A New Era of Home Sleep Apnea Testing.

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WatchPAT®️ is an innovative Home Sleep Apnea Test (HSAT) that utilizes the peripheral arterial signal (PAT®️).  It measures up to 7 channels (PAT®️ signal, heart rate, oximetry, actigraphy, body position, snoring, and chest motion) via three points of contact. Within one minute post-study, the raw data is downloaded and auto-scored identifying all types of apnea events. WatchPAT®️ provides AHI, AHIc, RDI, and ODI based upon True Sleep Time and Sleep Staging. WatchPAT®️ is clinically validated with an 89% correlation to PSG1. The PAT signal was included in the 2017 AASM Clinical Practice Guidelines as technically adequate.

Key Features

True Sleep Time

True Sleep Time reduces the risk of misdiagnosis and misclassification that has been reported up to 20% with using total recording time2

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Sleep Architecture

WatchPAT’s clinically validated Sleep Architecture provides information on sleep staging including sleep efficiency, sleep latency and REM latency 3-4

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Central Sleep Apnea

The Central PLUS Module enables specific identification of Central Sleep Apnea (CSA) and Percent of Sleep Time with Cheyne-Stokes Respiration

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Accurate Auto Scoring

Comprehensive report is created in less than a minute

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Seven Channels

PAT, HR, Pulse-oximetry, Actigraphy, Body Position, Snoring, Chest Motion

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- Home Sleep Apnea Testing is evolving. How will it Look in the Near future? Read the Full Interview with Gilad Glick.

- Itamar®️ Medical and BetterNight to Join Forces Offering Referred Patients Home Based Virtual-Care Sleep Solution for the Diagnosis and Treatment of Sleep Apnea

- Itamar®️ Medical Implements Broad Range of Actions in Response to COVID-19 Pandemic

References on this page:

  1. Yalamanchali et al. JAMA Otolaryngnol Head Neck Surg, 2013, Diagnosis of Obstructive Sleep Apnea by Peripheral Arterial Tonometry (Meta-Analysis)
  2. Comparison of AHI using recording time versus sleep time Schutte – Rodin et al., J Sleep Abs supl 2014, p. A373
  3. Hedner J. et al. A Novel Adaptive Wrist Actigraphy Algorithm for Sleep-Wake Assessment in Sleep Apnea Patients. SLEEP, Vol. 27, No. 8, 2004 :1560-1566
  4. Hedner J. et al. Sleep Staging Based on Automimcal Signals: A Multi-Center Validation Study. JCSM. Journal of Sleep Medicine, Vol. 7, No. 3, 2011: 301 – 306