Review of the Human Brain and EEG Signals
Teodiano Freire Bastos-Filho in Introduction to Non-Invasive EEG-Based Brain–Computer Interfaces for Assistive Technologies, 2020
The signal-to-noise ratio (SNR) is defined as the ratio of the average power in the signal to the average power in the noise [38]. As more epochs are used, the SNR of the time-locked event increases, allowing the observation of the ERP. In the ideal case, it is assumed that the measured EEG signals are made of a sequence of event-locked ERPs with invariable latency and shape, in addition to a noise, which can be approximated by a zero-mean Gaussian random process that is uncorrelated between trials and not time-locked to the event. The average power of the ERP signal is given by the expected value of its energy. When a signal is a stationary stochastic process, its power is defined to be the value of its correlation function at the origin. As the noise is supposed to be a stationary zero-mean Gaussian random process, its mean and variance do not vary with respect to time. Then, the correlation function at the origin is equal to its variance. The SNR of the EEG increases proportionally to the number of trials, and an excessive number of epochs will not result in significant changes in the ERP curve.
Radiographic Imaging
Eric Ford in Primer on Radiation Oncology Physics, 2020
The signal-to-noise ratio (SNR) is an important parameter and represents a key concept. Equation 19.2 suggests that as more photons are registered in the detector, the signal-to-noise ratio gets larger. That is, the image becomes less noisy. The design of the detector influences the number of photons. One could, for example, make the conversion layer like the copper plate thicker (Figure 19.1.4B), resulting in more photons. One could also make the scintillator thicker or use more sensitive material. All of these steps would improve the detective quantum efficiency (DQE) of the detector, a measure of the number of optical photons produced for each X-ray photon that enters. There are trade-offs however. Making a thicker conversion layer or scintillator results in a “cloud” of photons or particles that is spread out over a larger area. This blurs out the image and makes the resolution lower. These trade-offs are quantified through a metric called the modulation transfer function (MTF). A description of the MTF is beyond the scope of this text, but it essentially describes the responsiveness of the detector as a function of the frequency of features in images, i.e. the spatial resolution.
Intensity and Power Needed in Diagnostic Ultrasound
Marvin C. Ziskin, Peter A. Lewin in Ultrasonic Exposimetry, 2020
Sources of noise include those which originate in the patient and those which originate in the instrument. Speckle is a noise component produced by the random distribution of scatterers in most organs. It can be reduced only by averaging methods such as compounding or frame averaging which allows some tissue motion to change the speckle pattern between frames. Generally, averaging methods require more imaging time or increased power through increased pulse repetition rate. There are other body-produced noise sources in which the signal-to-noise ratio does not improve with a simple increase in power or intensity. Reverberation and multiple scattering are important examples of this type of noise, as is refractive and diffractive beam dispersal, discussed near the end of Section II. Where these noise sources obscure the desired signal, a simple decrease or increase in pulse voltage may not hurt nor help the image quality at all. Although in many anatomical situations these noise sources limit tissue discrimination well before receiver electronic noise does, there are ways of reducing these noise levels, such as reducing impedance mismatches at the body surface or correcting for refraction and other phase abberations.29 Furthermore, it has not been demonstrated in any broad ranges of situations or applications that these types of noise are consistently dominant.
Manganese-containing polydopamine nanoparticles as theranostic agents for magnetic resonance imaging and photothermal/chemodynamic combined ferroptosis therapy treating gastric cancer
Published in Drug Delivery, 2022
Zhian Chen, Zhenhao Li, Chuangji Li, Huilin Huang, Yingxin Ren, Zhenyuan Li, Yanfeng Hu, Weihong Guo
The morphology and elements mapping of NPs were characterized by transmission electron microscopy (TEM) (JEOL JEM-2100F TEM, Tokyo, Japan). The chemical state and composition were characterized by X-ray photoelectron spectroscopy (XPS) (ESCALAB250Xi, Thermo Fisher, Waltham, MA). Electron spin resonance (ESR, JEOL, Ltd., Tokyo, Japan) was used to measure the production of •OH. The Mn content in the PP@Mn NPs was determined by inductively coupled plasma mass spectrometry (ICP-MS) (Optima7300DV, PerkinElmer, Waltham, MA). A Shimadzu UV-2600 UV-vis spectrophotometer (Kyoto, Japan) was used to acquire ultraviolet (UV)–vis absorption spectra. The hydrodynamic diameter and zeta potentials were measured using a Zetasizer Nano ZS (Malvern, Worcestershire, UK) by dynamic light scattering (DLS). The powder X-ray diffraction (XRD) patterns were acquired on a PANalytical X’Pert PRO X-ray diffractometer. The photothermal capability was assessed used an 808 nm semiconductor lasers (Shanghai Xilong Optoelectronics Technology Co., Ltd., Shanghai, China). Relaxivity of different PP@Mn NPs concentrations (0, 125, 250, 500, and 1000 μg/mL) was placed in tube holders for measurements by a 3.0-T Philips Achieva clinical MRI scanner (Philips Healthcare, Best, The Netherlands). The signal-to-noise ratio (SNR) was defined as: SNR = SImean/SDnoise. Infrared (IR) thermal images were acquired using an IR thermal camera (FLIR E50, Wilsonville, OR).
Simultaneous bilateral stapes surgery after follow-up of 13 years
Published in Acta Oto-Laryngologica, 2021
Topi Jutila, Ville Sivonen, Timo P. Hirvonen
Pure-tone audiograms alone are insufficient to depict hearing abilities in everyday noisy environments. This has given rise to various tests that assess speech recognition in background noise. While a conductive hearing loss attenuates the levels of both the speech signal and noise, a SNHL impairs speech understanding even though audibility is compensated by increasing the levels. Therefore, in SNHL, a higher signal-to-noise ratio (SNR) is required to retain speech understanding [5]. Furthermore, speech-in-noise tests can be utilized to assess binaural hearing abilities by measuring speech recognition thresholds (SRTs) in noise for co-located and spatially separated speech and noise configurations. The improvement in SRT by presenting the speech signal and noise from different directions with respect to the listener is denoted as spatial release from masking (SRM). SRM is largest when speech and noise emanate from different acoustic hemifields, and in excess of 6 dB when comparing SRTs in noise for co-located speech and noise in the front with moving the noise source at 90 degrees on either side of the listener [6,7].
Evaluation of a game-based hearing screening program for identifying hearing loss in primary school-aged children
Published in International Journal of Audiology, 2023
Patrick Bowers, Kelley Graydon, Gary Rance
The speech-in-noise game is designed to be sensitive to SPD. A target English language speech signal (an object’s name) is applied to both ears at a 0° azimuth to the head (using a head-related transfer function). Simultaneously, distractor speech signals (a story) using the same voice are applied to both ears using head-related transfer functions (at a ±90° azimuth to the head). The signal-to-noise ratio (SNR) is decreased by 2 dB for a correct response and increased by 2 dB for no response or 4 dB for an incorrect response. A correct response consists of the child tapping the correct object named by the talker. The result of this test is a speech reception threshold (in noise), which is the average SNR the child required for them to correctly identify 50% of the target words following a practice phase (Dillon et al. 2018).
Related Knowledge Centers
- Coefficient of Variation
- Signal Transduction
- Imaging
- Expected Value
- Standard Deviation
- Distortion
- Coefficient of Variation
- Image
- Sensitivity Index
- Lock-In Amplifier
- Optical Spectrometer