Accurate whole-night sleep monitoring with dry-contact ear-EEG.
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ABSTRACT:
SUBMITTER: Mikkelsen KB
PROVIDER: S-EPMC6856384 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
Publications
Accurate whole-night sleep monitoring with dry-contact ear-EEG.
Mikkelsen Kaare B KB Tabar Yousef R YR Kappel Simon L SL Christensen Christian B CB Toft Hans O HO Hemmsen Martin C MC Rank Mike L ML Otto Marit M Kidmose Preben P
Scientific reports 20191114 1
Sleep is a key phenomenon to both understanding, diagnosing and treatment of many illnesses, as well as for studying health and well being in general. Today, the only widely accepted method for clinically monitoring sleep is the polysomnography (PSG), which is, however, both expensive to perform and influences the sleep. This has led to investigations into light weight electroencephalography (EEG) alternatives. However, there has been a substantial performance gap between proposed alternatives a ...[more]
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Project description:IntroductionA device comprising two generic earpieces with embedded dry electrodes for ear-centered electroencephalography (ear-EEG) was developed. The objective was to provide ear-EEG based sleep monitoring to a wide range of the population without tailoring the device to the individual.MethodsTo validate the device ten healthy subjects were recruited for a 12-night sleep study. The study was divided into two parts; part A comprised two nights with both ear-EEG and polysomnography (PSG), and part B comprised 10 nights using only ear-EEG. In addition to the electrophysiological measurements, subjects filled out a questionnaire after each night of sleep.ResultsThe subjects reported that the ear-EEG system was easy to use, and that the comfort was better in part B. The performance of the system was validated by comparing automatic sleep scoring based on ear-EEG with PSG-based sleep scoring performed by a professional trained sleep scorer. Cohen's kappa was used to assess the agreement between the manual and automatic sleep scorings, and the study showed an average kappa value of 0.71. The majority of the 20 recordings from part A yielded a kappa value above 0.7. The study was compared to a companioned study conducted with individualized earpieces. To compare the sleep across the two studies and two parts, 7 different sleeps metrics were calculated based on the automatic sleep scorings. The ear-EEG nights were validated through linear mixed model analysis in which the effects of equipment (individualized vs. generic earpieces), part (PSG and ear-EEG vs. only ear-EEG) and subject were investigated. We found that the subject effect was significant for all computed sleep metrics. Furthermore, the equipment did not show any statistical significant effect on any of the sleep metrics.DiscussionThese results corroborate that generic ear-EEG is a promising alternative to the gold standard PSG for sleep stage monitoring. This will allow sleep stage monitoring to be performed in a less obtrusive way and over longer periods of time, thereby enabling diagnosis and treatment of diseases with associated sleep disorders.
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Project description:Arousals during sleep are transient accelerations of the EEG signal, considered to reflect sleep perturbations associated with poorer sleep quality. They are typically detected by visual inspection, which is time consuming, subjective, and prevents good comparability across scorers, studies and research centres. We developed a fully automatic algorithm which aims at detecting artefact and arousal events in whole-night EEG recordings, based on time-frequency analysis with adapted thresholds derived from individual data. We ran an automated detection of arousals over 35 sleep EEG recordings in healthy young and older individuals and compared it against human visual detection from two research centres with the aim to evaluate the algorithm performance. Comparison across human scorers revealed a high variability in the number of detected arousals, which was always lower than the number detected automatically. Despite indexing more events, automatic detection showed high agreement with human detection as reflected by its correlation with human raters and very good Cohen's kappa values. Finally, the sex of participants and sleep stage did not influence performance, while age may impact automatic detection, depending on the human rater considered as gold standard. We propose our freely available algorithm as a reliable and time-sparing alternative to visual detection of arousals.
