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2020,  2 (5):   443 - 453

Published Date：2020-10-20 DOI: 10.1016/j.vrih.2020.09.001

Abstract

Background
Virtual Reality (VR) technologies have advanced fast and have been applied to a wide spectrum of sectors in the past few years. VR can provide an immersive experience to users by generating virtual images and displaying the virtual images to the user with a head-mounted display (HMD) which is a primary component of VR. Normally, an HMD contains a list of hardware components, e.g., housing pack, micro LCD display, microcontroller, optical lens, etc. Settings of VR HMD to accommodate the user’s inter-pupil distance (IPD) and the user’s eye focus power are important for the user’s experience with VR.
Methods
Although various methods have been developed towards IPD and focus adjustments for VR HMD, the increased cost and complexity impede the possibility for users who wish to assemble their own VR HMD for various purposes, e.g., DIY teaching, etc. In our paper, we present a novel design towards building a customizable and adjustable HMD for VR in a cost-effective manner. Modular design methodology is adopted, and the VR HMD can be easily printed with 3D printers. The design also features adjustable IPD and variable distance between the optical lens and the display. It can help to mitigate the vergence and accommodation conflict issue.
Results
A prototype of the customizable and adjustable VR HMD has been successfully built up with off-the-shelf components. A VR software program running on Raspberry Pi board has been developed and can be utilized to show the VR effects. A user study with 20 participants is conducted with positive feedback on our novel design.
Conclusions
Modular design can be successfully applied for building up VR HMD with 3D printing. It helps to promote the wide application of VR at affordable costs while featuring flexibility and adjustability.

