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Measuring physiological responses to colour through virtual reality environments

PROJECT OCELOT

M.S. CUTRERA,

University of New South Wales, Sydney, Australia

m.cutrera@ad.unsw.edu.au

Abstract.

This research focused on the effect that virtual reality has on the user through the analysis of their physiological responses. The virtual environment is focused around colour and how they can affect us physically. By replicating Mikellides 1990s experiment on colour arousal but replacing the setting of the experiment from a real room to a virtual environment while monitoring participants physiological responses, comparisons with the original experiment were made. Since both results were relatively equal virtual realities use as a tool to create reactions similar to reality was supported. Further expansion on the original experiment was made to test Mikellides conclusion that colour saturation has a higher arousal rate than colour hue, by adding more colours at full saturation and half saturation as well as at different hues. The results did not show a large margin of distinction between the hues and the saturation levels although high saturation colours had a marginally higher arousal rate. Although this research tested stark changes in environment, it has proven that they have an effect on physiological signals. Further development could lead to clients and end users reactions of real designs being analysed early in the process rather than relying on post occupation surveys.

Keywords. Virtual Reality; Physiological Responses; Surveys; Biometric sensors; Colour psychology.

1. Introduction: Research Aims and Motivations

Virtual reality (VR) is becoming more commonplace in architectural practice to visualise designs before they are confirmed for the building process. Rather than relying on post occupation surveys that can be bias. By using VR to experience the design, changes can be made during the virtual part of the build measure learn cycle, therefore saving time and money. It is generally assumed in architectural practice that the reactions observed in VR environments are the same as those experienced in a real physical environment. Little research has been done on the validity of this assumption since VR is a recent technology. Project Ocelot aims to further validate virtual reality as a useful proxy that achieves the same physiological reactions as reality. Within Project Ocelot this research is focusing on colours effect on our physiological state in VR. A benefit of using VR to test environments is that space and materials are saved since it does not have to be built in reality, ultimately saving time, money and resources.

2. Research Observations and Objectives

The objective of this research is to test VR users reactions to virtual environments without having to rely on surveys where answers can be untruthful and contain bias. Through monitoring physiological reactions to the virtual environment, correlations between the signal data and events or aspects in the environment can be found. Ultimately to test designs on customers and future end users rather than using post occupancy surveys. Through measuring the physiological signals such as Electrocardiography (ECG), Electrodermal activity (EDA) and Electroencephalography (EEG) while in VR reaction to events or scenes in VR can be further analysed.

3. Research Questions

This research focuses on the effect that colour has on a person's physiological response. Ultimately measuring physiological reactions to colour through virtual reality environments. The effect colours have on us has been looked at for many centuries so it would be beneficial to examine its effects inside of VR. Through exploring colour’s effect on physiological reactions in VR by replicating Mikellides (1990) experiment on colour arousal but replacing the real room with a virtual reality representation. If the results are similar it will substantiate VRs ability to produce physiological responses similarly to reality. While this research will replicate Mikellides’ experiment it will also extend it. Especially the claim that “chromatic strength (saturation) is the key dimension affecting how exciting or calming a colour is perceived and not on the dimension of hue”. In VR this experiment will be expanded by testing more than just two colours of red and blue but adding green and also the colours with different saturation levels. Therefore adding more depth to the methodology of the experiment by later comparing the results of rooms of different hues as well as different saturation levels.

There are two phases to this research, phase one is a replica of Mikellides’ 1990 experiment that consisted of placing participants for 20 minute intervals facing each wall of a room that has been painted half red and half blue while wearing physiological sensors. The replication of the experiment was in virtual reality rather than a physical space. The second phase consists of developing the experiment further within the virtual environment through extending the colours tested.

4. Background Research

1 4.1 Literary Review

This research is centred around how people react physiologically to different colours in a virtual reality environment, the main relevant literature can be divided into two main categories methodology and theoretical. This question can be divided into three main elements, those are: physiological responses, virtual reality environments and the effect of different colours.

