Comparison of Dreem to Clinical PSG for Sleep Monitoring in Apnea Patients
| Status: | Completed |
|---|---|
| Conditions: | Insomnia Sleep Studies, Insomnia Sleep Studies, Pulmonary |
| Therapuetic Areas: | Psychiatry / Psychology, Pulmonary / Respiratory Diseases |
| Healthy: | No |
| Age Range: | 18 - 70 |
| Updated: | 11/30/2018 |
| Start Date: | May 7, 2018 |
| End Date: | November 2, 2018 |
Performance of a Wireless Dry-EEG Device for Sleep Monitoring Compared to a Gold Standard Polysomnography in Patients With Suspected Sleep-Disordered Breathing
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.
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.
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.
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.
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)
We found this trial at
1
site
Redwood City, California 94063
Principal Investigator: Emmanuel H During, MD
Phone: 650-721-7552
Click here to add this to my saved trials
