.00 (range 0.70-217.0) µmol/L vs. 14.95 (range 2.10-40.10) µmol/L, P = 0.195].ConclusionsIt was concluded that the thiol/disulphide balance shifted towards disulphide in patients with pSS.     

Arterial Pressure Variation as a Biomarker of Preload Dependency in Spontaneously Breathing Subjects – A Proof of Principle

Objective

Pulse (PPV) and systolic pressure variation (SPV) quantify variations in arterial pressure related to heart-lung interactions and have been introduced as biomarkers of preload dependency to guide fluid treatment in mechanically ventilated patients. However, respiratory intra-thoracic pressure changes during spontaneous breathing are considered too small to affect preload and stroke volume sufficiently for the detection by PPV and/or SPV. This study addressed the effects of paced breathing and/or an external respiratory resistance on PPV and SPV in detecting preload dependency in spontaneously breathing subjects.

Methods

In 10 healthy subjects, hemodynamic and respiratory parameters were evaluated during progressive central hypovolemia (head-up tilt). Breathing conditions were varied by manipulating breathing frequency and respiratory resistance. Subjects responding with a reduction in stroke volume index ≥15% were classified as having developed preload dependency. The ability for PPV and SPV to predict preload dependency was expressed by the area under the ROC curve (AUC).

Results

A breathing frequency at 6/min increased the PPV (16±5% vs. 10±3%, p<0.001) and SPV (9±3% vs. 5±2%, p<0.001) which was further enhanced by an expiratory resistance (PPV: 19±3%, p = 0.025 and SPV: 10±2%, p = 0.047). These respiratory modifications, compared to free breathing, enhanced the predictive value of PPV with higher accuracy (AUC: 0.92 vs. 0.46).

Conclusion

Under conditions of progressive central hypovolemia, the application of an external respiratory resistance at a breathing frequency of 6/min enhanced PPV and SPV and is worth further study for detection of preload dependency from arterial pressure variations in non-ventilated subjects.     

Comparison of two different actigraphs with polysomnography in healthy young subjects

The present study aimed to compare two commercially available actigraphs, with a concurrent polysomnographic (PSG) recording. Twelve healthy volunteers (six women; age range 19-28 yrs) simultaneously wore the Basic Mini-Motionlogger^® and Actiwatch^® for seven overnight polysomnographic recordings. Comparisons of the following sleep measures were focused on: sleep onset latency (SOL), total sleep time, wake after sleep onset, and sleep efficiency. Both devices underestimated SOL in comparison to PSG, but they had similar performance compared to PSG for the other sleep measures. A limit of the study is that the results can be only generalized to healthy young subjects.     

Sleep quality in adult patients with sleep related bruxism

Sleep related bruxism (SB) is the grinding of teeth during sleep and may also be associated with various sleep disorders. However, little is known about sleep structures and disturbances of SB. This study aims to further understand sleep architectures using overnight polysomnography (PSG) in patients with SB. We analyze sleep parameters and architectures in 33 healthy subjects and 25 patients with SB. PSG and sleep questionnaires measured sleep variables including proportions of rapid eye movement (REM) sleep, non-REM sleep (N1, N2 and N3), latency to sleep onset, sleep efficiency, wake after sleep onset (WASO), apnea hypopnea index (AHI), respiratory disturbance index (RDI), and periodic limb movement index (PLMI) during sleep for both groups. Sleep efficiency and the proportion of N3 in the SB group were significantly lower than in the control group (P < 0.05). In addition latency to onset of sleep and WASO were markedly increased in the SB group (P < 0.05). AHI, RDI, and PLMI showed no differences between the groups. Epworth Sleepiness Scale was significantly higher in the SB group than in the control group (P < 0.05). In contrast to previous studies, we conclude that patients with SB are not good sleepers based on PSG study. Further studies are required to assess the relationship between sleep quality and the severity of SB.

