Name: using electroencephalography measurements and high-quality video recording for analyzing visual perception of media content
Uploaded: 2018-05-26T14:00:00
Description: Watch this Scientific Journal Video about Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content at JoVE.com

The present study has been supported by a Spanish Ministry of Economy and Competitiveness (BFU2014-56692-R and BFU2017-82375-R) grants.

All methods described here have been approved by the Ethics Commission for Research with Animals and Humans (CEEAH) of the Universitat Aut&#242;noma de Barcelona.
1. Creation and Presentation of the Visual Stimuli
<ol>
	<li>Create the video stimuli according to the desired goals.
	<ol>
		<li>Decide which variables are of interest for the video stimuli. 
		NOTE: For example, in the present investigation, the main variable of interest is the editing style.
		<ol>
			<li>Decide the duratio...

<ol>
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A method for analyzing visual perception of media content with purpose-made video creation is described here. Many other studies attempt to analyze the perception of media content in narrative contexts with pre-existing films. The present method proposes to create visual content with a narrative construction following the criteria of interest, and is based on the suggestion that eyeblink rate is connected to the viewer's attention9. For that reason, the study detects participants' eyeblinks while ...

The Purpose of This Method
This method proposes a dual protocol for detecting eyeblinks. The aim is to analyze viewers&#39; visual perception of media content, specifically created for this investigation, by using EEG recordings and HD video recording systems.
The Rationale Behind the Development and/or Use of This Method
Each eyeblink hides visual flow for 150-400 ms1,2. Blinking has physiological3,4,5 and psychological6,7 functions. The connection between attention and eyeblink rate has been studied and proven in different studies8. A higher level of attention decreases eyeblink rate and according to previous studies, humans share a mechanism for controlling the timing of blinks that searches for the best moment to avoid loss of important visual information9. Thus, analyzing eyeblink behavior of viewers when watching screens could provide information regarding the level of attention given to media contents.
One method for detecting spontaneous eyeblink rate is by using EEG electrodes to record the electrical activity. Eyeblinks can easily be detected by prefrontal and electrooculogram electrodes connected to an EEG recording system. In most EEG analyses, eyeblinks are considered artifacts. For this reason, many software packages designed for analyzing EEG data have eyeblink detectors10. The advantage of using EEG for detecting eyeblinks is the high temporal resolution (in the order of milliseconds) and the possibility of registering brain effects of different narratives and cuts in movies synchronized with those eyeblinks - a matter open to further study. Recording participants&#39; faces with an HD camera can also be useful for matching/contrast purposes9.
The Advantages over Alternative Methods with References to Relevant Studies
There are multiple methods for counting eye blinks. Some dedicated instruments for detecting blinks are magnetic coils, infrared (IR) light beams, optoelectronic motion detectors with eye movement analysis such as eye-tracking techniques, and several techniques based on bioelectrical signals, e.g., electrooculography (EOG), electromyography (EMG), and EEG. Another more accurate, but time-consuming option is manually counting blinks from a frame-by-frame video recording11. The technologies today can be classified broadly into two groups: a) contact-free recording which includes two modalities, the direct blink detection using computer vision and offline blink detection using eye-tracking, and b) contact-based recording using biological signals through EOG and EEG devices12,13.
The eye-tracking system is a widely used technology, ranging from traditional image-based passive designs to the active near-infrared-based approaches mainly used today with a high-resolution camera. The latter exploits the reflective properties of the pupil under IR illumination14. The concept underlying modern eye-tracking methods is Pupil Center Corneal Reflection (PCCR), which involves a camera tracking the center of the pupil, where light reflects from the cornea. However, there is a lack of blink detection algorithms published for eye-tracking protocols. Moreover, although the different models of eye-tracking on the market provide integrated software with blink detection, the source code is not always provided by manufacturers, making it difficult to modify or know how the algorithms work12. Also, during experiments with eye-tracking there are events that cause data loss, such as tracking delays and significant head or gaze movements. The eye area is very small in video captures, which is a problem for calculating the duration of the blink, and which sometimes introduces various types of artifacts15.
In this experiment, EEG and EOG methods are used. EEG is not usually used alone to detect eyeblinks. However, analyzing eyeblinks recorded with EEG electrodes is a standard procedure for the study of eyelid displacements. This procedure enables researchers to have information of exactly when eyeblinks take place. The most common signal pattern for detecting blinks is that of peak points, representing vertical movement responses. There are several peak detection algorithms applicable to raw EEG, time-domain, or frequency-domain signals. Processes involved in peak identification are peak detection, feature extraction, and classification. Eyeblinks have a considerable effect on frontal channels of the EEG signal. Typically, eyeblinks are detected in EEG by using a pre-determined amplitude threshold16. The algorithms in the analysis software used in this experiment are based on the signals&#39; standard deviation and the root mean square (RMS) of the pre-filtered EEG signal; they are open source and available to the scientific community17. However, some eye movements not involving eyeblinks can provoke electrical activity that may be confusing. For that reason, a second method - recording viewers&#39; faces with an HD video camera - allows researchers to match eyeblinks by manually counting them. With such a double method, the investigator achieves a matrix of eyeblinks that can be easily analyzed with statistical tools.
Therefore, the proposed method performs a data triangulation with two different sources to validate the detected eyeblinks. This method is based on Nakano et al. indications9 for confirmation. At the same time, it also enables researchers to collect brain-activity and frequency-band information for further analysis. The experiment described here is part of a wider future investigation into the effects of editing-style cuts on occipital and prefrontal brain areas.
Determine Whether the Method is Appropriate for an Investigation
This experimental protocol enables viewers&#39; eyeblinks while watching video content to be studied under three experimental conditions. First, eyeblink rate is detected by using two complementary techniques: EEG and recorded HD videos. Here, we use a wireless EEG with 20 channels. Second, specific stimuli adapted to the experiment are created, so that the researcher can manage all the variables of the visual content. Here, three videos with the same narrative but different video-editing style were created. The narrative consisted of a man who entered a room, sat at a desk, juggled with three balls, opened a laptop, looked up information in some books, typed something on the laptop, closed it, ate an apple, looked directly into camera, and left the room. The three video stimuli last 198 s each. The first was a one-shot movie; the second was edited according to classical Hollywood-style rules with 33 different shots; and the third was edited following MTV-style rules with 79 shots. A fourth stimulus was also presented in which the narrative was identical, but the format was a real representation with an actor instead of a video. This fourth non-video stimulus was not used in an initial study of editing-style differences but was used in a different investigation to compare eyeblink-rate differences between real representation and screened media8. Third, different groups of participants are selected depending on their previous expertise in the visual analysis of videos. The purpose is to determine differences in eyeblink rates of subject groups watching the same visual stimuli. In this case, 40 subjects took part in the investigation. Half of them were media professionals (16 males and 4 females; age 30-56 years, with an average age of 44.15 &#177;7.15 years) and the rest were non-media professionals (15 males, and 5 females; age 28-56 years, with an average age of 43.25 &#177; 8.59 years). Media professionals were chosen with the criterion of more than 6 years of experience in making decisions related to media editing in their everyday work.

