Non-24-hour sleep–wake disorderNon-24-hour sleep–wake disorder (non-24 or N24SWD) is one of several chronic circadian rhythm sleep disorders (CRSDs). It is defined as a "chronic steady pattern comprising [...] daily delays in sleep onset and wake times in an individual living in a society". Symptoms result when the non-entrained (free-running) endogenous circadian rhythm drifts out of alignment with the light–dark cycle in nature. Although this sleep disorder is more common in blind people, affecting up to 70% of the totally blind, it can also affect sighted people.
Circadian rhythm sleep disorderCircadian rhythm sleep disorders (CRSD), also known as circadian rhythm sleep-wake disorders (CRSWD), are a family of sleep disorders which affect the timing of sleep. CRSDs arise from a persistent pattern of sleep/wake disturbances that can be caused either by dysfunction in one's biological clock system, or by misalignment between one's endogenous oscillator and externally imposed cues. As a result of this mismatch, those affected by circadian rhythm sleep disorders have a tendency to fall asleep at unconventional time points in the day.
Delayed sleep phase disorderDelayed sleep phase disorder (DSPD), more often known as delayed sleep phase syndrome and also as delayed sleep–wake phase disorder, is the delaying of a person's circadian rhythm (biological clock) compared to those of societal norms. The disorder affects the timing of biological rhythms including sleep, peak period of alertness, core body temperature, and hormonal cycles. The diagnosis of this disorder is currently a point of contention among specialists of sleep disorders.
Binary classificationBinary classification is the task of classifying the elements of a set into two groups (each called class) on the basis of a classification rule. Typical binary classification problems include: Medical testing to determine if a patient has certain disease or not; Quality control in industry, deciding whether a specification has been met; In information retrieval, deciding whether a page should be in the result set of a search or not. Binary classification is dichotomization applied to a practical situation.
Feedforward neural networkA feedforward neural network (FNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. Its flow is uni-directional, meaning that the information in the model flows in only one direction—forward—from the input nodes, through the hidden nodes (if any) and to the output nodes, without any cycles or loops, in contrast to recurrent neural networks, which have a bi-directional flow.
Learning classifier systemLearning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic algorithm) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning). Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions (e.g. behavior modeling, classification, data mining, regression, function approximation, or game strategy).
Types of artificial neural networksThere are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.
Sleep deprivationSleep deprivation, also known as sleep insufficiency or sleeplessness, is the condition of not having adequate duration and/or quality of sleep to support decent alertness, performance, and health. It can be either chronic or acute and may vary widely in severity. Acute sleep deprivation is when an individual sleeps less than usual or does not sleep at all for a short period of time – normally lasting one to two days but tends to follow the sleepless pattern for longer with no outside factors in play.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.
Sleep disorderA sleep disorder, or somnipathy, is a medical disorder of an individual's sleep patterns. Some sleep disorders are severe enough to interfere with normal physical, mental, social and emotional functioning. Polysomnography and actigraphy are tests commonly ordered for diagnosing sleep disorders. Sleep disorders are broadly classified into dyssomnias, parasomnias, circadian rhythm sleep disorders involving the timing of sleep, and other disorders including ones caused by medical or psychological conditions.
Artificial neuronAn artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. Artificial neurons are elementary units in an artificial neural network. The artificial neuron receives one or more inputs (representing excitatory postsynaptic potentials and inhibitory postsynaptic potentials at neural dendrites) and sums them to produce an output (or , representing a neuron's action potential which is transmitted along its axon).
ActigraphyActigraphy is a non-invasive method of monitoring human rest/activity cycles. A small actigraph unit, also called an actimetry sensor, is worn for a week or more to measure gross motor activity. The unit is usually in a wristwatch-like package worn on the wrist. The movements the actigraph unit undergoes are continually recorded and some units also measure light exposure. The data can be later read to a computer and analysed offline; in some brands of sensors the data are transmitted and analysed in real time.
DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
Naive Bayes classifierIn statistics, naive Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong (naive) independence assumptions between the features (see Bayes classifier). They are among the simplest Bayesian network models, but coupled with kernel density estimation, they can achieve high accuracy levels. Naive Bayes classifiers are highly scalable, requiring a number of parameters linear in the number of variables (features/predictors) in a learning problem.
SleepSleep is a state of reduced mental and physical activity in which consciousness is altered and sensory activity is inhibited to a certain extent. During sleep, there is a decrease in muscle activity, and interactions with the surrounding environment. While sleep differs from wakefulness in terms of the ability to react to stimuli, it still involves active brain patterns, making it more reactive than a coma or disorders of consciousness. Sleep occurs in repeating periods, during which the body alternates between two distinct modes: REM and non-REM sleep.
Sleep medicineSleep medicine is a medical specialty or subspecialty devoted to the diagnosis and therapy of sleep disturbances and disorders. From the middle of the 20th century, research has provided increasing knowledge of, and answered many questions about, sleep–wake functioning. The rapidly evolving field has become a recognized medical subspecialty in some countries. Dental sleep medicine also qualifies for board certification in some countries. Properly organized, minimum 12-month, postgraduate training programs are still being defined in the United States.
Sleep apneaSleep apnea, also spelled sleep apnoea, is a sleep disorder in which pauses in breathing or periods of shallow breathing during sleep occur more often than normal. Each pause can last for a few seconds to a few minutes and they happen many times a night. In the most common form, this follows loud snoring. A choking or snorting sound may occur as breathing resumes. Because the disorder disrupts normal sleep, those affected may experience sleepiness or feel tired during the day.
Data managementData management comprises all disciplines related to handling data as a valuable resource. The concept of data management arose in the 1980s as technology moved from sequential processing (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems.
Fast Fourier transformA fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier transform (DFT) of a sequence, or its inverse (IDFT). Fourier analysis converts a signal from its original domain (often time or space) to a representation in the frequency domain and vice versa. The DFT is obtained by decomposing a sequence of values into components of different frequencies. This operation is useful in many fields, but computing it directly from the definition is often too slow to be practical.
