Assessment of Back Pointers as An Alternative for Direct Input in The Mobile Screens

Abstract

Mobile phones are of high utility in today’s era being a handy electronic device that provide is instant solutions to almost all the needs. However, with the advancement of the technology, there has been a significant rise in the need of mobile phones with larger screens. Users often prefer to have large display screens that can provide an elaborate experience in visualization. Unfortunately, with larger screen it becomes impossible to navigate through the screen to different options successfully and without much hassle. It is cumbersome and highly consuming to navigate through these big panes and these results in hindrances in the overall experience.

Use of fingers to navigate is not only difficult but also presents itself as a problem in the visibility of the screen harming the user experience. Alternative shave been explored to find better input methods that can help to enhance the user experience by totally abolishing the human touch on the capacitive touch screens of these mobile devices. In this paper we have performed a simple experiment to understand the applicability of one such alternative, that is, back pointer. The back pointer in individuals by asking them to perform a simple task that has been derived based on the outlines of the FItts Law.

Keywords: Fitts Law, mobile phones, direct input.

Introduction

Fitts Law was first defined by Paul Fitts as an empirical model that helped in formulation of the basic foundation of computer and human interaction. It calculates the speed and accuracy of the human muscle movement. While using the electronic devices like computers, mobile phones,, tablets the body responds to the stimuli in a highly specific manner. Having analyzed the accuracy of the human interaction with the system, one can create targeted graphical user interfaces that can aid in yielding the desired target. Mobile phones are the handy electronic devices that are used by the individuals all over.

A mobile involves a highly engaged user interaction and thus forms a suitable tool to study the Fitts law. Fitts law descriptively helps in articulated assessment and the relationship between the tool and human response aiding in the development of a comprehensive system that can be more user centric and also aids in targeted marketing. The Fitts law has also worked for the description of the effect of pointers and established significant parameters as:

  • Time taken to move to the target

  • Width of the target

  • Movement distance from the target position to the target center.

In this study we will analyze a mobile phone based interaction. In this study we will try and elucidate the impact of phone structure and the use of back pointers in users who often use the phone in landscape mode for gaming.

Literature Review

Almost all mobile phone interactions are performed using the touch screen. This is termed as the direct input method (Lazar et al., 2017). However, it has been studied by LaVioa, 2017 that in many cases the capacitive touch screen are not currently pressure sensitive and this may cause hindrances in the user interaction. Further, in the capacitive touch screens the human touch is recognized by the device by utilizing the human body as an electric conductor (Conor, 2018). However one hand this aids in the performance of the device and provides ease to the user, in case of presence of an insulator like a hand glove, these interactions are hindered. The current device interfaces often result in visual occlusion as the hand use on devices hides the overall visual user interface.

It has been elucidated by Lazar et al., 2017 that by removing the need to extensively interacting directly with the screen users may be able to reduce the amount of time and energy needed to interact with the device. The back pointers present in the devices allows for clicking on the targets with relatively more ease. The issue of screen occlusion and extending the input space of mobile devices has been researched through several different studies. Methods such as “Tap Tap” (Patel et al., 2016) are often used these devices. These methods demand that the user has to press on the screen to select a target. It is a stated fact that a typical interaction between the user and current devices hides the screen preventing user to directly associate with the target.

To overcome this screen occlusion issue various attempts have been made to create the interfaces in the mobile devices that do not involve a hindering direct contact with the screen (Sadana et al., 2016). One such method is to use the LucidTouch (Sun et al., 2017). Lucid Touch enables its users to use four fingers and interact with the device through a touch pad that is enabled at the back of the screen display. Applying Lucid Touch to the device requires an additional screen as well as an extra camera protruding at the back of the display (Lv et al., 2015). The interactivity in these devices is maintained through the direct association of the user with the touchpad. The location that is touched is directly in synchrony with the target on screen.

Technologies like Lucid Touch and Nanotouch allow for a more satisfying device use experience. Use of back pointers thus serves a promising alternative as an input method for the devices that will allow for data input without risking the screen occlusion. Another method that has been used to minimize the direct screen usage includes the use of camera gestures and screen sensitivity enhancement. These have been widely used in most of the recently launched devices. Through these, the user can input data directly into the device without requiring the touch on the screen. Some applications and interfaces also use” shake your phone” approach where the user simply shakes the phone and the data is registered based on this input.