<table border="0" cellpadding="0" cellspacing="0" width="1126">
	<tbody>
		<tr height="40">
			<td height="40" style="height:40px;width:276px;">EEG Device</td>
			<td style="width:279px;">Neurolectrics</td>
			<td style="width:344px;">Enobio 20 EEG/EMG system&#160;</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Ag/AgCl Electrodes</td>
			<td>Neuroelectrics</td>
			<td>[NE022b] GelTrode</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Recording EEG software</td>
			<td>Neuroelectrics</td>
			<td>NicOffline software</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">HD-video camera</td>
			<td>Sony Corporation&#160;</td>
			<td>Sony HDR-GW55VE</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Syringe</td>
			<td>Monoject</td>
			<td>Monoject 412, curved tip syringe, 50/box</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:276px;">Saline electrode EMG gel</td>
			<td>Signa-Gel</td>
			<td>X32-204: Signa Gel</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Visual Stimuli Presentation Software</td>
			<td>Paradigm Stimulus Presentation</td>
			<td>Perception Research System Incorporated</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="50">
			<td height="50" style="height:51px;">EEG software analysis</td>
			<td style="width:279px;">Centre National de la Recherche Scientifique and Montreal Neurological Institute</td>
			<td>Brainstorm3</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">EEG software analysis</td>
			<td>The MathWorks Inc.</td>
			<td>MATLAB 2013b</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">TV for video presentation</td>
			<td>Panasonic Corporation</td>
			<td>PanasonicTH- 42PZ70EA&#160; - 50&#34;</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">PC for presenting stimuli</td>
			<td>MacBook Air</td>
			<td>Year 2013, running Mac OSX Mountain Lion</td>
			<td style="width:227px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">PC for recording stimuli</td>
			<td>MacBook&#160;</td>
			<td>Year 2009 running Windows 7</td>
			<td style="width:227px;">With a bootcamp partition of the disk for providing Windows OS</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Statistical Analysis</td>
			<td>Systat Software Inc.</td>
			<td>Sigmaplot 11.0&#160;</td>
			<td style="width:227px;"></td>
		</tr>
	</tbody>
</table>

using electroencephalography measurements and high-quality video recording for analyzing visual perception of media content

This article explores a method to detect differences in visual perception in humans. The method used is based on the psychological (or "cognitive") function of eyeblinks. Participants' eyeblinks are detected and acquired while watching videos specifically created for the investigation. The detection and acquisition of eyeblinks are carried out with the help of a 20-channel electroencephalographic (EEG) wireless device. The international 10-20 system for electrode placement is followed. A high-definition (HD) video camera is used to record participants' facial expressions, for contrast purposes. Instead of using pre-existing media content, purpose-made video content has been created following specific criteria of interest for this investigation, with stimuli enabling researchers to manage the precise parameters of interest. Otherwise, results could be contaminated with uncontrolled variables. The synchronization of the presentation of video stimuli with EEG recordings needs to be done in milliseconds. Analysis of collected data is performed with robust software for working with big matrices. Statistically significant differences in eyeblink rate related to media professionalization and editing style are found with the reported experimental procedures.

Using the procedure presented here, the eyeblink rate of 40 participants while watching three different video movies was analyzed. For a comparative analysis on media professionalization, half of the participants were media professionals. They were selected based on the criterion of a minimum 6 years of job experience in making decisions related to media editing and audio-visual cuts. For a comparative analysis on editing styles, the three video stimuli were created with exactly the same ...

Watch this Scientific Journal Video about Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content at JoVE.com

Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content

We present detection, acquisition, and analysis of eyeblink rates while watching media content.

This article explores a method to detect differences in visual perception in humans. The method used is based on the psychological (or "cognitive") ...

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Implantation and Recording of Wireless Electroretinogram and Visual Evoked Potential in Conscious Rats

The full-field electroretinogram (ERG) and visual evoked potential (VEP) are useful tools to assess retinal and visual pathway integrity in both ...

Using Looming Visual Stimuli to Evaluate Mouse Vision

The visual system in the central nervous system processes diverse visual signals. Although the overall structure has been characterized from the retina ...

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

With the advent of new technological advances, it is possible to study social interactions at a microlevel with unprecedented accuracy. High frequency ...