Examining how people react to virtual reality stimuli has been explored since virtual reality became available, but in recent years more so because of the advances in virtual reality equipment. To collect participant’s reactions to different stimuli many researchers use physiological sensors (Wiederhold, 2002 and Garau, 2005) rather than surveys, some use both to compare the results (Koelstra, 2012) while others rely solely on surveys.

Colours and their impact on our emotions and physiological state have long been explored in a range of fields especially in art and interior architecture. But rarely colours’ effect in a virtual reality environment has been explored in recent years. The effects of nature and if “fake” virtual nature (de Kort, 2006 and Valtchanov, 2010) has the same restorative and calming effects that exposure to real nature has (Berto 2014) has been explored in two papers published four years apart. The method used to test this hypothesis was to constantly record physiological signals of heart rate and skin conductance levels while participants went through a stress inducing exercise and after the experience were exposed to natural scenes projected onto a large screen to increase immersion (de Kort, 2006). A very similar method was used in Restorative Effects of virtual nature setting (Valtchanov, 2010) but rather than using projections, participants were exposed to a virtual reality environment of a virtual forest, in Ocelot the methodology is similar to the previous studies except that participants will not be exposed to a stress inducing task prior to entering the coloured room variations, therefore not testing how the different colours calm or agitate the participants further but rather seeing if and how different colours cause a physiological change in the participant. Although from these studies the preferred physiological responses to monitor were heart rate and skin conductance, this is due to their link to detect and represent stress in participants “(Skin conductance sensor measuring the resistance between electrodes) This resistance decreases due to an increase of perspiration, which usually occurs when one is experiencing emotions such as stress or surprise” (Koelstra, 2012) the use of these specific sensors is a common thread found in other research testing physiological responses to virtual stimuli.

The concept of exposure to colour changing the state of mind of a person is something artist James Turrell looks at in depth in his coloured light installations especially the Ganzfelds series were whole rooms are filled with coloured light, blurring the edges of the space, “My work has no object, no image and no focus. With no object, no image and no focus, what are you looking at? You are looking at you looking. What is important to me is to create an experience of wordless thought.” (Turrell, 2017). Turrell takes colour in architecture to the extreme filling the whole space with that coloured light, guiding the audience to a specific reaction but letting each participant have their own view of the space, therefore not testing if they are actually getting the artists desired reaction to the space. Mikellides tests the effect that warm colours have versus cold colours with a method similar to Turrell’s famous installations. To test the difference warm and cold colours have on human physiological state (Gerald, 1958), a room was painted half red (R) and half blue(B), red representing warm colours and blue cold colours, all surfaces in the room were painted in these colours. The participants were then exposed to each side of the room, all R, RB, BR and all B, for a set time while physiological responses were measured. This kind of experiment has also been done previously by R.M. Gerald, 1958 but using coloured light directly on the participant's eyes. In the Ocelot research project will adapt this procedure to a modern virtual reality experiment. In Colour psychology and colour therapy: Caveat emptor (O’Connor, 2011) the beliefs and theories surrounding colour are compared and analysed, providing good summary of foundation knowledge on the literature of colour theory.

2 4.2 equipment research

|[pic] |

Figure 1. Image of BITalino revolution Board kit.

The equipment that will be used for this research is the BITalino (r)evolution Board Kit, a biomedical data acquisition dev board with cable extensions to snap on electrodes to the end for easy application . This is due to its range to measure multiple physiological signals at once with relatively good accuracy. Other sensors were tested but the BITalino proved to the most effective. The chosen physiological responses that will be measured are ECG and EDA since they are the most responsive and easier to analyse the signal produced. These two sensors are also the ones used for multiple other experiments in projects of similar nature.

1 4.2.1 About the Sensors

Electrocardiography (ECG) refers to the measurement of electrical impulses passing through the heart; it measures heart rate. The sensors are usually placed on the chest, but can also be placed on the hands. For this experiment, they will be placed on the left side of upper chest. ECG uses electrodes to gauge the frequency of electrical impulses generated through the heart, measuring in units in microvolts. External bumping of the sensors will affect the data recorded.

