Personalized automatic sleep staging with single-night data: a pilot study with Kullback-Leibler divergence regularization.

OBJECTIVE: Brain waves vary between people. This work aims to improve automatic sleep staging for longitudinal sleep monitoring via personalization of algorithms based on individual characteristics extracted from sleep data recorded during the first night. APPROACH: As data from a single night are very small, thereby making model training difficult, we propose a Kullback-Leibler (KL) divergence regularized transfer learning approach to address this problem. We employ the pretrained SeqSleepNet (i.e. the subject independent model) as a starting point and finetune it with the single-night personalization data to derive the personalized model. This is done by adding the KL divergence between the output of the subject independent model and it of the personalized model to the loss function during finetuning. In effect, KL-divergence regularization prevents the personalized model from overfitting to the single-night data and straying too far away from the subject independent model. MAIN RESULTS: Experimental results on the Sleep-EDF Expanded database consisting of 75 subjects show that sleep staging personalization with single-night data is possible with help of the proposed KL-divergence regularization. On average, we achieve a personalized sleep staging accuracy of 79.6%, a Cohen's kappa of 0.706, a macro F1-score of 73.0%, a sensitivity of 71.8%, and a specificity of 94.2%. SIGNIFICANCE: We find both that the approach is robust against overfitting and that it improves the accuracy by 4.5 percentage points compared to the baseline method without personalization and 2.2 percentage points compared to it with personalization but without regularization

Sleep monitoring using ear-centered setups: Investigating the influence from electrode configurations.

Modern sleep monitoring development is shifting towards the use of unobtrusive sensors combined with algorithms for automatic sleep scoring. Many different combinations of wet and dry electrodes, ear-centered, forehead-mounted or headband-inspired designs have been proposed, alongside an ever growing variety of machine learning algorithms for automatic sleep scoring. OBJECTIVE: Among candidate positions, those in the facial area and around the ears have the benefit of being relatively hairless, and in our view deserve extra attention. In this paper, we seek to determine the limits to sleep monitoring quality within this spatial constraint. METHODS: We compare 13 different, realistic sensor setups derived from the same data set and analysed with the same pipeline. RESULTS: All setups which include both a lateral and an EOG derivation show similar, state-of-the-art performance, with average Cohen's kappa values of at least 0.80. CONCLUSION: If large electrode distances are used, positioning is not critical for achieving large sleep-related signal-to-noise-ratio, and hence accurate sleep scoring. SIGNIFICANCE: We argue that with the current competitive performance of automated staging approaches, there is a need for establishing an improved benchmark beyond current single human rater scoring

In-Ear EEG From Viscoelastic Generic Earpieces: Robust and Unobtrusive 24/7 Monitoring

We introduce a novel in-ear sensor which satisfies key design requirements for wearable electroencephalography (EEG)—it is discreet, unobtrusive, and capable of capturing high-quality brain activity from the ear canal. Unlike our initial designs, which utilize custom earpieces and require a costly and time-consuming manufacturing process, we here introduce the generic earpieces to make ear-EEG suitable for immediate and widespread use. Our approach represents a departure from silicone earmoulds to provide a sensor based on a viscoelastic substrate and conductive cloth electrodes, both of which are shown to possess a number of desirable mechanical and electrical properties. Owing to its viscoelastic nature, such an earpiece exhibits good conformance to the shape of the ear canal, thus providing stable electrode–skin interface, while cloth electrodes require only saline solution to establish low impedance contact. The analysis highlights the distinguishing advantages compared with the current state-of-the-art in ear-EEG. We demonstrate that such a device can be readily used for the measurement of various EEG responses

Impact of urban geology on model simulations of shallow groundwater levels and flow paths

