Name: measuring engagement of spectators of social digital games
Uploaded: 2021-07-03T13:00:00
Description: Watch this Scientific Journal Video about Measuring Engagement of Spectators of Social Digital Games at JoVE.com

We would like to thank MITACS in partnership with the company that created the game to have funded this research project.

The following protocol was approved by HEC Montr&#233;al&#39;s ethics committee prior to the beginning of the data collection.
1. Participant screening for the experiment
<ol>
	<li>Recruit participants 18 years and older. Ensure that participants understand the language of the experiment, can stand for 20 min, possess a smartphone dating from a maximum of 5 years, do not have skin allergies or sensitivities, do not have a pacemaker and do not suffer from epilepsy or any other diagnosed healt...

<ol>
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M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+wild+is+too+wild:+Lessons+learned+and+recommendations+for+ecological+validity+in+physiological+computing+research.">How wild is too wild: Lessons learned and recommendations for ecological validity in physiological computing research.</a> PhyCS 2018 - Proceedings of the 5th International Conference on Physiological Computing Systems. , (2018).</li><li>Rozendaal, M. C., Braat, B. A. L., Wensveen, S. A. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exploring+sociality+and+engagement+in+play+through+game-control+distribution.">Exploring sociality and engagement in play through game-control distribution.</a> AI and Society. 25 (2), 193-201 (2010).</li><li>Downs, J., Smith, W., Vetere, F., Loughnan, S., Howard, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Audience+experience+in+social+videogaming.">Audience experience in social videogaming.</a> Conference on Human Factors in Computing Systems - Proceedings. , 3473-3482 (2014).</li><li>Tekin, B. S., Reeves, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ways+of+spectating:+Unravelling+spectator+participation+in+Kinect+play.">Ways of spectating: Unravelling spectator participation in Kinect play.</a> Conference on Human Factors in Computing Systems - Proceedings. 2017, 1558-1570 (2017).</li><li>Downs, J., Vetere, F., Smith, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differentiated+participation+in+social+videogaming.">Differentiated participation in social videogaming.</a> OzCHI 2015: Being Human - Conference Proceedings. , 92-100 (2015).</li><li>Courtemanche, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Method+of+and+system+for+processing+signals+sensed+from+a+user.">Method of and system for processing signals sensed from a user.</a> US Patent. , (2018).</li><li>Batista, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Benchmarking+of+the+BITalino+biomedical+toolkit+against+an+established+gold+standard.">Benchmarking of the BITalino biomedical toolkit against an established gold standard.</a> Healthcare Technology Letters. 6 (2), 32-36 (2019).</li><li>L&#233;ger, P. M., Courtemanche, F., Fredette, M., S&#233;n&#233;cal, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+cloud-based+lab+management+and+analytics+software+for+triangulated+human-centered+research.">A cloud-based lab management and analytics software for triangulated human-centered research.</a> Lecture Notes in Information Systems and Organisation. 29, 93-99 (2019).</li><li>Greco, A., Valenza, G., Lanata, A., Scilingo, E. P., Citi, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+convex+optimization+approach+to+electrodermal+activity+processing.">A convex optimization approach to electrodermal activity processing.</a> IEEE Transactions on Biomedical Engineering. 63 (4), 797-804 (2015).</li><li>Braithwaite, J., Watson, D., Robert, J., Mickey, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Guide+for+Analysing+Electrodermal+Activity+(EDA)+&amp;+Skin+Conductance+Responses+(SCRs)+for+Psychological+Experiments.">A Guide for Analysing Electrodermal Activity (EDA) &amp; Skin Conductance Responses (SCRs) for Psychological Experiments.</a> Psychophysiology. (49), (2015).</li><li>O'Brien, H. L., Cairns, P., Hall, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+practical+approach+to+measuring+user+engagement+with+the+refined+user+engagement+scale+(UES)+and+new+UES+short+form.">A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form.</a> International Journal of Human Computer Studies. (112), 28-39 (2018).</li><li>Baron, R. M., Kenny, D. 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Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+store+environment+on+shopping+behaviors:+A+critical+review.">The effects of store environment on shopping behaviors: A critical review.</a> Advances in Consumer Research. 28 (1), 190-197 (2001).</li></ol>

Please note that the steps were performed in the studio of the creators of the game but could be replicated in a laboratory setting or another environment that has enough space to fit the game. It is important to note that the sync box can only transmit a pulse to the lights and EDA boxes that are within 20 meters. Therefore, the game room or playing field must not be larger.
Existing laboratory methods have used software to simultaneously begin both the recording of the videogame screen and p...

