Spinal cord stimulation[edit]
Spinal cord stimulation (SCS) is an effective therapy for the treatment of chronic and intractable pain including diabetic neuropathy, failed back surgery syndrome, complex regional pain syndrome, phantom limb pain, ischemic limb pain, refractory unilateral limb pain syndrome, postherpetic neuralgia and acute herpes zoster pain. Another pain condition that is a potential candidate for SCS treatment is Charcot-Marie-Tooth (CMT) disease, which is associated with moderate to severe chronic extremity pain.[9] SCS therapy consists of the electrical stimulation of the spinal cord to 'mask' pain. The gate theory proposed in 1965 by Melzack and Wall[10] provided a theoretical construct to attempt SCS as a clinical treatment for chronic pain. This theory postulates that activation of large diameter, myelinated primary afferent fiberssuppresses the response of dorsal horn neurons to input from small, unmyelinated primary afferents. A simple SCS system consists of three different parts. First, microelectrodes are implanted in the epidural space to deliver stimulation pulses to the tissue. Second, an electrical pulse generator implanted in the lower abdominal area or gluteal region while is connected to the electrodes via wires, and third a remote control to adjust the stimulus parameters such as pulse width and pulse rate in the PG. Improvements have been made in both the clinical aspects of SCS such as transition from subdural placement of contacts to epidural placement, which reduces the risk and morbidity of SCS implantation, and also technical aspects of SCS such as improving percutaneous leads, and fully implantable multi-channel stimulators. However, there are many parameters that need to be optimized including number of implanted contacts, contact size and spacing, and electrical sources for stimulation. The stimulus pulse width and pulse rate are important parameters that need to be adjusted in SCS, which are typically 400 us and 8–200 Hz respectively.[11]
Transcutaneous supraorbital nerve stimulation[edit]
Tentative evidence supports transcutaneous supraorbital nerve stimulation.[12] Side effects are few.[13]
Visual prosthesis[edit]
Theoretical and experimental clinical evidences suggest that direct electrical stimulation of the retina might be able to provide some vision to subjects who have lost the photoreceptive elements of their retina.[19] Therefore, visual prostheses are developed to restore vision for the blind by using the stimulation. Depending upon which visual pathway location is targeted for neural stimulation, different approaches have been considered. Visual pathway consists mainly of the eye, optic nerve, lateral geniculate nucleus (LGN), and visual cortex. Therefore, retinal, optic nerve and visual cortex stimulation are the three different methods used in visual prostheses.[20] Retinal degenerative diseases, such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD), are two likely candidate diseases in which retinal stimulation may be helpful. Three approaches called intraocular epiretinal, subretinal and extraocular transretinal stimulation are pursued in retinal devices that stimulate remaining retinal neural cells to bypass lost photoreceptors and allow the visual signal to reach the brain via the normal visual pathway. In epiretinal approach, electrodes are placed on the top side of the retina near ganglion cells,[21] whereas the electrodes are placed under the retina in subretinal approaches.[22] Finally, the posterior scleral surface of the eye is the place in which extraocular approach electrodes are positioned. Second Sight and the Humayun group at USC are the most active groups in the design of intraocular retinal prostheses. The ArgusTM 16 retinal implant is an intraocular retinal prosthesis utilizing video processing technologies. Regarding to the visual cortex stimulation, Brindley, and Dobelle were the first ones who did the experiments and demonstrated that by stimulating the top side of the visual cortex most of the electrodes can produce visual percept.[11] More recently Sawan built a complete implant for intracortical stimulation and validated the operation in rats.[23]
LGN, which is located in the midbrain to relay signals from the retina to the visual cortex, is another potential area that can be used for stimulation. But this area has limited access due to surgical difficulty. The recent success of deep brain stimulation techniques targeting the midbrain has encouraged research to pursue the approach of LGN stimulation for a visual prosthesis.[24]
Cardiac electrostimulation devices[edit]
Implantable pacemakers were proposed for the first time in 1959 and became more sophisticated since then. The therapeutic application of pacemakers consists of numerous rhythm disturbances including some forms of tachycardia (too fast a heart beat), heart failure, and even stroke. Early implantable pacemakers worked only a short time and needed periodic recharging by an inductive link. These implantable pacemakers needed a pulse generator to stimulate heart muscles with a certain rate in addition to electrodes.[25] Today, modern pulse generators are programmed non-invasively by sophisticated computerized machines using RF, obtaining information about the patient's and device's status by telemetry. Also they use a single hermetically sealed lithium iodide (LiI) cell as the battery. The pacemaker circuitry includes sense amplifiers to detect the heart's intrinsic electrical signals, which are used to track heart activity, rate adaptive circuitry, which determine the need for increased or reduced pacing rate, a microprocessor, memory to store the parameters, telemetry control for communication protocol and power supplies to provide regulated voltage.[26]
