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 Table of Contents  
Year : 2022  |  Volume : 24  |  Issue : 2  |  Page : 109-112

Evolution of Polysomnography

1 Department of Psychiatry, INS Angre, Mumbai, Maharashtra, India
2 Department of Medicine, AHR&R, New Delhi, India
3 PMO, INS Angre, Mumbai, Maharashtra, India
4 Department of Respiratory Medicine, CMRI and BM Birla hospital, Kolkata, West Bengal, India

Date of Submission05-Aug-2022
Date of Decision12-Aug-2022
Date of Acceptance20-Aug-2022
Date of Web Publication07-Sep-2022

Correspondence Address:
Surg Cdr (Dr) Priyadarshee Patra
INS Angre, SBS Marg, Mumbai - 400 001, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jmms.jmms_128_22

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How to cite this article:
Patra P, Singhal A, Singh V, Krishnan S. Evolution of Polysomnography. J Mar Med Soc 2022;24:109-12

How to cite this URL:
Patra P, Singhal A, Singh V, Krishnan S. Evolution of Polysomnography. J Mar Med Soc [serial online] 2022 [cited 2023 Apr 2];24:109-12. Available from: https://www.marinemedicalsociety.in/text.asp?2022/24/2/109/355697

  The History of Polysomnography Top

Hans Berger is considered to be the father of electroencephalography (EEG). He made his first recordings using a device called the string galvanometer in 1924.[1] He suspended a reed between electromagnets using a string so that the oscillations could expose a light-sensitive material. With this device, he was able to record fluctuating potential differences/EEG activity. He found that when an individual remained relaxed but wakeful, an 8–13-cycle/s waveform appeared. He named this rhythm “alpha” but many referred to it as the “Berger's wave.” Another finding was that when a person fell asleep, the alpha rhythm disappeared. Even after a century later, we define sleep onset by determining the point at which alpha EEG activity reduces. This conceptually marked the beginning of what would evolve into polysomnography (PSG). The string galvanometer was not suited for recordings over long time periods. A one-channel EEG machine was developed by Gibbs and Garceau by utilising the Weston Union Morse Code inkwriting undulator. Soon a three-channel EEG machine was developed by Albert Grass while working on earthquake seismographs. The popularity of EEG greatly increased after 1938 in both clinical practice and research. Scientists working on neurological disorders and mental illness were discovering newer waveforms. They described the periods of low-amplitude mixed-frequency activity alternating with high-amplitude slow waves by studying the sleep EEG. Gibbs and Gibbs discovered that during sleep EEG revealed mostly symmetrical waveforms during sleep, except during the low-voltage, mixed-frequency episodes.[2] The first report from continuous, all-night studies of human sleep was published in 1937.[3] Loomis, along with Harvey and Hobart described alpha waves, low voltage, spindles, “random,” and spindles plus random sleep state sequences. In 1953, a study was published by Aserinsky and Kleitman, showing that the sleep stage associated with low-voltage, mixed-frequency activity was associated with dreaming and rapid eye movement (REM).[4] Jouvet found that during REM sleep muscle tone was lost.[5] Newer discoveries and advancement in technology led to the development of electrooculogram, multichannel recording of EEG, and sometimes electromyogram (EMG) for studying sleep. Simultaneous recording of other parameters such as electrodermal activity, respiration, and cardiac rhythm led the way toward what we now call PSG. Once REM sleep was discovered, the sleep researchers realized that the Loomis system was not adequate to study the sleep architecture, continuity and integrity. Hence the creation of new scoring rules and definitions started. A new system to classify sleep as per EEG criteria was developed by Dement and Kleitman.[6] A time domain or “epoch” of the set duration was established and the dominant activity within that timeframe-dictated classification. According to EEG characteristics, this epoch, was classified as sleep Stage 1, 2, 3, or 4 or awake. REM sleep stage was described when REMs occurred during Stage 1 sleep. However, standardization was lacking in the various sleep laboratories. The major militaries of the time; US and USSR among other, were studying the effects of sleep deprivation on physical ability, cognition, behavior, and attention. They were also studying sleep's homeostatic regulation by examining the sleep stage rebound secondary to selective sleep stage deprivation.