     

CHANGES IN PHYSIOLOGICAL TREMOR RESULTING FROM SLEEP DEPRIVATION UNDER CONDITIONS OF INCREASING FATIGUE DURING PROLONGED MILITARY TRAINING

The aim of the study was to define the changes of the characteristics of physiological postural tremor under conditions of increasing fatigue and lack of sleep during prolonged military training (survival). The subjects of the study were 15 students of the Polish Air Force Academy in Dęblin. The average age was 19.9±1.3 years. During the 36-hour-long continuous military training (survival) the subjects were deprived of sleep. Four tremor measurements were carried out for each of the subjects: Day 1 – morning, after rest (measurement 0); Day 2 – morning, after overnight physical exercise (measurement 1); afternoon, after continuous sleep deprivation (measurement 2); Day 3 – morning, after a full night sleep (measurement 3). The accelerometric method using an acceleration measuring kit was applied to analyse tremor. A significant difference between mean values of the index evaluating tremor power in low frequencies L_2-4 in measurement 0 and measurement 3 was observed (p<0.01). No significant differences were found in mean values of index L_10-20. Mean frequencies F_2-4 differed significantly from each other (F_2,42=4.53; p<0.01). Their values were 2.94±0.11, 2.99±0.9, 2.93±0.07 and 2.91±0.07 for successive measurements. A gradual, significant decrease of F_8-14 was observed (F_2,42=5.143; p<0.01). Prolonged sleep deprivation combined with performing tasks demanding constant physical effort causes long-lasting (over 24 hours) changes of the amplitude of low-frequency tremor changes. This phenomenon may significantly influence psychomotor performance, deteriorating the ability to perform tasks requiring movement precision.     

Effects of Slow Deep Breathing at High Altitude on Oxygen Saturation,Pulmonary and Systemic Hemodynamics

Slow deep breathing improves blood oxygenation (Sp_O2) and affects hemodynamics in hypoxic patients. We investigated the ventilatory and hemodynamic effects of slow deep breathing in normal subjects at high altitude. We collected data in healthy lowlanders staying either at 4559 m for 2–3 days (Study A; N = 39) or at 5400 m for 12–16 days (Study B; N = 28). Study variables, including Sp_O2 and systemic and pulmonary arterial pressure, were assessed before, during and after 15 minutes of breathing at 6 breaths/min. At the end of slow breathing, an increase in Sp_O2 (Study A: from 80.2±7.7% to 89.5±8.2%; Study B: from 81.0±4.2% to 88.6±4.5; both p<0.001) and significant reductions in systemic and pulmonary arterial pressure occurred. This was associated with increased tidal volume and no changes in minute ventilation or pulmonary CO diffusion. Slow deep breathing improves ventilation efficiency for oxygen as shown by blood oxygenation increase, and it reduces systemic and pulmonary blood pressure at high altitude but does not change pulmonary gas diffusion.     

Human sleep‐wake cycles in the high arctic: Effects of unusual photoperiodicity in a natural setting

Abstract

Studies of human circadian rhythms are typically conducted in artificial environments that are low in ecological validity. In the current study, six subjects and the field director lived in temporal isolation in a completely natural environment with constant daylight (a high Arctic research camp) for six weeks. Detailed daily sleep logs were kept. In keeping with past findings, five of the six subjects developed a free‐running sleep‐wake cycle longer than 24 hours. Unlike past results, the isolated subjects did not exhibit any synchronicity in their rhythms. There was a high degree of intersubject variability in circadian patterns. The findings have important implications for the comparison of the results of laboratory and field investigations of sleep‐wake cycles.     

Gender differences in polysomnographic sleep in young healthy sleepers

Middle-aged and elderly populations exhibit gender differences in polysomnographic (PSG) sleep; however, whether young men and women also show such differences remains unclear. Thirty-one young healthy sleepers (16 men and 15 women, aged 18 to 30 yr, mean+/-SD, 20.5+/-2.4 yr) completed 3 consecutive overnight sessions in a sleep laboratory, after maintaining a stable sleep-wake cycle for 1 wk before study entry. Standard PSG sleep and self-rated sleepiness data were collected each night. Across nights, women showed better sleep quality than men: they fell asleep faster (shorter sleep onset latency) and had better sleep efficiency, with more time asleep and less time awake (all differences showed large effect sizes, d=0.98 to 1.12). By contrast, men were sleepier than women across nights. Both men and women demonstrated poorer overall sleep quality on the first night compared with the subsequent 2 nights of study. We conclude young adult healthy sleepers show robust gender differences in PSG sleep, like older populations, with better sleep quality in women than in men. These results highlight the importance of gender in sleep and circadian rhythm research studies employing young subjects and have broader implications for women's health issues relating to these topics.