Bachelor of Science in Computer Science October 2020
Physical Fitness VS. Reaction Time in E-sports.
A Design of an Experiment.
Eric Hallengren
This thesis is submitted to the Faculty of Computing at Blekinge Institute of Technology in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science. The thesis is equivalent to 10 weeks of full-time studies.
The authors declare that they are the sole authors of this thesis and that they have not used any sources other than those listed in the bibliography and identified as references. They further declare that they have not submitted this thesis at any other institution to obtain a degree.
Contact Information:
Author(s):
Eric Hallengren E-mail: erhf15@bth.se
University advisor:
Mats-Ola Landbris
Universitet Adjunkt
A BSTRACT
Background: E-sports is a grand industry and has been gaining momentum in the latest decades.
Reaction time (RT) is an important part of most e-sports games and therefore a possible way to evaluate and improve RT is desired. A tool that evaluates the players and shows them what executive functions they should improve on through what physical activity would be a great way to evaluate and improve RT. There has been a lot of studies performed on the effects of physical fitness on RT. Most studies seem to agree that improved physical fitness results in improved RT.
Objectives: The aim of this thesis is to design an experiment that will evaluate the connection between e-sports players physical fitness, their RT and their executive functions through different tests.
There will also be an evaluation of if it is possible to reliably find a connection between specific kinds of physical fitness and specific executive functions. The objectives are therefore to find suitable tests to evaluate RT and executive functions as well as finding a physical fitness test that allows for easy comparison between subjects.
Methods: Literature study is used to find the answers to the research questions through reading different studies and papers. Scopus was chosen as the database to find the different studies to read because of the vast amount of material available there.
Results: The test used to evaluate physical fitness will be the Army Physical Fitness Test (APFT).
The tests that will evaluate RT and executive functions are the Stroop test, the Trail Making Test A &
B, Tower of Hanoi and a variation of the n-Back test. It is very difficult to isolate executive functions and evaluate them without something else interfering with the results. This thesis’s hypothesis changed from the beginning of the research to that it was done. At first it was believed that executive functions could be isolated and evaluated separately, but that is no longer the case.
Conclusion: The experiment will most likely show that subjects with greater APFT score will achieve a better overall score on the RT tests than those with lower score. This experiment will most likely not work as a tool to evaluate the executive functions connection to specific physical exercises of e-sports players in the state that the experiment is currently envisioned. More studies are required to link specific physical exercises to specific executive functions before a tool can be created.
Keywords: Reaction Time, Physical Fitness, Executive Functions, Gaming, Aerobics
C ONTENTS
ABSTRACT ... III CONTENTS ... IV
1 INTRODUCTION ... 1
2 RELATED WORK ... 3
3 METHOD ... 7
3.1 SECONDARY RESEARCH QUESTIONS ... 7
3.2 RESEARCH METHOD ... 7
3.3 SELECTION OF FITNESS TESTS ... 7
3.4 SELECTION OF REACTION TIME TESTS ... 8
4 RESULTS AND ANALYSIS ... 10
4.1 FITNESS TEST ... 10
4.2 REACTION TIME TEST ... 10
4.3 HOW THIS EXPERIMENT IS MEANT TO BE PERFORMED ... 11
4.4 HOW THE SCORE IS PRESENTED FOR RTTESTS ... 11
4.5 HOW TO INTERPRET THE RESULTS FROM THE TESTS ... 12
4.6 EQUIPMENT NEEDED TO PERFORM THE EXPERIMENT ... 13
5 DISCUSSION ... 14
5.1 DISCUSSION ABOUT RESEARCH QUESTIONS AND HYPOTHESIS ... 14
5.2 WHAT COULD BE DONE DIFFERENTLY WITH THE PROTOTYPES AND CHOICE OF RTTESTS ... 15
5.3 THE RELIABILITY OF THE RESULTS... 15
5.4 THE EXPERIMENT USED AS A TOOL ... 15
5.5 ISOLATING EXECUTIVE FUNCTIONS ... 16
6 CONCLUSION AND FUTURE WORK ... 17
6.1 CONCLUSION ... 17
6.2 FUTURE WORK ... 17
7 REFERENCES ... 2
1 I NTRODUCTION
Electronic Sports (e-sports) is becoming more widespread every day and it is starting to resemble a traditional sport in viewership and price pool money. League of Legends (2009) had during the 2019 World Championship a peak of 44 million concurrent viewers1. The 2019 Dota 2 (2013) International had a prize pool of over $34 million2. Competing in this sport is therefore more popular than it has ever been. Just as regular sports, e-sports are very competitive and every advantage a player can get over the competition is extremely valuable. An evaluation of the players fitness level on different tasks and their different executive functions would therefore be useful to see what they need to improve on. How such a test could look will be described in this thesis. If a higher score on a fitness test always results in faster reaction time (RT) in the cognitive tests than those with lower score, we can quite comfortably say that a better score at this test will result in faster RT. If it is discovered that a part of the fitness test contributes more to improving a specific executive function than the others, it would be very valuable information when evaluating executive functions. E-sports teams could then use this experiment to realize what executive function their players need to improve on and what physical fitness corresponds to that executive function.
• Background
RT is noticeable in our everyday life and as we get older our RT declines, suggested by (Salthouse, 1996). Therefor people may seek ways to improve their RT. Older people gain an increase in RT from aerobic training suggested by (Spirduso and Clifford, 1978), (Colcombe and Kramer, 2003) and (Smith et al., 2010). This RT increase may benefit younger people as well.
As e-sports are played on the computer, people might think that certain skills that would be extremely useful in traditional sports would not matter here. Such as the ability to continuously run at high speeds for longer periods of time in football, or the strength required to hit and kick hard in martial arts. However, there might be a stronger connection between the sports than one might first believe.