Content

1 Introduction
More than fifty years have passed since Ivan Sutherland presented his early prototype of a tracked 3D head-mounted display (HMD) in 1968[1]. After that, a vast amount of technologies have emerged but it was not until 1989 when Jaron Lanier coined the term “Virtual Reality (VR)” which tried to aggregate the different concepts[2]. In VR, a virtual environment is created and VR also constitutes a human computer interface that allows users to interact with the virtual environment[3]. In 2012, a Kickstarter project named Oculus Rift, with the purpose of providing an affordable high-quality HMD to the public, achieved the goal of $250000 in less than 24 hours and was acquired by Facebook in 2014[4]. This was considered the initial spark that triggered the so-called second wave of VR inside after which a vast amount of products have been developed and applied into different domains. As of today, VR has been investigated significantly. Early works include the paper by Psotka in 1995 who discussed the benefits of VR and many of the cognitive factors that affect immersion in virtual environments[5]. In 1999, Mazuryk and Gervautz gave a detailed perspective on VR, defining its benefits and challenges, and outlined possible applications[6]. In 2016, Anthes et al. overviewed the state of VR technology by comparing various types of VR HMDs and their limitations[7]. With the fast development of VR technologies and the supporting software, VR has been applied in various domains, as for manufacturing processes[8], military training[9], training for children with special needs[10], architectural design[11], learning and social skills training[12], simulations of surgical procedures[13,14], gaming[15,16], biological imaging[17], etc. Freeman et al. published a review paper showing the efficacy of VR in assessing and treating different psychological disorders as anxiety, schizophrenia, depression, and eating disorders[18]. HMD is the primary component for VR systems. According to Mujber et al., many of the VR technologies have historically been prohibitively expensive, ranging from$800 for low quality devices to \$1 million for military HMDs[8]. It is only recently that the advancements in VR HMD technology make high quality and usable HMDs commercially and economically accessible by the general public, and therefore available for research, professional and large scale enterprise deployment[19]. Nowadays many manufacturers have been producing their own versions of VR HMDs for their consumers, such as the Oculus Rift by Facebook[20]. The Oculus Rift is a VR HMD designed for gaming, boasting a large library of games, good ergonomic design to keep the HMD secure and comfortable, and superb inside-out tracking that can accurately map and translate your movements into VR space. However, not everyone can afford the Oculus Rift as the Oculus Rift requires a decent PC to run with. Another option is the Oculus Quest, which costs the same price but unlike the Oculus Rift, users do not need a PC[21]. Additionally, due to its standalone nature, it requires minimal setup, and features the guardian system that remembers the boundaries of your play space to help you avoid bumping into objects while you play.
There are factors that will affect the user experience of VR for every individual, such as the IPD and the distance between the screen and the eyes for a VR HMD. Wearing an HMD with the wrong IPD may cause a distortion in the image formed, which in turn generates discomfort for the user during prolonged use. Moreover, most HMDs are designed for the average IPD, which means that users on either end of the spectrum will be unable to find an HMD that can fit them comfortably. Standard HMDs have a fixed distance between the display component and the optical lens and do not allow the user’s eyes to accommodate. This results in a sensory conflict known as the vergence-accommodation conflict (VAC)[22,23], which has been shown to contribute to distorted depth perception, visual fatigue and general discomfort, especially when using such displays over long periods[23-26].
To address the above-mentioned challenges, we present in this paper a novel design towards building a customizable and adjustable HMD for VR. Modular design methodology is adopted, and part of the VR HMD can be easily printed with 3D printers. The design also features adjustable IPD and variable optical focus settings thus it can help to mitigate the VAC issue. A prototype of the customizable and adjustable VR HMD has been successfully built up with off-the-shelf components. A VR software program running on Raspberry Pi board has been developed and can be utilized to show the VR effects. A preliminary user study has been conducted with a group of 20 users and the obtained study result positively supports the advantages of our design.
2 Methods
VR is defined as the computer-generated simulation of a three-dimensional image or environment that can be interacted with in a real or physical way by a person using special equipment, such as a helmet with a screen inside or external controllers[3]. HMD is an indispensable component for VR as it simulates binocular vision by presenting slightly different images to each eye, giving the illusion that a two-dimensional picture is a three-dimensional environment[27]. Although there have been vast advancements achieved for VR HMD in the past, all designs involve tradeoffs among a number of different metrics, including resolution, form factor, correct focus cures, field of view (FOV), etc. Therefore, the greatest challenge in VR HMD is not in optimizing any individual metric, but instead simultaneously providing a wide FOV, variable focus, high resolution, ease of manufacturing and a slim form factor.
Besides the abovementioned requirement metrics, there are also other factors that impact how each individual user experiences VR with HMD, such as the IPD and the distance between the display screen and the eyes. Normally the commercialized VR HMDs allow the user to manually adjust the parameters for IPD. There have also been a number of solutions developed to solve the VAC issue for VR display[28,29]. To mitigate the VAC issue, Padmanaban et al. proposed a method using tunable lens, gaze tracking and actuated motors to dynamically adjust the optical focus[30]. Some other methods choose to enhance the perception quality of VR HMD using computing method. For example, Konrad et al. proposed ocular parallax rendering, a technology that accurately renders small amounts of gaze-contingent parallax capable of improving depth perception and realism in VR[31]. However, these methods always introduce extra computation or mechanical hardware components which results in increased cost for affordable VR HMD.
