4 resultados para FFT

em Brock University, Canada


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The EEG of the sleep onset period of psychophysiological insomniacs, psychiatric insomniacs and controls was compared using power spectral analysis (FFT). Eighteen drug-free subjects were equally divided into three groups according to their responses in the Brock Sleep and Insomnia Questionnaire, the Minnesota Multiphasic Personality Inventory and the Sleep Disorders Questionnaire. Group 1 consisted of psychophysiological insomniacs, group 2 included insomniacs with an indication of psychiatric disturbances, and group 3 was a control group. EEG, EOG and EMG were recorded for two consecutive nights. Power spectral analysis (FFT) of EEG at C4 from the sleep onset period (defined as lights out to the first five minutes of stage 2) was performed on all standard frequency bands, delta: .5-4 Hz; theta: 4-8 Hz; alpha: 8-12 Hz; sigma: 12-15 Hz beta: 15-25 Hz. Psychophysiological insomniacs had less alpha during wakefulness than the other two groups and did not show the dramatic drop in alpha across the sleep onset period, which characterizes normal sleep. They also had less delta, especially during stage 2 on night 2. They also showed less delta in the last quartile of the chronological analysis of the sleep onset period. Psychiatric insomniacs showed lower relative beta power values overall while psychophysiological insomniacs showed higher relative beta power values during wakefulness. This microanalysis 11 confirms that the sleep onset period is generally similar for psychiatric insomniacs and normal sleepers. This may be due to the sample of psychiatric insomniacs being heterogeneous or may reflect a sleep onset system that is essentially intact. Psychophysiological insomniacs have higher cortical arousal during the sleep onset period than do the psychiatric insomniacs and the controls. Clear differences in the sleep onset period of psychophysiological insomniacs exist. The dramatic changes in power values in these two groups are not seen in the psychophysiological insomniacs, which may make the discrimination between wakefulness and sleep more difficult.

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The main purpose ofthis study was to examine the effect ofintention on the sleep onset process from an electrophysiological point ofview. To test this, two nap conditions, the Multiple Sleep Latency Test (MSLT) and the Repeated Test of Sustained Wakefulness (RTSW) were used to compare intentional and inadvertent sleep onset. Sixteen female participants (aged 19-25) spent two non-consecutive nights in the sleep lab; however, due to physical and technical difficulties only 8 participants produced compete sets of data for analysis. Each night participants were given six nap opportunities. For three ofthese naps they were instructed to fall asleep (MSLT), for the remaining three naps they were to attempt to remain awake (RTSW). These two types of nap opportunities represented the conditions ofintentional (MSLT) and inadvertent (RTSW) sleep onset. Several other sleepiness, performance, arousal and questionnaire measures were obtained to evaluate and/or control for demand characteristics, subjective effort and mental activity during the nap tests. The nap opportunities were scored using a new 9 stage scoring system developed by Hori et al. (1994). Power spectral analyses (FFT) were also performed on the sleep onset data provided by the two nap conditions. Longer sleep onset latencies (approximately 1.25 minutes) were obseIVed in the RTSW than the MSLT. A higher incidence of structured mental activity was reported in the RTSW and may have been reflected in higher Beta power during the RTSW. The decent into sleep was more ragged in the RTSW as evidenced by an increased number shifts towards higher arousal as measured using the Hori 9 stage sleep scoring method. 1ll The sleep onset process also appears to be altered by the intention to remain awake, at least until the point ofinitial Stage 2 sleep (i.e. the first appearance of spindle activity). When only examining the final 4.3 minutes ofthe sleep onset process (ending with spindle activity), there were significant interactions between the type ofnap and the time until sleep onset for Theta, Alpha and Beta power. That is to say, the pattern of spectral power measurements in these bands differed across time as a function ofthe type ofnap. The effect ofintention however, was quite small (,,2 < .04) when compared to the variance which could be accounted for by the passage oftime (,,2 == .10 to .59). These data indicate that intention alone cannot greatly extend voluntary wakefulness if a person is sleepy. This has serious implications for people who may be required to perform dangerous tasks while sleepy, particularly for people who are in a situation that does not allow them the opportunity to engage in behavioural strategies in order to maintain their arousal.