(Hansen et al., 2004) and (Griffin et al., 2011) show that aerobic training can improve executive functions in younger people. Studies such as (Colcombe and Kramer, 2003) and (Eckardt et al., 2020) shows similar results in that resistance training may be beneficial when using executive functions to complete tasks, which would be prominent in e-sports. Executive functions are used when you figure out the correct solution to more complex problems. Simply pressing the shoot button to eliminate the enemies would not require executive functions, but other parts of the game will. Some examples are focusing on several things at the same time, such as where several of the enemies most likely are at a certain point in time. Another is remembering several things at the same time and switch out that information, which could be where enemies was lastly seen. Another yet is ignoring unimportant stimuli, which during a live game can be the crowd, or in the game, your teammates firing their gun or your teammates visual representation so that you are still focused on the enemy.
Studies has shown that playing action video games have more impact on RT than playing non- action video games (Hutchinson et al., 2016), (Green et al., 2012) and (Wu and Spence, 2013). This may indicate that RT plays a bigger role in these genres of games and is therefore improved upon more frequently. In First-Person Shooter (FPS) games, such as “Counter Strike: Global Offensive” (2012) or
“Valorant” (2020), the RT of the player is extremely important. The engagement time, which is the time from when a player spots and engages an enemy player to that their fight is done, is often very short in these games and about 1 – 2 seconds. With such narrow time windows, small improvements in RT would yield quite substantial results.
1 https://www.businessinsider.com/league-of-legends-world-championship-100-million-viewers-2019- 12?r=US&IR=T (visited 19-08-2020)
2 https://dotesports.com/dota-2/news/the-international-2019-prize-pool-surpasses-34-million-with-one-day- left (visited 19-08-2020)
• Defining the Scope of This Thesis and Limitations
This experiment is designed to be performed on e-sports players with a lot of experience in FPS games on the computer as they know how to use a mouse and keyboard very well and RT has a big impact in their performance in the games. The players will have to evaluate themselves on how much experience they have as it cannot be checked by an outside source, except perhaps game time on Steam for Counter Strike, but they will be asked to at least have 200 hours played in FPS games. These subjects will yield a good testing group of different and similar subjects. Both fit and unfit players play FPS games and they have the drive to try to become better at FPS games, otherwise they would not have over 200 hours of time played.
This experiment will only be described and not performed due to time limit and difficulty to perform a test with human subjects during current time.
This experiment seeks to discover if this kind of testing works to establish a connection between physical fitness and RT and if so, it can be added to the body of research in that field. Furthermore, it also seeks to understand if there is a connection between specific forms of physical fitness and specific executive functions.
• Aim and Objectives
The aim of this thesis is to evaluate if there is a distinct connection between certain kinds of physical fitness of an e-sports player and their RT. Also, if there is a connection between specific executive functions and specific physical fitness. The results will be compared between e-sports players. As there are several ways to evaluate RT, the most suitable tests to perform needs to be found. Because these e- sports players play on the computer, it is suitable for the tests to be performed on the computer as well, as they are well acquainted with the mouse and keyboard. The physical fitness of the players will also need to be evaluated in some way. The objectives of this thesis are to firstly research suitable tests to evaluate RT and executive functions. Secondly prototypes of some of the tests will be made to show how they could be done. Lastly research needs to be done on a suitable way to evaluate the fitness level of subjects.
• Main Research Question
Is it possible to develop a series of tests to find out the correlation between physical fitness, RT and executive functions in e-sports players?
This question will be answered when the objectives from "aim and objectives" are completed. By researching the most optimal tests to use we can evaluate if we will find reliable results. The hypothesis of this thesis is that it will be possible to accurately find the physical fitness level of subjects through a physical fitness test and that result can then be compared between subjects. Furthermore, those who score overall better on the fitness test will most likely also get an overall better score on the cognitive tests. The parts that make up RT can possibly be accurately measured through different tests and that we can isolate those different parts of RT. Hopefully we can then see what specific parts of the physical fitness affects which part of the RT and the executive functions.
2 R ELATED W ORK
There are a lot of papers that support the idea that physical fitness improves RT in older adults. As early as 1975, Spirduso started to find a difference in simple RT, choice RT and movement time (the time it takes to perform a movement) between men of active lifestyles and those with sedentary lifestyles (Spirduso, 1975). This idea was later recreated and expanded on with Clifford (Spirduso and Clifford, 1978) where they performed the study on RT in older active men and older nonactive men. They found that older active men performed significantly better at all activities than the nonactive men. These activities included simple RT, choice RT and movement time.
This was the earliest study found where the purpose was to study the difference in RT between active and nonactive men. Papers like this is important to start the research in specific areas. Scopus was used and the search term was ("cognitive" OR "executive function" OR "reaction time" AND "aerobics"
OR "physical activity" OR "resistance training").
(Colcombe and Kramer, 2003) performed a meta-analysis on fitness effect on cognitive functions.
This analysis contained 18 articles and the all subjects of the studies included had an average age of above 55. All studies also had an aerobic fitness component. They found that the exercise had the most impact on executive process. Simple RT was also improved, although not to as high of a degree as the executive process. Subjects who performed both aerobic training and strength training improved more than those who only performed aerobic training. The length of training sessions also impacted the improvements. Training sessions under 30 minutes provided much lesser improvements than sessions between 30 and 60 minutes.
This paper shows that prolonged training gives better results and a combination of strength and aerobics are best for improvements in RT. Therefor both strength and aerobic fitness needs to be evaluated in this thesis’s experiments physical fitness evaluation.
Animals, specifically mice, gained a more adaptive and efficient brain and increased ability to learn through aerobic training (van Praag et al., 1999). (Colcombe et al., 2004) later tried to find if this change would translate to humans. The subject used in this study were older adults and the experiment lasted for 6 months. It was discovered that more aerobic fit people had higher activation in certain parts of the brain used for task completion and less activation in parts of the brain that activates when there is conflict on how to react to stimuli.
This study shows changes in how we use our brains when aerobic fitness is practiced compared to when it is not. This is valuable information when discussing the links between physical fitness and cognitive function.
One meta-analysis (Smith et al., 2010) condensed 24 studies about attention and processing speed into a graph showing their independent and collective results (Figure 1). Executive functions were also gathered from 19 studies and made into a similar graph (Figure 2). Some of the criteria for the studies included were that the mean age of the subjects was 18 or over, that the duration of the tests was over one month long and that it involved aerobic exercise.
