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Study and Analysis of the Visual P300 Speller on Neurotypical Subjects
Published in Mridu Sahu, G. R. Sinha, Brain and Behavior Computing, 2021
Mridu Sahu, Vyom Raj, Shreya Sharma, Samrudhi Mohdiwale
Brainwaves are classified according to their frequencies and have been labelled under five different categories according to the division of bandwidth [44,45]. These are described herewith:Infra low waves (frequency range less than 0.5 Hz). They are the basic rhythms that underlie all our brain functions. They have not been studied deeply because of their low frequency which makes them difficult to detect.Delta waves (frequency range 0.5–3 Hz). They are low frequency and highly penetrating waves that are observed during deep meditation and dreamless sleeps. Healing and regeneration are stimulated in this state.Theta waves (frequency range 3–8 Hz). They are the semi-awake state waves and the times of drifting to sleep or getting awake.Alpha waves (frequency range 8–12 Hz). They regulate over-all mental coordination, calmness, and alertness. They basically determine the relaxed attentive states.Beta waves (frequency range 12–38 Hz). They dominate our nor-mal waking state of consciousness. They direct attentiveness towards cognitive works and the outer world.
Time and Frequency Representation of Continuous Time Signals
Published in Afshin Samani, An Introduction to Signal Processing for Non-Engineers, 2019
This intuition is correct. Parseval’s theorem mathematically shows that the calculated signal energy in the time domain is directly related to its energy in the frequency domain. This is quite interesting because the energy of a signal in a certain frequency band may reflect a specific phenomenon. For example, in the context of and electroencephalogram (EEG) representing the electrical activity of the brain, alpha waves have a frequency band of 8 to 12.99 Hz, and they are dominant in the wakeful state, but in a coma state, they are diffused (Rana, Ghouse, and Govindarajan, 2017). Thus, the average signal energy in a unit of time is called the signal power.
Introduction
Published in Narayan Panigrahi, Saraju P. Mohanty, Brain Computer Interface, 2022
Narayan Panigrahi, Saraju P. Mohanty
Alpha waves are the “frequency bridge” between our conscious thinking (beta) and subconscious (theta) mind. They are known to help calm you down and promote feelings of deeper relaxation and content. Beta waves play an active role in network coordination and communication and do not occur until three years of age in humans. In a state of stress, a phenomenon called “alpha blocking” can occur, which involves excessive beta activity and little alpha activity. In this scenario, the beta waves restrict the production of alpha because our body is reacting positively to the increased beta activity, usually in a state of heightened cognitive arousal.
Using Brain -Computer Interface to evaluate the User eXperience in interactive systems
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2023
Sandra Cano, Jonathan Soto, Laura Acosta, Victor M. Peñeñory, Fernando Moreira
In Figures 3 and 4 show the values averaged by types of bands and sub-bands obtained for the theta, alpha, beta, and delta channel and for the two interactive systems. The relative energies are calculated by dividing them by the total energy of the signal. Figure 2 shows the decomposition sub-bands used: delta sub-band (A6, 0-4 Hz), theta sub-band (D6, Hz), alpha sub-band (D5, Hz), beta sub-band (D4, Hz). Alpha waves arise when a person is relaxed but conscious. The asymmetry of Alpha waves in the frontal lobe (Fp1, Fp2, F3 and F4) reflects the valence of emotions. Therefore, it plays an essential role in the study of EEG signals (Pane et al. 2018). Whereas Beta waves occur when the human mind is active and highly concentrated. Beta waves in the frontal lobe can reflect emotional valence. Thus, there is a relationship between Alpha and Beta waves, which reflect the active state of the brain (Bos 2012).
Feature analysis for drowsiness detection based on facial skin temperature using variational autoencoder : a preliminary study
Published in Quantitative InfraRed Thermography Journal, 2022
A. Masaki, K. Nagumo, K. Oiwa, A. Nozawa
The measured physiological indices were the following: facial skin temperature (FST), electroencephalograms (EEG) as brainwaves. The bioinstrumentation system consisted of an infrared thermography device (A-615, FLIR, America) and wireless biological measuring equipment (Polymate Mini AP108, TEAC Co., Japan). The infrared thermography device was set at a distance 100 cm from the face. Thermal images were created at 1-s sampling intervals. The size of each thermal image was 640 × 480 pixels, and the temperature resolution was less than 0.1°C. The infrared emissivity of the skin was ε = 0.98. The infrared thermography image sensor used in the experiment was an uncooled microbolometer type. The spectral wavelength is 7.5 14 μm. The infrared thermography camera was turned on at least 20 minutes before the start of the experiment to ensure stability. The experiment was started after confirming that the measured temperature values did not deviate from the general skin temperature. The wireless biological measuring equipment recorded the EEG with a sampling frequency of 500 Hz. To evaluate relative an alpha waves, EEG was recorded by a referential electrode derivation method. The EEG electrode was fixed at parietal (Pz) positions according to the international 10–20 system. The right ear lobe (A2) was used as a reference. Before data acquisition, the contact impedance between the EEG electrodes and scalp was calibrated to be less than 10 kΩ. Figure 1. shows the experimental image.
Using brain waves to assess the colour effect on promoting spirituality in the mosque architecture
Published in Architectural Science Review, 2022
As previously stated, EEG signals are categorized into five various wave types ‘alpha, beta, theta, delta, and gamma’ (Basar 2012). Delta waves are located in a range of 0.5-3 Hz. People in the delta wave state are lethargic, immobile, inattentive, and have a low level of arousal. Theta waves, the rate of changes is between 4 and 7 Hz. Theta waves are slow waves with a sinus rhythm. Theta is associated with emotion, creativity, deep thinking. The alpha signals’ frequency is from 8-12 Hz. Alpha waves are associated with relaxation, alertness, and concentration. They are often characterized by creativity and dream thinking. This wavelength is observed when a person is relaxed. Beta waves are created in a range of 13-30 Hz. The beta frequency wave is also the fastest and most active form of short-wave brain waves and is related to intellectual activity, concentration, and attention. The gamma waves fluctuate in frequencies beyond 30 Hz and are observed more during the cross quality of sensory processing. It is also known to accommodate short-term memory of objects, sounds, or sense of touch using gamma rays. (Kamal, Mahmood, and Zakaria 2013)