Thursday, October 17, 2024

Sleep


Modulation of Sleep Architecture by Whole-Body Static Magnetic Exposure: A Study Based on EEG-Based Automatic Sleep Staging

Sleep disturbance has been the main issue for an increasing number of individuals with the progression of society. It can lead to decreased memory and learning, gastrointestinal disorders, depression, and exacerbation of chronic conditions 

Approximately 30% of adults and 48% of older adults in particular experience chronic insomnia []. Chronic insomnia is difficult to cure using the currently available pharmacotherapy 

Therefore, physical therapies have been used to treat chronic insomnia. Electric, magnetic, and electromagnetic fields have been applied to modulate sleep in a series of clinical and experimental studies. Most of these treatment approaches were non-invasive and less stimulant.

 Therefore, the application of such therapies is promising, although the effects were not always consistent, nor a clear mechanism of action has been elaborated.

In most studies, questionnaires and self-reported scales are commonly applied to evaluate sleep quality []. Among them, the Pittsburgh Sleep Quality Index (PSQI) [] and the Self-Rating Scale of Sleep (SRSS) [] are useful tools for sleep-related psychiatric research and practice. The former measures the overall sleep quality during a period, while the latter assesses short-term sleep quality, e.g., the efficacy of a sleep disorder therapy for each night during an experiment.

Sleep has a complex architecture and includes various physiological changes that occur during the period. A person usually experiences four to six sleep cycles per night, which includes different sleep stages. The American Academy of Sleep Medicine (AASM) has divided the sleep process into five stages: awake (N0), non-rapid eye movement (N1-N3), and rapid eye movement (REM) sleep []. N3 is slow-wave sleep, which is the most recuperative sleep period and is often indicative of high-quality sleep []. Sleep staging is commonly used as an indicator in diagnosing sleep diseases and related psychiatric disorders. In contrast, self-reported questionnaires may implicitly associate with the overall sleep quality but could be undermined by subjectivity; therefore, it is difficult to discriminate the individual sleep stage by using self-reported questionnaires.

Neurophysiological analyses, e.g., using electroencephalogram (EEG), are used in the research of electromagnetic field exposure effects [,] and sleep quality determination []. Sophisticated paradigms have been developed to process sleep EEG signal into characteristics that reflect sleep rhythms, neural tension, or neural activity []. Sleep staging calculates the dwelling time of sleep in each stage by using time-domain signals from multiple electrodes. It traditionally requires extensive manual intervention to discern the specific EEG features. For example, the dataset for an 8-h consecutive sleep may have a volume of 500 MB if sampled at 1000 Hz. In such a case, the results are prone to human error due to fatigue []. Therefore, automatic sleep staging is required, and sleep staging based on the machine learning method is a promising alternative [].

A great number of scientific literatures about automatic sleep staging detection were presented. The majority of these scientific literatures use single-channel EEG recordings for automatic sleep staging [] and in most cases classified models are built on extracted features. Features are extracted from linear or nonlinear. For improving the classification accuracy and accelerating the model construction procedure, feature selection has become an important step in data preprocessing []. There are many feature selection algorithms, including filtering, encapsulation and embedded ones. Decision tree is a typical embedded feature selection algorithm. A decision tree by Liu et al. is suitable for sleep EEG staging due to that it could achieve feature selection for imbalanced data. Selected features are generally used as input for classic algorithms such a support vector machines (SVM), k-nearest neighbor, decision tree (DT), etc. []. SVM shows good generalization performance for high dimensional data due to its convex optimization problem [].

In this study, changes in sleep architecture by static magnetic field exposure (SMFE) were evaluated. Forty-one subjects were randomly divided into two groups (real SMFE group and sham SMFE group) for participation in the experiment for four consecutive nights. Whole-body SMFE was applied by a magnetostatic mattress. During the experiment, sleep EEG was recorded, while PSQI and SRSS were used to report the individual overnight sleep quality. Twenty temporal, frequency and nonlinear metrics were extracted from the labeled sleep EEG by using the Physionet database. A decision tree (DT) was trained using data from this sleep EEG database to select a set of features for sleep staging. The acquired sleep EEG was then classified by a support vector machine (SVM). The purpose of this study is to explore whether there is an ameliorative effect of SMFE on sleep and to explore the adjuvant treatment of chronic sleep disorde

Sunday, October 13, 2024

How to Treat Fungal Toenails

Apple cider vinegar

  • Apple cider vinegar. This particular type of vinegar has a mild acidity, which both prevents the fungal infection from spreading and eradicates the offensive fungus (along with other microorganisms, like odor-causing bacteria). To correctly perform this form of treatment, mix apple cider vinegar with an equal amount of water in a basin. Soak the affected foot (or feet) in the solution for about thirty minutes.

Baking Soda

  • Baking soda. Baking soda is a versatile product. In addition to treating the fungal infection, it can also help with neutralizing foot odor. To use baking soda correctly as a treatment for toenail fungus, start by mixing a half-cup of it—along with a half-cup of Epsom salt and a quarter-cup of hydrogen peroxide (3%)—in four cups of hot water. After mixing those ingredients, add a quarter-cup of white vinegar and then soak your feet in the solution for about ten minutes. When you’re done, rinse off your feet with clean water and dry them completely.

Tea Tree Oil

  • Tea tree oil. This essential oil contains both antifungal and antiseptic properties. To use this for treating a fungal nail condition, start by mixing a few drops of tea tree oil with a teaspoon of either coconut oil or olive oil. Apply this mixture to any infected toenails with a cotton ball. After letting it sit for about ten minutes, gently scrub the treated nails with a clean toothbrush. For optimal results, repeat the process two or three times a day.

An important consideration with all types of toenail fungus treatment is the fact you have a role to play as well. We can put together the plan, but it is up to you to follow the directions for consistent use of medication and taking measures—keeping feet dry and clean, trimming toenails properly, protecting feet in public areas—to prevent reinfection.

Sunday, September 29, 2024

MUSIC

❤️ MUSIC IS GOOD MEDICINE

174 Hertz - Removes Pain
285 Hertz - Influences Energy Field
396 Hertz - Liberates you of fear & guilt
417 Hertz - Facilitates Change
432 Hertz - Miracle Tone of Nature, planet Earth frequency
528 Hertz - Repairs DNA
639 Hertz - Heals Relationships
741 Hertz - Awaken Intuition
852 Hertz - Attracts Soul Tribe
963 Hertz - Connect with Light & Spirit

“DNA not only reacts to but can be repaired with certain frequencies. This is why music is good medicine.”

Drumming is natures medicine, hence why the ancients did it.

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