There are however multiple reasons why these graphs are not representative of e-sports players.
Firstly, the subjects of these tests were older, except for those in the Stroth 2009 experiment. Secondly, several of the studies consist of subjects with underlying diseases. One example is the Oken 2004 experiment where the subjects suffered from multiple sclerosis and several other studies included subjects suffering from mild cognitive impairment. E-sports players are usually young and as such suffers less diseases making these results less relevant for them. Even so, it still shows a relation between aerobic fitness, processing speed and executive functions.
Hedges g is a number in statistics which indicates the difference between two variables. In this case it indicates the difference between a group not performing aerobic fitness and a group performing aerobic fitness, for an extended period. In Figure 1 we can see that the Hedges’s g, represented by a rhombus, is 0.158. In Figure 2 the Hedges’s g is 0.123. These are low numbers which indicates that the processing speed increase is minor. The rule of thumb for Hedges’s g is that if it is under 0.2 it is considered a small change. If, however, these results hold true for younger people with less diseases, a small increase in RT would still be valuable.
In this thesis a connection between the subject’s RT, aerobic fitness and strength is explored.
According to these findings, it seems the subjects who would be performing better on the run part of this thesis’s fitness evaluation test would have a better RT than those who do not. However (Colcombe
and Kramer, 2003) supports the notion that a combination of strength and aerobics should provide the best result.
(Eckardt et al., 2020) tested the impact of stable and unstable resistance training on executive functions. The stable resistance training (SRT) uses machines for the strength training while the unstable resistance training (URT) utilizes free-weights. The URT requires more balance, which is what makes it unstable. Therefor it is more cognitive challenging. The subjects were separated in three groups, one URT group and two SRT groups. There were two SRT groups to make sure a training routine on a specific set of machines did not cause significantly worse results than a training routine on other machines.
The subjects consisted of 68 healthy older adults ranging from 65-79 years old. Both the URT group and the two SRT groups performed their training twice per week, for 10 weeks. They were then measured in the Stroop Color-Word Test (Stroop), Trail Making Test (TMT), Digit Memory Test (DMT) and Digit Symbol Substitution Test (DSST). The URT group performed significantly better on the DMT and the DSST. There was no significant improvement in the Stroop and TMT test. With this, it appears that URT mainly improves working memory.
This study supports the idea that strength training does improve executive functions. This study is however about free-weights training, but perhaps the people who do well on the strength part of this thesis’s fitness evaluation test show similar results. The pushups and sit--ups in this thesis’s experminets fitness evaluation could also be in the same area as the free-weights used in this paper, as balance is required to perform them correctly and no machine is available. (Colcombe and Kramer, 2003) agrees with this notion that strength played a role in improving executive functions.
All these previously mentioned findings revolve around older adults. Experiments involving young people are rarer but noteworthy research was found.
Figure 1: Attention and processing speed graph
Figure 2: Executive Functions graph
A study (Hansen et al., 2004) tried to evaluate the relation between physical fitness and cognitive function. This experiment included 37 male sailors with a mean age of 19.1 years. All the subjects firstly went through basic training for 8 weeks, performed a pre-test, and then were split into two groups, a detrained group (DG) and a trained group (TG). The TG then went on to continue training for 4 additional weeks while the DG did not. After these 4 weeks they performed the post-test. Both the pre- test and post-test are the same test. The test involves a continues performance task (CPT) and a working memory test (WMT). The chosen CPT test was The California Computerized Assessment Package (CalCAP). This package of tests includes two simple tests that do not include any executive functions, meaning the subject do not have to think too deeply. The other two tests are executive tests where they test working memory and planning. As the WMT test they choose a variation of the 2-back test where the subject must remember certain information, this test requires executive functions. As a result of the post-test, only DG performed better on the tasks not requiring executive functions. However, the TG performed better at executive tasks than the DG, which is more relevant in complex situations. The TG also had much greater improvements than DG in true positive responses in the post-test compared to the pre-test. A true positive response is when the subjects responds correctly to the stimuli.
During the pre- and post-test heart rate variability (HRV) was tested as well as maximum oxygen consumption (V̇O2max). The TG showed much higher V̇O2max than the DG in the post-test. The DG also showed a decrease in HRV from the pre- to the post-test while the TG did not. What Hansen et al believe to be the reason for the DG performing worse than the TG on the cognitive tasks including executive functions in the post-test, is the difference in resting HRV and V̇O2max between the two groups.
This experiment used only male subjects. Hansen et al agree that a similar experiment could be done using mixed gender. However, they state that in their earlier studies gender was not a factor when studying the relation between HRV and cognitive performance.
As this test includes people with the mean age of 19.1 it is much more representative of e-sports players than the tests which includes older people.
According to these findings, aerobic exercise provides a notable improvement in executive functions for younger adults too, like older adults. It also shows that even after only 4 weeks without training, a considerable change to executive functions happens.
In an experiment done (Griffin et al., 2011) they found that aerobic exercise on sedentary young adults increased their performance on a face-name task. The face-name task involves the subjects seeing unfamiliar faces paired with names then a distraction task and then the faces are presented without the names. The faces are shown 3.5 seconds each and the distraction task is 40 seconds long. The subjects must then recall the correct name with the correct face. This test will evaluate how well you can collect and retain information under a longer time. The task includes executive functions as the subjects must update their working memory all the time and they switch stimuli very often. The subjects were 47 male subjects of the age ranging from 20 to 24. There were two groups who performed aerobic exercise, one for 5 weeks and one for 3 weeks. The subjects who exercised for 5 weeks performed much better at the face-name task than the sedentary subjects and the subjects who only exercised for 3 weeks.
This thesis supports the idea that longer training period yields continuous results, at least up to 5 weeks. It also supports the idea that younger people gain increased executive functions from aerobic exercise.
