Comparison of Dreem to Clinical PSG for Sleep Monitoring in Apnea Patients

Dreem

Status

Completed

Conditions

Sleep Apnea

Sleep

Treatments

Diagnostic Test: Dreem

Study type

Interventional

Funder types

Other

Industry

Identifiers

NCT03657329

OCTAVE Stanford

Details and patient eligibility

About

This study aims to evaluate the accuracy of apnea detection and automated sleep analysis by the Dreem dry-EEG headband and deep learning algorithm in comparison to the consensus of 5 sleep technologists' manual scoring of a gold-standard clinical polysomnogram (PSG) record in adults during a physician-referred overnight sleep study due to suspicion of sleep-disordered breathing.

Full description

The study will enroll up to 70 adults who are referred to the Stanford Sleep Medicine Center by their physician for an overnight polysomnographic sleep study due to suspicion of sleep-disordered breathing, with the aim of collecting 60 usable data sets (i.e., eligible subjects with high-quality PSG and Dreem recordings). Upon arrival to the clinic, patients provide informed consent, are interviewed to determine eligibility, and complete a detailed demographic, medical, health, sleep, and lifestyle questionnaire (Alliance Sleep Questionnaire; ASQ). After the ASQ, participants are fitted with the PSG and the Dreem headband by the sleep technologist. During the PSG sleep study, the Dreem headband records EEG, pulse, oxygen saturation (SO2), movement, and respiratory rate. Many participants may undergo a split-night study with a continuous positive airway pressure (CPAP) device during their participation, as deemed necessary by the clinical staff pursuant to the sleep study.

The PSG data from the first 30 eligible participants will be manually scored by 5 sleep technologists. These manually-scored PSG data files (referred to as the training dataset) will be synchronized with Dreem data files from the same night and the synchronized files will be used to train Dreem's deep learning algorithms. Following training, the algorithms will be deployed to automatically score the final 30 participants' Dreem datasets (testing dataset). Finally, PSG records for the second 30 participants will be provided to the sponsor and manually scored by 5 sleep technologists. The manual scoring results will be compared to the Dreem automatic analysis to determine the accuracy of Dreem's apnea-hypopnea index (AHI) severity detection and sleep staging algorithms.

Enrollment

67 patients

Sex

All

Ages

18 to 70 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

18-70 years of age
Capable of providing informed consent
Suspicion of sleep breathing disorder (both diagnostic and split-night studies)

Exclusion criteria

Concomitant diagnosis of a sleep disorder other than sleep apnea syndrome or insomnia
Morbid obesity (BMI > 39)
Use of benzodiazepines, nonbenzodiazepine (Z-drugs), or Gammahydroxybutyrate (GHB) the day/night of the study
Concomitant diagnosis of cardiopulmonary or neurological comorbidities (such as heart failure, COPD, neurodegenerative conditions)