Case Study: Sleep Profiler EEG Sleep Monitor – Bridging the Gap in Sleep Analysis

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The Sleep Profiler EEG Sleep Monitor has revolutionised sleep diagnostics and research with its unparalleled precision and reliability. Globally recognised and extensively researched, Sleep Profiler is distinguished by its robust performance in over 125,000 sleep studies. It is not just a device but a comprehensive sleep analysis solution, providing in-depth insights into various sleep stages and conditions.

The Sleep Profiler offers a reliable and comprehensive solution for sleep analysis when compared to its competitors in the research market, and this article will highlight the depth of data offered by Advanced Brain Monitoring.

Single or multi-night analysis of Sleep Architecture using medical-grade equipment has never been easier.

Enhanced Signal Acquisition and Technology

Sleep Profiler’s technology is a leap forward in sleep analysis. Utilising three sophisticated channels (EEG, LEOG, and REOG) from strategically placed sensor sites, Sleep Profiler captures a wide array of sleep data with remarkable accuracy. This tri-channel system ensures a comprehensive capture of sleep patterns, setting a high standard in the industry. In contrast, a leading competitor device adopts a dual-channel approach, focusing on different sensor sites. This method, while innovative, differs from Sleep Profiler in terms of data richness and potential reliability, underlining the unique strengths of Sleep Profiler’s tri-channel system.

In real-world applications, particularly in in-home settings, Sleep Profiler demonstrates unmatched reliability. An Australian study[1] revealed a failure rate of only 1.7%, even under conditions where one or more of the  EEG channels had poor data. This is due to the device’s design, which enables reprocessing of the EEG data using the best available. This significantly reduces the likelihood of data loss or the need for study repetition. It was also shown to deliver consistently accurate data in SpO2 monitoring, essential for diagnosing OSA, with minimal instances of signal loss.

Advanced Accuracy, Reliability and Inter-study Consistency

Sleep Profiler’s innovative approach features real-time signal acquisition, quality alerts, which adds an extra layer of reliability in sleep studies. Its capacity to accurately autoscore the data has been validated against the gold standard of laboratory polysomnography[2], plus reduce interscorer variability[3,7,8]. This validation further demonstrates Sleep Profiler’s capability to provide reliable and clinically relevant data.

Sleep Profiler detects phasic REM using sensors placed superior to the canthus at Af7 and Af8 for precise REM detection, competitor technologies rely on different sensor placements, potentially affecting the accuracy of REM stage detection and AHI determination. This difference underscores the significance of sensor placement in sleep studies. While competitor devices may offer alternative approaches to sleep analysis, Sleep Profiler’s methodology and sensor placement are specifically designed for optimal accuracy and reliability[4].

The American Clinical Neurophysiological Society Guideline recommends a sampling rate three times the high-frequency filter setting [6]. Sleep Profiler is the only device available that meets this recommended sampling rate, and uses EMG, measured at the frontalis (forehead) at 250hz which is the minimum required to accurately analyse EMG. For example, 256hz is split into two, giving 128hz each channel.

The signals received from the frontalis (forehead) detecting sleep onset and transition to REM was found to be much stronger and more accurate than the signals received from the Submentalis (chin) [5].  Even when passed through a filter that all systems have, this still enables analysis in the range of 90hz where EMG is strongest.

Other available systems that analyse at 128hz, split to 79hz per channel, then lose ~30hz through the filter, therefore missing much of the data available from the EMG signal. It is important to note that the EMG power extracted from the EEG signal above 40hz is highly dependent on the sampling rate and anti-aliasing low-pass filter.

The Sleep Profiler EEG Sleep Monitor is backed by extensive research and clinical validation, making it an invaluable asset in both clinical and research settings. Its innovative design, advanced technology, and proven reliability not only set it apart from competitors but also highlight its role as a crucial tool in advancing sleep medicine.

*New* Sleep Profiler Real Time Analysis – ICU detection of Sepsis/Delirium

Sleep Profiler Real Time Analysis combines wireless transmission of the signals to a tablet with real-time sleep staging for the monitoring of sleep quality and abnormal EEG/EMG patterns in hospitalised patients, or for research applications – Sepsis, Delerium and Ventilator-induced Arousal.

