Measuring sleep: The squiggles explained! (Part 2)

By Karyn O'Keeffe 07/04/2011

In a previous post, I provided an overview of the stages of human sleep.  But how do we determine what stage of sleep a person is in?

The current gold standard for objectively measuring sleep is called polysomnography or PSG. This mouthful is derived from the Greek poly meaning ‘many’, somnus meaning ‘sleep’ and graphein meaning ‘to write’.  Polysomnography allows us to record a wide range of physiologic signals during a sleep period.  At the simplest level, we will record signals that allow us to stage human sleep, but in addition we often measure signals such as heart rate, breathing (effort and airflow), muscle movement, oxygen saturation, carbon dioxide levels and behaviour (via video input).  Each recorded signal requires a sensor, or several sensors, often making this quite an overwhelming experience for a patient or research participant.

To be able to determine the stage of human sleep, we need to simultaneously measure three particular signals; electroencephalogram (EEG; brain waves), electrooculogram (EOG; eye movements) and electromyogram (EMG; chin muscle tone).  These measurements are taken via Grass gold cup electrodes (although silver chloride may also be used) filled with a conductive paste or gel. To be able to accurately stage sleep, each electrode needs to be placed at a particular site. For example, the EEG is applied according to the International 10-20 electrode placement system.  After the recording is completed, a trained Sleep Physiologist (also known as a Sleep Technologist or Sleep Scientist) visually examines each 30 second epoch of the EEG, EOG, EMG signals, and applies a sleep stage following international rules for sleep staging [1, 2].  This is an incredibly time consuming process that requires a reasonable level of skill.  Unfortunately, no computer can yet accurately see what a Physiologist can with their own eyes.

There are advantages and disadvantages to quantifying sleep in this way.  The discussion is too big for this post but in essence, sleep has been measured this way for most of its (fairly) short existence as a science.  Continuing to do so allows us to put any new research in context.  However, applying static sleep stages in this manner does not take into account the continuous nature of sleep and in addition, brief changes in sleep status are lost with our current method.  Many researchers are now looking at additional ways of analysing brain activity during sleep and I hope to share some of these with you in later posts.


  1. Iber, C., Ancoli-Israel, S., Chesson, A., & Quan, S. F. (Eds.). (2007). The AASM manual for the scoring of sleep and associated events: Rules, terminology and technical specifications (1st ed.). Westchester, IL: American Academy of Sleep Medicine.
  2. Rechtschaffen, A., & Kales, A. (Eds.). (1968). A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. Los Angeles, CA: Brain Information Service/Brain Research Institute, University of California.

0 Responses to “Measuring sleep: The squiggles explained! (Part 2)”

  • Karyn, the following may be of interest to you. I stumbled across it last week when I was searching for something else. It was originally published in Nature, but here is a pre-print.

    “Self-organized criticality occurs in non-conservative neuronal networks during Up states”