This study examines the impact of urban geology and spatial discretization on the simulation of shallow groundwater levels and flow paths at the city scale. The study uses an integrated hydrological model based on the MIKE SHE code that couples surface water and 3D groundwater simulations with a leaky sewer system. The effect of the geological configuration was analyzed by applying three geological models to an otherwise identical hydrological model. The effect of spatial discretization was examined by using two different horizontal discretizations for the hydrological models of 50 and 10 m, respectively. The impact of the geological configuration and spatial discretization was analyzed based on model calibration, simulations of high water levels, and particle tracking. The results show that a representation of the subsurface infrastructure, and near-terrain soil types, in the geological model impacts the simulation of the high water levels when the hydrological model is simulated in a 10 m discretization. This was detectable even though the difference between the geological models only occurs in 7 % of the volume of the geological models. When the hydrological model was run in a 50 m horizontal discretization, the impact of the urban geology on the high water levels was smoothed out. Results from particle tracking show that representing the subsurface infrastructure in the hydrological model changed the particles' flow paths and travel time to sinks in both the 50 and 10 m horizontal discretization of the hydrological model. It caused less recharge to deeper aquifers and increased the percentage of particles flowing to saturated-zone drains and leaky sewer pipes. In conclusion, the results indicate that even though the subsurface infrastructure and fill material only occupy a small fraction of the shallow geology, it affects the simulation of local water levels and substantially alters the flow paths. The comparison of the spatial discretization demonstrates that, to simulate this effect, the spatial discretization needs to be of a scale that represents the local variability in the shallow urban geology.</p

Component analysis of nutritionally rich chloroplasts: recovery from conventional and unconventional green plant species

A study of the literature indicates that chloroplasts synthesise a range of molecules, many of which have nutritional value for humans, but as yet no one has established the nutritional credentials of chloroplasts recovered from plant cells. Chloroplast-rich-fractions (CRFs) were prepared from green plant species and the macro- and micronutrient composition compared with the whole leaf materials (WLMs). The results indicated that, on a dry weight basis, CRF material from a range of green biomass was enriched in lipids and proteins, and in a range of micronutrients compared with the WLM. Vitamins E, pro-vitamin A, and lutein were all greater in CRF preparations. Of the minerals, iron was most notably concentrated in CRF. Spinach CRFs possessed the highest α-tocopherol (62 mg 100 g-1 , dry weight (DW)), β-carotene (336 mg 100 g- 1 DW) and lutein (341 mg 100 g-1 DW) contents, whilst grass CRFs had the highest concentration of alpha-linolenic acid (ALA) (69.5 mg g-1). The higher concentrations of α-tocopherol, β-carotene, lutein, ALA and trace minerals (Fe and Mn) in CRFs suggest their potential use as concentrated ingredients in food formulations deficient in these nutrients

Assaying Total Carotenoids in Flours of Corn and Sweetpotato by Laser Photoacoustic Spectroscopy

This study describes the application of the laser photoacoustic spectroscopy (PAS) for quantification of total carotenoids (TC) in corn flours and sweetpotato flours. Overall, thirty-three different corn flours and nine sweetpotato flours were investigated. All PAS measurements were performed at room temperature using 488-nm argon laser radiation for excitation and mechanical modulation of 9 and 30 Hz. The measurements were repeated within a run and within several days or months. The UV–Vis spectrophotometry was used as the reference method. The concentration range that allows for the reliable analysis of TC spans a region from 1 to 40 mg kg−1 for corn flours and from 9 to 40 mg kg−1 for sweetpotato flours. In the case of sweetpotato flours, the quantification may extend even to 240 mg kg−1 TC. The estimated detection limit values for TC in corn and sweetpotato flours were 0.1 and 0.3 mg kg−1, respectively. The computed repeatability (n = 3–12) and intermediate precision (n = 6–28) RSD values at 9 and 30 Hz are comparable: 0.1–17.1% and 5.3–14.7% for corn flours as compared with 1.4–9.1% and 4.2–23.0% for sweetpotato flours. Our results show that PAS can be successfully used as a new analytical tool to simply and rapidly screen the flours for their nutritional potential based on the total carotenoid concentration

Structure and dynamics of the active Gs-coupled human secretin receptor

The class B secretin GPCR (SecR) has broad physiological effects, with target potential for treatment of metabolic and cardiovascular disease. Molecular understanding of SecR binding and activation is important for its therapeutic exploitation. We combined cryo-electron microscopy, molecular dynamics, and biochemical cross-linking to determine a 2.3 Å structure, and interrogate dynamics, of secretin bound to the SecR:Gs complex. SecR exhibited a unique organization of its extracellular domain (ECD) relative to its 7-transmembrane (TM) core, forming more extended interactions than other family members. Numerous polar interactions formed between secretin and the receptor extracellular loops (ECLs) and TM helices. Cysteine-cross-linking, cryo-electron microscopy multivariate analysis and molecular dynamics simulations revealed that interactions between peptide and receptor were dynamic, and suggested a model for initial peptide engagement where early interactions between the far N-terminus of the peptide and SecR ECL2 likely occur following initial binding of the peptide C-terminus to the ECD