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Introduction
Published in Narayan Panigrahi, Saraju P. Mohanty, Brain Computer Interface, 2022
Narayan Panigrahi, Saraju P. Mohanty
Electroencephalography (EEG) is the physiological method to record the electrical activity generated by the brain. EEG is measured through electrodes placed on the surface of the scalp. For faster application, electrodes are mounted in elastic caps similar to bathing caps, ensuring that the data can be collected from identical scalp positions across all respondents.
Artificial Intelligence in Systems Biology
Published in P. Kaliraj, T. Devi, Artificial Intelligence Theory, Models, and Applications, 2021
S. Dhivya, S. Hari Priya, R. Sathishkumar
Recent advancement in biomedicine and medical informatics has laid the foundation for the evolution of complex biomedical systems. Implementation of machine learning (ML) algorithms in biomedicine help in disease diagnosis, biomedical data processing, analyzing the function of living organisms, and biomedical research. In disease diagnosis integration of machine learning algorithms, Point-of-Care Testing (POCT), and biochips can easily spot cardiac ailments at a very early stage (Rong et al., 2020). AI can also be used to analyze the survival rate of cancer patients. In biomedical imaging, AI technology can be implemented with electroencephalography (EEG) for an exact prediction of the epileptic seizure (Usman and Fong, 2017). Apart from this, AI technology is adapted to process huge complex clinical data, by incorporating logical reasoning and providing valuable conclusion within a short period.
Analyzing the effect of video media on emotion using a VR headset platform and physiological data
Published in Shin-ya Nishizaki, Masayuki Numao, Jaime Caro, Merlin Teodosia Suarez, Theory and Practice of Computation, 2019
Hayato Uraji, Taweesak Emsawas, Juan Lorenzo Hagad, Ken-ichi Fukui, Masayuki Numao
Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity of the brain. And it is typically noninvasive, with the electrodes placed along the scalp. The latter analyzes the type of neural oscillations (popularly called “brain waves”) that can be observed in EEG signals in the frequency domain. Brainwaves are produced by synchronized electrical pulses from masses of neurons communicating with each other.
Human cognition and emotional response towards visual environmental features in an urban built context: a systematic review on perception-based studies
Published in Architectural Science Review, 2023
Table 1 represents the meta-analysis of the data from the selected articles that followed an empirical study. For point score generation, one point is given to the symbol * in Table 1. The table plots the research status based on the search criteria. The section ‘medium’ represents the simulated environment used for the experimental process. In contrast, the other medium, such as VR, represents the virtual reality-based environment, ‘image’ for photos or 2D visual simulations, and ‘video’ for ordinary moving images. The 3D videos indicate rendered videos, while the medium ‘environment’ indicates the experiment that represents real space. The literature review highlights studies that considered specific environmental parameters in its investigation identified from the literature surveys. The section ‘cognition’ shows the studies performed using an electroencephalography (EEG) device to measure the participant’s neural responses. The researchers also considered electrodermal activity (EDA) and heart rate variability (HRV), which measures the physiological variations of participants. Similarly, it highlighted perception-based studies that employed eye-tracking devices to explore gaze behaviour.
A device to detect leakage at the patient end of total intravenous anaesthesia
Published in Journal of Medical Engineering & Technology, 2022
Rajkumar Chandran, Kalindi De Sousa, Seok Hwee Koo, Yin Yu Lim, Lei Shang, Fleming Paiputra, Joanne Huishan Tan, Terry Tsz Him Ching, Xiaojuan Khoo
The use of total intravenous anaesthesia (TIVA) has become increasingly practical and widely established throughout the world, especially in the arena of paediatric anaesthetic practice [1]. Its increased usage was attributed to progress in pharmacological understanding and the availability of modern systems facilitating its administration [2]. However, pharmacological monitoring of drug delivery is not possible with TIVA [3], loose connections between syringes, taps, extension tubing, and intravenous cannulas can result in loss of anaesthetic agent [4], the cannula being used for TIVA is often not visible [3], and alarms present on the current commercially available TIVA or target controlled infusion (TCI) pumps do not highlight the disconnections at the patient end. The leaks are only recognised very late, often leading to awareness. Electroencephalography (EEG)-based devices for monitoring brain electrical activity may be applied as a tool to aid in preventing intraoperative awareness.
Investigation of an EEG-based Indicator of Skill Acquisition as Novice Participants Practice a Lifeboat Maneuvering Task in a Simulator
Published in International Journal of Human–Computer Interaction, 2020
Rifat Biswas, Brian Veitch, Sarah D. Power
Most of these studies have employed modern neuroimaging technologies like functoinal magnetic resonance imaging (fMRI) and positron emission tomography (PET), which are well-suited for studying neural changes in response to practice or repeated exposure to tasks as they have excellent spatial resolution and can be used to image deep brain structures. However, these technologies are not suited for use in a BCI due to practical limitations (e.g., cost, size, imaging procedure). Electroencephalography (EEG) is a functional imaging technology that records neuroelectrical activity via electrodes placed on the scalp. While it has relatively poor spatial resolution as compared to fMRI and PET, and cannot reliably image deep brain structures, its portability, excellent temporal resolution, and relative affordability make it an excellent candidate for BCI applications.