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Several recent studies have described the period of impaired alertness and performance known as sleep inertia that occurs upon awakening from a full night of sleep. They report that sleep inertia dissipates in a saturating exponential manner, the exact time course being task dependent, but generally persisting for one to two hours. A number of factors, including sleep architecture, sleep depth and circadian variables are also thought to affect the duration and intensity. The present study sought to replicate their findings for subjective alertness and reaction time and also to examine electrophysiological changes through the use of event-related potentials (ERPs). Secondly, several sleep parameters were examined for potential effects on the initial intensity of sleep inertia. Ten participants spent two consecutive nights and subsequent mornings in the sleep lab. Sleep architecture was recorded for a fiiU nocturnal episode of sleep based on participants' habitual sleep patterns. Subjective alertness and performance was measured for a 90-minute period after awakening. Alertness was measured every five minutes using the Stanford Sleepiness Scale (SSS) and a visual analogue scale (VAS) of sleepiness. An auditory tone also served as the target stimulus for an oddball task designed to examine the NlOO and P300 components ofthe ERP waveform. The five-minute oddball task was presented at 15-minute intervals over the initial 90-minutes after awakening to obtain six measures of average RT and amplitude and latency for NlOO and P300. Standard polysomnographic recording were used to obtain digital EEG and describe the night of sleep. Power spectral analyses (FFT) were used to calculate slow wave activity (SWA) as a measure of sleep depth for the whole night, 90-minutes before awakening and five minutes before awakening.

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The present study has both theoretical and practical aspects. The theoretical intent of the study was to closely examine the relationship between muscle activity (EMG) and EEG state during the process of falling asleep. Sleep stages during sleep onset (SO) have been generally defined with regards to brain wave activity (Recht schaff en & Kales (1968); and more precisely by Hori, Hayashi, & Morikawa (1994)). However, no previous study has attempted to quantify the changes in muscle activity during this same process. The practical aspect of the study examined the reliability ofa commercially developed wrist-worn alerting device (NovAlert™) that utilizes changes in muscle activity/tension in order to alert its user in the event that he/she experiences reduced wakefulness that may result in dangerous consequences. Twelve female participants (aged 18-42) sp-ent three consecutive nights in the sleep lab ("Adaptation", "EMG", and "NOVA" nights). Each night participants were given 5, twenty-minute nap opportunities. On the EMG night, participants were allowed to fall asleep freely. On the NOV A night, participants wore the Nov Alert™ wrist device that administered a Psychomotor Vigilance Test (PVT) when it detected that muscle activity levels had dropped below baseline. Nap sessions were scored using Hori's 9-stage scoring system (Hori et aI, 1994). Power spectral analyses (FFT) were also performed. Effects ofthe PVT administration on EMG and EEG frequencies were also examined. Both chin and wrist EMG activity showed reliable and significant decline during the early stages ofHori staging (stages HO to H3 characterized by decreases in alpha activity). All frequency bands studied went through significant changes as the participants progressed through each ofHori's 9 SO stages. Delta, theta, and sigma activity increased later in the SO continuum while a clear alpha dominance shift was noted as alpha activity shifted from the posterior regions of the brain (during Hori stages HO to H3) to the anterior portions (during Hori stages H7 to H9). Administration of the PVT produced significant increases in EMG activity and was effective in reversing subjective drowsiness experienced during the later stages of sleep onset. Limitations of the alerting effects of the PVTs were evident following 60 to 75 minutes of use in that PVTs delivered afterwards were no longer able to significantly increase EMG levels. The present study provides a clearer picture of the changes in EMG and EEG during the sleep onset period while testing the efficacy of a commercially developed alerting device. EMG decreases were found to begin during Hori stage 0 when EEG was - dominated by alpha wave activity and were maximal as Hori stages 2 to 5 were traversed (coincident with alpha and beta activity). This signifies that EMG decrements and the loss of resting alpha activity are closely related. Since decreased alpha has long been associated with drowsiness and impending sleep, this investigation links drops in muscle tone with sleepiness more directly than in previous investigations. The EMG changes were reliably demonstrated across participants and the NovAlert™ detected the EMG decrements when Hori stage 3 was entered. The alerting vibrations produced by the NovAlert™ occurred early enough in the SO process to be of practical importance as a sleepiness monitoring and alerting device.