Stimulation microelectrode technologies[edit]
Microelectrodes are one of the key components of the neurostimulation, which deliver the current to neurons. Typical microelectrodes have three main components: a substrate (the carrier), a conductive metal layer, and an insulation material. In cochlear implants, microelectrodes are formed from platinum-iridium alloy. State-of-the-art electrodes include deeper insertion to better match the tonotopicplace of stimulation to the frequency band assigned to each electrode channel, improving efficiency of stimulation, and reducing insertion related trauma. These cochlear implant electrodes are either straight or spiral such as Med El Combi 40+ and Advanced Bionics Helix microelectrodes respectively. In visual implants, there are two types of electrode arrays called planar type or three dimensional needle or pillar type, where needle type array such as Utah array is mostly used for cortical and optic nerve stimulations and rarely used in retinal implants due to the possible damage of retina. However, a pillar-shaped gold electrode array on thin-film polyimide has been used in an extraocular implant. On the other hand, planar electrode arrays are formed from flexible polymers, such as silicone, polyimide, and Parylene as candidates for retinal implants. Regarding to DBS microelectrodes an array, which can be controlled independently, distributed throughout the target nucleus would permit precise control of the spatial distribution of the stimulation, and thus, allow better personalized DBS. There are several requirements for DBS microelectrodes that include long lifetime without injury to the tissue or degradation of the electrodes, customized for different brain sites, long-term biocompatibility of the material, mechanically durable in order to reach the target without being damaged during handling by the implant surgeon, and finally uniformity of performance across the microelectrodes in a particular array. Tungsten microwire, iridium microwires, and sputtered or electrodeposited[27] Platinum-iridium alloy microelectrodes are the examples of microelectrode used in DBS.[11] Silicon carbide is a potential interesting material for realizing biocompatible semiconductor devices.[28]
History[edit]
The primary findings about neurostimulation originated from the idea to stimulate nerves for therapeutic purposes. The 1st recorded use of electrical stimulation for pain relief goes back to 46 AD, when Scribonius Largus used torpedo fish (electric ray) for relieving headaches.[29] In the late 18th century, Luigi Galvani discovered that the muscles of dead frog legs twitched when struck by direct current on the nervous system.[30] The modulation of the brainactivity by electrical stimulation of the motor cortex in dogs was shown in 1870 that resulted in limb movement.[31] From the late 18th century to today many milestones have been developed. Nowadays, sensory prosthetic devices, such as visual implants, cochlear implants, auditory midbrain implants, and spinal cord stimulators and also motor prosthetic devices, such as deep brain stimulators, Bion microstimulators, the brain control and sensing interface, and cardiac electro-stimulation devices are widely used.[11]
In 2013 the British pharmaceutical company GlaxoSmithKline (GSK) coined the term "electroceutical" to broadly encompass medical devices that use electrical, mechanical, or light stimulation to affect electrical signaling in relevant tissue types.[32][33] Clinical neural implants such as cochlear implants to restore hearing, retinal implants to restore sight, spinal cord stimulators for pain relief or cardiac pacemakers and implantable defibrillators are proposed examples of electroceuticals.[32] GSK formed a venture fund and said it would host a conference in 2013 to lay out a research agenda for the field.[34] A 2016 review of research on interactions between the nervous and immune systems in autoimmune disorders mentioned "electroceuticals" in passing and quotation marks, referring to neurostimulation devices in development for conditions like arthritis.[35]
Research[edit]
In addition to the enormous usage of neurostimulation for clinical applications, it is also used widely in laboratories started dates back to 1920s by people like Delgado who used stimulation as an experimental manipulation to study basics of how the brain works. The primary works were on the reward center of the brain in which stimulation of those structures led to pleasure that requested more stimulation. Another most recent example is the electrical stimulation of the MT area of primary visual cortex to bias perception. In particular, the directionality of motion is represented in a regular way in the MT area. They presented monkeys with moving images on screen and monkey throughput was to determine what the direction is. They found that by systematically introducing some errors to the monkey's responses, by stimulating the MT area which is responsible for perceiving the motion in another direction, the monkey responded to somewhere in between the actual motion and the stimulated one. This was an elegant use of stimulation to show that MT area is essential in the actual perception of motion. Within the memory field, stimulation is used very frequently to test the strength of the connection between one bundle of cells to another by applying a small current in one cell which results in the release of neurotransmitters and measuring the postsynaptic potential.