One meta study (Diamond and Ling, 2016) claims that aerobic exercise and resistance training that does not include executive functions does in turn not improve executive functions. One such an activity would be running on a treadmill. They do however also mention that it is consistently found that people with better aerobic fitness also possess greater executive functions. They present the idea that maybe years would be needed to provide the improvement instead of just a few months. Another theory is that people who enjoy the exercise would get better results, which is more likely if they choose to do it themselves instead of being told to do it for a study.
In a follow up paper (Diamond and Ling, 2019) they respond to criticism they got for their paper published in 2016. They provide strong counterarguments against their criticism.
These are important studies to oppose the idea that aerobic exercise improves the RT. It rises many valid points about previously performed studies and how the results may depend on something else, or that the increases are minor. One example is that they oppose the results of (Smith et al., 2010) because the results found were minor.
No studies were found that evaluated the relation between specific exercises and specific executive functions. Scopus was used to search for studies, and the search string used was ("executive function"
AND "physical training" OR "aerobics" OR "aerobic training" OR "resistance training" AND "targeted"
OR "specific" OR "certain").
This thesis focuses a bit more on the strength of the subjects compared to the other studies and aims to see if there is a strong connection between strength and RT. It also aims to see if there is a connection between different kinds of fitness and different executive functions, which was not done in previously mentioned studies. Dissimilar to the other studies, this experiment does not take use of sedentary subjects to train half and leave half as sedentary. This experiment aims to use the subjects as they are and simply evaluate their fitness level and their cognitive functions, showing how well they do on each task. One of the purposes of this experiment is to be used as a tool to figure out improvements in the people who use it. This will only be possible if the connection between fitness and RT is concluded and that specific executive functions correspond to specific physical fitness.
3 M ETHOD
3.1 Secondary Research Questions
RQ 1: Can you evaluate how well-trained a person is on a numeric scale and if so, how?
It is important that we can evaluate the physical fitness of the subjects to measure them between subjects. We will also need to differentiate between different kinds of fitness such as endurance and strength. This relates to the main research question in that we need a way to evaluate a person’s physical fitness to find its connection to RT.
RQ 2: Which tests are viable tests to measure a subject’s RT and different executive functions?
The tests we choose to evaluate RT must grant us reliable and clear results so that we can measure the results between subjects. The tests also need to focus on different executive functions. As the subjects of the tests should be e-sports players then the technicality of how the tests work and how to use the mouse and keyboard should not be a problem. This relates to the main research question in that we need a way to measure a person’s RT to be able to relate it to the physical fitness of the same person.
3.2 Research Method
Literature study: Literature study was chosen because there is a lot of literature written about RT, what affects it and how to test it. This approach lets me gather valuable information from other sources to design this experiment. In this approach no tests must be performed with subjects which is suitable right now during the ongoing Covid-19 pandemic and due to time constraints. The site most used for research was Scopus where keywords such as “processing speed”, “reaction time”, “exercise”, “physical fitness”, “aerobic”. “cognitive function” and “cognitive performance” was applied.
Interview: Interview was not chosen as the subjects would have to have been in vastly different levels of fitness in their life but also remember how well they performed in e-sports then. This would have the added factor of that maybe they got less fit later in their life but as they played more e-sports they became better at e-sports and got improved RT, but not because of their fitness.
Longitudinal study: Longitudinal study would have been a valid choice to study people over a longer period. You would have the subjects’ fitness score in the beginning of the experiment as well as their RT score and how well they did on different executive functions. Then you would train the subjects in the properties of the fitness test and then when the subjects have significantly increased their fitness score you would evaluate them in the RT tests to see if they have improved. In this sort of study, a control group that did not perform the exercises could have been used to compare to the exercise group.
This would make the results more convincing.
Observation: E-sports players could have been observed during matches in tournaments to evaluate their RT and then ask them to perform a fitness test themselves at home and send in their results.
This method would have been vastly more time consuming to evaluate their RT and the data would be difficult to gather. However, the fitness evaluation would not be time consuming for the experimenters but the results from the fitness test would be less trustworthy. Executive functions would have to be evaluated in some way too, which is not clear how.
3.3 Selection of Fitness Tests
The test chosen needs to be able to evaluate both endurance and strength. A lot of different kinds of muscles needs to be included in the test. The tests also need a system to collect data and to compare it between the different subjects.
The Army Physical Fitness Test (APFT) evaluates both running and muscle strength in different muscles. It also uses a scoring system making it suitable for this experiment. A problem with the scoring system, however, is that it is designed for relatively fit people. To get a score at all in the pushup section
you will have to perform 5 correct pushups, which not everyone can do. Maybe the score limit needs to be lowered to be accessible for all kinds of people.
Another kind of fitness test is one that could use V̇O2max instead of a timed run to evaluate endurance. This is how they did it in (Hansen et al., 2004). A higher V̇O2max would then be a sign that a person is more trained that one with lower V̇O2max, however this also varies from person to person.
Strength could be evaluated through free-weights with full body exercises such as the squat, overhead press, bench press and deadlift. A higher maximum weight would then equal a higher score.
One thing that makes the APFT more suitable is that they consider age and gender and in turn change requirements accordingly, which this test does not. Another point in favor of the APFT is that most people have most likely run, made a sit-up and a pushup sometime in their life. While the squat, overhead press, bench press and deadlift are common for people who go to the gym to do strength training, they are much less known to people outside the gym. They rely heavily on the person knowing how to perform them correctly, and as such people who know how to perform them will have a significant advantage over those that do not.
Taken this into consideration, APFT was chosen as this thesis’s fitness evaluation test.
3.4 Selection of Reaction Time Tests
According to Cognifit.com3 there are three important parts of a person’s RT. Firstly, they will use their perception. This is the ability to see, feel or hear stimuli. Secondly, they will use their processing skill. This is their ability to understand what the correct way is to react to the specific stimuli. The processing part of the RT involves the executive functions. The executive functions (Miyake et al., 2000) includes the abilities of switching and performing multiple tasks concurrently (shifting), filtering between important and unimportant stimuli (inhibition), and switching out and updating the working memory (updating). Processing speed is the time from when you receive the information to that you understand it and start to respond. Lastly the person will make a response. This is when they physically act on their action prompted by the stimuli.
