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Methods to Detect Blink from the EEG Signal
Published in Narayan Panigrahi, Saraju P. Mohanty, Brain Computer Interface, 2022
Narayan Panigrahi, Saraju P. Mohanty
An electroencephalogram (EEG) is a measure of the electrical signals of the brain of a human being. It is a readily available test that provides the evidence of how the brain functions over time. Brain computer interface (BCI) is a collaboration between a brain and a device that enables EEG signals from the brain to control some external activity, such as control of a cursor or a prosthetic limb (Roy et al 2011). The interface enables a direct communication pathway between the brain and the object to be controlled. Electrooculography (EOG) is a technique for measuring the corneo-retinal standing potential that exists between the front and the back of the human eye. The resulting signal is called the electrooculogram. Tracking the movement of the eye through sensors enables us to compute and fix the position where one's eyes are focused (Panigrahi et al 2019). Study of the EOG can determine presence, attention, focus, drowsiness, consciousness, or other mental states of the subject (TejeroGimeno et al 2006; Liu et al 2013; Lin et al 2005). Event related potential (ERP) is a small voltage generated in the brain due to the occurrence of a specific event or stimuli. ERPs can be reliably measured from an EEG.
The Multi-Aspect Measurement Approach: Rationale, Technologies, Tools, and Challenges for Systems Design
Published in Pamela Savage-Knepshield, John Martin, John Lockett, Laurel Allender, Designing Soldier Systems, 2018
Kelvin S. Oie, Stephen Gordon, Kaleb McDowell
Electrooculogram The tracking of eye movements, including gaze and fixation behavior, blink rate, and pupillary responses can provide valuable measurements of attention allocation (Fairclough and Venables 2006) and cognitive and fatigue state (Stern, Boyer, and Schroeder 1994). The electrophysiological technique for recording eye activity, electrooculography (EOG), is based upon the existence of a consistent electrical potential between the cornea and the retina of the eye (Andreassi 2000). As the eye rotates about its axes, the voltage difference causes measurable changes in the potential across each axis. EOG measurements, therefore, are made by placing electrodes across the eyes in both the horizontal and vertical directions. Figure 11.6 illustrates a simple layout for recording horizontal eye movements. Placing an additional electrode between the eyes is helpful in differentiating the independent movements of the eyes that occur during vergence motions.
Working hours and sleep
Published in Karl H.E. Kroemer, Fitting the Human, 2017
The brain and the muscles are the human organs that show the largest changes from sleep to wakefulness: their electrical activities have allowed for well-established techniques of observation. Electrodes attached to the surface of the scalp can pick up electrical activities of the brain, encephalon. Thus, the name of this measuring technique is electroencephalography (EEG). The EEG signals provide some general information about brain activities. The other common technique records the electrical activities associated with the muscles that move the eyes and those in the chin and neck regions. The recording of eye activities is called electrooculography (EOG). Both techniques (already mentioned in Chapter 9) are often applied together to record and describe events during sleep. EEG signals during sleep
Gaze Interaction With Vibrotactile Feedback: Review and Design Guidelines
Published in Human–Computer Interaction, 2020
Jussi Rantala, Päivi Majaranta, Jari Kangas, Poika Isokoski, Deepak Akkil, Oleg Špakov, Roope Raisamo
In addition to VOG, eye movements can also be detected by electro-oculography (EOG), based on the cornea-retinal potential difference (Majaranta & Bulling, 2014). This method is most useful in detecting relative eye movements when the exact point-of-gaze is not needed. This is because the accuracy of the absolute gaze point position is not high. Earlier versions of EOG trackers were invasive, as they required sticky electrodes to be placed on the skin around the eyes. Most recent implementations hide the contact points, for example, to the nosepiece of eyeglass frames (Ishimaru et al., 2014) or to earpods (Manabe, Fukumoto, & Yagi, 2015), making the EOG a viable alternative to VOG. However, in our studies, we used the VOG-based eye tracking.
The circadian effect on psychophysiological driver state monitoring
Published in Theoretical Issues in Ergonomics Science, 2021
Sylwia I. Kaduk, Aaron P. J. Roberts, Neville A. Stanton
Electrooculography (EOG) is a measure of the ocular behaviours through the resting potential of the retina, measured through the difference between potential on the retina and cornea (Siddiqui and Shaikh 2013). Similarly, to eye-tracking, it provides data about blinks and horizontal eye movements, but it does not show changes in the pupil size. The states that could be measured with EOG were drowsiness (Borghini et al. 2014), fatigue (Lal and Craig 2001), sleep (Oken, Salinsky, and Elsas 2006) and mental workload (Richter et al. 1998). The increased mental workload was associated with decreased blinking rate and blinking duration (Maglione et al. 2014). Drowsiness was reported to be correlated with the decreased saccadic eye-movements, increased slow eye-movements, increased blinking duration, delayed lid opening, and decreased lid closure (Borghini et al. 2014; Schleicher et al. 2008). It was also identified with PERCLOS (Papadelis et al. 2007). Two papers reported an increase of blinking rate due to drowsiness (Borghini et al. 2014; Papadelis et al. 2007), while one reported a decrease (Minhad, Ali, and Reaz 2017). Fatigue was reported to be associated with the increased blinking speed, the disappearance of saccadic eye movements, and an increase of PERCLOS (Lal and Craig 2002; Rodríguez-Ibáñez et al. 2011). One paper reported an increase in the blinking rate (Stern, Boyer, and Schroeder 1994), while one a decrease (Morris and Miller 1996) as an indicator of the fatigue. Sleep was identified with slow eye movements (Oken, Salinsky, and Elsas 2006). Most of the results were consistent with eye-tracking data except for the reported decrease of saccades number that contradicted the finding of Wang et al. (2017), however, saccades are very fast movements and their detection might depend on the sampling rate of the device.
Developments in the human machine interface technologies and their applications: a review
Published in Journal of Medical Engineering & Technology, 2021
Harpreet Pal Singh, Parlad Kumar
Electroencephalography (EEG) and electromyography (EMG) are two highly significant types of bioelectrical signal monitoring and recording methods. The signals generated by the brain by the phenomenon of pushing the ions of calcium, potassium, sodium and chlorine through the neuron membranes in the direction commanded by the membrane potential are collected by EEG [8–11]. Whereas, the signals produced by skeletal muscles through the muscular contractions caused by the potential difference across the muscle sarcolemma are evaluated and recorded by EMG [12]. These signals are characterised by their respective spatial and temporal resolutions. The EEG signals are used for brain-controlled interface systems such as assistive robotic devices and wheelchairs, while EMG signals are mainly used for prosthetic controls [13,14]. Electrooculography (EOG) is another important type of signal recording technique for measuring the corneo-retinal standing potential that exists between the front and the back portions of the human eye. These signals can be used by a paralysed person to control the EOG based motorised wheel chairs [15]. It is now possible to use all these signals in combination to give multiple instructions to a machine [16]. The movements of the head and hands, eye blinking, and other gesture controls can be used as inputs to the HMI systems by using tactile sensor technologies [17,18]. The gadgets like smartphones, computers, smart watches, video games, smart games and other commonly used applications are based on tactile sensor technology [19,20]. The increasing trend of wearable sensors with predefined touch control strategies using tapping, sliding and the combinations of mechanical contact is mostly done by using the fingers on the surface of sensors by proximity sensing, which provides easy to use HMI systems [17,21]. Many applications are based on the piezoelectric or triboelectric effect of the material in which a small electrical current is generated by mechanical stimulation, which is utilised for the application control of the devices by voice commands and virtual reality glasses inputs [22,23].