Skin Conductance (SC) also known as galvanic skin response (GSR) or Electrodermal activity (EDA) modulates the amount of sweat secretion from sweat glands. These terms refer to the variation of the electrical properties of the skin in response to sweat secretion. It measures arousal. The higher the arousal, the higher the skin conductance. Both positive (“happy” or “joyful”) and negative (“threatening” or “saddening”) stimuli can result in an increase in arousal–and in an increase in skin conductance.

Although this physiological response happens on the whole skin surface of the body, a sensitive analysis can only be measured from the hands or feet. In these places there is a high density of the eccrine sweat glands, which are known to be responsive to emotional and other psychological stimuli. For this experiment EDA sensors will be placed on medial phalange of the index and middle fingers of the non-dominant hand. It is measured by applying a low constant voltage, the change in skin conductance can be measured non-invasively. High activity can affect the conductance as high physical activity will cause the body to respond with sweating to cool down.

5. Methodology

This text after another first order heading begins at the left-hand margin.

1 5.1 Scene Development

There are two phases to this research. Phase one consists of replicating Mikellides experiment in virtual reality. Phase two aims to develop the experiment further by testing more colour variations, consisting of red, green and blue at both full and half saturation levels, to compare results between colour saturation and hue.

The virtual reality scene was developed to be as simple as possible to not interfere with the participants reactions to colour. The scene is plain room with the dimensions of 3.5✕4.5m with the walls, ceiling and floor all painted with the same colour and a light in the middle. The reason the room is square rather than a sphere where one would only be exposed to just the colour without shadows in the corners that change the colour slightly, is to maintain immersion and the feeling that the scene could be real like the experiment that this study is replicating. By being square the room has difference in shades of the colour especially visible in the corners but since all the rooms have the same lighting qualities this variable is controlled. The colours for the rooms in phase two are all on an RGB scale with changes in saturation (the addition of white into the colour). The chosen colours are:

TABLE 1. Colours used in VR

|R100 |[pic] |

|Red value |Green value |Blue value | |

|255 |0 |0 | |

|Saturation (%) |Hue |Hex code #RRGGBB | |

|100 |0 |#ff0000 | |

|G100 |[pic] |

|Red value |Green value |Blue value | |

|0 |255 |0 | |

|Saturation (%) |Hue |Hex code #RRGGBB | |

|100 |120 |#00ff00 | |

|B100 |[pic] |

|Red value |Green value |Blue value | |

|0 |0 |255 | |

|Saturation (%) |Hue |Hex code #RRGGBB | |

|100 |240 |#0000ff | |

|R50 |[pic] |

|Red value |Green value |Blue value | |

|255 |128 |128 | |

|Saturation (%) |Hue |Hex code #RRGGBB | |

|50 |0 |#ff8080 | |

|G50 |[pic] |

|Red value |Green value |Blue value | |

|128 |255 |128 | |

|Saturation (%) |Hue |Hex code #RRGGBB | |

|50 |120 |#80ff80 | |

|B50 |[pic] |

|Red value |Green value |Blue value | |

|128 |128 |255 | |

|Saturation (%) |Hue |Hex code #RRGGBB | |

|50 |240 |#8080ff | |

The reason these are the chosen colours is because they are universal and easily transferable to other screens since they are composed of LEDs consisting of RGB. Green was added to the original colours in the experiments of red and blue to add more variety rather than the usual cool versus warm colours, adding another dimension. In future tests a large variety of colours could be tested but for this research the main colours of RGB (Red, Green, Blue) that construct all other colours in the spectrum will be the only ones tested. To further test Mikellides conclusion that colour saturation has a larger impact than colour hue, the colours tested are RGB with 100% saturation and the same colours but with a saturation value of 50%.

The program used to create the VR environment was Unreal Engine 4 version 4.17, this was due to the programs ability to easily produce high quality scenes as well as its adaptability to create VR compatible content. To create a greater resolution to the scene, the lightmap resolution was modified to have the ideal texel density. The images show the room at 4, 52 and 250 texel density, 52 was the final value used for the rooms as it was the most efficient and effective at producing a realistic feeling spaces.

