An automatic EEG-based sleep staging system with introducing NAoSP and NAoGP as new metrics for sleep staging systems

Different biological signals are recorded in sleep labs during sleep for the diagnosis and treatment of human sleep problems. Classification of sleep stages with electroencephalography (EEG) is preferred to other biological signals due to its advantages such as providing clinical information, cost-effectiveness, comfort, and ease of use. The evaluation of EEG signals taken during sleep by clinicians is a tiring, time-consuming, and error-prone method. Therefore, it is clinically mandatory to determine sleep stages by using software-supported systems. Like all classification problems, the accuracy rate is used to compare the performance of studies in this domain, but this metric can be accurate when the number of observations is equal in classes. However, since there is not an equal number of observations in sleep stages, this metric is insufficient in the evaluation of such systems. For this purpose, in recent years, Cohen’s kappa coefficient and even the sensitivity of NREM1 have been used for comparing the performance of these systems. Still, none of them examine the system from all dimensions. Therefore, in this study, two new metrics based on the polygon area metric, called the normalized area of sensitivity polygon and normalized area of the general polygon, are proposed for the performance evaluation of sleep staging systems. In addition, a new sleep staging system is introduced using the applications offered by the MATLAB program. The existing systems discussed in the literature were examined with the proposed metrics, and the best systems were compared with the proposed sleep staging system. According to the results, the proposed system excels in comparison with the most advanced machine learning methods. The single-channel method introduced based on the proposed metrics can be used for robust and reliable sleep stage classification from all dimensions required for real-time applications.Electronic supplementary materialThe online version of this article (10.1007/s11571-020-09641-2) contains supplementary material, which is available to authorized users.     

Comparison of the usability of an automatic sleep staging program via portable 1-channel electroencephalograph and manual sleep staging with traditional polysomnography

Sleep and Biological Rhythms - Automatic algorithms are a proposed alternative to manual assessment of polysomnography data for analyzing sleep structure; however, none are acceptably accurate for...     

A transition-constrained discrete hidden Markov model for automatic sleep staging

ABSTRACT: BACKGROUND: Approximately one-third of the human lifespan is spent sleeping. To diagnose sleep problems, all-night polysomnographic (PSG) recordings including electroencephalograms (EEGs), electrooculograms (EOGs) and electromyograms (EMGs), are usually acquired from the patient and scored by a well-trained expert according to Rechtschaffen & Kales (R&K) rules. Visual sleep scoring is a time-consuming and subjective process. Therefore, the development of an automatic sleep scoring method is desirable. METHOD: The EEG, EOG and EMG signals from twenty subjects were measured. In addition to selecting sleep characteristics based on the 1968 R&K rules, features utilized in other research were collected. Thirteen features were utilized including temporal and spectrum analyses of the EEG, EOG and EMG signals, and a total of 158 hours of sleep data were recorded. Ten subjects were used to train the Discrete Hidden Markov Model (DHMM), and the remaining ten were tested by the trained DHMM for recognition. Furthermore, the 2-fold cross validation was performed during this experiment. RESULTS: Overall agreement between the expert and the results presented is 85.29%. With the exception of S1, the sensitivities of each stage were more than 81%. The most accurate stage was SWS (94.9%), and the least-accurately classified stage was S1 (<34%). In the majority of cases, S1 was classified as Wake (21%), S2 (33%) or REM sleep (12%), consistent with previous studies. However, the total time of S1 in the 20 all-night sleep recordings was less than 4%. CONCLUSION: The results of the experiments demonstrate that the proposed method significantly enhances the recognition rate when compared with prior studies.     

A transition-constrained discrete hidden Markov model for automatic sleep staging

Background

Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems.

Method

In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing

Results and discussion

Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA.

Conclusion

Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants.     

Evaluation of a commercially available automated sleep staging tool in healthy infants

Sleep and Biological Rhythms - The ALICE5 software package provides a commercially available automated sleep staging system designed for infants. This study aims to evaluate the accuracy of this...     

Genetics of sleep and sleep disorders

Sleep remains one of the least understood phenomena in biology--even its role in synaptic plasticity remains debatable. Since sleep was recognized to be regulated genetically, intense research has launched on two fronts: the development of model organisms for deciphering the molecular mechanisms of sleep and attempts to identify genetic underpinnings of human sleep disorders. In this Review, we describe how unbiased, high-throughput screens in model organisms are uncovering sleep regulatory mechanisms and how pathways, such as the circadian clock network and specific neurotransmitter signals, have conserved effects on sleep from Drosophila to humans. At the same time, genome-wide association studies (GWAS) have uncovered ～14 loci increasing susceptibility to sleep disorders, such as narcolepsy and restless leg syndrome. To conclude, we discuss how these different strategies will be critical to unambiguously defining the function of sleep.     