Stroop Test: There are three experiments in the Stroop test (Stroop, 1935). In the first experiment in the first test, the subjects must read the name of the color written in black. In the second test they must read the word, which is the name of a color, regardless of what color it is written in. The colors used in all the experiments is red, blue, green, brown and purple.
In the second experiments first test, the words in experiment 1 was replaced with solid squares and the subjects will state the color of the squares. The second test of experiment 1 was also used but slightly different, the subjects will now name the color of the word instead of the word itself. The word is the name of the different colors it can be written in. The third experiment simply evaluated the impact practice has upon the tests. It used the same tests as in experiment 1 and 2.
The test from experiment 2 test 2 evaluates the persons delay in RT to congruent and incongruent stimuli and will be useful to include in this experiment. This test will mostly evaluate the processing part of the RT and inhibition.
Trail Making Test (TMT) A & B: The TMT evaluates several abilities useful when playing FPS games. According to Tombaugh (2004) it will evaluate the person ability to search and scan, the speed of processing, mental flexibility and executive actions. TMT-A mainly evaluates the processing speed of the subjects while TMT-B adds more executive functions such as the need to perform multiple tasks at the same time, shifting, which increases its difficulty. Both TMT-A and TMT-B also require a lot of switching out and updating the working memory, updating is however more intense in TMT-B. TMT will be a useful test to include in this experiment to evaluate the before mentioned executive functions.
Tower of Hanoi (TOH): This test could be performed non-virtually with a Tower of Hanoi three- peg set. (Miyake et al., 2000) stated that performance on TOH was most related to inhibition. This test would involve a lot of the response part of the RT as the subjects need to move the pieces a lot. It is
important to include and evaluate all parts of the RT, therefore this test will be included in this experiment.
n-Back Test: First invented by Kirchner back in 1958 (Kirchner, 1958) the experiment involved 20 young (18-24 years old) and 20 older (60-84 years old) subjects. The experiment consisted of different lights that would turn on and off, one at a time, and a keyboard with corresponding keys to the lights. There would be 6 lights/keys in the warmup and 12 lights/keys in the real test. Several different tests were part of the experiment, the No-back, One-back, Two-back and Three-back test. The No-back test have the subject press the corresponding key to the light that is on. The One-back would have the subject press the key of the light that appeared before the current light. In the Two-back and Three-back the subject must press the key of the light that appeared two and three steps back compared the current light. This test evaluates a person’s updating skill because they must save the position of the lights in working memory while responding to the current light. There is a lot switching out information in the working memory for new, important information. This test will be included in the RT tests of this experiment as it evaluates updating skill thoroughly. The only other test that evaluates updating is TMT test, which also evaluates other skills, so this will be a more focused test.
Eye Tracking Visual World Paradigm Test: The visual world paradigm test created by Michael Tanenhaus is a test where you hear a word and you should identify the correct picture, out of four pictures. This would evaluate the RT between hearing a sound and correctly identify what it means. This test would not involve as many muscles as the other tests performed with the mouse as the choices would be determined with the eyes via eye-tracking. This would involve the inhibition part of the processing skill. While it would be interesting to lessen the impact of the response part of the RT from the arms to only the eyes, enough test is included to evaluate inhibition and the Stroop test is more intricate than this test. response is also a very important skill to have in e-sports so lessening it would make it less related to real RT in the games themselves but useful when isolating the different parts of RT.
The Simon Effect Test: The Simon effect was first introduced in the paper (Simon and Rudell, 1967). There they found that if a subject was given a verbal “right” or “left” in the right or left ear (regardless of the word), they would respond faster if the correct response was on the same side as the word indicates. In other words, if the subject heard “right” in the right ear they would respond faster than if they heard “right” in the left ear. The Simon effect can also be demonstrated using a computer screen and two buttons in two different colors. The computer screen will display an object in either of the two colors somewhere on the screen. If the object is closer to the button of the wrong color it will take longer to respond correctly to the object than if the object was closer to its right answer. The test involves the processing part of the RT and uses the inhibition part of the executive functions. (Simon and Berbaum, 1990) claims that the Simon effect and the Stroop effect are different in that they involve separate stages of processing. They claim that the Stroop effect is focused on congruence while the Simon effect is focused on spatial correspondence. Although an interesting test, this test will not be included as enough tests evaluate the inhibition skill of the subject.
Suitable software for tests: E-Prime or SuperLab can be used to create the Stroop test, the TMT and most likely the n-back test, although a prototype of the n-back test is not shown in this thesis.
SuperLab 5.0 demo version was used to create the prototypes of the Stroop test and TMT because it is simple to get started with and create experiments in. However, to collect data a full version of SuperLab is required.
4 RESULTS AND A NALYSIS 4.1 Fitness Test
To evaluate how well-trained the subjects are in this experiment the APFT4 will be used. This test is used in the USA army to evaluate the dexterity and strength of their personnel. The APFT consists of three different tasks. The first task is used to test the chest, shoulders and triceps muscles. The subjects will be asked to complete as many pushups as possible in under two minutes. The pushups must be performed correctly and will not count if an error is made. The second task will test the abdominal and hip-flexor muscles. The subject will be asked to complete as many sit-ups as possible in under two minutes. These will also need to be performed correctly and will not count if performed incorrectly. The third and final task will test the subject’s aerobic fitness and leg muscles. The task is a two-mile, 3.2 km, run and must be completed as fast as possible.
The APFT gives great accuracy in fitness level as the three different tasks are graded individually with a 0-100 score depending on result, the sex of the subject and age. An APFT Calculator5 will be used to calculate the final score of each subject.
The USA army is highly focused on the physical fitness of its members and use APFT to evaluate said fitness and it points to the test being a good way of measuring physical performance. The test evaluates the strength, endurance and dexterity of the entire body. This means that if a subject is a lot better at the run task and the sit-up task but less so at the pushup task, they can still get a good score.