The objective of our work is to develop a novel design towards customizable and adjustable VR HMD. The VR HMD should allow the user to easily adjust the gap between the optical lens to match their IPD. It should also allow the user to flexibly adjust the distance between the display screen and the user’s eyes such as to match the user’s eyesight status. We also expect the design to have fun feature such that it could motivate more non-professionals in VR to easily assemble their own VR headset at affordable cost. Therefore, we were inspired from the modular design mindset from other domains and applied it to the design for our target VR HMD. To verify our design, we use a 3D printer to print out each of the designed components and a prototype is successfully assembled at working state.
Before we introduce our novel design for VR HMD, we’d like to first discuss two main categories of modern VR HMD: Mobile VR HMD and Tethered VR HMD.
2.1　Two main categories of VR HMD
Mobile VR HMD does not require an exterior computer hardware and they are a casing with lenses into which a capable smartphone is placed. The software engine running on the smartphone render two images for the eyes thus turning the smartphone into a VR device. There are a few advantages with this category of VR HMD: (1) all the computing is done by the smart device and therefore, it allows more freedom to the users; (2) its price is relatively cheap as no costly hardware is used. However, this category of VR HMD also suffers a few disadvantages, including low quality resolution, inaccurate tracking, lack of interactions, etc. Figure 1 shows two examples for mobile HMDs. On the left side an original Google Cardboard is shown representing the simple cases and the right shows the GearVR representing the ergonomic cases.
Tethered VR HMD is a dedicated hardware for VR with better quality images and interactions and is either physically connected to a computer or has its own computing unit. They usually contain a dedicated display, optical lens, built-in motion sensors and an external camera tracker. They also contain accelerometers, magnetometers and gyrosc-opes and use sensor fusion to combine this inform-ation with the optical tracking. One disadvantage of tethered VR HMD when compared to mobile VR is the cable connections that can be unwieldy. Figure 2 shows the three big competitors in tethered VR HMD: the Oculus Rift, PlayStation VR, and the HTC Vive. All seem to have good chances on the market since the all provide their own online marketplace with an already established customer base.
2.2　System architecture
In view of the challenges with present VR HMD, we have come up with an idea for a customizable and adjustable VR HMD. The HMD can be built from modular parts, each of which is 3D printed by users. This do-it-yourself (DIY) theme creates a sense of satisfaction to the user, increasing the likelihood that they will cherish their HMD. Additionally, its modular and physical nature allows for more intuitive methods of adjusting the HMDs, all of which do not require extensive knowledge on programming or engineering. This low barrier for entry would allow almost anyone to easily learn about VR, including kids which may spark their interest and encourage them to learn more about VR technology from a younger age.
Figure 3 shows the diagram of the key components and their connections for our VEGO VR HMD design. Since VEGO is designed to be a standalone device, no external PC is required. In VEGO, a Portable Central Processing Unit, Raspberry Pi, handles 3D rendering. An MPU-9250 Inertia Measurement Unit (IMU)[32] chip is attached to the Raspberry Pi for tracking the 6 degree-of-freedom (DoF) movement of the HMD which can be utilized to control the rendering task at the Raspberry Pi. A pair of images for left and right eye respectively is sent to and displayed on an off-the-shelf LCD monitor. A centralized casing is 3D printed which is utilized to hold all the components together.
2.3　Modular design with support for adjustable IPD and optical settings
In order to allow the users to flexibly adjust the HMD, we decompose the centralized case of VEGO into separate and attachable components and each component can be 3D printed separately. Figure 4 shows the modular design for the centralized casing of VEGO. The “Raspberry Pi Holder” component is utilized to hold the Raspberry Pi board and the IMU sensor together with the connection cables. The “Screen Holder” component is used to hold the LCD display with holes punched in the four corners. The punched holes are utilized to connect to the “Screen Distance Adjuster” component which can be easily stacked to increase the distance between the optical lens and the LCD display. Two pieces of “Lens Support” components are used to hold the optical lens for each eye and the gap between the two “Adjustable Lens Holder” components could be changed by inserting or removing the “IPD Connector” in-between. Given the printing precision of the 3D printer used, each “IPD connector” is printed with 1mm thickness. A “Base of the HMD” acts as the base to hold the other components directly or indirectly.
An Ultimaker Cura 3 3D printer is deployed to print each of the designed component (Figure 5). It is worthy to point out that some of the default profiles in the software may be modified , leading to some printing failures due to the layer height difference. This could cause the failure of affected modules which need to be reprinted.
2.4　Software component
As Raspberry Pi board deployed in our design runs on Linux OS, we chose Pi3D[33] as the game engine for the rendering simple 3D environments. Pi3D is a Python module that allows us to write 3D in Python whilst using the Raspberry Pi graphics processing unit[34]. We incorporate the MPU-9250 (IMU) drivers[32] with a program written in Python to enable position tracking. With the aid of the IMU, we can rotate our view and move around the earth using the gyroscope and the accelerometer respectively. Figure 6 shows the image for the earth demo example in Pi3D[34] rendered by Raspberry Pi board and displayed on the LCD.
