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| Name | Class |
|---|---|
| Zealand University Hospital | OTHER |
| Cambridge Cognition Ltd | INDUSTRY |
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This study aims to evaluate the agreement between automated sleep analysis by UNEEG medical's 24/7 EEGâ„¢ SubQ device using a deep learning algorithm and the consensus score of multiple sleep technologists' manual scoring of 120 gold-standard polysomnograms (PSG) from healthy subjects.
The aim of the study is to evaluate the agreement between automated sleep analysis by UNEEG medical's 24/7 EEGâ„¢ SubQ device using a deep learning algorithm and the consensus score of multiple sleep technologists' manual scoring of 120 gold-standard polysomnograms (PSG).
The study will enroll 20 healthy subjects who will wear the UNEEGâ„¢ SubQ device for 365 consecutive nights. All subjects are prescreened and invited to an interview to confirm eligibility. Subjects who provide informed consent are enrolled and will complete a detailed demographic, medical, health, sleep, and lifestyle survey. The enrolled subjects will have the UNEEGâ„¢ SubQ implanted and after approximately 10 days of healing the study subjects will start wearing the external part of the 24/7 EEGâ„¢ SubQ. Throughout the study the subjects will wear an ActiGraph, fill out a sleep diary and conduct cognitive tests. The duration of the study from screening to removal of sutures will be approximately 58 weeks.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Healthy adults | Experimental | UNEEGâ„¢ medical 24/7 EEGâ„¢ SubQ |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 24/7 EEGâ„¢ SubQ | Diagnostic Test | 24/7 EEGâ„¢ SubQ device will be worn by each subject for 365 nights |
|
| Measure | Description | Time Frame |
|---|---|---|
| Sleep stage agreement | Automatically determined sleep stages using data from 24/7 EEG SubQ, sleep stages manually determined according to the American Academy of Sleep Medicine (AASM) manual using the PSG recordings. The goal is to evaluate the performance of classification of AASM sleep stages at each 30-sec epoch determined automatically from the data recorded using the 24/7 EEG SubQ, to those determined by the consensus score (most prevalent score) of the sleep technologists' scoring of each subject's PSG record from the same night. | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Quantitative sleep parameters agreement | The quantitative sleep parameters recommended by the AASM manual. The goal is to evaluate the agreement between automatically determined clinically relevant parameters using data recorded from the 24/7 EEG SubQ and to those determined by the consensus score (most prevalent score) of the sleep technologists' scoring of each subject's PSG record from the same night. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Troels W Kjær, Professor | Zealand University Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Zealand University Hospital | Roskilde | 4000 | Denmark |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39406630 | Derived | Ahrens E, Jennum P, Duun-Henriksen J, Djurhuus B, Homoe P, Kjaer TW, Hemmsen MC. Automatic sleep staging based on 24/7 EEG SubQ (UNEEG medical) data displays strong agreement with polysomnography in healthy adults. Sleep Health. 2024 Dec;10(6):612-620. doi: 10.1016/j.sleh.2024.08.007. Epub 2024 Oct 15. |
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| Type | Date | Date Unknown |
|---|---|---|
| Release | Jan 28, 2025 | |
| Reset | Feb 14, 2025 | |
| Release | Apr 1, 2025 | |
| Reset | Apr 18, 2025 |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Jan 28, 2025 | Feb 14, 2025 | |||
| Apr 1, 2025 |
| ID | Term |
|---|---|
| D007319 | Sleep Initiation and Maintenance Disorders |
| ID | Term |
|---|---|
| D020919 | Sleep Disorders, Intrinsic |
| D020920 | Dyssomnias |
| D012893 | Sleep Wake Disorders |
| D009422 | Nervous System Diseases |
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| 1 year |
| Non-Inferiority in sleep/wake monitoring | Automatically determined sleep/wake epochs using data from 24/7 EEG SubQ, automatically determined sleep/wake epochs using ActiLife 6 and data from ActiGraph Link GT9X, sleep/wake epochs manually determined according to the AASM manual using the PSG recordings. The goal is to show non-inferiority of sleep/wake monitoring using 24/7 EEG SubQ in a head-to-head comparison with actigraphy using PSG as a reference and gold standard. | 1 year |
| Apr 18, 2025 |
| D001523 |
| Mental Disorders |