  Development of Sleep Tests Top

Multiple sleep latency test

Carskadon and Dement[7] conducted an experiment involving 90-min sleep–wake schedule and then described multiple sleep latency changes across the day. Over each 24-h period, the subjects had 16 opportunities to fall asleep as they underwent PSG recordings of baseline, sleep deprivation, and recovery periods. The instruction to them was “try to fall asleep,” “lie quietly and close your eyes.” These PSG later helped form procedures used in multiple sleep latency test (MSLT). Daytime sleep latency findings for narcolepsy and controls was published by Richardson et al.[8] Studies on acute sleep deprivation and chronic sleep restriction validated sleep latency as a biomarker for sleepiness.[9],[10] Soon MSLT became an essential part of sleep medicine and research mostly as it could objectively measure sleepiness and confirm narcolepsy. In 1986, MSLT guidelines were published in the journal sleep.[11]

Maintenance of wakefulness test

Sleep researchers were also studying the difficulty in remaining awake in soporific circumstances. The maintenance of wakefulness test was developed by Mitler et al.[12] His procedures were similar to those of MSLT except that his instruction to the subjects were “try to remain awake.”

  Clinical Polysomnography Top

Robert L. Williams conducted an experiment where he would make all-night sleep recordings in normal, healthy male and female children, adolescents, teenagers, young adults, adults, and seniors. Later these findings were in The EEG of Human Sleep.[13] By then it was known that in adults, REM sleep did not occur until after approximately 70–100 min of non-REM sleep and also that REM sleep rarely occurred during daytime naps. In patients with narcolepsy, PSG verified REM sleep occurring on or near sleep onset both during nocturnal sleep studies and during daytime naps.[14] This finding established a PSG diagnostic marker. PSG was also found to be useful in differentiating nocturnal seizure and parasomnias. Newer research revealed that that patients with major depressive disorders had shorter than normal REM sleep latencies.[15] Sleep-related erection monitoring helped differentiate men suffering from organic versus psychological erectile dysfunction.[16] Periodic leg movement activity became apparent and its potential for disturbing sleep understood. PSG also helped in understanding sleep pathophysiologies such as cessation of breathing with arousals, oxyhemoglobin desaturations, or both. Soon sleep apnea syndromes were indisputably verified.[17] Clinical PSG also led to discovery of new sleep disorders; for example, REM sleep behavior disorder.[18] PSG provided an objective method to assess insomnia. While this approach ultimately was deemed impractical except under specific circumstances.[19] PSG was now being used to study the effect of various drugs in sleep.[20]

  Rise of Sleep Laboratories Top

As clinical PSG became popular, sleep disorders centers began to open. Most of the clinical PSG was utilized for ruling-in or ruling-out sleep-disordered breathing, especially sleep apnea.

  Computerization Top

PSG was a time-consuming process. Even after 6–8 h of recording, analysis could require another couple of hours. Advancement in technology like the advent of minicomputers and signal processing techniques in 1970 led to automation of sleep analysis. However, there were teething problems to the completely digital analytic approach, especially in the form of: Artifacts, event detection, and technological limitations.

Polysomnography artefacts

An artifact is an electrical signal arising from activity other than that under study and may masquerade as potentially valid data. PSGs usually contain artefact. Artifacts tend to contaminate the data and hence compromise analysis. Common biological artefacts include blinking and eye movements masquerading as EEG waveforms, movement, and EMG activity contaminating EEG signals with high-frequency components, and heartbeat intruding into other bioelectric tracings. Other biological EEG artifacts include sweating, twitching, coughing, teeth clinching or grinding, and shivering, etc. Common environmental artifacts include electrode popping, alternating current (50 or 60 cycles/s) interference, and any other electrical signal like a pacemaker).