TABLE 2. Lightmap Resolution and texel density

|Texel Density: 4 |Texel Density: 52 |Texel Density: 250 |

|[pic] |

|Insufficient texel density (4) |Ideal texel density (52) |

|[pic] |[pic] |

Each room scene is exactly the same with just the colour of the material changing. The light is placed in the middle of the room providing the same lighting for all the walls. The material for the room had to be modified to not be reflective by changing the specular value to 0 to prevent a distracting hotspot on the wall.

|[pic] |[pic] |

Figure 1. Left, showing room before and right side the specular value in material was set to 0 to reduce light hotspot.

There were some problems encountered when building the lighting in Unreal Engine 4, all the lighting that was inside of the rooms would go black. The rooms were created by having two BSP’s, a smaller subtractive one within a larger one to create the cavity inside to ensure that it was a sealed room. These BSPs were then converted to static meshes for easier duplication and material assignation. It was found that the lighting problem was a result of using BSP brush since there is a problem with the current version of ue4 with dealing with bsps and lights. To fix this the rooms had to be remodelled through 3dsMax or by using a static mesh cube transformed to be each wall, ceiling and roof.

2 5.2 Timing

Mikellides’ experiment consisted of testing participants in the room for 20 minutes for each colour variation. For the replication of this experiment participants were also be exposed to the variations for 20 minutes each to replicate the experiment as faithfully as possible. Although for phase two of the experiment on extending the research into the effects that colour saturation has versus colour hue since there are more colours to test. To get a larger sample size, the time spent in each coloured room will be one minute. Accounting for a total of six minutes inside of the coloured environments. This is because one minute is the shortest time it could be taken to to still achieve required exposure time to get valid results. Exposure to the scene was tested at 30 seconds per room but this proved to be insufficient time for an appropriate reaction to be measured. The shorter the experience, the more likely participants would be willing to go through it since it’s easier to fit 15 minutes into the work routine than 1 hour and 10 minutes, especially in the busy work environment.

1 5.2.1 Iteration I

The first prototype of the scene, the order of the coloured rooms was the high saturation rooms first followed by the low saturation rooms i.e. R100, G100, B100, R50, G50, B50. The participant spent 40 seconds in each room. The results showed a contrast between the high saturation (HS) colours and the low saturation(LS) colours but since the HS colours were at the beginning of the experience, The decrease in reaction especially in the EDA results could be due to the saturation or because the participant has grown used to the experience therefore grows more relaxed as time progresses. To decrease the reactions being according to time relaxation, the coloured rooms were mixed up for the second iteration.

2 5.2.2 Iteration II

In the second iteration the sequence was: Start (S), R100, white room intermission (WI), G50, WI, B100, WI, R50, WI, G100, WI, B50. The time in each room remained the same as iteration one but interlude rooms were added in between each coloured room for 7 seconds. The interlude room was coloured a light gray/white since it is a neutral colour. The interlude room was also added to the beginning of the sequence so that participants have a moment to become accustomed to the dimensions of the room and the VR experience. The white interlude space did not have the desired effect on the tested participant. Rather than relaxing their eyes, the colour white was a stark contrast that agitated the eyes. In this prototype it was noticed that the current exposure time of 40 seconds would not be enough to achieve a valid mean, therefore for the next iteration the time was increased to 1 minute.

3 5.2.3 Iteration III

In the third prototype, the intermission rooms were eliminated since they were not helpful to the participant but the starting room remained since it provided time for participants to become accustomed and also allowed for leeway in case anything was wrong with the equipment such as loss of signal from the Bitalino or if there was a problem with the headset. The sequence was: S, R100, G50, B100, R50, G100, B50. The time in each room was one minute. The problem with this iteration was that the participants tested did not see the real rooms colour but an overlap of the previous colour with the new, this is explained further in section 5.3.

4 5.2.4 Iteration IV

The fourth and final iteration was a collection of the best aspects of the previous iterations. Resulting in a sequence of: S, R100, black intermission (BI), G50, BI, B100, BI, R50, BI, G100, BI, B50, S.

|[pic] |

Figure 2. Sequence of Events for Virtual Reality environment.