Studying the experience of game spectators helps to better understand the positive and negative aspects of the game, and in turn, can help to improve its design1. Recent innovations in the gaming industry have allowed new types of experiences that move forward from traditional console-based gaming2. With digital games that use motion tracking systems that are not confined within a screen, audiences do not have to be positioned in a fixed spot anymore. This new reality creates challenges in the assessment of spectators&#39; experience. The experiment was performed in the studio of the creators of the game but could be replicated in a laboratory setting or another environment that has enough space to fit the game.
The purpose of this methodology is to measure spectator engagement during a social digital game. More precisely, arousal, which leads to engagement, will be measured when the spectator has access to a web application that influences the gameplay. This method combines physiological and self-reported data. As this game is social and involves a group of people that move, the experiment is filmed. With the use of cameras and portable physiological devices, we were able to synchronize physiological data with events in the game. The portable devices (EDA boxes) are 3D printed boxes that are connected to electrodes that record physiological activity. The boxes have an ON/OFF switch, visual indicators, a microSD card slot and charging slots. The visual indicators help in case of troubleshooting. For example, these indicate whether the microSD is functional, show the state of the Bluetooth and Wi-Fi connections and signal whether physiological data are being recorded.
The use of physiological measures is a common and validated approach for measuring game engagement3. Physiological valence has been measured in the context of video games4. It has also been used in other research domains such as education5. Because emotional engagement is not observable and self-report can be biased, Charland et al. have used physiological arousal to assess emotional engagement in learners that were solving problems5. They used electrodermal activity (EDA) to measure physiological arousal, which is a widely used method6. EDA is the measurement of skin conductivity, which varies according to the differences in sweat gland activity3. This measurement is an important correlation to real-time emotional variations. EDA is associated with many constructs such as stress, excitement, frustration, and engagement7. Complementing EDA data with self-report responses are therefore recommended to associate the data with the right construct3. The Self-Assessment Manikin (SAM) is a self-reported pictographic scale that assesses three dimensions of emotion: valence, arousal, and dominance8. The current work used the arousal dimension, assessed using a visual 9-point Likert scale, ranging from calm to excited. Perceived arousal has been used in combination with physiological arousal7.
In traditional video games contexts, spectators are seated in a chair and stay more or less in the same position for the duration of the experiment. They are expected to look at a screen where the actions take place. This setting has been seen in previous games studies using physiological data9. In this case, it is simple to start the recording of the game at the same time as the recording of the physiological data10.
In the context of new digital games that are played outside of the screen, and in which participants stand and are free to move, traditional EDA recording might not be appropriate. The game used in this study is akin to a life-size Pong11. This game is composed of a ball and two paddles, each on an extremity of the playing field. Players move their paddle in order to push the ball from one end of the field to the other. In the version used for this research, the game is projected on the ground and players use their bodies as controllers for the paddles. Movement detection technology allows the paddle to follow the two players who are situated at opposite sides of the playground. An example of how the players prevent the ball from hitting the virtual wall behind them is presented in Figure 1. The game also involves spectators standing on the sides of the playground, who can use their smartphones to influence the gameplay. Using a mobile web application, spectators can vote for certain power-ups or obstacles that can either help or harm the players (e.g., less walls versus more balls, or modulating the speed of the ball). The option with the most votes wins.
In this study, we investigate the influence of interactivity on spectators. The conditions of interactivity are with or without smartphone. We compared the engagement of the spectators in these two conditions. A within-subject design was used for the interactivity condition, in order to assess the difference in arousal, and therefore in engagement. In the current study, groups of 12 people were ideal to promote ecological validity of the game12. two people as players and 10 as spectators. Only two EDA boxes were available for our study, so we had a total of eight groups which totalized 16 EDA data sets (two participants with EDA recording per group of 12). Each member of the public was randomly assigned to two games with access to their smartphone to influence the gameplay and one game without access to their smartphone. Game engagement literature suggests that giving many interactive options can lead to higher engagement13. Research in education has found that physiological arousal is a correlate of emotional engagement5. Building on game engagement literature and research in education, we hypothesized that giving the spectators access to interactivity will increase arousal which will in turn increase their engagement.