Advanced Capabilities of the PSG2

The Sleep Profiler may spec’d or upgraded to the PSG2 to meet the needs of Type 2 unattended studies.

Advanced Accuracy and inter-study Consistency

Sleep Profiler’s/PSG2 innovative approach to oximetry includes an audible alert if the probe comes off, adding an extra layer of reliability in sleep studies. A 0% failure rate was observed during this study[1].

Its capacity to accurately autoscore the data, including the respiratory channels, has been validated against the gold standard of laboratory polysomnography[2]. Auto-scoring followed by human review saves time and costs, plus reduces interscorer variability[3,7,8]. This validation further demonstrates Sleep Profiler’s capability to provide reliable and clinically relevant data for clinical and research use.

The PSG2 is adept at detecting a range of sleep-disordered breathing conditions. Its capabilities include identifying apnoeas, hypopnoeas, and associated desaturations or arousals, differentiating between obstructive and central apneas, and assessing hypoxemia exposure during sleep. It also evaluates REM and positional influences on OSA severity, along with the frequency and intensity of positional snoring.

This 13-channel system incorporates a wide array of signals, including EEG, EOG, EMG, wireless oximetry, and various respiratory effort indicators. Additionally, it tracks forehead and finger pulse rates, head movement and position, and quantifies snoring, offering a comprehensive assessment of sleep patterns and abnormalities.

Real-time detection of poor airflow and oximetry signal quality, coupled with corrective voice alerts, contribute to an impressive 94% success rate for Type 2 studies.

Web-Based Analysis and Reporting

The PSG2 uses web-based software, providing recorded signal presentations with validated auto-staging and technical editing. This system significantly reduces scoring time and allows customisation of apnoea/hypopnoea indexes based on various criteria. The software facilitates the insertion of diagnostic and treatment recommendations, streamlining the reporting process.

Sleep Profiler PSG2 and Neurodegenerative Disease Detection 

The research team at ABM are currently using Sleep Profiler and PSG2 to embark on groundbreaking studies to identify and track markers that will detect early signs of a range of neurodegenerative diseases.


Further reading: 

Newly discovered sleep biomarkers pave the way for early detection of Parkinson’s disease, Alzheimer’s disease, Lewy body dementia, and other neurodegenerative diseases.

Comparison of Sleep and Wake EEG Biomarkers in Mild Cognitive Impairment

and Alzheimer’s Disease Dementia. 

Sleep Profiler Biomarkers for Characterisation of Neurodegenerative Disorders. 


  1. Agreement between auto-scored and edited unattended in-home polysomnography. Levendowski D, Dawson D, Levi M et al. Sleep Medicine 2017;40;89.
  2. Non-inferiority between the overall and REM-related apnea-hypopnea indexes obtained by polysomnography and a forehead worn, auto-scored system. Levendowski DJ, Henninger D, Smith J, et al. Sleep, 2016; 39:A380
  3. The accuracy, night-to-night variability, and stability of frontopolar sleep electroencephalography biomarkers. Levendowski DJ, Ferini-Strambi L, Gamaldo C, Cetel M, Rosenberg R, Westbrook PR. J Clin Sleep Med. 2017;13(6):791–803
  4. Sleep staging agreement between PSG and Sleep Profiler in isolated REM sleep behavior disorder. Levendowski DJ, Lee-Iannotti JK, Shprecher D, et al. Sleep Advances, 2021 2(1):45-46.
  5. Comparison of EMG power during sleep from the submental and frontalis muscles. Levendowski DJ, St. Louis, E, Ferini-Strambi L, et al. Nat Sci Sleep. 2018; 10:431-437.
  6. Guideline 8: Guidelines for recording clinical EG on digital media. Amer Clin Neurophys Soc, 2006.
  7. A comparison between auto-scored apnea-hypopnea index and oxygen desaturation index in the characterisation of positional obstructive sleep apnea. Levendowski DJ, Hamilton GS, St. Louis EK, et al. Nat Sci Sleep. 2019; 11;69-78.
  8. Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters. Stepnowsky C, Levendowski D, Popovic D, et al. Sleep Med. 2013; 14(11):1199-077.