A wearable EEG device: LANMAO Sleep Recorder compared to polysomnography in terms of EEG recording and sleep analysis

BackgroundPolysomnography (PSG) is the gold standard for sleep monitoring and diagnosis, yet it is difficult to use in home environments. This study evaluated the performance of a wearable electroencephalographic (EEG) device, LANMAO Sleep Recorder in EEG recording and sleep staging algorithm by comparing with PSG. MethodSleep of 7 Chinese adults were recorded concurrently with PSG and LANMAO devices. First, we validated the consistency of the raw signals with relative spectral power and Pearson correlation coefficient. Second, we evaluated the performance of the automated sleep staging algorithm integrated in the LANMAO device by comparing with the staging by experts. ResultsThe Pearson correlation coefficient between the relative spectral power of multiple frequency bands during the sleep stages ranged from 0.7613 to 0.8816, with the strongest correlation observed for delta waves (r=0.8816). The overall F1-Score of the automated sleep staging algorithm was 84.03%, with individual F1-Scores for each class as follows: Wake: 93.67%, REM: 87.23%, Light Sleep: 72.10%, and Deep Sleep: 82.82%. ConclusionThe results suggest that the EEG recorded by the LANMAO Sleep Recorder is precise and valid, and its automated sleep staging algorithm can accurately perform sleep staging with high accuracy. Therefore, in specific scenarios such as the home environment, LANMAO devices can work as a promising PSG alternative for sleep monitoring.