Tension headacheTension headache, also known as stress headache, or tension-type headache (TTH), is the most common type of primary headache. The pain can radiate from the lower back of the head, the neck, eyes or other muscle groups in the body typically affecting both sides of the head. Tension-type headaches account for nearly 90% of all headaches. Pain medications, such as paracetamol and ibuprofen, are effective for the treatment of tension headache. Tricyclic antidepressants appear to be useful for prevention.
HeadacheHeadache, also known as cephalalgia, is the symptom of pain in the face, head, or neck. It can occur as a migraine, tension-type headache, or cluster headache. There is an increased risk of depression in those with severe headaches. Headaches can occur as a result of many conditions. There are a number of different classification systems for headaches. The most well-recognized is that of the International Headache Society, which classifies it into more than 150 types of primary and secondary headaches.
Cluster headacheCluster headache (CH) is a neurological disorder characterized by recurrent severe headaches on one side of the head, typically around the eye(s). There is often accompanying eye watering, nasal congestion, or swelling around the eye on the affected side. These symptoms typically last 15 minutes to 3 hours. Attacks often occur in clusters which typically last for weeks or months and occasionally more than a year. The cause is unknown. Risk factors include a history of exposure to tobacco smoke and a family history of the condition.
Medication overuse headacheA medication overuse headache (MOH), also known as a rebound headache, usually occurs when painkillers are taken frequently to relieve headaches. These cases are often referred to as painkiller headaches. Rebound headaches frequently occur daily, can be very painful and are a common cause of chronic daily headache. They typically occur in patients with an underlying headache disorder such as migraine or tension-type headache that "transforms" over time from an episodic condition to chronic daily headache due to excessive intake of acute headache relief medications.
Linear regressionIn statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.
Robust regressionIn robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise (i.e. are not robust to assumption violations).
Thunderclap headacheA thunderclap headache is a headache that is severe and has a sudden onset. It is defined as a severe headache that takes seconds to minutes to reach maximum intensity. Although approximately 75% are attributed to "primary" headaches—headache disorder, non-specific headache, idiopathic thunderclap headache, or uncertain headache disorder—the remainder are secondary to other causes, which can include some extremely dangerous acute conditions, as well as infections and other conditions.
Magnetic resonance imagingMagnetic resonance imaging (MRI) is a medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes of the body. MRI scanners use strong magnetic fields, magnetic field gradients, and radio waves to generate images of the organs in the body. MRI does not involve X-rays or the use of ionizing radiation, which distinguishes it from computed tomography (CT) and positron emission tomography (PET) scans.
Star clusterStar clusters are large groups of stars held together by self-gravitation. Two main types of star clusters can be distinguished: globular clusters are tight groups of ten thousand to millions of old stars which are gravitationally bound, while open clusters are more loosely clustered groups of stars, generally containing fewer than a few hundred members, and are often very young.
MigraineMigraine (UK, US) is a genetically influenced complex neurological disorder characterized by episodes of moderate-to-severe headache, most often unilateral and generally associated with nausea and light and sound sensitivity. Other characterizing symptoms may include nausea, vomiting, cognitive dysfunction, allodynia, and dizziness. Exacerbation of headache symptoms during physical activity is another distinguishing feature.
Open clusterAn open cluster is a type of star cluster made of tens to a few thousand stars that were formed from the same giant molecular cloud and have roughly the same age. More than 1,100 open clusters have been discovered within the Milky Way galaxy, and many more are thought to exist. They are loosely bound by mutual gravitational attraction and become disrupted by close encounters with other clusters and clouds of gas as they orbit the Galactic Center.
Globular clusterA globular cluster is a spheroidal conglomeration of stars. Globular clusters are bound together by gravity, with a higher concentration of stars towards their centers. They can contain anywhere from tens of thousands to many millions of member stars. Their name is derived from Latin globulus (small sphere). Globular clusters are occasionally known simply as "globulars". Although one globular cluster, Omega Centauri, was observed in antiquity and long thought to be a star, recognition of the clusters' true nature came with the advent of telescopes in the 17th century.
Myofascial trigger pointMyofascial trigger points (MTrPs), also known as trigger points, are described as hyperirritable spots in the skeletal muscle. They are associated with palpable nodules in taut bands of muscle fibers. They are a topic of ongoing controversy, as there is limited data to inform a scientific understanding of the phenomenon. Accordingly, a formal acceptance of myofascial "knots" as an identifiable source of pain is more common among bodyworkers, physical therapists, chiropractors, and osteopathic practitioners.
Regression analysisIn statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome' or 'response' variable, or a 'label' in machine learning parlance) and one or more independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features'). The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits the data according to a specific mathematical criterion.
Skeletal muscleSkeletal muscles (commonly referred to as muscles) are organs of the vertebrate muscular system and typically are attached by tendons to bones of a skeleton. The muscle cells of skeletal muscles are much longer than in the other types of muscle tissue, and are often known as muscle fibers. The muscle tissue of a skeletal muscle is striated – having a striped appearance due to the arrangement of the sarcomeres. Skeletal muscles are voluntary muscles under the control of the somatic nervous system.
Neurological disorderA neurological disorder is any disorder of the nervous system. Structural, biochemical or electrical abnormalities in the brain, spinal cord or other nerves can result in a range of symptoms. Examples of symptoms include paralysis, muscle weakness, poor coordination, loss of sensation, seizures, confusion, pain and altered levels of consciousness. There are many recognized neurological disorders, some relatively common, but many rare. They may be assessed by neurological examination, and studied and treated within the specialities of neurology and clinical neuropsychology.
Smooth muscleSmooth muscle is an involuntary non-striated muscle, so-called because it has no sarcomeres and therefore no striations (bands or stripes). It is divided into two subgroups, single-unit and multiunit smooth muscle. Within single-unit muscle, the whole bundle or sheet of smooth muscle cells contracts as a syncytium. Smooth muscle is found in the walls of hollow organs, including the stomach, intestines, bladder and uterus. In the walls of blood vessels, and lymph vessels, (excluding blood and lymph capillaries) it is known as vascular smooth muscle.
Robust statisticsRobust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal. Robust statistical methods have been developed for many common problems, such as estimating location, scale, and regression parameters. One motivation is to produce statistical methods that are not unduly affected by outliers. Another motivation is to provide methods with good performance when there are small departures from a parametric distribution.
Local regressionLocal regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced ˈloʊɛs. They are two strongly related non-parametric regression methods that combine multiple regression models in a k-nearest-neighbor-based meta-model.
Principal component analysisPrincipal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.
