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A hypnogram is a form of Polysomnography. It is a graph that represents the stages of sleep as a function of time. It was devolved as an easy way to present the recordings of the brain wave activity from an electroencephalogram (EEG) during a period of sleep. It allows the different stages of sleep: rapid eye movement sleep (REM) and non-rapid eye movement sleep (REM) to be identified during the sleep cycle. NREM sleep can be further classified into 3 sub sections: NREM stage 1, 2 and 3. The previously considered 4th stage of NREM sleep has now been included within stage 3; this stage is also called Slow wave sleep (SWS) and is the deepest stage of sleep. [1] Each of the 3 NREM stages as well as the period of REM sleep and the awake state can be determined and displayed on hypnogram.

Example hypnogram for a normal, healthy adult. Within the first hour of sleep SWS is diplayed. Cycles of REM and NREM sleep proceed. During the third cycle of sleep there are 2 breif wake states. During the second half of the sleep period more REM sleep is displayed and there is litle SWS is detected
Example hypnogram of a normal, healthy adult

Method

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Hypnograms are usually obtained by visually scoring the recordings from EEGs, EOGs and EMGs [2] . The output from these three sources is recorded simultaneously on a graph by a monitor or computer. The collection of this large amount of information is contained and displayed on a hypnogram. Certain frequencies displayed by EEGs, EOGs and EMGs are characteristic and determine what stage of sleep or wake the subject is in. There is a defined protocol for sleep scoring as defined by the American Academy of Sleep Medicine (AASM), whereby the sleep or wake state is recorded in 30 second epochs. [3] Prior to this the Rechtschaffen and Kales (RK) rules were used, which used set definitions to classify each stage of sleep. [4]

Output

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Normal Sleep

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Cycles of REM and non REM stages make up sleep. A normal healthy adult requires between 7-9 hours of sleep a night. The number of hours of sleep is variable, however the proportion of sleep spent in a particular stage remains mostly consistent; for example healthy adults normally spend around 20-25% of their sleep in REM sleep. During rest following a sleep deprived state, there is a period of rebound sleep which has longer and deeper episodes of SWS to make up for the lack of sleep.

As shown on a hypnogram, one sleep cycle is usually around 90 minutes long and 4-6 sleep cycles occur during a major period of sleep. The first one or two cycles are the ones in which the most SWS occurs so this is the deepest period of sleep. The second half of the sleeping period contains most REM sleep and little or no SWS and may contain brief periods of wakefulness which can be recorded but are not usually perceived. [5] The stage that occurs before waking is normally REM sleep. [6]

A standard hypnogram for a healthy person will vary slightly according to their age, emotional state as well as other environmental factors.

Disrupted sleep

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Sleep architecture can be evaluated using hypnograms, so irregular sleeping patterns associated with sleep disorders can also be seen on hypnograms. Disruptions or irregularities to the normal sleep cycle or sleep stage transitions can be detected; for example a hypnogram can show that in obstructive sleep apnea (OSA) the stability of transition beteen REM and NREM stages are disrupted. [7]

The effects of certain medication on sleep architecture can be visualised on a hypnogram. For example the Anticonvulsant Phenytoin (PHT) can be seen to disrupt sleep by increasing the duration of NREM stage 1 and decreasing the duration of SWS; whereas the drug Gabapentin is seen to revive sleep by increasing the duration of SWS. [8]

Analysis

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The main use of a hypnogram is as a qualitative method to visualise the time period of each stage of sleep, as well as the number of transitions between stages. Hypnograms are rarely used to provide quantitative data, however it has been suggested that statistical evaluation can be carried out using multistate survival analysis and log-linear models to provide numerical significance. [9]

Limitations

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The restrictions of measuring sleep at short 30 second epochs, limits the ability to record short events, so occurrences shorter than 30 seconds are ignored. Due to this only the macrostructure of sleep can be evaluated and the microstructure is not seen; the process of sleep is smoothened out in such a way that it would not naturally occur in. Also some specific features of sleep such as sleep spindles and K complexes may not be defined in the hypnogram; this is particularly true for sleep scoring that is automated. [10]

The method of obtaining the data used in a hypnogram is restricted to the input from an EEG, EOG and EMG. The interval of recording may include features from several stages, in which case it is recorded as the stage whose features occupy the recording for the longest duration. For this reason, the stage of sleep may be misrepresented on the hypnogram.