2.5　Prototype
The diagram for each frame component was done using Google SketchUp[35], and then later exported as a STL file and printed with the 3D printer. The LCD has a resolution of 1080×1920 with the model of Topfoison 5.5 inch. Figure 7 shows the printed components with the 3D printer and Figure 8 shows the integrated VEGO VR HMD. It can be easily seen that VEGO has an easy-to-fit design which allows the user to flexibly fit the parts together.
3 Results
To evaluate the effectiveness of our prototyped VR design, a user study is conducted for a group of 20 participants aged between 18 to 24 years old. Before the participants started trying VEGO, a simple survey is made to learn more about their familiarity with VR, e.g., the models of VR products in the market they know or tried with, the issues with the existing VR HMD, etc. This helps to establish the baseline opinion before they test with VEGO.
After that, each participant is tasked to interact with VEGO (Figure 9). For safety purpose, each participant is asked to conduct the testing within a pre-defined area. During the interaction, each participant is allocated a fixed amount of nine-minute time, including three minutes for trying out the VR program to get a feel of the HMD, three minutes to try to make adjustments to the HMD using the IPD and FOV adjustment module and another three minutes to try out the VR program again after adjustments were made. This is to allow them to have a feel of how IPD and FOV will affect their VR experience, be it negatively or positively.
Upon the completing of interacting with VEGO, each participant is asked three questions with regards to their experience. The first question is about the participant’s general opinion on a customizable and flexible HMD before and after they tried with VEGO. The Mann-Whitney U Test is used to look for differences in Likert scale responses between the pre and post-study surveys[36]. Participants rated their general opinion on a customizable and adjustable head-mounted display before experiencing VEGO on a 5 point Likert scale, 1 being Very Negative and 5 Being Very Positive and the survey results appeared to have a neutral outlook giving a median of 3 and a mean of 3.44. Then the participants rate their general opinion on our customizable and adjustable head-mounted display after their experiencing VEGO on a 5 point Likert scale too, with 1 being Very Negative and 5 Being Very Positive and the survey appears to have a positive outlook giving a median of 4.5 and a mean of 4.22. A full breakdown of both responses between both conditions can be seen in Figure 10.
The second question is about if the participants feel the proposed design is effective for IPD and focus adjustments. Overall, the participants feel that the mechanisms used by us were effective. Out of the total 20 participants, 16 gave ‘yes’ and 4 participants gave ‘no’ for the IPD adjustment; and 13 gave ‘yes’ and 7 gave ‘no’ for the focus adjustment. A full breakdown of the response can be seen from Figure 11.
The last user study question is about the effectiveness of our design for instilling interests for users to assemble their own VR HMD. Majority of the participants feel that a modular designed helped to instill interest in virtual reality for them, with 12 participants giving ‘yes’ and 8 participants giving ‘no’. Overall, the participants felt interested in VR after having experience with our modular head-mounted display. A full breakdown of the response can be seen from Figure 12.
4 Discussion and future work
Most of market available VR HMDs are designed for users with average IPD. As such, many users whose IPD are outside of the designed range suffer from fatigue easily and hinders their experience with VR. Moreover, VR HMDs in the market are expensive and it impedes people, like students, to try to build up their own VR HMD. To mitigate such factors, we introduced our novel design towards flexible and customizable VR HMD. Our design utilizes the modular design to allow users to adjust IPD and optical settings for different users. A prototype is built following our design with 3D printer. An evaluation user study with the prototype is conducted with 20 participants. The evaluation results show that the modular design can help to develop interest of the participants in VR. The features for IPD adjustment and focus setting adjustment receive positive feedback from the participants.
For future work, the research group would like to delve into eye tracking in VR to leverage the benefits of both technologies. Eye tracking in VR allows us to have enhanced interactions where the user can interact with an object in VR simply by looking at the object as a form of target selection, combined with hand or speech enabled controls. Foveated rendering is also a perk of eye tracking as it renders the graphics of the user is looking in high quality while rendering things in the peripheral. This creates a focused feel and makes it more immersive as though the user is really in the virtual environment. Foveated rendering also aids the processor and puts less workload on the processor, allowing constant frames per second (FPS) to ensure smoothness of the experience.
Additionally, the current setup does not allow for an external gamepad or controller, which severely limits user input. Hence, a gamepad or controller could be implemented with the current program to allow for user interaction with the virtual environment. As VEGO is designed to be portable, a gamepad or controller will aid the user in giving user inputs without the aid of a physical keyboard. These controllers could be used with eye tracking to enable a smooth experience for the user, such as target selection using the eye tracker and confirmation using the controller.
Moreover, the research group has plans to create an application that will facilitate the VR application deployment through a cloud-based system. This will allow us to create a network where all VEGOs are connected to the cloud-based system and deployment of the program could be run over the net. This will allow many developments for educational programs to occur and can be used in schools to give students an experience of VR without the hassle of writing their own program.