3 5.3 Eye Colour Perception

During participant test of model in iteration 3, where the duration inside of coloured rooms increased to 60 seconds with no interludes, there was a change in colour perception for participants. This was most evident in the change from R100 to G50, rather than seeing the light green multiple participants saw a turquoise/aqua blue. This is due to the extended exposure to the red room, the brain is tricked into changing its perception of the light green. This problem is being fixed by providing an interlude time in between each colour change to give the eyes time to ‘reset’.

The interlude was tested as a white/light grey painted room but this did not provide the needed rest for the eyes since the effect of colours crossing over still took place. Therefore a black screen will be used as the reset interlude. The time needed for this interlude was tested by exposing participant to four different variations of interlude times and recording the colours that were perceived after the interlude.

1 5.3.1 Interlude of 5 seconds

TABLE 3. Annotations of testing an interlude of 5 seconds.

|Colours in order |Actual Room Colour |Colours perceived |

|R100 | |Normal |

|G50 | |Bright aqua colour, towards the |

| | |end of the minute it starts to |

| | |fade slightly into the required |

| | |colour |

|B100 | |Normal |

|R50 | |Normal but slightly brighter |

|G100 | |Normal but there are circles where|

| | |the headset moves, as if caused by|

| | |a mounted spotlight |

|B50 | |Normal but slightly stronger |

2 5.3.2 Interlude of 10 seconds

While testing the environments a slight defect was found that the lighting intensity changes according to where the user looks, similar to having a spot light mounted on the headset. This spotlight effect was most evident in the full saturation green. This defect was fixed so that environment colours seen by the user are not modified.

3 “Finding that my eyes grow tired and am thankful for the black space. Although I feel like closing my eyes during this period but scared of missing the (room) transmission”

To fix this issue a sound was added at the end of each black intermission so if participants want to rest eyes by closing them they can until they hear the beep. This will also help in the signal data by providing markers for when it changes colour. At the end of the simulation the last scene is like the start, a white/grey room, a few sounds will play when they reach this stage to show that they have finished the experiment.

TABLE 4. Annotations of testing an interlude of 10 seconds.

|Colours in order |Actual Room Colour |Colours perceived |

|R100 | |Normal |

|G50 | |No aqua but lighter than before |

|B100 | |Normal |

|R50 | |Normal |

|G100 | |Normal |

|B50 | |Normal |

4 5.3.3 Interlude of 15 seconds

This interlude time provides enough time for eyes to readjust to normal. The light green room that was troublesome does not appear bright aqua anymore. Although while in the interlude from R100 to G50 with eyes open there is a slight blue tint on the black, similar to when one looks at a light for a bit then closes eyes there is a leftover colour where you were looking at the light.

TABLE 5. Annotations of testing an interlude of 15 seconds.

|Colours in order |Actual Room Colour |Colours perceived |

|R100 | |Normal |

|G50 | |Normal |

|B100 | |Normal |

|R50 | |Normal |

|G100 | |Normal |

|B50 | |Normal |

5 5.3.4 Interlude of 30 seconds

The 30 second interlude provide more than an adequate amount of time for the eyes to adjust although this time is longer than is necessary.

TABLE 6. Annotations of testing an interlude of 30 seconds.

|Colours in order |Actual Room Colour |Colours perceived |

|R100 | |Normal |

|G50 | |Normal |

|B100 | |Normal |

|R50 | |Normal |

|G100 | |Normal |

|B50 | |Normal |

In conclusion the time of the interlude will be 15 seconds since it provides the needed time for resting and ‘resetting’ eyes without taking up too much time of the overall experience. A short beep sound has been added to the end of the interlude times so that participants are warned when there will be a colour change in the room. This sound only appears at the end of the interlude time not at the beginning of the interlude, due to not wanting to saturate participants with the noise. The functionality of the noise is in case participants close eyes during the rest period they are warned to open them again when they hear the beep.

4 5.4 Sensor Data Analysis

The Bitalino has a complementary program called OpenSignals (r)evolution, this program is used during the recording of the signals providing a real-time sensor data recording. This data was then exported as a .txt file to be processed in Jupyter notebooks with custom made Python code.