Traditional devices involve the use of human hands for input of the information. This type of interaction is popular these days but is not high favorable. Gestures ease out the utility of these devices but their application is still limited. For users who use big screen phones and tablets, navigating through the fingers is a huge hurdle where the users are often compelled to use both their hands. This is a big hindrance when the user is using software that is highly elaborate. Also, Manotas et al., 2016 have reported that users prefer smaller navigating distances in between the softwares underuse for their higher utility. Having alternatives like back pointers seems to solve this problem. a user will be able to simply navigate through the screen of the device without interacting with the screen directly masking its primary data. Back pointer devices have been proposed by Morelli and Ripke in their paper published in 2015 and its efficiency has been studies in this paper.

Research Methodology

In this study we conducted primary research where 20 individuals aged between 17 and 23 years were taken. These people recognized themselves as effective gamers who used their mobile devices often solely for the purpose of gaming. The interface ISO 9241-9 (Zhang & MacKenzie, 2007) was chosen in this study to test the Fitts law on the input devices. ISO 9241-9 describes a method for a two dimensional task for the user input methods and the devices.

The Experiment:

To apply the Fitts law and to assess the efficiency of the back pointers in the study target selection task was designed, as illustrated in figure 1. The study population was divided in two groups of ten individuals each. Group A was provided back pointers in the devices and the group B was handed regular smartphones with the capacitive touch.

Task to be performed: The individuals in the study will be trying to rotate the red ball in the given perimeter of the square. The time taken for each circulation will be measured at all the three levels designated with different size of circles .As the squares are shown on the screen, the participants will have to use the tip of their left index finger to move the corresponding red circle on the screen. To complete this task following steps have been taken, as follows:

  1. Task designing

  2. Selection of participants

  3. Setting up of controls

  4. Successful completion of task.

  5. Time assessment

  6. Calculations

  7. Derivation of results

image shows Target selection task: Three different targets have been constructed for analysis of the Fitts law

Figure 1: Target selection task: Three different targets have been constructed for analysis of the Fitts law

The time difference will be calculated in the members of group A and B and to deduce the efficacy of the back pointers in relation with the Fitts law. A standard of both the groups was set by performing the task for fifteen times each and then establishing a standard for same. The time after each completion was automatically measured in the task window design and mean of three reading was calculated and taken for calculations. When targets were selected, the time required to select the target was recorded along with the recognized marker size. The marker size could be used in post analysis to approximate the distance the finger was from the back of the screen at the time of the selection.

Results:

It is evident through the results that the time taken to complete the task was less in individuals that were using the back pointer assisted devices than the individuals who used the capacitive touch display. The time taken to complete the task by the participants of the group A and group B are shown in Table 1 and Table 2 respectively.

The data was collected using primary research methodology that was used for the assessment of the results. The mean values have been taken and displayed in this table with three distinct observations for each value.

GROUP-A

Individual

Time taken( Seconds)

Set A

Set B

Set C

A1

5.7

5.5

4.5

A2

5.8

5.7

5

A3

5.9

5.5

5

A4

6.2

5.8

5

A5

4.9

4.5

5.1

A6

6.8

6.6

5.9

A7

7

6.2

5.5

A8

5

4.5

4

A9

5.2

4.9

4

A10

6.1

5.5

5

Table 1: Time measurements for task completion in group A

GROUP-B

Individual

Time taken (Seconds)

Set A

Set B

Set C

B1

5.2

4.8

4.2

B2

5

4.5

4.3

B3

4.5

4.6

4.1

B4

5.1

4.5

4

B5

4.5

4.5

4.1

B6

4.8

4.2

4.2

B7

4.7

4.1

4.2

B8

4.5

4

4

B9

4.5

4.5

4

B10

5

4.6

4.1

Table 2: Time measurements for task completion in in group B

The results obtained by this experiment were further analyzed to see how the target size also affected the user interaction. For individuals in group a, a significant difference in time in task completion is observed. An analysis of variance (ANOVA) showed significant difference between seek times for each target in the test based on its perimeter (F (10, 77) =3.69 p <0.01)). A post hoc turkey test was also conducted. The test showed that the first target was the only one with a significant difference (p <0.01) when compared to other values. On average, participants that used the back pointer required an average time of 4.78 seconds for the task completion with the smallest circle against the 5.86 seconds required by the individuals without the pointer.