Contrary to studies about player experience, studies about spectators of a digital game rarely use psychophysiological measures. They are mostly done with questionnaires14, observation15, and interviews16. One difficulty of using psychophysiological measures with spectators is that they are often a group and their movements are less predictable than those of the players. This methodology uses multiple cameras to capture the participants and light boxes, enabling linking of participants video and physiological data.
As we used a within-subject design for the smartphone condition, each subject participated in two games with the interactivity condition, using their smartphone, and one game in the control condition, without the use of their smartphone. Synchronization of EDA data with the starts and ends of each game was therefore crucial to enable the assessment of the differences in each condition of interactivity. It would be impossible to start the recording of all the three cameras at the same time as the recording of the EDA on the spectators due to the dimensions of the room. To overcome that issue, we have used a new synchronization technique called wireless synchronization protocol for the acquisition of multimodal user data17. Bluetooth Low Energy (BLE) signals are sent from a sync box simultaneously to the EDA boxes and to light boxes (see Figure 2). The sync box is a 3D printed box with ON/OFF and auto/manual switches and a button. The manual function is used for testing the signals using the button. The signals are incrementing numbers that start at one and that are shown on the 3D printed light boxes. There numbers are shown to the cameras, and the same numbers are also logged on the EDA data file (see Figure 3). This allows synchronization of events happening in the game to variations in the EDA recordings. In our case, the events identified were the starts and ends of the three games. Then we could link the game to the condition and to the participant number. In this way, we identified which dataset corresponded to each condition.
The following section describes the protocol that allows the use of the technique developed by Courtemanche et al.17. We adapted the technique to answer our research question. This protocol received an ethical certificate from our institution&#39;s ethics committee. In this protocol, we use physiological devices18, mounted into a 3D-printed casing. We will refer to the device as the EDA boxes (boxes used to record the EDA of the participant), the light box (the box with a digital light), and the sync box (box that sends signals to the EDA boxes and the light boxes to synchronize data). The synchronization software enabling the wireless synchronisation protocol for the acquisition of multimodal user data17 was embedded onto the boxes.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>BITalino (r)evolution Freestyle Kit (PLUX Wireless biosignals S.A.)&#160;</td>
			<td>BITalino</td>
			<td>810121006</td>
			<td></td>
		</tr>
		<tr>
			<td>Devices (1 syncbox, 3 light boxes, 2 EDA boxes)</td>
			<td>Developed by Tech3Lab researchers1</td>
			<td>n/a</td>
			<td></td>
		</tr>
		<tr>
			<td>CubeHX2</td>
			<td>n/a</td>
			<td>n/a</td>
			<td></td>
		</tr>
		<tr>
			<td>Charging station</td>
			<td>Prime 60W 12A 6-Port Desktop Charger</td>
			<td>RP-PC028</td>
			<td></td>
		</tr>
		<tr>
			<td>6 USB3 wires for charging</td>
			<td>Insignia 3m (10 ft.) Charge-and-Play USB A/ Micro USB Cable</td>
			<td>NS-GPS4CC101-C2</td>
			<td></td>
		</tr>
		<tr>
			<td>3D scanner</td>
			<td>Velodyne LiDAR</td>
			<td>VLP-16</td>
			<td></td>
		</tr>
		<tr>
			<td>Projectors</td>
			<td>Barco</td>
			<td>F90-W13</td>
			<td></td>
		</tr>
		<tr>
			<td>Jerseys* (fabric, tape, string)</td>
			<td>Any</td>
			<td>Any</td>
			<td></td>
		</tr>
		<tr>
			<td>2 low light cameras</td>
			<td>Sony</td>
			<td>A7S</td>
			<td></td>
		</tr>
		<tr>
			<td>2 tripods for the A7S</td>
			<td>Manfrotto</td>
			<td>MVK500190XV</td>
			<td></td>
		</tr>
		<tr>
			<td>2 light stands for the go pro and the syncbox</td>
			<td>Impact&#160;</td>
			<td>LS-8AI</td>
			<td></td>
		</tr>
		<tr>
			<td>1 plier for the light stand of the syncbox</td>
			<td>Neewer&#160;</td>
			<td>Super Clamp Plier Clip</td>
			<td></td>
		</tr>
		<tr>
			<td>1 magic arm for the light box of the go pro</td>
			<td>Magic Arm</td>
			<td>143A</td>
			<td></td>
		</tr>
		<tr>
			<td>1 Go Pro</td>
			<td>Go Pro</td>
			<td>5</td>
			<td></td>
		</tr>
		<tr>
			<td>1 Microphone</td>
			<td>Rode&#160;</td>
			<td>VideoMic Rycote</td>
			<td></td>
		</tr>
		<tr>
			<td>2 armbands</td>
			<td>Amyzor</td>
			<td>Moisture Wicking Sweatband&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>*Make them yourself by taping the number on the fabric and perforating two holes to enter the string</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sources: 
			1.Courtemanche, F. et al. Method of and System for Processing Signals Sensed 
			From a User. US 15/552,788 (2018). 
			2. L&#233;ger, P.M., Courtemanche, F., Fredette, M., S&#233;n&#233;cal, S. A cloud-based lab 
			management and analytics software for triangulated human-centered research. 
			In Lecture Notes in information Systems and Neuroscience. Edited by Thomas 
			Fischer, 93-99, Springer. Cham (2019).</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