5 5.5 Experiment Procedure

Participants were seated in a chair and a brief introduction of the equipment and experiment requirements was given along with a written explanation. The Bitalino board that was mounted in an adjustable arm band was placed midway on left arm, adjusting the position depending on the length of the arm so that the cables that extended from the Bitalino could reach the participant's left hand and left side of the upper chest. Guidance was provided for the application of the ECG sensors on the left side of the chest and for the EDA sensors. Open Signals (r)evolution was used to record sensor data and a brief test before experiment commencement was done to check that signal outputs are correct.

|[pic] |

Figure 2. Diagram of sensor placement.

6. Case Study

For phase one due to its duration, only one participant was able to go through the experiment. The average value for all four scenarios was roughly the same. These results although their analysis was not as in depth as Mikellides results portray the same level of arousal is maintained throughout all four scenarios.

For phase two, 18 participants were tested (7 female and 11 male) although only 17 of the results were usable since the data recorded for participant 7 had a system error. Phase 2 results showed main changes in the EDA results with a common trend of starting high then decreasing, with the majority the lowest point being in the high saturation green (G100) then increasing at the low saturation blue (B50). The slow decrease in arousal from the start till the green could be considered due to participants getting used to the experience but the trend of an uprise in the data when getting to the B50 suggests that the colours are having a physiological impact.

The ranges of values acquired for each participant varied. For example p1 had a larger range and base level of skin conductance than p8 but there were still variations between the different stages. Therefore if the actual values for all participants were overlaid it would be hard to distinguish a clear trend. This is why to graph all participants results for EDA in one graph, the values were normalised. When plotting the normalised EDA changes, it was found that there was a clear trend of a decreasing slope and a rapid change in the last stage of B50.

The results of colour a high colour saturation having a bigger effect than colour hue have not been reflected in the results of phase 2. When comparing the average of each colour and compiling them per colour (testing hue) and per saturation, the colour Red has the largest average (50.1%) followed by blue (32.46%) and green (28.60%). While the difference in saturation is slightly higher value for high saturated colours it’s not a very large difference only 5.15%.

The ECG data analysis needs to the worked on since there was a lot of noise in the signals. This caused the final values to be very varied and not fully correct. Table 9 shows a graph of the normalised values although the data has to be cleaned further to be able to produce a readable graph.

TABLE 7. EDA results graphed

|P1 |P2 |P3 |

|[pic] |[pic] |[pic] |

|P4 |P5 |P6 |

|[pic] |[pic] |[pic] |

|P7 |P8 |P9 |

|Error with data |[pic] |[pic] |

|P10 |P11 |P12 |

|[pic] |[pic] |[pic] |

|P13 |P14 |P15 |

|[pic] |[pic] |[pic] |

|P16 |P17 |P18 |

|[pic] |[pic] |[pic] |

TABLE 8. EDA combined results graphed

|[pic] |

TABLE 9. Colour hue versus saturation results

|[pic] |

TABLE 10. Beats per Minute chart

|[pic] |

7. Significance of Research

The significance of this research is that although the results were not as expected, they show a participant having physiological reactions to virtual stimuli. With a clear trend in participant data analysis that the decrease as time progresses with fluctuations in the data at particular points in time, this is most evident in the decrease to G100 then a rapid increase when in B50. This trend shows that although it was not the expected reactions, users in VR have similar reactions ultimately proving that it is a useful tool for extracting reactions from people. Therefore showcasing that VR can be used to extract physiological reactions that can be measured and analysed. Ultimately VR and biometric analysis can be used not only to analyse the effects the virtual environment is having but also provide estimate of how people would react to the real world counterpart.

8. Evaluation of research project

A limitation found in phase one of the experiment was the modeling of the virtual room was derived from the information present in the original experiment report from 1990, some details were approximated. Therefore the replica is the most detailed possible limited by the description and diagrams given in the report. Another limitation is that unlike Mikellides’ sample count of 24 participants only 1 participant was able to go through the virtual reality replica. Another limitation is the sensors for the EEG were placed as closely as possible to the experiment but are not quite in the same position since the EEG sensors are in a pre-set hard frame.

