A novel in-ear sensor to determine sleep latency during the Multiple Sleep Latency Test in healthy adults with and without sleep restriction

Abstract

ObjectivesDetecting sleep latency during the Multiple Sleep Latency Test (MSLT) using electroencephalogram (scalp-EEG) is time-consuming. The aim of this study was to evaluate the efficacy of a novel in-ear sensor (in-ear EEG) to detect the sleep latency, compared to scalp-EEG, during MSLT in healthy adults, with and without sleep restriction.MethodsWe recruited 25 healthy adults (28.5±5.3 years) who participated in two MSLTs with simultaneous recording of scalp and in-ear EEG. Each test followed a randomly assigned sleep restriction (≤5 hours sleep) or usual night sleep (≥7 hours sleep). Reaction time and Stroop test were used to assess the functional impact of the sleep restriction. The EEGs were scored blind to the mode of measurement and study conditions, using American Academy of Sleep Medicine 2012 criteria. The Agreement between the scalp and in-ear EEG was assessed using Bland-Altman analysis.ResultsTechnically acceptable data were obtained from 23 adults during 69 out of 92 naps in the sleep restriction condition and 25 adults during 85 out of 100 naps in the usual night sleep. Meaningful sleep restrictions were confirmed by an increase in the reaction time (mean ± SD: 238±30 ms vs 228±27 ms; P=0.045). In the sleep restriction condition, the in-ear EEG exhibited a sensitivity of 0.93 and specificity of 0.80 for detecting sleep latency, with a substantial agreement (κ=0.71), whereas after the usual night’s sleep, the in-ear EEG exhibited a sensitivity of 0.91 and specificity of 0.89, again with a substantial agreement (κ=0.79).ConclusionThe in-ear sensor was able to detect reduced sleep latency following sleep restriction, which was sufficient to impair both the reaction time and cognitive function. Substantial agreement was observed between the scalp and in-ear EEG when measuring sleep latency. This new in-ear EEG technology is shown to have a significant value as a convenient measure for sleep latency.

Hearables: Automatic Overnight Sleep Monitoring With Standardized In-Ear EEG Sensor

“…The same data were also used for automatic sleep stage classification in [12], which further demonstrated the possibility of out-of-clinic sleep monitoring with ear-EEG. After this initial proof-of-concept stage, Alqurashi et al [13] conducted comprehensive multiple daytime nap recordings to establish the degree of matching of the corresponding sleep latencies based on ear-EEG and scalp-EEG under two conditions: 1) after normal sleep and 2) after sleep restriction. The same nap data over twenty three participants were used by Nakamura et al [14] to establish the potential of ear-EEG in automatic detection of drowsiness (i.e.…”

“…Nguyen et al [15] conducted overnight sleep recordings over eight participants to evaluate their in-ear sensing system; their sensors were able to record the EEG, EOG, and EMG, key physiological variables for sleep monitoring. It is important to highlight that the sleep studies in [11][12][13][14][15], together with this study, were conducted using one-size-fits-all viscoelastic in-ear sensors, which are not optimised for a particular user but are convenient for wide deployment and promise an affordable out-of-clinic solution. Owing to their flexibility and favourable stress-strain properties (memory foam) [28], these viscoelastic earpieces can be squeezed and shaped up to fit comfortably any ear; such a 'generic' in-ear sensor is readily applicable to a large population, a pre-requisite for the future eHealth in the community.…”

Accurate whole-night sleep monitoring with dry-contact ear-EEG

“…Similar work was done by Nguyen et al . and Alqurashi et al ., but with only nap studies instead of full nights 8,9 . More recently, Mikkelsen et al .…”

Recent advances in wearable sensors and portable electronics for sleep monitoring

“…The biggest design challenge of sleep monitoring devices that can be used outside of hospitals is making electrodes that can measure EEG from the scalp, mostly covered by hairs (Arai et al, 2016). In standard PSG, conductive gels are widely used to penetrate through the hairs and make an electrical path between the scalp (Arnal et al, 2019) Forehead (Arnal et al, 2019), (Levendowski et al, 2017), (Lin et al, 2017), (Shustak et al, 2019) Ear (Alqurashi et al, 2018), (Sterr et al, 2018), (Mikkelsen et al, 2019) Heart activity ECG Wet/dry electrode Chest (Klum et al, 2020), (Ilen et al, 2019), (Di Rienzo et al, 2018), (Yoon et al, 2018 (Liao et al, 2020), (Kinnunen et al, 2020) Nose (Manoni et al, 2020) Forehead (Arnal et al, 2019), (Levendowski et al, 2017)…”

“…More recently, other body parts other than the forehead have been tested to measure EEG with less obtrusion and interference with natural sleep behavior, and the ear is the most popular measurement location among them. Figure 2 B shows an in-ear-type EEG measurement platform with two fabric-based EEG electrodes integrated with a memory-foam substrate ( Alqurashi et al., 2018 ). The author explains that memory foam's unique mechanical property provides a comfortable fit to the user's ear, makes reliable skin-electrode contact, and effectively reduces signal artifacts from pulsatile ear canal movements due to blood vessel pulsation.…”