The different tasks will all need to be performed correctly as to minimize chance of injury for the subjects but also so that the task is equal effort between subjects. A physical overseer will preferably be on site to display how the tasks are done correctly and to correct any mistakes done by participants.
4.2 Reaction Time Test
The RT evaluation part of the experiment conducted from this study will consist of four different tests. The first test is a Color Word Stroop Test (Stroop, 1935) where the subjects will name the color of the text that different words are written in, where the words are names of different colors. This incongruent test will evaluate how well the subjects can focus on the important stimuli while ignoring the unimportant. The test used will be a modernized version of the classic Stroop test and will be performed on a computer. Keys on the keyboard will correspond to the colors of the words where G = Green, B = Blue, R = Red and Y = Yellow. The total time to complete the test will be recorded in a file.
A wrong answer will be recorded in a file, and the same word will be presented again. This6 is an example of the prototype that was created for the Stroop test.
The second test is a TMT with parts A & B (Reitan, 1958). Part A of this test, Figure 3, will ask the subjects to find and click the numbers 1 – 25 in ascending order as fast as possible. If a mistake is made an error sound will be heard and the subject will have to correct their mistake. Part B, Figure 4, is a lot like part A but will ask the subjects to alternate between ascending numbers and ascending letters from 1 – 12 and A – L. These TMT tests will also be modernized and made on a computer. Before each TMT test there will be a tutorial on how the test is completed. The tutorial version of TMT-A will have the numbers 1 – 4 and the tutorial for TMT-B will have the numbers 1 and 2 and the letters A and B.
The purpose of TMT-A is to evaluate how fast the subject can process information and TMT-B is about how fast they can switch between different focus areas. The time to complete each part is saved in a file separately. These are the prototypes made for TMT-A tutorial7, TMT-B tutorial8, TMT-A9 and TMT- B10.
4 https://usarmybasic.com/army-physical-fitness/apft (visited 19-04-2020)
5 https://usarmybasic.com/army-physical-fitness/apft-calculator (visited 19-04-2020)
Figure 3: Trail Making Test A Figure 4: Trail Making Test B
The third test will be a TOH test. This test was created by Édouard Lucas in 1883. The subject will be given a set of TOH which contains seven discs of wood with varying sizes and a block with three pegs on it. The discs will then start with the biggest disc on the bottom of a peg with all the other discs above it in size order with the smallest on top. The subject may only move one disc at a time, and it may only be placed on an empty peg or on a disc of bigger size. The game is completed when the entire stack has moved to another peg than the starting one and the discs are in the same order as when the game started. This test will be focused on the physical part of the RT.
The fourth and last test will be a variation of the classic n-back test. Instead of lights that turn on and go out, numbers or letters are often used. This test will use numbers and performed on a computer.
How the test is performed is that a fixation cross will be shown, then after some time a number will appear and then disappear. Varying between the 1-back, 2-back and 3-back, subjects will have to answer if this is the same number that was shown 1, 2 or 3 steps back.
The 1-back test will be used as a sort of demo to make sure the subjects understand how the test is performed. The 2-back and 3-back tests will then be performed, and these are the results that will be compared between subjects.
Subjects will answer verbally “yes” or “no” into a microphone if the number matches the number shown 1/2/3 steps back, with regards to what test they are performing. An administrator will then, for the 2-back and 3-back test, review the audio file to collect the data of how many correct and wrong answers. This test will be used to evaluate the working memory of the subjects.
4.3 How This Experiment is Meant to Be Performed
This experiment will not have separate groups, the results will be compared in the group between subjects. Every subject will have their own APFT results and their result from each of the RT tests.
Because acute exercise improves RT according to (Brush et al., 2016), the RT tests will be done before the APFT to counteract any effect from one test to the other. At least 50 subjects will be needed in this experiment to reliably conclude some sort of connection, but more participants are always good as the results will be clearer.
4.4 How the Score is Presented for RT Tests
Score is important when creating graphs of the different RT tests. (Scarpina and Tagini, 2017) shows that there are many ways to calculate score on the Stroop test. However, they also state that none of the different Stroop scoring methods correctly evaluate the Stroop effect and that innovation is required for well working scoring.
Both the speed and accuracy of the performance must be measured. Therefore, the time to complete the test and the number of errors made will be shown in two different graphs for the Stroop test.
(Bowie and Harvey, 2006) writes that the commonly used maximum time to complete the TMT is 300 seconds, so that will be used in this test too. They also point out that errors do not need to be tracked, as they will reflect the total time to complete the test. Therefor they will not be tracked in this experiment
neither. The graph for the TMT-A and -B will be two separate graphs that show the total time to complete each test, with lower time indicating better performance on the tests.
TOH performance will be measured only by the time required to complete the tasks. There is an optimal way to solve the TOH and wrong moves could be calculated with how many extra moves were made. These wrong moves will however be reflected on in the time required to complete the TOH test, so they will not be tracked.
N-back test results could be shown by how many correct and wrong answers were made, but also with how many close to right answers were made. If the subject for example on the 3-back test said the answer that is 2-back or 4-back. In this experiment the graph will only include the number of correct answers. This is to make the graph simple to understand and the results clear. Separate graphs of the 2- back and 3-back test will be made.
4.5 How to Interpret the Results from the Tests
The total score on the APFT physical fitness test gathered from all the subjects would be put into a graph. Graphs for each of the separate tasks of the APFT would also be made (the pushups, sit-ups and run). Two graphs for the Stroop test and TMT and one for the TOH and n-back test. Then we can see if a specific fitness test result gave more improvement in a specific RT test. In other words, let us say we have one group, group A, which includes subjects who score well on the run but poorly on the pushups and sit-ups. Then we have another group, group B, which includes subjects who scored well on the pushups and sit-ups but poorly on the run. If then group A performs much better than group B, or contrariwise, on a specific RT tests then we can see some sort of connection there.