The analysis of the results for the second phase have not shown the desired results of a clear difference between the full saturation rooms versus the half saturation rooms while there is a small difference of 5.15% between the low saturation rooms and the high saturation rooms. There is a higher average of arousal in the full saturation rooms than in the half saturation rooms; the analysis also showed no difference in between the different hues. These results have to be reinforced with further tests of different participants to statistically validate them. Limitations to this research are the time participants are exposed to the different room colours. Each participant was exposed to each room colour for sixty seconds, adding up to a total of 7m 40s inside the virtual reality, therefore roughly ten minutes in total including placing and removing the sensors. The exposure time could be increased in the future to provide longer reaction times. As well as extending time inside of the virtual reality experience, a longer baseline could be taken of participants with the headset turned off to create a baseline to compare results to.

A limitation with the testing was the external audio of the space where participants were tested. Since the testing was in an open office area, there was a lot of external sounds from the surrounding environment. This could have affected the reactions recorded. For future experiments the external audio should be monitored to see if there were correlations between the audio and the sensor data. It would also be beneficial for results if the testing was done in a closed room so that external audio could be controlled as well as providing privacy to the participant. Since being in an open exposed area could cause altered reactions from self awareness.

To increase statistical validity the order of coloured rooms should be altered to have a variety of reactions to results, nullifying the possibility that results decrease across time due to getting used to the experience.

9. Conclusion

The outcome of this research supports VR’s use as a valuable tool for representation. This has been a success by achieving getting the same results in phase one, with the replication of Mikellides experiment but in VR. Since the results showed that people have the same physiological reaction to virtual reality stimuli as they do to real world stimuli it supports the use of virtual reality as a reliable visualisation medium. This also opens up opportunities to use physiological sensors as an added layer of information rather than relying on surveys where responses can be unreliable and skewed. In phase two where colour saturation versus colour hue was tested, the analysis of the results does not confirm Mikellides’ conclusion that colour saturation has a higher arousal rate than colour hue but rather that red has a high arousal rate compared to other colours and that there is a slight difference between higher saturated colours than low saturation colours, adding to Mikellides’ conclusion but not through a large margin. The use of these findings in virtual reality can lead the use of colours to steer a user's reactions to be close to what the designer intends.

Future work could lead to developing the analysis tools for the physiological sensors to allow for real world designs to be seen in virtual reality and small oscillations in signals to be analysed in more depth rather than relying on big stark changes like the whole room colour, smaller changes can be made and analysed. In conclusion providing a valuable tool not only for the built environment industry but for a broader audience.

References

Berto, R., 2014. The Role of Nature in Coping with Psycho-Physiological Stress: A Literature Review on Restorativeness. Behavioral Sciences 4, 394–409.

de Kort, Y.A.W., Meijnders, A.L., Sponselee, A.A.G., IJsselsteijn, W.A., 2006. What’s wrong with virtual trees? Restoring from stress in a mediated environment. Journal of Environmental Psychology 26, 309–320. · Valtchanov, D., Barton, K.R., Ellard, C., 2010. Restorative Effects of Virtual Nature Settings. Cyberpsychology, Behavior, and Social Networking 13, 503–512

Garau, M., Slater, M., Pertaub, D.-P., Razzaque, S., 2005. The Responses of People to Virtual Humans in an Immersive Virtual Environment. Presence 14, 104–116.

Koelstra, S., Mühl, C., Soleymani, M., Lee, J. S., Yazdani, A., Ebrahimi, T., et al. (2012). Deap: a database for emotion analysis; using physiological signals. IEEE Trans. Affect. Comput. 3, 18–31

Mikellides, B., 1990 COLOR AND PHYSIOLOGICAL AROUSAL. Journal of Architectural and Planning Research. · Gerard RM (1958) Differential effects of colored lights on psychophysiological functions. Doctoral dissertation, University of California

O'Connor, Z (2011) Colour psychology and colour therapy: Caveat emptor. Color Research & Application

Turrell, James. 2017, accessed on 7 September 2017,

Wiederhold, B.K., Jang, D.P., Kim, S.I., Wiederhold, M.D., 2002. Physiological monitoring as an objective tool in virtual reality therapy. Cyberpsychology & behavior : the impact of the Internet, multimedia and virtual reality on behavior and society 5, 77–82.

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