measuring engagement of spectators of social digital games

The goal of this methodology is to assess explicit and implicit measures of engagement of spectators during social digital games in a group of participants with motion tracking systems. In the context of games that are not confined within a screen, measuring the different dimensions of engagement such as physiological arousal can be challenging. The focus of the study is made on the spectators of the game and the differences in their engagement according to interactivity. Engagement is measured with physiological and self-reported arousal, as well as an engagement questionnaire at the end of the experiment. Physiological arousal is measured with electrodermal activity (EDA) sensors that record the data on a portable device (EDA box). Portability was essential because of the nature of the game, which is akin to a life-size pong and includes many participants that move. To have an overview of the events of the game, three cameras are used to film three angles of the playing field. To synchronize the EDA data with events happening in the game, boxes with digital numbers are used and put in the frames of cameras. Signals are sent from a sync box simultaneously to the EDA boxes and to light boxes. The light boxes show the synchronization numbers to the cameras, and the same numbers are also logged on the EDA data file. That way, it is possible to record EDA of many people that move freely in a large space and synchronize this data with events in the game. In our particular study, we were able to assess the differences in arousal for the different conditions of interactivity. One of the limitations of this method is that the signals cannot be sent farther than 20 meters away. This method is, therefore, appropriate for recording physiological data in games with an unlimited number of players but is restricted to a limited space.

This section describes the representative results of this study. We recruited participants using social media and our institution&#39;s panel of participants. Of the 78 participants, 40 were women. The mean age was 22 years old. None of the participants had previously played the game. Other exclusion criteria can be found in step 1 of the protocol.
The descriptive statistics, which can be seen in Table 1, contain the mean per condition, for each measure. The mean of the arousa...

Watch this Scientific Journal Video about Measuring Engagement of Spectators of Social Digital Games at JoVE.com

Measuring Engagement of Spectators of Social Digital Games

We propose a methodology that enables measuring engagement of spectators in a social digital game combining physiological and self-reported data. As this digital game involves a group of freely moving people, the experience is filmed using a synchronizing technique that links physiological data with events in the game.

The goal of this methodology is to assess explicit and implicit measures of engagement of spectators during social digital games in a group of ...