Generally, a short but high-frequency current in the range of 100 Hz helps strengthening the connection known as long-term potentiation. However, longer but low-frequency current tends to weaken the connections known as long-term depression.[36]
https://en.wikipedia.org/wiki/Neurostimulation#Transcutaneous_supraorbital_nerve_stimulation
Non-invasive cerebellar stimulation is the application of non-invasive neurostimulation techniques on the cerebellum to modify its electrical activity. Techniques such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) can be used.[1] The cerebellum is a high potential target for neuromodulation of neurological and psychiatric disorders due to the high density of neurons in its superficial layer, its electrical properties, and its participation in numerous closed-loop circuits involved in motor, cognitive, and emotional functions.[2]
Cerebellar TMS is a relatively new field that is undergoing experimental research. There is not yet sufficient evidence of the therapeutic effects of cerebellar TMS,[3] although some successful results have been reported in other clinical studies of TMS used to treat the frontal lobe.[4]
See also[edit]
- Deep brain stimulation
- Transcranial alternating current stimulation (tACS)
- Transcranial random noise stimulation (tRNS)
Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to the natural intelligencedisplayed by humans or animals. Leading AI textbooks define the field as the study of "intelligent agents": any system that perceives its environment and takes actions that maximize its chance of achieving its goals.[a]Some popular accounts use the term "artificial intelligence" to describe machines that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving", however this definition is rejected by major AI researchers.[b]
AI applications include advanced web search engines (i.e. Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri or Alexa), self-driving cars (e.g. Tesla), and competing at the highest level in strategic game systems (such as chess and Go),[2] As machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the AI effect.[3] For instance, optical character recognition is frequently excluded from things considered to be AI,[4] having become a routine technology.[5]
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,[6][7] followed by disappointment and the loss of funding (known as an "AI winter"),[8][9] followed by new approaches, success and renewed funding.[7][10] AI research has tried and discarded many different approaches during its lifetime, including simulating the brain, modeling human problem solving, formal logic, large databases of knowledge and imitating animal behavior. In the first decades of the 21st century, highly mathematical statistical machine learning has dominated the field, and this technique has proved highly successful, helping to solve many challenging problems throughout industry and academia.[11][10]
The various sub-fields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects.[c] General intelligence (the ability to solve an arbitrary problem) is among the field's long-term goals.[12] To solve these problems, AI researchers use versions of search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability and economics. AI also draws upon computer science, psychology, linguistics, philosophy, and many other fields.
The field was founded on the assumption that human intelligence "can be so precisely described that a machine can be made to simulate it".[d] This raises philosophical arguments about the mind and the ethics of creating artificial beings endowed with human-like intelligence. These issues have been explored by myth, fiction and philosophy since antiquity.[14] Science fiction and futurology have also suggested that, with its enormous potential and power, AI may become an existential risk to humanity.[15][16]
https://en.wikipedia.org/wiki/Artificial_intelligence
A hypercentric or pericentric lens is a lens system where the entrance pupil is located in front of the lens, in the space where an object could be located. This has the result that, in a certain region, objects that are farther away from the lens produce larger images than objects that are closer to the lens, in stark contrast to the behavior of the human eye or any ordinary camera (both entocentric lenses), where farther-away objects always appear smaller.
The geometry of a hypercentric lens can be visualized by imagining a point source of light at the center of the entrance pupil sending rays in all directions. Any point on the object will be imaged to the point on the image plane found by continuing the ray that passes through it, so the shape of the image will be the same as that of the shadow cast by the object from the imaginary point of light. So the closer an object gets to that point (the center of the entrance pupil), the larger its image will be.
This inversion of normal perspectivity can be useful for machine vision. Imagine a six-sided die sitting on a conveyor belt being imaged by a hypercentric lens system directly above, whose entrance pupil is below the conveyor belt. The image of the die would contain the top and all four sides at once, because the bottom of the die appears larger than the top.