固态间歇补料乙醇生料发酵新工艺

浓醪发酵是酒精生产的发展方向。与现行酒精厂普遍采用的热蒸煮工艺相比, 生料发酵技术的发展使得浓醪发酵更容易进行。本研究首次在生料发酵中直接采用固态原料间歇补料, 比较了STARGENTM生淀粉水解酶间歇补料工艺和传统无补料工艺, 并对不同补料方式进行了研究。结果表明: 与传统无补料生料发酵工艺相比, 在相同的干基配料浓度30%、相同的生料酶添加量0.22%(W/W)的条件下, 采用15%的起始配料浓度、发酵15~25 h进行间歇补料的新工艺, 酒精产量从17.06%提高到18.50%。该间歇补料优化工艺的建立, 丰富了生料发酵技术的应用。     

Sleep staging with movement-related signals

Body movement related signals (i.e., activity due to postural changes and the ballistocardiac effort) were recorded from six normal volunteers using the static-charge-sensitive bed (SCSB). Visual sleep staging was performed on the basis of simultaneously recorded EEG, EMG and EOG signals. A statistical classification technique was used to determine if reliable sleep staging could be performed using only the SCSB signal. A classification rate of between 52% and 75% was obtained for sleep staging in the five conventional sleep stages and the awake state. These rates improved from 78% to 89% for classification between awake, REM and non-REM sleep and from 86% to 98% for awake versus asleep classification.     

Overview of sleep and sleep medicine in Asian countries

While there are a number of sleep medicine and sleep research publications in Asia, and their quality is increasing each year, the actual situation of sleep disorders in the general population still remains an issue of major concern. Scientists and medical doctors believe that, for the first time in history, the general lack of sleep could lead to a diminution of life expectancy. It is also known that, as people are working more and more and are more tired, they are more likely to become victims of accidents. Most of the time these incidents have little gravity, but sometimes they can cost thousands of innocent lives or contribute to disasters such as the Chernobyl nuclear plant explosion or the Bhopal gas tragedy. Based on the Asian Sleep Research Society Summit and Symposium Round Table held during the fall of 2009 on Okinawa, this review aims to give an accurate view of the actual situation of sleep research and medicine in Asia. The particular example of the obstructive sleep apnea syndrome will illustrate the importance of sleep medicine in this part of the world. Finally, the actual situation will be discussed to elaborate some possible strategies to improve the sleep situation for Asian populations.

     

Developmental staging table of the green iguana

Embryonic staging tables provide information to standardize embryological investigations and to subsidize discussions about evolution. We have established a developmental staging table for Iguana iguana iguana. The sample was composed of 142 embryos, incubated at a constant temperature and collected at regular intervals. Morphological features as pharyngeal arches, craniofacial structures, eyes, limbs, claws, pigmentation, scales and egg tooth were evaluated to determine development stages. The normal staging table includes 17 stages from oviposition to hatching, based on chronology and morphological external features. Stages from 1 to 27 occur before oviposition. Stage 28 was the first described, because all embryos presented limb bud anlage, key feature of the previous stage. We used pharyngeal arches and limb buds to describe the first stages; claws, genital papilla and scales to describe the middle stages; and pigmentation, size and egg tooth to describe the last stages. Incubation lasted approximately 2 months in a controlled environment. The results were similar to the data from other lizards, confirming the embryonic conservative pattern of the group.     

Genetics of sleep

Main achievements in general and molecular genetics of sleep, especially NREM sleep, are regarded. Among them, discovery of such heredity disorders, as FFI, FASPS and DSPS, the finding of genetic hallmarks of sleep EEG, etc.     

Age-related changes in the association of sleep satisfaction with sleep quality and sleep–wake pattern

Sleep and Biological Rhythms - Age-specific relationship of sleep–wake pattern with night sleep satisfaction was examined to address a question of why sleep satisfaction does not accurately...     

Masseter EMG activity during sleep and sleep bruxism

The masseter muscle is involved in the complex and coordinated oromotor behaviors such as mastication during wakefulness. The masseter electromyographic (EMG) activity decreases but does not disappear completely during sleep: the EMG activity is generally of low level and inhomogeneous for the duration, amplitude and intervals. The decreased excitability of the masseter motoneurons can be determined by neural substrates for NREM and REM sleep. The masseter EMG activity is increased in association with the level of arousal fluctuations within either sleep state. In addition, there are some motor events such as REM twitches, swallowing and rhythmic masticatory muscle activity (RMMA), whose generation might involve the additional activation of specific neural circuits. Sleep bruxism (SB) is characterized by exaggerated occurrence of RMMA. In SB, the rhythmic activation of the masseter muscle can reflect the rhythmic motor inputs to motoneurons through, at least in part, common neural circuits for generating masticatory rhythm under the facilitatory influences of transient arousals. However, it remains elusive as to which neural circuits determine the genesis of sleep bruxism. Based on the available knowledge on the masseter EMG activity during sleep, this review presents that the variety of the masseter EMG phenotypes during sleep can result from the combinations of the quantitative, spatial and temporal neural factors eventually sending net facilitatory inputs to trigeminal motoneurons under sleep regulatory systems.     

Characteristics of sleep structure in patients with sleep apnea]

The course of different sleep phases has been studied in group of patients. A decrease in duration of deep sleep phase and increase in the number of awakenings are found in them.