Several studies have shown faster choice-reaction times to positive than to negative facial expressions. The present study examined whether this effect is exclusively due to faster cognitive processing of positive stimuli (i.e., processes leading up to, and including, response selection), or whether it also involves faster motor execution of the selected response. In two experiments, response selection (onset of the lateralized readiness potential, LRP) and response execution (LRP onset-response onset) times for positive (happy) and negative (disgusted/angry) faces were examined. Shorter response selection times for positive than for negative faces were found in both experiments but there was no difference in response execution times. Together, these results suggest that the happy-face advantage occurs primarily at premotoric processing stages. Implications that the happy-face advantage may reflect an interaction between emotional and cognitive factors are discussed.

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OBJECTIVES: To investigate how abdominal adiposity assessed by different anthropometric measurements and dualenergy X-ray absorptiometry measurements is associated with metabolic risk factors for cardiovascular disease and non-insulin-dependent diabetes mellitus in obese women. DESIGN: Cross-sectional study. SUBJECTS: Forty-three healthy, obese, middle-aged women (age: 29±64 y, BMI: 28±42 kg/m 2 ). MEASUREMENTS: (1) Anthropometry: waist circumference, waist-to-hip ratio, waist-to-height ratio, abdominal sagittal and transverse diameters and their ratio. (2) Dual-energy X-ray absorptiometry: the amount of total and regional abdominal fat. (3) Metabolic measurements: serum total, VLDL, LDL, HDL cholesterol, triglycerides, fasting and postglucose serum insulin and glucose. RESULTS: After adjustment for age and BMI, all the anthropometric measurements except waist-to-hip ratio and waist-to-height ratio related signi®cantly to HDL and LDL cholesterol. On the other hand, waist-to-hip ratio and waistto-height ratio showed an association with triglycerides. In addition, all the anthropometric measurements except transverse diameter correlated signi®cantly with fasting insulin and fasting glucose. Waist-to-hip ratio was the only measure that associated with 2 h glucose concentration. The differences between the correlation coef®cients were not statistically signi®cant in the z-transformed correlation coef®cient test.As to dual-energy X-ray absorptiometry results, the region from the dome of diaphragm to the top of femur (`abdominal fat') and the area between the ®rst and the fourth lumbal vertebrae (`upper lumbal fat') inversely related to HDL cholesterol and positively to triglycerides. Both of these regions correlated signi®cantly with fasting insulin, and`upper lumbal fat' associated also with fasting glucose even after adjustment for age and BMI. CONCLUSION: None of the anthropometric measurements (waist circumference, waist-to-hip ratio, waist-to-height ratio or sagittal diameter) was signi®cantly superior to others to assess the metabolic risk pro®le.`Upper lumbal fat' (the area between the ®rst and the fourth lumbal vertebrae) measured by dual-energy X-ray absorptiometry discerned obese women with elevated fasting insulin and fasting glucose.

Obstructive sleep apnea syndrome (OSAS) is a well-recognized disorder conventionally diagnosed with an elevated apnea–hypopnea index. Prolonged partial upper airway obstruction is a common phenotype of sleep-disordered breathing (SDB), which however is still largely underreported. The major reasons for this are that cyclic breathing pattern coupled with arousals and arterial oxyhemoglobin saturation are easy to detect and considered more important than prolonged episodes of increased respiratory effort with increased levels of carbon dioxide in the absence of cycling breathing pattern and repetitive arousals. There is also a growing body of evidence that prolonged partial obstruction is a clinically significant form of SDB, which is associated with symptoms and co-morbidities which may partially differ from those associated with OSAS. Partial upper airway obstruction is most prevalent in women, and it is treatable with the nasal continuous positive pressure device with good adherence to therapy. This review describes the characteristics of prolonged partial upper airway obstruction during sleep in terms of diagnostics, pathophysiology, clinical presentation, and comorbidity to improve recognition of this phenotype and its timely and appropriate treatment.

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The work considers automatic sleep stage classification, based on heart rate variability (HRV) analysis, with a focus on the distinction of wakefulness (WAKE) from sleep and rapid eye movement (REM) from non-REM (NREM) sleep. A set of 20 automatically annotated one-night polysomnographic recordings was considered, and artificial neural networks were selected for classification. For each inter-heartbeat (RR) series, beside features previously presented in literature, we introduced a set of four parameters related to signal regularity. RR series of three different lengths were considered (corresponding to 2, 6, and 10 successive epochs, 30 s each, in the same sleep stage). Two sets of only four features captured 99 % of the data variance in each classification problem, and both of them contained one of the new regularity features proposed. The accuracy of classification for REM versus NREM (68.4 %, 2 epochs; 83.8 %, 10 epochs) was higher than when distinguishing WAKE versus SLEEP (67.6 %, 2 epochs; 71.3 %, 10 epochs). Also, the reliability parameter (Cohens's Kappa) was higher (0.68 and 0.45, respectively). Sleep staging classification based on HRV was still less precise than other staging methods, employing a larger variety of signals collected during polysomnographic studies. However, cheap and unobtrusive HRV-only sleep classification proved sufficiently precise for a wide range of applications.

Objective: The EMFIT QS (Quantified Sleep) is an unobtrusive monitoring device with a state-of-theart analysis platform that tracks heart (HR) and respiration rate (RR), as well as heart rate variability, in addition to providing a sleep stage estimation and sleep quality analysis. The device consists of a thin ferroelectret sensor that can be placed underneath a bed mattress and sleep analysis can be overviewed conveniently from the EMFIT QS web interface. With this kind of sensitive and contactless sensor subject's vital signs can be easily monitored without discomfort. Approach: We compared the EMFIT QS HR and RR to those evaluated from the electrocardiogram (ECG) and respiratory inductive plethysmography (RIP) of 33 patients measured in an overnight polysomnography. The Bland-Altman analysis was used for comparison and ±6 heart beats per minute (bpm) and ±4 respiration cycles per minute (rpm) were considered to be acceptable differences. Main results: The 95% limits of agreement (LoA) for the heart rate are −4.4 (CI 95% : [−5.8, −4.2]) and 4.4 (CI 95% : [4.3, 5.9]) bpm, whereas the respiration rate LoA are −2.5 (CI 95% : [−2.8, −2.4]) and 2.2 (CI 95% : [2.1, 2.5]) rpm. Significance: The EMFIT QS measures reliably heart and respiration rate. It can be readily deployed for vital monitoring when a subject is lying in bed e.g. when tracking athletes' night-time recovery or consumers' well-being. It also has potential in telemedicine applications.