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Project description:STUDY OBJECTIVES:To develop and validate a novel non-contact system for whole-night sleep evaluation using breathing sounds analysis (BSA). DESIGN:Whole-night breathing sounds (using ambient microphone) and polysomnography (PSG) were simultaneously collected at a sleep laboratory (mean recording time 7.1 hours). A set of acoustic features quantifying breathing pattern were developed to distinguish between sleep and wake epochs (30 sec segments). Epochs (n = 59,108 design study and n = 68,560 validation study) were classified using AdaBoost classifier and validated epoch-by-epoch for sensitivity, specificity, positive and negative predictive values, accuracy, and Cohen's kappa. Sleep quality parameters were calculated based on the sleep/wake classifications and compared with PSG for validity. SETTING:University affiliated sleep-wake disorder center and biomedical signal processing laboratory. PATIENTS:One hundred and fifty patients (age 54.0±14.8 years, BMI 31.6±5.5 kg/m2, m/f 97/53) referred for PSG were prospectively and consecutively recruited. The system was trained (design study) on 80 subjects; validation study was blindly performed on the additional 70 subjects. MEASUREMENTS AND RESULTS:Epoch-by-epoch accuracy rate for the validation study was 83.3% with sensitivity of 92.2% (sleep as sleep), specificity of 56.6% (awake as awake), and Cohen's kappa of 0.508. Comparing sleep quality parameters of BSA and PSG demonstrate average error of sleep latency, total sleep time, wake after sleep onset, and sleep efficiency of 16.6 min, 35.8 min, and 29.6 min, and 8%, respectively. CONCLUSIONS:This study provides evidence that sleep-wake activity and sleep quality parameters can be reliably estimated solely using breathing sound analysis. This study highlights the potential of this innovative approach to measure sleep in research and clinical circumstances.
| S-EPMC4339734 | biostudies-literature
Project description:The interest in dry electroencephalography (EEG) electrodes has increased in recent years, especially as everyday suitability earplugs for measuring drowsiness or focus of auditory attention. However, the challenge is still the need for a good electrode material, which is reliable and can be easily processed for highly personalized applications. Laser processing, as used here, is a fast and very precise method to produce personalized electrode configurations that meet the high requirements of in-ear EEG electrodes. The arrangement of the electrodes on the flexible and compressible mats allows an exact alignment to the ear mold and contributes to high wearing comfort, as no edges or metal protrusions are present. For better transmission properties, an adapted coating process for surface enlargement of platinum electrodes is used, which can be controlled precisely. The resulting porous platinum-copper alloy is chemically very stable, shows no exposed copper residues, and enlarges the effective surface area by 40. In a proof-of-principle experiment, these porous platinum electrodes could be used to measure the Berger effect in a dry state using just one ear of a test person. Their signal-to-noise ratio and the frequency transfer function is comparable to gel-based silver/silver chloride electrodes.
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Project description:Background:Sleep is commonly assessed by recording the electroencephalogram (EEG) of the sleeping brain. As sleep assessments in a lab environment are cumbersome for both the participant and researcher, it would be highly desirable to record sleep EEG with a user-friendly and mobile device. Dry electrodes that are reusable, low-cost, and easy to apply would be an essential component of such a device. In this study, we developed a testing protocol to investigate the performance of novel flat-type dry electrodes for sleep EEG recordings in free-living conditions. Methods:Overnight sleep EEG, electrooculogram and electromyogram of four young and healthy participants were recorded at home. Two identical ambulatory recording devices, one using novel flat-type dry electrodes, the other using self-adhesive pre-gelled electrodes, simultaneously recorded sleep EEG. Between both electrode types, we then compared the signal quality, the incidence of artifacts, the sensitivity, specificity and inter-scoring reliability (Cohen's kappa) of sleep staging, as well as the agreement of important characteristics of sleep-specific EEG microstructure features, such as slow waves (0.5-4 Hz) and sleep spindles (10-16 Hz). Results:Our testing protocol comprehensively compared the two electrode types on a macro- and microstructure level of sleep. The dry and pre-gelled electrodes both had comparable signal quality and sleep staging was feasible with both electrodes. Also, slow-wave and spindle characteristics were similar. However, sweat artifacts were more prevalent in the flat-type dry electrodes. Conclusion:With a reliable testing protocol, the performance of dry electrodes can be compared to reference technologies and objectively assessed also in free-living conditions.
