This study aims to evaluate the agreement between automated sleep analysis by UNEEG medical's 24/7 EEG™ 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 EEG™ 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 UNEEG™ 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 UNEEG™ SubQ implanted and after approximately 10 days of healing the study subjects will start wearing the external part of the 24/7 EEG™ 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.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
25
24/7 EEG™ SubQ device will be worn by each subject for 365 nights
Zealand University Hospital
Roskilde, Denmark
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.
Time frame: 1 year
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.
Time frame: 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.
Time frame: 1 year
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