Configurable Mobile System for Autonomous High-Quality Sleep Monitoring and Closed-Loop Acoustic Stimulation

Abstract

Present-day sleep research in humans is largely dependent on complex and costly laboratory setups, which require controlled supervision. As it is highly desirable to study sleep and to monitor sleep interventions in a realistic setting at home, new mobile approaches with equivalent performance to lab-based systems are needed. We present here the development and evaluation of a mobile system for sleep-biosignal monitoring and real-time intervention for ambulatory sleep research. We evaluated the system for electroencephalogram (EEG) signal quality and compared it to an established sleep EEG recording system. The real-time EEG signal processing performance was evaluated by implementing a closedloop auditory deep-sleep stimulation algorithm, and we calculated the precision of slow wave (SW) phase targeting during 93 nights. The obtained EEG signals contained similar power spectrograms and high correlations in the delta (0.98) and sigma (0.99) bands when compared to the reference system. The SW phase targeting [mean 44.6°, standard deviation (SD) 46.8°] was comparable to previously published, lab-based approaches. We have, thus, demonstrated that our device is suitable for performing unobtrusive, multinight monitoring and intervention at home. Index Terms-Sensor applications, biosensor sensing and processing, electroencephalogram (EEG), acoustic stimulation, braincomputer interface, sleep, mobile devices.

Save Muscle Information–Unfiltered EEG Signal Helps Distinguish Sleep Stages

“…There are several possible applications of recycling the muscle tone information from the EEG signal. Recently, an increasing number of wearable biosignal amplifiers have been developed (e.g., around ear applications, wearable headbands) to obtain large-scale data and allow for in-field, long-term assessments of sleep [7][8][9]. One important aspect of these wearable devices is a non-obtrusive design and therefore a reduction of electrodes is desired.…”

“…Furthermore, the raw data might be dumped from the commercial polysomnogram (PSG) and the raw data might have been filtered at the frequency range 0.3-35 Hz. Due to the advance of technology and focus on large-scale applications, there is an increasing number of mobile devices capable of recording EEG signal in in-home settings (e.g., single channel amplifiers on the forehead or in-ear/around ear applications) [6][7][8][9]. These mobile solutions might not include EMG and EOG information, and the raw data might be bandpassed for different purposes, like data storage or transmission.…”

A Protocol for Comparing Dry and Wet EEG Electrodes During Sleep

“…In a feasibility study of a tattoo-based electrode setup for sleep, four nights were recorded at the subjects' home, and sleep is scored by an expert to qualitatively evaluate the EEG and to visually determine whether typical sleep patterns (e.g., spindles and slow waves) can be distinguished (Shustak et al, 2019). Introducing additional quantitative measures, Ferster et al (2019) compare the correlation of the mean square power in the delta (0.5-4 Hz) and sigma (10-15 Hz) bands during NREM sleep. This comparison uses two separate portable amplifiers that are designed for home-based sleep screening, of which the reference system is a clinically established device.…”

“…This comparison uses two separate portable amplifiers that are designed for home-based sleep screening, of which the reference system is a clinically established device. The challenge of using two completely separate systems is the time synchronization between the amplifiers, which leads to only visual and qualitative comparisons or large comparison windows (Ferster et al, 2019). More often, comparative electrode studies rely on a single amplifier system that shares a common reference (and ground) of either electrode type, which enables correlation analysis in the time domain, but may introduce unwanted distortions in the opposite channel (Casson, 2019).…”

Changes in cross-frequency coupling following closed-loop auditory stimulation in non-rapid eye movement sleep

“…Although the majority of closed-loop auditory stimulation studies are still conducted in lab environments, recently, the first systems for unsupervised closed-loop enhancement of slowwave activity have been developed (e.g., Debellemaniere et al 2018;Ferster et al 2019) with the goal to boost memory consolidation for prolonged periods and in clinical populations. Given the importance of local sleep characteristics for use-dependent neuroplasticity and considering the translational trend in the auditory closed-loop stimulation field, it is important to investigate whether slow waves, theta and sigma oscillations and their interaction can be manipulated selectively in a particular brain region.…”