Similarly, average time for the intermediately sized circle in the participants with a back pointer was recorded as 4.43 seconds and in the participants without the pointer it was calculated to be 5.47 seconds. For the largest circle to be moved across the perimeter the average time taken by Group A participants was 4.9 seconds and in the individuals of Group B was 4.12 seconds. It can be elucidated from this data that participants of group B who had the access to back pointer in their devices were able to perform the task in much lesser time than the participants of group B who used the capacitive touch screen devices for the completion of task.

Discussion

Considering the possible use of this type of interface in a gaming environment, the results will be relevant in the study of throughput for different types of game interfaces. It has been discretely elucidated that back pointers increase the efficiency of the user and also reduces the time of action using the mobile device. This experiment provides a foundation for a further scope and development of an input method in the electronic devices. In this study, mobile devices were used that were enabled with back pointers and used in the study in contrast to the traditionally available mobile devices that hold a capacitive touch screen. It was elucidated through this research that the back pointer serves as an alternative for the input methods.

In the previous studies it has been understood that the classical input methods that involve the use of touch screen lead to a visual occlusion. The fingers used to transcribe message also hide the screen and thus minor details can be missed. When we use a back pointer, the entire display is available in the sight. This provides a greater experience to the user in terms of the feasibility and also enhances the screen visibility. Through this experiment we have presented the back pointer as an available alternative to the input method in the electronic devices like mobile phones. Having a more enhanced and highly elaborated structure for data input in the mobile devices, there will be a more enhanced input system, better apps and softwares can be developed in future.

A better graphical user interface will be enables by adoption of this technology in the mainstream. It will also allow for ease and enhancement of the overall device usage and accessibility and also provide more room for larger displays and that give a better viewing experience. Visualization of the devices will be enhanced and the gaming experience will also see improvements. People will be able to use these devices even while multi tasking and thus providing a better overall utility to these electronic devices. Further research can be done to enhance the sensitivity and efficacy of the back pointers. 

Conclusion

The participants of both the groups A and B completed the task with their respective tasks where they were supposed to move the red circle using an input method to cover the perimeter of the square give. The participants in the group A used the classical method of input by using the capacitive touch screens. The participants of Group B also performed the task, but instead of using the traditional input methods of the smart phone via touch screen, they used the back pointer access that was provided additionally to their devices. Post the experimental analysis it has been concluded that the participants who used the back pointer input devices performed better and completed the task faster compared to the individuals who were using the capacitive touch screen. Data also reveals that the task was completed fastest in the largest circle irrespective of the mode of task completion. This verifies the Fitts law to explain that the time required to rapidly move to a target area is a function of the ratio between the distance to the target and the width of the target.

References

Connor, R. A. (2018). U.S. Patent Application No. 15/960,477.

LaViola Jr, J. J., Kruijff, E., McMahan, R. P., Bowman, D., & Poupyrev, I. P. (2017). 3D user interfaces: theory and practice. Addison-Wesley Professional.

Lazar, J., Feng, J. H., & Hochheiser, H. (2017). Research methods in human-computer interaction. Morgan Kaufmann.

Lv, Z., Feng, S., Feng, L., & Li, H. (2015, March). Extending touch-less interaction on vision based wearable device. In 2015 IEEE Virtual Reality (VR). IEEE.

Manotas, I., Bird, C., Zhang, R., Shepherd, D., Jaspan, C., Sadowski, C., ... & Clause, J. (2016, May). An empirical study of practitioners' perspectives on green software engineering. In 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE). IEEE.

Morelli, T., & Ripke, T. (2015, October). Back-Pointer—Fitts' law analysis of natural mobile camera based interactions. In 2015 IEEE Games Entertainment Media Conference (GEM). IEEE.

Patel, V. M., Chellappa, R., Chandra, D., & Barbello, B. (2016). Continuous user authentication on mobile devices: Recent progress and remaining challenges. IEEE Signal Processing Magazine33(4), 49-61.

Sadana, R., & Stasko, J. (2016, June). Designing multiple coordinated visualizations for tablets. In Computer Graphics Forum ,35,3, 261-270.

Sun, K., Wang, Y., Yu, C., Yan, Y., Wen, H., & Shi, Y. (2017, May). Float: One-Handed and Touch-Free Target Selection on Smartwatches. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM.

Zhang, X., & MacKenzie, I. S. (2007, July). Evaluating eye tracking with ISO 9241-part 9. In International Conference on Human-Computer Interaction. Springer, Berlin, Heidelberg.

Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Management Assignment Help

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