Reference

1.

Sutherland I E. A head-mounted three dimensional display. In: Fall Joint Computer Conference (Fall, part I). San Francisco, California, New York, ACM Press, 1968, 757–764 DOI:10.1145/1476589.1476686

2.

Rheingold H. Virtual Reality. Summit Books, 1991 DOI:10.1080/00140139308967935

3.

McMillan K, Flood K, Glaeser R. Virtual reality, augmented reality, mixed reality, and the marine conservation movement. Aquatic Conservation: Marine and Freshwater Ecosystems, 2017, 27(S1): 162–168 DOI:10.1002/aqc.2820

4.

5.

Psotka J. Immersive training systems: Virtual reality and education and training. Instructional Science, 1995, 23(5): 405–431 DOI:10.1007/bf00896880

6.

Mazuryk T, Gervautz M. Virtual reality―history, applications, technology and future. 1999

7.

Anthes C, García-Hernández R J, Wiedemann M, Kranzlmüller D. State of the art of virtual reality technology. In: 2016 IEEE Aerospace Conference. Big Sky, MT, USA, IEEE, 2016, 1–19 DOI:10.1109/aero.2016.7500674

8.

Mujber T S, Szecsi T, Hashmi M S J. Virtual reality applications in manufacturing process simulation. Journal of Materials Processing Technology, 2004, 155/156: 1834–1838 DOI:10.1016/j.jmatprotec.2004.04.401

9.

Alexander T, Westhoven M, Conradi J. Virtual environments for competency-oriented education and training. In: Advances in Human Factors, Business Management, Training and Education. Cham: Springer International Publishing, 2016: 23–29 DOI:10.1007/978-3-319-42070-7_3

10.

Cai Y Y, Chia N K H, Thalmann D, Kee N K N, Zheng J M, Thalmann N M. Design and development of a virtual dolphinarium for children with autism. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2013, 21(2): 208–217 DOI:10.1109/tnsre.2013.2240700

11.

Song H, Chen F Y, Peng Q J, Zhang J, Gu P H. Improvement of user experience using virtual reality in open-architecture product design. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2018, 232(13): 2264–2275 DOI:10.1177/0954405417711736

12.

Schmidt M, Beck D, Glaser N, Schmidt C. A prototype immersive, multi-user 3D virtual learning environment for individuals with autism to learn social and life skills: A virtuoso DBR update. In: Communications in Computer and Information Science. Cham: Springer International Publishing, 2017, 185–188 DOI:10.1007/978-3-319-60633-0_15

13.

Gallagher A G, Ritter E M, Champion H, Higgins G, Fried M P, Moses G. Virtual reality simulation for the operating room: proficiency-based training as a paradigm shift in surgical skills training. Annals of Surgery, 2005, 241: 364 DOI:10.1002/bjs.1800840237

14.

Ba R K T A, Cai Y Y, Guan Y Q. Augmented reality simulation of cardiac circulation using APPLearn (heart). In: 2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR). Taichung, Taiwan, China, IEEE, 2018, 241–243 DOI:10.1109/aivr.2018.00055

15.