Event detection

Electrophysiological data are broken down by signal processing techniques into its frequency components that are then expressed as duration or power. However, specific event detection requires analysis of feature or envelop. Furthermore, some of these waveforms which defined sleep stages, have overlapping frequency signatures. Available laboratory computers then had far less capacity than today's powerful microprocessors.

Technological limitations

Processing speed, storage space, available computer analytics, etc., were the rate limiting steps. With passage of time, each innovation added power, speed, and storage capacity.

  Rise of Powerful Microcomputers Top

Microcomputer was common in laboratories by the mid-1970s. They were game changers as they were much cheaper and took fraction of the space as compared to the computers then.

By early 1990s, microcomputer systems reach adequate power at a low enough cost to become marketable. It became necessary to modernise software, video graphics, and having larger capability storage devices. Scaling data were a big advantage when reviewing digital PSGs. Some systems evolved to allow split screen display with different resolution for selected channel.

  Advent of Home Sleep Testing Top

The next game changer was the rise of home sleep testing (HST). It involved overnight recordings of airflow, respiratory effort, oxyhemoglobin saturation level, heart rate, and sometimes snoring sounds and EEG. Its only validated use is to verify the presence of sleep apnea[21] but HST can rule-in but not rule-out sleep apnea. Hence, only patients who are at risk of sleep apnea (based on sign, symptoms, and comorbidities) should be tested.

  Indications for Polysomnography Top

The following clinical indications for PSG are based on the guidelines published by the American Academy of Sleep Medicine (AASM):[22] (a) diagnosis of sleep-related breathing disorders (SRBD); (b) positive airway pressure titration; (c) preoperative assessment for snoring or obstructive sleep apnea (OSA); (d) evaluating results of treatment for moderate-to-severe OSA with oral appliances, surgery, or dental procedures; (e) treatment results requiring follow-up PSG for substantial weight gain or loss; (f) treatment results when clinical response is insufficient or when symptoms return; (g) patients with systolic or diastolic heart failure and nocturnal symptoms of SRBD; (h) patients whose symptoms continue despite optimal management of congestive heart failure; (i) neuromuscular disorders with sleep-related symptoms; (j) narcolepsy (for which PSG is followed by the MSLT); (k) periodic limb movement disorder in cases secondary to complaints by the patient or observer. According to the AASM, PSG is not required to diagnose (a) parasomnias; (b) seizure disorders; (c) restless legs syndrome; (d) common, uncomplicated noninjurious events such as nightmares, enuresis, sleep-talking or bruxism; (e) circadian rhythm disorders. PSG is also being used for diagnosing and treating patients with complicated forms of SRBD requiring the use of advanced positive airway pressure that deliver nocturnal noninvasive ventilation as PSG provides information regarding the patient's physiological responses to therapy during all phases of titration.

  Polysomnography versus Home Sleep Apnoea Test Top

There are basically four types of sleep monitors. They are classified as Type I–IV where PSG is a Type I sleep monitor is for in-laboratory testing, and Type II–IV sleep monitors are for home testing home sleep apnea test (HSAT).[23] A Type II portable monitor (PM) is a full unattended portable PSG with seven or more channels. A Type III monitors have 4–7 channels. A Type IV monitors have 1–2 channels with one of them being oximetry. Level 1 sleep testing is PSG. It requires an overnight stay in a sleep laboratory with a technician in attendance. It usually captures 16 or more channels of data (minimum 7 channels) including respiratory, cardiovascular, and neurologic parameters. Level 1 sleep testing is considered the reference standard for diagnosing all types of sleep disorders and sleep-disordered breathing.[24],[25],[26] Level 2 sleep is similar to level 1 equipment but does not have a technician in attendance. Level 3 sleep testing is done at the patient's home or elsewhere as it uses PMs. It is a much cheaper and accessible alternative to in-laboratory PSG. Level 3 sleep tests captures at least 3 channels of data (e.g., oximetry, airflow, and respiratory effort). However, unlike level 1, it cannot measure the duration of sleep, the number of arousals or sleep stages, and nonrespiratory sleep disorders.[27] Level 4 devices captures usually only 1 or 2 channels.[28] They too are portable and relatively inexpensive. The current AASM guideline recommends performing a confirmatory PSG in patients with negative HSAT. The guideline allows the use PSG or HSAT with a technically adequate device in uncomplicated patents with moderate to high risk of OSA and only PSG for those with significant comorbidities.[29]