See also[edit]
In electronics[edit]
In alternating current, the zero-crossing is the instantaneous point at which there is no voltage present. In a sine wave or other simple waveform, this normally occurs twice during each cycle. It is a device for detecting the point where the voltage crosses zero in either direction.
The zero-crossing is important for systems that send digital data over AC circuits, such as modems, X10 home automation control systems, and Digital Command Control type systems for Lionel and other AC model trains.
Counting zero-crossings is also a method used in speech processing to estimate the fundamental frequency of speech.
In a system where an amplifier with digitally controlled gain is applied to an input signal, artifacts in the non-zero output signal occur when the gain of the amplifier is abruptly switched between its discrete gain settings. At audio frequencies, such as in modern consumer electronics like digital audio players, these effects are clearly audible, resulting in a 'zipping' sound when rapidly ramping the gain or a soft 'click' when a single gain change is made. Artifacts are disconcerting and clearly not desirable. If changes are made only at zero-crossings of the input signal, then no matter how the amplifier gain setting changes, the output also remains at zero, thereby minimizing the change. (The instantaneous change in gain will still produce distortion, but it will not produce a click.)
If electrical power is to be switched, no electrical interference is generated if switched at an instant when there is no current—a zero crossing. Early light dimmers and similar devices generated interference; later versions were designed to switch at the zero crossing.
In image processing[edit]
In the field of Digital Image Processing, great emphasis is placed on operators that seek out edges within an image. They are called 'Edge Detection' or 'Gradient filters'. A gradient filter is a filter that seeks out areas of rapid change in pixel value. These points usually mark an edge or a boundary. A Laplace filter is a filter that fits in this family, though it sets about the task in a different way. It seeks out points in the signal stream where the digital signal of an image passes through a pre-set '0' value, and marks this out as a potential edge point. Because the signal has crossed through the point of zero, it is called a zero-crossing. An example can be found here, including the source in Java.
In the field of Industrial radiography, it is used as a simple method for the segmentation of potential defects.[1]
References[edit]
- ^ Mery, Domingo (2015). Computer Vision for X-Ray Testing. Switzerland: Springer International Publishing. p. 271. ISBN 978-3319207469.
See also[edit]
In computer vision and image processing, a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. Other examples of features are related to motion in image sequences, or to shapes defined in terms of curves or boundaries between different image regions.
More broadly a feature is any piece of information which is relevant for solving the computational task related to a certain application. This is the same sense as feature in machine learning and pattern recognition generally, though image processing has a very sophisticated collection of features. The feature concept is very general and the choice of features in a particular computer vision system may be highly dependent on the specific problem at hand.
https://en.wikipedia.org/wiki/Feature_(computer_vision)
https://en.wikipedia.org/wiki/Inverse_square_potential
https://en.wikipedia.org/wiki/Inverse_square_law
https://en.wikipedia.org/wiki/Blob_detection
https://en.wikipedia.org/wiki/Scale_space
https://en.wikipedia.org/wiki/Scale_invariance
https://en.wikipedia.org/wiki/Probability_distribution
For instance, a side of the Koch snowflake is both symmetrical and scale-invariant; it can be continually magnified 3x without changing shape. The non-trivial similarity evident in fractals is distinguished by their fine structure, or detail on arbitrarily small scales. As a counterexample, whereas any portion of a straight line may resemble the whole, further detail is not revealed.
https://en.wikipedia.org/wiki/Self-similarity
In mathematics, conformal geometry is the study of the set of angle-preserving (conformal) transformations on a space.
In a real two dimensional space, conformal geometry is precisely the geometry of Riemann surfaces. In space higher than two dimensions, conformal geometry may refer either to the study of conformal transformations of what are called "flat spaces" (such as Euclidean spaces or spheres), or to the study of conformal manifolds which are Riemannian or pseudo-Riemannian manifolds with a class of metrics that are defined up to scale. Study of the flat structures is sometimes termed Möbius geometry, and is a type of Klein geometry.
https://en.wikipedia.org/wiki/Conformal_geometry
In physics, spacetime is any mathematical model which fuses the three dimensions of space and the one dimension of time into a single four-dimensional manifold. Spacetime diagrams can be used to visualize relativistic effects, such as why different observers perceive differently where and when events occur.
https://en.wikipedia.org/wiki/Spacetime
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