The purpose of this protocol is to enable the measurement of engagement of participants of a social digital game. This method combines physiological and self-reported data. As this game is social and therefore involves a group of people that move, the experiment is filmed in order to synchronize physiological data with events in the game.This is the material needed to perform the protocol. We will refer to the boxes as EDA Box, the box used to record the EDA of the participant. Light box, the box with digital numbers.And sync box, the box that sends signals to the EDA box and the light boxes to synchronize data. We also need two armbands, EDA electrodes, EDA sensors, medical tape, and antiseptic wipes. Plug the EDA boxes, the three light boxes, and the sync box into the charging station.Place the consent forms, the pre-experimental questionnaire, and the jerseys on a table in the greeting area. Then, test the Bluetooth connection on the light boxes. Set the sync box to manual.Turn on the three light boxes. Turn on the two EDA boxes. Turn on the Bluetooth on the EDA boxes.Turn on the sync box and then push the pulse button on the sync box. The light box should flash the number one. Then, set the sync box and light boxes in place for the collection.Place the light boxes in view of each camera. Put the sync box on the tripod at a height of six feet and set it to auto. Place the camera in order for the framing to include all four extremities of the game's playing field and the light box.Greet the participants at the front door. Tell them to go sit at the table. Once all the participants have arrived and are seated, describe the tools which will be used to collect data for the present study.This description should be written in the consent form. Then, tell the two randomly chosen participants to follow you to install the EDA equipment. During that time, the other participants can start to fill the pre-experiment questionnaire.On the non-dominant hand, ask the participant to remove any jewelry. Use an antiseptic wipe to clean the area where the electrodes will be placed. Remove the electrode from the plastic and place them on the hand of the participant.Then, snap the two sensors on the two electrodes. The red wire must be placed on the thumb side. The black wire must be placed on the other side, under the pinky finger.Plug the sensor wire to the A3 port of the EDA box. Ask the participant if they tend to have sweaty palms. If they say that they do, wrap medical tape around the electrodes without touching the metal part.Then add an arm band over the palm of the hand to secure the sensors and electrodes in place. Then turn on the EDA device. Check that the Bluetooth switch is still on.Check that the four lights flash. Note the number of the participant and the number of the EDA box, then place the EDA box on their belt or in the pocket of the participant. Once all the participants have completed the pre-experimental questionnaire, walk them to the game studio, then record a base light.To do so, tell the participants you need to calibrate your tools and ask them to breathe calmly and to fix something in front of their eyes for two minutes. Simultaneously, turn the EDA devices off and then on. Then start a timer for two minutes.After the minutes end, turn the EDA device off and turn it on again. Start the recording of the three cameras and turn on the three light boxes. Also verify that the light boxes and the full playing field are still within the camera frame.Verify that the sync box is on auto and turn on the sync box. Explain the game. Tell them that they game is similar to ping-pong and that they will understand while playing.To win, one player needs to make three points. Also tell them that some members of the public will use their smartphones to influence the game by visiting the website URL that is projected on the playground. Then tell them who will take the role of player and who will be on the sidelines as spectators.Announce which spectator will be using their smartphone for this game. While the participants are playing, visually check that the lights are flashing every 10 seconds. In between each game, ask participants to fill in the self assessment mannequin scale questionnaire on their smartphone, on an URL.Give them the link of the questionnaire. Ask the participant to give you the box. Turn off the device.Turn off the Bluetooth of the device, unplug the sensor from the A3 port and then remove the arm band. Unsnap the sensors from the electrodes and ask the participant to remove the medical tape and electrodes on their hand. Give the participants a tissue to remove the cream in the hand.Then, remove the mini SD card from the EDA box and do the same with the second EDA participant. When it's over, ask the participants with EDA to fill in the end of experience questionnaire, too. Then debrief the participants.Once they finish, thank them for their participation, tell them the goals of their research and their compensation. Then walk them out. After disassembling and putting away the data collection materials, transfer to physiological data on the computer.Put the mini SD card from the EDA box in the adapter. Transfer the data to the computer in a folder named by the number of the participant. Verify the data is valid.Select the data and put it in a spreadsheet. Hide the columns that are not useful. Select approximately one to 3000 and make a scatterplot.If the data is between 240 and 550, the data is valid. Then verify if the markers generated by the sync box are present by selecting the event column and by sorting it. Sometimes there are markers that didn't appear.This is not a problem. With only one marker, you can calculate the beginnings and ends of your events. Press control Z to put back the markers where they are.Prepare the data for analysis. Add an event_start_end column. Watch the footage and when there is the beginning of an event, calculate the difference between the time of the event and the last marker.When you find the seconds related to the event start, add a marker named event1_start. Do the same for the end of the event. Then repeat these steps for the baseline.When you are finished adding the markers, export the spreadsheet in text file. You will have two per participant, one with the data and one with the baseline. Then, import these files into software.This will generate a file ready for analysis that contains the relative time, absolute time, events, and EDA signal. Please note that the software is still in its early versions. Some of the icons may be missing.I will guide you through the steps to get the physiological data file ready for analysis. Click on add project. Add a title.Add a description. Enter the dates of the project and the total number of participants. Click on the name of the project.Click on experimental design. Click on signals and choose physiological, EDA, blue box recorder, blue box, version three. Click on events and enter the events as they were previously named in the spreadsheet.Choose blue box, version three. Click on transformations. Choose GSR, which refers to galvanic skin response or EDA.Click unlocked to lock your project. Click on file import to import the files previously prepared. Click on the profile of the participant to give information about the participants by entering their email addresses.Click on participant is there. Click on OK complete. Upload the data file, which needs to be zipped in order for the software to recognize it.Click on the arrow. Click on the pies to upload the file. Go to analysis and choose data exportation.Select the participant and their data. Click on export data to have a file ready for analysis. This can take hours, if you have many participants.The file will appear under file name at the end of the exportation. Use the file generated for physiological data analysis. Here's an example of the file extracted from the software.It is organized according to the starts and ends of events. It is all ready to be analyzed. The results found that perceived arousal, measured with the self assessment mannequin scale, and the physiological arousal, measured with EDA, were higher when the spectators had access to their smartphone to influence the game, which in turn, increased their engagement.These results showed that this method provides the necessary data to evaluate engagement when mediated by physiological, as well as self-reported arousal. To conclude, in the context of digital games that do not take place within a screen, this method is adequate. We can video capture the action that takes place during the game while also being able to associate these actions to EDA variations.Due to its portable equipment, this method could be used outside of the laboratory setting. It could be recreated in the real context of the game, which is a public space, in our case. Future development of the EDA device could also support other measurements, such as electrocardiogram, which will require another sensor and two other electrodes, accelerometer, and geolocalization.These developments could allow the more precise assessment of the bodily reactions as well as movements in the context of games.

