Wearable technologyWearable technology is any technology that is designed to be used while worn. Common types of wearable technology include smartwatches and smartglasses. Wearable electronic devices are often close to or on the surface of the skin, where they detect, analyze, and transmit information such as vital signs, and/or ambient data and which allow in some cases immediate biofeedback to the wearer.
Wearable computerA wearable computer, also known as a body-borne computer, is a computing device worn on the body. The definition of 'wearable computer' may be narrow or broad, extending to smartphones or even ordinary wristwatches. Wearables may be for general use, in which case they are just a particularly small example of mobile computing. Alternatively, they may be for specialized purposes such as fitness trackers. They may incorporate special sensors such as accelerometers, heart rate monitors, or on the more advanced side, electrocardiogram (ECG) and blood oxygen saturation (SpO2) monitors.
Wear OSWear OS (also known simply as Wear and formerly Android Wear) is a version of Google's Android operating system designed for smartwatches and other wearables. By pairing with mobile phones running Android version 6.0 "Marshmallow" or newer, or iOS version 10.0 or newer with limited support from Google's pairing application, Wear OS integrates Google Assistant technology and mobile notifications into a smartwatch form factor. Wear OS supports Bluetooth, NFC, Wi-Fi, 3G, and LTE connectivity, as well as a range of features and applications.
SeizureAn epileptic seizure, informally known as a seizure, is a period of symptoms due to abnormally excessive or synchronous neuronal activity in the brain. Outward effects vary from uncontrolled shaking movements involving much of the body with loss of consciousness (tonic-clonic seizure), to shaking movements involving only part of the body with variable levels of consciousness (focal seizure), to a subtle momentary loss of awareness (absence seizure). Most of the time these episodes last less than two minutes and it takes some time to return to normal.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Data analysisData analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
Seizure typesIn the field of neurology, seizure types are categories of seizures defined by seizure behavior, symptoms, and diagnostic tests. The International League Against Epilepsy (ILAE) 2017 classification of seizures is the internationally recognized standard for identifying seizure types. The ILAE 2017 classification of seizures is a revision of the prior ILAE 1981 classification of seizures. Distinguishing between seizure types is important since different types of seizures may have different causes, outcomes, and treatments.
Psychogenic non-epileptic seizurePsychogenic non-epileptic seizures (PNES), which have been more recently classified as functional seizures, are events resembling an epileptic seizure, but without the characteristic electrical discharges associated with epilepsy. PNES fall under the category of disorders known as functional neurological disorders (FND), also known as conversion disorders. These are typically treated by psychologists or psychiatrists. PNES has previously been called pseudoseizures, psychogenic seizures, and hysterical seizures, but these terms have fallen out of favor.
EpilepsyEpilepsy is a group of non-communicable neurological disorders characterized by recurrent epileptic seizures. An epileptic seizure is the clinical manifestation of an abnormal, excessive, purposeless and synchronized electrical discharge in the brain cells called neurons. The occurrence of two or more unprovoked seizures defines epilepsy. The occurrence of just one seizure may warrant the definition (set out by the International League Against Epilepsy) in a more clinical usage where recurrence may be able to be prejudged.
Atrial fibrillationAtrial fibrillation (AF or A-fib) is an abnormal heart rhythm (arrhythmia) characterized by rapid and irregular beating of the atrial chambers of the heart. It often begins as short periods of abnormal beating, which become longer or continuous over time. It may also start as other forms of arrhythmia such as atrial flutter that then transform into AF. Episodes can be asymptomatic. Symptomatic episodes may involve heart palpitations, fainting, lightheadedness, shortness of breath, or chest pain.
Causes of seizuresGenerally, seizures are observed in patients who do not have epilepsy. There are many causes of seizures. Organ failure, medication and medication withdrawal, cancer, imbalance of electrolytes, hypertensive encephalopathy, may be some of its potential causes. The factors that lead to a seizure are often complex and it may not be possible to determine what causes a particular seizure, what causes it to happen at a particular time, or how often seizures occur. Malnutrition and overnutrition may increase the risk of seizures.
Focal seizureFocal seizures (also called partial seizures and localized seizures) are seizures which affect initially only one hemisphere of the brain. The brain is divided into two hemispheres, each consisting of four lobes – the frontal, temporal, parietal and occipital lobes. A focal seizure is generated in and affects just one part of the brain – a whole hemisphere or part of a lobe. Symptoms will vary according to where the seizure occurs. When seizures occur in the frontal lobe the patient may experience a wave-like sensation in the head.
Reflex seizureReflex seizures are epileptic seizures that are consistently induced by a specific stimulus or trigger making them distinct from other epileptic seizures, which are usually unprovoked. Reflex seizures are otherwise similar to unprovoked seizures and may be focal (simple or complex), generalized, myoclonic, or absence seizures. Epilepsy syndromes characterized by repeated reflex seizures are known as reflex epilepsies. Photosensitive seizures are often myoclonic, absence, or focal seizures in the occipital lobe, while musicogenic seizures are associated with focal seizures in the temporal lobe.
Smart deviceA smart device is an electronic device, generally connected to other devices or networks via different wireless protocols (such as Bluetooth, Zigbee, near-field communication, Wi-Fi, LiFi, or 5G) that can operate to some extent interactively and autonomously. Several notable types of smart devices are smartphones, smart speakers, smart cars, smart thermostats, smart doorbells, smart locks, smart refrigerators, phablets and tablets, smartwatches, smart bands, smart keychains, smart glasses, and many others.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Deep reinforcement learningDeep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. Deep RL incorporates deep learning into the solution, allowing agents to make decisions from unstructured input data without manual engineering of the state space. Deep RL algorithms are able to take in very large inputs (e.g.
Activity trackerAn activity tracker, also known as a fitness tracker, is a device or application for monitoring and tracking fitness-related metrics such as distance walked or run, calorie consumption, and in some cases heartbeat. It is a type of wearable computer. The term is now primarily used for smartwatches that are , in many cases wirelessly, to a computer or smartphone for long-term data tracking. There are also independent mobile and Facebook apps. Some evidence has found that the use of these type of devices results in less weight loss rather than more.
Mobile deviceA mobile device (or handheld computer) is a computer, small enough to hold and operate in the hand. Mobile devices typically have a flat LCD or OLED screen, a touchscreen interface, and digital or physical buttons. They may also have a physical keyboard. Many such devices can connect to the Internet and connect with other devices such as car entertainment systems or headsets via Wi-Fi, Bluetooth, cellular networks or near field communication.
SmartwatchA smartwatch is a wearable computer in the form of a watch; modern smartwatches provide a local touchscreen interface for daily use, while an associated smartphone app provides management and telemetry, such as long-term biomonitoring. While early models could perform basic tasks, such as calculations, digital time telling, translations, and game-playing, smartwatches released since 2015 have more general functionality closer to smartphones, including mobile apps, a mobile operating system and WiFi/Bluetooth connectivity.
Reinforcement learningReinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected.