An example of an APFT graph can be seen in Figure 5 and an example of a TOH result can be seen in Figure 6. Be aware that these are not real results, these are just examples. If we for a moment pretend that these are real results, we can then compare subjects score across the graphs. Subject nr is a number given to each subject before testing starts. Seven subjects are not enough to gain reliable results in a real test, but for this example it is enough. In these graphs we can see that those who scored lower on the APFT got lower results on the TOH. We could then also compare the separate graphs for each task of the APFT and see if this trend continues across all the graphs or only in one or two of them. If there are for example only one of the fitness graphs that contains the trend, then this would be the task that had the highest impact on that RT test. For example, the fitness graph could be the pushups and the RT test could be the TOH test. Then we could look at what the TOH evaluates more specifically, which is inhibition and response. Then we may hypothesize that there is a connection between the physical fitness required to do many pushups in a short amount of time and inhibition and response. There are other things that may impact this result, that is why it is only a hypothesis and not reliable results. More experiments need to be done thereafter to conclude the results as reliable.
As only e-sports players are subjects in this experiment, the results found may not translate to other kinds of people. The results may translate, but another experiment with different kinds of people need to be completed to be sure that the results translate.
Both updating and shifting will be tested in TMT. TMT-A will test updating at lower capacity and TMT-B will test updating at higher capacity and shifting. TMT-A and TMT-B will have separate graphs.
Figure 5: Fitness Score Figure 6: Tower of Hanoi Result
4.6 Equipment Needed to Perform the Experiment
A computer with a screen, a mouse and keyboard will be required for the version of the Stroop test, TMT and n-back test explained in this experiment. Almost any version of this equipment can be used as all the subjects will use the same equipment no difference will be made there. The software used for the tests does not require much performance from the computer, so any computer available should be usable.
A microphone to record the subjects answer on the n-back test will also be required. Any standalone microphone should do fine if the voice can be heard clearly. A mobile phone with a microphone could otherwise be used if no standalone microphone is available to record the audio. A license to E-Prime or SuperLab is required to get the data from the tests onto a file.
One physical TOH set will be required to complete the TOH test. The exact numbers of pegs and discs included is not important if it is not lower than three pegs and seven discs and all subjects use a TOH set with the same number of pegs and discs.
5 D ISCUSSION
5.1 Discussion About Research Questions and Hypothesis
Here I will discuss the answers that were found to answer my research questions and how my hypothesis changed from the beginning of the research to currently.
RQ 1: Can you evaluate how well-trained a person is on a numeric scale and if so, how?
This is possible, at least to some extent. Using the APFT we can gain a somewhat detailed description of a person’s fitness level on basic tasks. This does not fully evaluate the persons health or training. A bigger, broader evaluation will have to be done if a more detailed description of a person’s health and training is needed. However, the APFT works fine for what I am trying to accomplish in this experiment. What I try to do is compare the fitness level of the different subjects, and the score system of the APFT lets this be done very cleanly and the results will be easily understood. I also try to see how different parts of fitness impacts the different RT tests. As APFT involves 3 distinct tasks, it works well in that aspect too.
RQ 2: Which tests are viable tests to measure a subject’s RT and different executive functions?
There were a lot of tests that meet these criteria. The ones that were chosen were the Stroop test, the TMT, the TOH and the n-back test for their ability to test different executive functions. A simple reaction time test could have been used to test basic RT, for example see how fast a person can press a button on a keyboard when something flashes on the computer screen. This test would then simply evaluate physical fitness relation to RT. The tests I choose where however more focused on the executive functions, a deeper connection between RT and fitness.
Main RQ: Is it possible to develop a series of tests to find out the correlation between physical fitness, RT and executive functions in e-sports players?
I believe that the correlation between physical fitness and RT will be possible to see in this experiment. This is because so many experiments have previously shown a relation between aerobics and RT and the APFT involves running, which is an aerobic exercise (Colcombe and Kramer, 2003), (Hansen et al., 2004), (Smith et al., 2010) and (Griffin et al., 2011). The APFT also test strength, which was shown to increase some executive functions (Colcombe and Kramer, 2003) and (Eckardt et al., 2020).
The relation between specific physical fitness aspects of the APFT and specific executive functions will be much harder to conclude.
Original Hypothesis: “My hypothesis is that it will be possible to accurately find the physical fitness level of subjects through a physical fitness test and that result can then be compared between subjects. Furthermore, I believe that those who score overall better on the fitness test will also get an overall better score on the cognitive tests. The parts that make up RT can possibly be accurately measured through different tests and that we can isolate those different parts of RT. Hopefully we can then see what specific parts of the physical fitness affects which part of the RT and the executive functions.”
Current Hypothesis: I still believe that the we can find an overall fitness level of the subjects through APFT, and it will be possible to compare that result between subjects to find the more fit subjects. I still agree that a better overall score on the fitness test should correlate to a better score on the RT tests, and vice versa. I do not believe we can measure the different parts of RT accurately enough with the setup described in this thesis. The executive functions are too complicated and closely related to other cognitive functions that they are very difficult to isolate.
5.2 What Could Be Done Differently with the Prototypes and Choice of RT Tests
While my example of a Stroop test included the colors red, blue, green and yellow, the original Stroop test (Stroop, 1935) used the colors red, blue, green, brown and purple. He did not use yellow because, in his words, “… the difficulty of printing words in yellow that would approximate the stimulus intensity of the other colors used …”. Therefor I suggest removing yellow and adding brown and purple instead.
In the original Stroop test, the subject could read the next word as soon as they were done with a word. In my version, however, there is a fixation cross and a timer before the next word is shown after response to a word. This waiting time could be removed to resemble a closer version of the original Stroop test.
A prototype could have been made for the n-back test. SuperLab 5.0 has the capabilities of creating the n-back test described in this thesis. It was however not made because of time constraints. To alleviate the need of microphone, the n-back test could perhaps be programmed to know the correct answer is await input from the user. Instead of verbally saying “yes” the use could press 1 and instead of saying
“no” the user could press 0. It could then save in a file if the answer is correct or not.
(Jaeggi et al., 2010) raise concerns that fluid intellect among other things impacts the n-back test more than working memory itself. That the n-back test is not a pure working memory test and that it gives mixed results, making it unreliable. However, it is still widely used in experimental environments.