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Project description:Difficulty sleeping in a novel environment is a common phenomenon that is often described as the first night effect (FNE). Previous works have found FNE on sleep architecture and sleep power spectra parameters, especially during non-rapid eye movement (NREM) sleep. However, the impact of FNE on sleep parameters, including local differences in electroencephalographic (EEG) activity across nights, has not been systematically assessed. Here, we performed high-density EEG sleep recordings on 27 healthy individuals on two nights and examined differences in sleep architecture, NREM (stages 2 and 3) EEG power spectra, and NREM power topography across nights. We found higher wakefulness after sleep onset (WASO), reduced sleep efficiency, and less deep NREM sleep (stage 3), along with increased high-frequency NREM EEG power during the first night of sleep, corresponding to small to medium effect sizes (Cohen's d ≤ 0.5). Furthermore, study individuals showed significantly lower slow-wave activity in right frontal/prefrontal regions as well as higher sigma and beta activities in medial and left frontal/prefrontal areas, yielding medium to large effect sizes (Cohen's d ≥ 0.5). Altogether, these findings suggest the FNE is characterized by less efficient, more fragmented, shallower sleep that tends to affect especially certain brain regions. The magnitude and specificity of these effects should be considered when designing sleep studies aiming to compare across night effects.
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Project description:A problem inherent to recording EEG is the interference arising from noise and artifacts. While in a laboratory environment, artifacts and interference can, to a large extent, be avoided or controlled, in real-life scenarios this is a challenge. Ear-EEG is a concept where EEG is acquired from electrodes in the ear.We present a characterization of physiological artifacts generated in a controlled environment for nine subjects. The influence of the artifacts was quantified in terms of the signal-to-noise ratio (SNR) deterioration of the auditory steady-state response. Alpha band modulation was also studied in an open/closed eyes paradigm.Artifacts related to jaw muscle contractions were present all over the scalp and in the ear, with the highest SNR deteriorations in the gamma band. The SNR deterioration for jaw artifacts were in general higher in the ear compared to the scalp. Whereas eye-blinking did not influence the SNR in the ear, it was significant for all groups of scalps electrodes in the delta and theta bands. Eye movements resulted in statistical significant SNR deterioration in both frontal, temporal and ear electrodes. Recordings of alpha band modulation showed increased power and coherence of the EEG for ear and scalp electrodes in the closed-eyes periods.Ear-EEG is a method developed for unobtrusive and discreet recording over long periods of time and in real-life environments. This study investigated the influence of the most important types of physiological artifacts, and demonstrated that spontaneous activity, in terms of alpha band oscillations, could be recorded from the ear-EEG platform. In its present form ear-EEG was more prone to jaw related artifacts and less prone to eye-blinking artifacts compared to state-of-the-art scalp based systems.
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Project description:Study objectivesTo validate a contact-free system designed to achieve maximal comfort during long-term sleep monitoring, together with high monitoring accuracy.MethodsWe used a contact-free monitoring system (EarlySense, Ltd., Israel), comprising an under-the-mattress piezoelectric sensor and a smartphone application, to collect vital signs and analyze sleep. Heart rate (HR), respiratory rate (RR), body movement, and calculated sleep-related parameters from the EarlySense (ES) sensor were compared to data simultaneously generated by the gold standard, polysomnography (PSG). Subjects in the sleep laboratory underwent overnight technician-attended full PSG, whereas subjects at home were recorded for 1 to 3 nights with portable partial PSG devices. Data were compared epoch by epoch.ResultsA total of 63 subjects (85 nights) were recorded under a variety of sleep conditions. Compared to PSG, the contact-free system showed similar values for average total sleep time (TST), % wake, % rapid eye movement, and % non-rapid eye movement sleep, with 96.1% and 93.3% accuracy of continuous measurement of HR and RR, respectively. We found a linear correlation between TST measured by the sensor and TST determined by PSG, with a coefficient of 0.98 (R = 0.87). Epoch-by-epoch comparison with PSG in the sleep laboratory setting revealed that the system showed sleep detection sensitivity, specificity, and accuracy of 92.5%, 80.4%, and 90.5%, respectively.ConclusionsTST estimates with the contact-free sleep monitoring system were closely correlated with the gold-standard reference. This system shows good sleep staging capability with improved performance over accelerometer-based apps, and collects additional physiological information on heart rate and respiratory rate.
| S-EPMC5337599 | biostudies-literature