Future Development

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There is a drive to improve the automated output of hypnograms to provide more reliable and accurate results. Suggestions include using increasing the measures of sleep, for example by additionally measuring sleep with an electrocardiogram (ECG). [11] Another advancement involves comibining hypnograms with Color Density Spectral Arrays to improve the quality of sleep analysis. [12]

References

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  1. ^ Silber MH; Ancoli-Israel S; Bonnet MH; Chokroverty S; Grigg-Damberger MM; Hirshkowitz M; Kapen S; Keenan (2007). "The visual scoring of sleep in adults". Journal of Clinical Sleep Medicine. 3 (2): 121–131.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  2. ^ Cabiddu R,Cerutti S,Werner S,Viardot G,Bianchi AM (2012). "Modulation of the sympatho-vagal balance during sleep". Frontiers in Physiology. 3. doi:10.3389/fphys.2012.00045.{{cite journal}}: CS1 maint: multiple names: authors list (link) CS1 maint: unflagged free DOI (link)
  3. ^ McGrogan N, Braithwaite E, Tarassenko L (2001). "Biosleep: A comprehensive sleep analysis system". Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE. 2: 1608–1611. doi:10.1109/IEMBS.2001.1020520.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  4. ^ Danker-Hopfe H, Anderer P, Zeitlhofer J, Boeck M, Dorn H; et al. (2009). "Interrater reliability for sleep scoring according to the Rechtschaffen & Kales and the new AASM standard". Journal of Sleep Research. 18 (1): 74–84. doi:10.1111/j.1365-2869.2008.00700.x. {{cite journal}}: Explicit use of et al. in: |author= (help)CS1 maint: multiple names: authors list (link)
  5. ^ Lee-Chiong TL (2009). Sleep Medicine Essentials. Wiley-Blackwell. pp. 2–3.
  6. ^ Merica H, Fortune RD (2004). "State transitions between wake and sleep, and within the ultradian cycle, with focus on the link to neuronal activity". Sleep Medicine Reviews. 8: 473–485. doi:10.1016/j.smrv.2004.06.006. {{cite journal}}: line feed character in |title= at position 46 (help)
  7. ^ Bianchi MT, Cash SS, Mietus J, Peng C-K, Thomas R (2010). "Obstructive Sleep Apnea Alters Sleep Stage Transition Dynamics". PLoS ONE. 5 (6). doi:10.1371/journal.pone.0011356.{{cite journal}}: CS1 maint: multiple names: authors list (link) CS1 maint: unflagged free DOI (link)
  8. ^ Legros B, Bazil CW (2003). "Effects of antiepileptic drugs on sleep architecture: apilotstudy". Sleep Medicine. 4 (1): 51–55. doi:10.1016/s1389-9457(02)00217-4.
  9. ^ Swihart B, Caffo B, Bandeen-Roche K, Punjai N (2008). "Characterizing Sleep Structure Using the Hypnogram". Journal of Clinical Sleep Medicine. 4: 349–355.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  10. ^ Barcaro U, Navona C, (1998). "A simple method for the quantitative description of sleep microstructure". Electroencephalography and Clinical Neurophysiology. 106 (5): 429–432. doi:10.1016/S0013-4694(98)00008-X. {{cite journal}}: Text "Belloli S, Bonanni E, Gneri C, Murri L" ignored (help)CS1 maint: extra punctuation (link) CS1 maint: multiple names: authors list (link)
  11. ^ Krakovská A, Mezeiová K (2011). "Automatic sleep scoring: A search for an optimal combination of measures". Artificial Intelligence in Medicine. 3 (1): 25–33. doi:10.1016/j.artmed.2011.06.004.
  12. ^ Pracki1 T, Pracka1 D, Ziółkowska-Kochan M, Tafil-Klawe1 M, Szota A, Wiłkość M (2008). "The modified Color Density Spectral Array- an alternative method for sleep presentation". Acta Neurobiol Exp (Wars). 68 (4): 516–518.{{cite journal}}: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link)
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