Even if other factors may impact the results other than working memory, it will still give some indication of the working memory capabilities of the subject.
Fluid intelligence impacts TOH significantly according to (Zook et al., 2004). This would make it less dependent on the physical reaction part of the RT. Maybe the physical part of RT could be evaluated in some other way? Perhaps a simple reaction time test where the subject would just press a button when they see a flashing on the screen. This would isolate the physical part of reaction time. However, TOH displays physical RT more like the games an e-sports player would play, in that they are more complex.
The physical reaction in TOH happens after the problem of how they should react is solved. In the simple reaction time, the subject already knows how to react. So perhaps switch the TOH with a simple RT test, or maybe not. I would suggest keeping the TOH test.
5.3 The Reliability of the Results
The conclusions drawn from this experiments data will a bit different compared to the experiments discussed under the “related works” chapter. This experiment does not include a control group and does not compare the subjects results between two points in their life to see the results of an interception on the subjects. This means that we are not sure where the results from the tests origin from. We should, however, at least still see that people who perform better on the run should perform better on the RT than those with worse results. This would align with the results from (Colcombe and Kramer, 2003), (Hansen et al., 2004), (Smith et al., 2010) and (Griffin et al., 2011) that found that aerobic fitness resulted in improved RT. Even (Diamond and Ling, 2016) agrees with this. Because even if they are sceptic against these experiment that tries to prove a connection between aerobic fitness and RT, they do agree that people with better overall aerobic fitness do perform better on executive functions than those with worse aerobic fitness. Subjects performing better on sit-ups and pushups should also attain greater results in RT according to (Colcombe and Kramer, 2003) and (Eckardt et al., 2020), but perhaps not to the same extent as the run.
If a person who performs better on a specific part of the APFT fitness test also performs better on one of the RT tests we can see a link. This link might however not be a true link between the two actions, meaning that the result always happens, and it might be the result of something else.
5.4 The Experiment Used as a Tool
Being able to use a test to evaluate what kind of physical activity would benefit your RT would be great to have both for professional e-sports players and casual players alike. If we see connections between different tasks of the APFT and executive functions, this experiment might be able to be used as a tool.
However, there is still problems if this experiment is used as a tool as it is currently described. A problem with this experiment is that if it is used as a tool to see where an e-sports player need to improve, there will be an effect of the person learning how to perform the test better. Let us say a subject performs acceptable on the Stroop test then increases his score in the running fitness task from for example 30 to 50 and then performs better on the Stroop task than previously. We cannot for sure state that this would be a result of the increased points in running and not that he got better at the test itself.
Perhaps a second task that evaluates the same executive functions could be used, so in the second taking of the RT tests, Stroop would be replaced with another test that evaluates inhibition, for example the Simon Effect Test. There would however be great complications in comparing the results from the Stroop test to the Simon Effect test. As described in the chapter “Available Reaction Time Tests”, even if both the Stroop test and the Simon Effect test both evaluated inhibition, they still work in different ways. The Stroop test evaluates congruence and the Simon Effect test evaluates spatial correspondence.
Even so, the two tests will vary in time required to complete them, making comparison difficult.
5.5 Isolating Executive Functions
A lot of tests that are meant to evaluate specific executive functions also include other cognitive functions to lesser extent. While the Stroop test is used in this experiment to evaluate inhibition, (Kane and Engle, 2003) found that the working memory of the subjects was important. Those with high working memory capabilities performed better on five different Stroop tests, with varying amount of incongruent words.
All the RT tests will also require a physical reaction in some way to communicate that the subject understands what the correct solution is to a given problem. This means that isolating and evaluating only a specific executive function becomes very difficult.
More research needs to be read, or done, about if it is possible to isolate and test executive functions.
6 C ONCLUSION AND F UTURE W ORK 6.1 Conclusion
To sum things up, as aerobic exercise and strength training combined with aerobic exercise increases RT and executive functions, we will most likely see that a higher score on the physical fitness test yields better results on the RT tests.
We might see a trend between different tasks of the APFT leading to better results on some of the RT tests.
The experiment will most likely not work as a tool to evaluate users to show them what physical exercise they must focus on to improve certain executive functions. In the state that the experiment currently exists in, it is difficult to confirm reliable connections between specific executive functions and tasks on the APFT. A more robust tool needs to be created after a connection between different physical fitness and specific executive functions is firmly confirmed.
6.2 Future Work
There is a lot of papers and research that could not be read due to time constraints. These different papers may yield different perspectives that may improve this experiment.
Heart rate variability used in (Hansen et al., 2004) would be interesting to include in this experiment. It would need to be researched in what way it relates to cognitive functions, but it might be another way of determining the physical fitness of the subjects.
There is a lot of papers about the relation between physical fitness and RT. So much that it would be impossible to read it all. It would however be interesting to read more about it and the opposition against it.
It would be interesting to read more about the executive functions, and to see if they can truly be isolated. As it stands now, it is not clear how that would be done.
Most test evaluating the connection between RT and fitness mostly involves seniors and people with underlying diseases, this is most likely because the research tries to alleviate some of the problems these people are experiencing. More studies need to be done comparing RT between two groups of youths where one of the groups undergoes training and the other does not. This research would not help in the sense of creating a better day to day experience for the people, but more to understand the relation between training and RT.
Performing the experiment described in this thesis would be needed to see what results would be found. We can speculate what would happen, but we do not know for certain until it is done.
Another interesting experiment would be to evaluate subjects result on the RT tests and the APFT.
Then train half the subjects in the APFT tasks, so the sit-ups, the pushups and the run over several months. Then see what results they get in the APFT and the RT test and if they both improved.
If interesting results are found in this experiment, then the experiment should be replicated with different kinds of subject apart from e-sports players to see if the results translates to them too.
More work needs to be done regarding the connection between specific executive functions and specific training. Only then can we truly start to assemble a tool that can accurately evaluate what physical exercise the user needs to perform to improve their overall RT through specific executive functions.
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