Long-term, reliable, at-home sleep electroencephalography assessment in young and older adults: a validation study of a novel, wireless, soft electronics sleep monitoring system (Preprint)

BACKGROUND Sleep quality declines with age and is a known contributor to multiple chronic health conditions including Alzheimer’s disease (AD). There is great interest in determining if sleep quality, and what specific features thereof, may serve as a non-invasive biomarker of memory decline and AD. Emerging evidence suggests that certain electroencephalography (EEG) neural signatures measured during sleep may be predictive of cognitive decline in cognitively normal people years before AD diagnosis. Sleep EEG signals are traditionally measured using bulky, rigid, uncomfortable equipment in an unfamiliar lab setting that can negatively impact sleep signals. Due to these limitations, sleep EEG data acquisition is typically limited to a single night. As night-to-night sleep variability is predictive of poor cognitive performance and health outcomes, it is essential to sample multiple nights of sleep. OBJECTIVE This study aimed to validate our recently developed portable, skin-like EEG monitoring patch for seven nights in the home environment in a pilot sample of young and older adults by evaluating usability and acceptance and replicating the age-related differences in sleep architecture observed in polysomnography literature. METHODS Eighteen young and 18 cognitively unimpaired older adults without sleep disorders participated in a 7-night study in which they wore our novel, gel-free, wireless, ultra-thin, skin-forming sleep monitoring, fabric-based patches, self-applied to the forehead and face for optimal usability and comfort. Patches incorporate laser cut mesh electrodes with low-profile electronics (rechargeable battery, amplifier, Bluetooth microcontroller) and send EEG signals to a subject-controlled Bluetooth tablet-based data acquisition app. An automated algorithm was used to stage sleep and assess microarchitecture features from the EEG commonly impacted by age in traditional, polysomnography studies for each subject. Averages across nights were computed for these sleep features for each subject. RESULTS Young and older adults reported that the sleep patch to be easy to use and comfortable to wear, allowing them to sleep without discomfort. There was no loss in signal power over 7 nights of wear across subjects. While some datasets were not retained due to reference electrode adhesion, trained sleep technologists verified that retained datasets were of sufficient quality to be scored without difficulty. Finally, expected age group differences in sleep features were observed, including age-related reductions in %N3 sleep and reduced sleep spindle density. CONCLUSIONS This study validates that our novel, high comfort, wearable patch can reliably measure physiological sleep data over multiple nights at home in adults across the lifespan, thus making multi-night 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, which will make this technology and research accessible to individuals who may have difficulty traveling or are hesitant to travel to a lab or clinic. These results help lay the groundwork for studies in participants at risk for AD to determine whether particular sleep EEG patterns can help identify individuals most likely to exhibit cognitive decline.