Zyda M. From visual simulation to virtual reality to games. Computer, 2005, 38(9): 25–32 DOI:10.1109/mc.2005.297

16.

Meldrum D, Glennon A, Herdman S, Murray D, Mcconn-Walsh R. Virtual reality rehabilitation of balance: assessment of the usability of the Nintendo Wii®Fit Plus. Disability and Rehabilitation: Assistive Technology, 2012, 7(3): 205–210 DOI:10.3109/17483107.2011.616922

17.

Indhumathi C, Cai Y Y, Guan Y Q, Opas M. 3D boundary extraction of confocal cellular images using higher order statistics. Journal of Microscopy, 2009, 235(2): 209–220 DOI:10.1111/j.1365-2818.2009.03203.x

18.

Freeman D, Reeve S, Robinson A, Ehlers A, Clark D, Spanlang B, Slater M. Virtual reality in the assessment, understanding, and treatment of mental health disorders. Psychological Medicine, 2017, 47(14): 2393–2400 DOI:10.1017/s003329171700040x

19.

Slater M, Sanchez-Vives M V. Enhancing our lives with immersive virtual reality. Frontiers in Robotics and AI, 2016, 3: 74 DOI:10.3389/frobt.2016.00074

20.

Available from:https://www.oculus.com/rift-s/features/

21.

Available from:https://www.oculus.com/quest/features/

22.

Lambooij M, IJsselsteijn W, Fortuin M, Heynderickx I. Visual discomfort and visual fatigue of stereoscopic displays: a review. Journal of Imaging Science and Technology, 2009, 53(3): 030201 DOI:10.2352/j.imagingsci.technol.2009.53.3.030201

23.

Hoffman D M, Girshick A R, Akeley K, Banks M S. Vergence-accommodation conflicts hinder visual performance and cause visual fatigue. Journal of Vision, 2008, 8(3): 1–30 DOI:10.1167/8.3.33

24.

Vienne C, Sorin L, Blondé L, Huynh-Thu Q, Mamassian P. Effect of the accommodation-vergence conflict on vergence eye movements. Vision Research, 2014, 100: 124–133 DOI:10.1016/j.visres.2014.04.017

25.

Kooi F L, Toet A. Visual comfort of binocular and 3D displays. Displays, 2004, 25(2/3): 99–108 DOI:10.1016/j.displa.2004.07.004

26.

Shibata T, Kim J, Hoffman D M, Banks M S. The zone of comfort: Predicting visual discomfort with stereo displays. Journal of Vision, 2011, 11(8): 11 DOI:10.1167/11.8.11

27.

Fuchs H, Bishop G. Research directions in virtual environments. Chapel Hill, NC, University of North Carolina at Chapel Hill. 1992

28.

Konrad R, Padmanaban N, Molner K, Cooper E A Wetzstein G. Accommodation-invariant computational near-eye displays. ACM Transactions on Graphics, 2017, 36, 4 DOI:10.1145/3072959.3073594

29.

Laffont P Y, Hasnain A. Adaptive dynamic refocusing: towards solving discomfort in virtual reality. In: ACM Siggraph 2017 Emerging Technologies. ACM, 2017, 1, 1–2 DOI:10.1145/3084822.3084839

30.

Padmanaban N, Konrad R, Stramer T, Cooper E A, Wetzstein G. Optimizing virtual reality for all users through gaze-contingent and adaptive focus displays. PNAS, 2017, 114(9): 2183–2188 DOI:10.1007/978-3-642-04898-2_615

31.

Konrad R, Angelopoulos A, Wetzstein G. Gaze-contingent ocular parallax rendering for virtual reality. In: ACM SIGGRAPH 2019 Talks. Los Angeles California, New York, NY, USA, ACM, 2019 DOI:10.1145/3306307.3328201

32.

Available from:https://github.com/FaBoPlatform/FaBo9AXIS-MPU9250-Python

33.