Research

JoVE Journal

Behavior

Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials

Social exclusion is a complex social phenomenon with powerful negative consequences. Given the impact of social exclusion on mental and emotional health, ...

Moderate Prenatal Alcohol Exposure and Quantification of Social Behavior in Adult Rats

Alterations in social behavior are among the major negative consequences observed in children with Fetal Alcohol Spectrum Disorders (FASDs). Several ...

The Modified Hole Board - Measuring Behavior, Cognition and Social Interaction in Mice and Rats

This protocol describes the modified hole board (mHB), which combines features from a traditional hole board and open field and is designed to measure ...

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: ...

Quantifying Social Motivation in Mice Using Operant Conditioning

In this protocol, social motivation is measured in mice through a pair of operant conditioning paradigms. To conduct the experiments, two-chambered ...

The Social Dimension of Stress: Experimental Manipulations of Social Support and Social Identity in the Trier Social Stress Test

In many situations humans are influenced by the behavior of other people and their relationships with them. For example, in stressful situations ...

Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

Human beings are constantly surrounded by uncertainty and change. The question arises how people cope with such uncertainty. To date, most research has ...

Examining Recall Memory in Infancy and Early Childhood Using the Elicited Imitation Paradigm

The ability to recall the past allows us to report on details of previous experiences, from the everyday to the significant. Because recall memory is ...

Assessment of Social Transmission of Food Preferences Behaviors

Olfactory recognition deficits are suggested to be able to serve as clinical marker to differentiate Alzheimer&#39;s disease (AD) subjects from healthy ...

A Visual Guide for Studying Behavioral Defenses to Pathogen Attacks in Leaf-Cutting Ants

The complex lifestyle, evolutionary history of advanced cooperation, and disease defenses of leaf-cutting ants are well studied. Although numerous studies ...