11 resultados para sleep tracking

em University of Queensland eSpace - Australia


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Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.

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Experimental suppression of chaos has been achieved in an optically pumped far-infrared (NH3)-N-15 laser which displays Lorenz-like chaos. The method of control involves the application of a large amplitude slow (i.e., nonresonant) modulation of the pump power. This may be related to a delayed bifurcation to chaos observed when the pump power is ramped at a constant late.

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It is well established that insomniacs overestimate sleep-onset latency. Furthermore, there is evidence that brief arousals from sleep may occur more frequently in insomnia. This study examined the hypothesis that brief arousals from sleep influence the perception of sleep-onset latency. An average of four sleep onsets was obtained from each of 20 normal subjects on each of two nonconsecutive, counterbalanced, experimental nights. The experimental nights consisted of a control night (control condition) and a condition in which a moderate respiratory load was applied to increase the frequency of microarousals during sleep onset (mask condition). Subjective estimation of sleep-onset latency and indices of sleep quality were assessed by self-report inventory. Objective measures of sleep-onset latency and microarousals were assessed using polysomnography. Results showed that sleep-onset latency estimates were longer in the mask condition than in the control condition, an effect not reflected in objective sleep-stage scoring of sleep-onset latency. Furthermore, an increase in the frequency of brief arousals from sleep was detected in the mask condition, and this is a possible source for the sleep-onset latency increase perceived by the subjects. Findings are consistent with the concept of a physiological basis for sleep misperception in insomnia.

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The sensitivity and specificity of four self-report measures of disordered sleep - the Sleep Impairment Index (SII), the Sleep Disorders Questionnaire (SDQ), the Dysfunctional Beliefs and Attitudes About Sleep Scale (DBAS) and the Sleep-Wake Activity Inventory (SWAI) - were compared in subjects with insomnia and normal sleep. Nineteen young adult subjects met DSM-IV criteria for primary insomnia and another 19 were normal control subjects. Discriminatory characteristics of each measure were assessed using receiver operator characteristic curve analyses. Discriminatory power was maximised for each measure to produce cut-scores applicable for identification of individuals with insomnia. The DBAS, SII and SDQ psychiatric DIMS subscale were found to correlate, and discriminated well between the two groups. The SWAI nocturnal sleep subscale was not found to be an accurate discriminator. The results suggest differences in the measures in their ability to detect insomnia, and offer guidelines as to the optimal use of test scores to identify young adults suspected of insomnia.

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While there is a developing understanding of the influence of sleep on cardiovascular autonomic activity in humans, there remain unresolved issues. In particular, the effect of time within the sleep period, independent of sleep stage, has not been investigated. Further, the influence of sleep on central sympathetic nervous system (SNS) activity is uncertain because results using the major method applicable to humans, the low frequency (LF) component of heart rate Variability (HRV), have been contradictory, and because the method itself is open to criticism. Sleep and cardiac activity were measured in 14 young healthy subjects on three nights. Data was analysed in 2-min epochs. All epochs meeting specified criteria were identified, beginning 2 h before, until 7 h after, sleep onset. Epoch values were allocated to 30-min bins and during sleep were also classified into stage 2, slow wave sleep (SWS) and rapid eye movement (REM) sleep. The measures of cardiac activity were heart irate (HR), blood pressure (BP), high frequency (HF) and LF components of HRV and pre-ejection period (PEP). During non-rapid eye movement (NREM) sleep autonomic balance shifted from sympathetic to parasympathetic dominance, although this appeared to be more because of a shift in parasympathetic nervous system (PNS) activity. Autonomic balance during REM was in general similar to wakefulness. For BP and the HF and LF components the change occurred abruptly at sleep onset and was then constant over time within each stage of sleep, indicating that any change in autonomic balance over the sleep period is a consequence of the changing distribution of sleep stages. Two variables, HR and PEP, did show time effects reflecting a circadian influence over HR and perhaps time asleep affecting PEP. While both the LF component and PEP showed changes consistent with reduced sympathetic tone during sleep, their pattern of change over time differed.

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