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The Coupling of Atmospheric Electromagnetic Fields with Biological Systems
Published in Shoogo Ueno, Tsukasa Shigemitsu, Bioelectromagnetism, 2022
Tsukasa Shigemitsu, Shoogo Ueno
There has been the speculation of the similarity between EEG rhythms and SR. The most common frequencies of human brain waves include α, β, δ, and θ. The α wave is the major rhythm in a normal relaxed condition. The β wave reflects active processing. The δ wave is the rhythm that occurs in a deep dreamless sleep or unconsciousness. The θ wave is associated with drowsiness. When healthy adults relax with their eyes closed, brain waves of 8–12 Hz frequency and about 5–100 μV can be measured (α waves). The α wave is the main component of brain waves of humans with β waves (13–30 Hz, 5–30 μV) being another component, representing normal alert mental state. The δ wave activity declines during deep sleepiness, and 4–7 Hz low voltage slow waves (θ waves) appear, representing dreaming states. The human electrical activity occurs in a frequency range below 50 Hz. It has been noted that the form of brain waves is similar to the SR waves. If one compares α and δ waves with the record obtained from the electric field in ELF range, there are similarities between α wave and type I signal, and between δ waves and type II signal (König et al., 1981). Under similar conditions, brain waves in the same frequency ranges are spontaneously observed for all vertebrates.
Introduction to Neural Networks for Signal Processing
Published in Yu Hen Hu, Jenq-Neng Hwang, Handbook of Neural Network Signal Processing, 2018
How do we use the signals obtained from various measurements? Simply put, a signal carries information. Based on building temperature readings, we may turn the building’s heater on or off. Based on a stock price quote, we may buy or sell stocks. The faint radiation from a distant galaxy may reveal the secret of the universe. Brain waves from a human body may be used to communicate and control external devices. In short, the purpose of signal processing is to exploit inherent information carried by the signal. More specifically, by processing a signal, we can manipulate the information by injecting new information into the signal or by extracting inherent information from the signal. There are many ways to process signals. One may filter, transform, transmit, estimate, detect, recognize, synthesize, record, or reproduce a signal.
Measurement of Brain Activity Using Optical and Electrical Methods
Published in Yunhui Liu, Dong Sun, Biologically Inspired, 2017
Atsushi Saito, Alexsandr Ianov, Yoshiyuki Sankai
On the other hand, there are methods using portable devices, such as electroencephalograms (EEGs) and functional near-infrared spectroscopy (fNIRS). EEG is a method that measures brain activity using electrical brain waves that propagate through the scalp (Sanei and Chambers 2007). Brain waves can be measured using a small, portable device, so an EEG is suitable for daily use. EEG signals are, however, susceptible to noise. Bioelectrical signals originating from eye movements, facial muscular movement, and external power sources such as electronic devices are common noise sources. Furthermore, due to the fact that the electrical signals produced by the brain have to travel through the skull and cerebrospinal fluid, it is difficult to determine the origin of the signal.
Brain activity during a working memory task in different postures: an EEG study
Published in Ergonomics, 2020
Ju-Yeon Jung, Hwi-Young Cho, Chang-Ki Kang
Beta and gamma waves are classified as high-frequency brain waves, and they are found during states of high alertness or awakening. Both waves are known to be higher during upright posture than supine in frontal and occipital regions, and significantly higher during sitting postures than supine in central regions (Chang et al. 2011; Thibault et al. 2014). The present study found similar results, possibly due to different impacts of gravity during supine, sitting, and standing postures. Gravity stimulates the arterial baroreceptor of the heart, and the brainstem modulates ANS activity to control the heart rate (Mohrman and Heller 2014), thereby affecting brain waves (Chang et al. 2011). Delta and theta waves increase according to parasympathetic nerve activity during supine, and beta and gamma waves increase according to sympathetic nerve activity during upright postures (Chang et al. 2011; Mohrman and Heller 2014; Schneider et al. 2008).
Medical textiles
Published in Textile Progress, 2020
Prosthetics for amputees are critical in rehabilitation. There have been several advances over the years. There are broad categories; passive devices, body-powered designs and externally powered designs. Take for example, the hand. In a hand, the thumb provides approximately 40% of hand function, the index and middle finger 20% and the ring and little finger 10%. Opposition is critical for normal hand function and the reason why loss of a thumb is so detrimental to hand function. With advances in biomaterials and engineering design, the ability to provide critical grips, such as opposition, three-digit hands and multi grasp anthropomorphic hands have seen evolutions in upper limb prosthetics [628, 629]. Electrodes placed on functioning muscle units allows prosthetics to be driven by myoelectric activity which allows a prosthesis to mimic the previous functioning limb. Prosthetic fingers can then be covered with materials resembling natural skin. Examples of prosthetics include ProDigits (Optimus Prosthetics, Columbus, OH, USA) and iLIMB (Touch Bionics, Mansfield, MA, USA). Research has been directed at the use of direct brain-wave control for operating prosthetics. Cerebral control has the major advantage that it bypasses the peripheral nervous system in the remaining limb, which may be damaged [630]. Another avenue of interest is whether prosthetics can be directly implanted into a stump.
Brain–Computer Interface Games Based on Consumer-Grade EEG Devices: A Systematic Literature Review
Published in International Journal of Human–Computer Interaction, 2020
Gabriel Alves Mendes Vasiljevic, Leonardo Cunha de Miranda
Brain waves can be measured in a relatively simple way, using electrodes placed on the scalp. This reading and measuring of brain waves is called electroencephalography, or EEG. EEG is the most used measurement method of brain waves, for its non-invasive (does not require implants nor surgeries) and simple nature (Marshall et al., 2013). However, the captured signals are very weak and of poor quality, as they need to cross several layers of tissues—such as the meninges (i.e., dura mater, arachnoid and pia mater), the skull and the scalp—before being captured by the electrodes. For this reason, it is often necessary to use several electrodes to have a higher spatial resolution and a more precise system. Figure 1 represents the several layers of tissues that the brain wave must travel before being captured by the electrodes in the scalp.