  Summary Top

PSG is a complex procedure and requires a great amount of training to master. PSG yields a plethora of information that is not available by other form of sleep testing. Not only does PSG helps us understand the physiology of sleep but also it offers diagnostic options for multitude of illnesses such as narcolepsy, movement disorders, sleep disordered breathing, seizure disorders, medication effects on sleep, parasomnias, and other disorders that are not detectable during a person's waking hours.

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Conflicts of interest

There are no conflicts of interest.

  References Top

Berger H. Ueber das electroenkephalogramm des menschen. J Psychol Neurol 1930;40:160-79.  Back to cited text no. 1
Frederic A, Gibbs Erna L. Atlas Of electroencephalography 1. Methodology and normal controls. Cambridge: Addison-Wesley; 1950.  Back to cited text no. 2
Loomis AL, Harvey N, Hobart GA. Cerebral states during sleep, as studied by human brain potentials. J Exp Psychol 1937;21:127-44.  Back to cited text no. 3
Aserinsky E, Kleitman N. Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. Science 1953;118:273-4.  Back to cited text no. 4
Jouvet M, Michel F. Nerve Pathways responsible for rapid activity during physiological sleep in cats (paradoxical phase). CR Soc Biol. 1960:154-995-8.  Back to cited text no. 5
Dement W, Kleitman N. Cyclic variation in EEG during sleep and their relation to eye movements, body motility, and dreaming. Clin Neurophysiol 1957;9:673-90.  Back to cited text no. 6
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Richardson GS, Carskadon MA, Flagg W, Van den Hoed J, Dement WC, Mitler MM. Excessive daytime sleepiness in man: Multiple sleep latency measurement in narcoleptic and control subjects. Electroencephalogr Clin Neurophysiol 1978;45:621-7.  Back to cited text no. 8
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Carskadon MA, Dement WC, Mitler MM, Roth T, Westbrook PR, Keenan S. Guidelines for the multiple sleep latency test (MSLT): A standard measure of sleepiness. Sleep 1986;9:519-24.  Back to cited text no. 11
Mitler MM, Gujavarty KS, Browman CP. Maintenance of wakefulness test: A polysomnographic technique for evaluation treatment efficacy in patients with excessive somnolence. Electroencephalogr Clin Neurophysiol 1982;53:658-61.  Back to cited text no. 12
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Guilleminault C, Dement WC. Sleep Apnea Syndromes (The Kroc Foundation Series: V 11). New York: AR Liss; 1978.  Back to cited text no. 17
Schenck CH, Bundlie SR, Ettinger MG, Mahowald MW. Chronic behavioral disorders of human REM sleep: A new category of parasomnia. Sleep 1986;9:293-308.  Back to cited text no. 18
Littner M, Hirshkowitz M, Kramer M, Kapen S, Anderson WM, Bailey D, et al. Practice parameters for using polysomnography to evaluate insomnia: An update. Sleep 2003;26:754-60.  Back to cited text no. 19
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Hirshkowitz M, Sharafkhaneh A. Comparison of portable monitoring with laboratory polysomnography for diagnosing sleeprelated breathing disorders: Scoring and interpretation. Sleep Med Clin 2011;6:283-92.  Back to cited text no. 21
Kushida CA, Littner MR, Morgenthaler T, Alessi CA, Bailey D, Coleman J Jr., et al. Practice parameters for the indications for polysomnography and related procedures: An update for 2005. Sleep 2005;28:499-521.  Back to cited text no. 22
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The History of P...
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