At-Home Sleep Electroencephalography Assessment in Young and Older Adults Using a Novel Wireless Soft Electronics...

Sleep quality declines with age and is a known contributor to multiple chronic health conditions, including Alzheimer disease. Emerging evidence suggests that certain electroencephalography (EEG) neural signatures measured during sleep may be predictive of cognitive decline in older adults. Sleep EEG signals are traditionally measured using bulky, rigid, and uncomfortable equipment in an unfamiliar laboratory setting, which can negatively impact sleep signals. Due to these limitations, sleep EEG data acquisition is typically limited to a single night.

This study aimed to validate our recently developed portable, skin-like EEG monitoring patch for 7 nights in the home environment in a pilot sample of young and older adults by evaluating usability and acceptance, and replicating age-related differences in sleep architecture observed in the polysomnography literature.

Eighteen young adults and 18 cognitively unimpaired older adults without sleep disorders were enrolled (data from 11 young adults and 12 older adults were included in the analyses) in a 7-night study during which they wore novel, gel-free, wireless, ultrathin, skin-conforming, sleep monitoring, fabric-based patches. These patches were self-applied to the forehead and face for optimal usability and comfort. The patches incorporate laser-cut mesh electrodes with low-profile electronics (including a rechargeable battery and amplifier) and transmit EEG signals to a participant-controlled, Bluetooth-enabled, tablet-based data acquisition app. An automated algorithm was used to stage sleep and assess microarchitecture features from the EEG commonly impacted for each participant. Averages across nights were computed for these sleep features for each participant.

Young and older adults reported that the sleep patch was easy to use and comfortable to wear. There was no loss of signal power over 7 nights of wear across participants (retained-data signal-to-noise ratio over the 7-d period: young adult, mean 20.69, SD 12.78, maximum 52.13, minimum 5.19; older adult, mean 22.10, SD 9.39, maximum 49.96, minimum 13.79). Most datasets not retained were lost due to poor reference electrode adhesion on the nose (75/101, 74% of lost datasets in young adults and 57/88, 65% in older adults). Trained sleep technologists verified that the retained datasets were of sufficient quality to be scored without difficulty. Expected age-group differences in sleep features were observed, including age-related reductions in stage N3 sleep (young adult, mean 18.55, SD 6.70; older adult, mean 10.40, SD 6.43; Mann-Whitney U=42.0; P=.01) and reduced sleep spindle density (young adult, mean 2.92, SD 2.24; older adult, mean 0.94, SD 1.33; Mann-Whitney U=45.0; P=.006).

This study demonstrates that our novel, comfortable, wearable patch can reliably measure physiological sleep data over multiple nights at home in adults across the lifespan, thereby making multinight sleep assessment in cognitive aging studies and clinical research more accessible than traditional polysomnography. In future studies, the small, lightweight system, which is highly scalable, can be shipped inexpensively to participants' homes, making this technology and research accessible to individuals who may have difficulty traveling or who are hesitant to travel to a laboratory or clinic.