Paper Reading #15: Madgets

Madgets: Actuating Widgets on Interactive Tabletops


Authors - Malte Weiss, Florian Schwarz, Simon Jakubowski, and Jan Borchers


Authors Bios - Malte Weiss is a PhD student and research assistant at the Media Computing Group of RWTH Aachen University specializing in interactive surfaces.
Florian Schwarz is a Diploma Thesis Student at RWTH Aachen University and is interested in translucent controls on interactive tabletops.
Simon Jakubowski is a student assistant at RWTH Aachen University and is supervised by Malte Weiss.

Jan Borchers is a professor at RWTH Aachen University and leads the Media Computing Group in researching human computer interaction.


Venue - This paper was presented at the UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.


Summary


Hypothesis - In this paper, researchers introduce magnetic widgets, or Madgets, which let interactive tabletops give and receive information from widgets placed on their surface. Madgets are easy to build, flexible, inexpensive, and do not require any builtin electronics or power source. The hypothesis is that Madgets enables new interaction with complex actuated tabletop tangibles and will prove valuable as research in this field continues.


Methods - The researchers implemented Madgets using custom hardware, actuation algorithms, tracking algorithms, and ideas concerning what needed to be supported by the project.

Results - The surface used for Madgets was built by the researchers using a TFT panel from a Samsung TV, a sheet of EL foil, 228 electromagnets, fiber optic cables, LEDs, and 3 cameras. The surface utilized Diffused Surface Illumination (DSI) for touch recognition. The widgets are built using clear acrylic parts and magnets to both hold it in place and perform tasks. The actuation algorithms control the magnets when they are moving widgets, tangential actuation, or performing tasks with widgets, normal actuation and they also keep the magnets relatively cool by cycling magnets for other magnets. The tracking algorithms calculate input on the surface by using gradient markers on the IR results returned to the cameras. Widget and finger inputs are detected in this manner and pattern matching is used in determining which widget is present before mapping the location to internal coordinates. 


Content - Madgets allow for persistence (GUI interaction), remote calibration (group control), and ad-hoc use (moving a Madget closer to a user by touch). Height is an important aspect to Madgets and allows for buttons to move up and down. Resistance and vibrations are 2 possible types of feedback that Madgets can deliver to users indicating a completed action or an exceeded limit.


Conclusion - The researchers conclude by saying Madgets provides low-cost widgets and new actuation dimensions allowing for more research to continue in prototyping more widgets easily and working on better aestethics for the system as a whole as well as finding more appropriate feedback that coincides with the goals of Madgets.


Discussions


I think the researchers achieved their goal of expanding actuation interaction but I remain unconvinced of the need for such a device. They gave good examples for widgets but they did not expand upon what they could be used for or how they could possibly work together as I imagine they would in a real-world setting. Future work will be needed in figuring out applications for this system. I think the way in which the hardware was built was interesting using many different components in innovative ways and combining that with new algorithms to track and interpret data given the unusual hardware.

Paper Reading #14: TeslaTouch

TeslaTouch: Electrovibration for Touch Surfaces


Authors - Olivier Bau, Ivan Poupyrev, Ali Israr, and Chris Harrison


Authors Bios - Olivier Bau is a researcher at Disney Research and received his PhD from INRIA Saclay.
Ivan Poupyrev has a PhD from Hiroshima University and currently works in interactive technologies at Disney Research.
Ali Israr has a PhD in mechanical engineering from Purdue University and specializes in haptics.
Chris Harrison is PhD student at Carnegie Mellon University and is a Microsoft Research PhD Fellow.


Venue - This paper was presented at the UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.


Summary


Hypothesis - In this paper, the researchers note that current touch surfaces do not give users any kind of haptic feedback resulting in drops in efficiency when used. The researchers propose using electrovibration in conjunction with touch surfaces to create a new kind of interface capable of many different haptic interactions with users. The hypothesis is that this new interface, TeslaTouch, will lead to new feedback possibilities resulting in more efficient interactions with users and be easily added to existing hardware.


Content - TeslaTouch was implemented using diffusing illumination for touch recognition on a 3M Microtouch panel originally designed for capacitive touch. Current is applied to the panel by a standard sound card controlled by the Pure Data sound programming environment. Due to the interaction users will have with different voltages, the researchers note many of the safety procedures followed in designing the device such as the fact that electrovibration does not actually pass current through a user's body and a user is exposed to the same current given off by conventional capacitive touch surfaces.The researchers explain that their implementation approach is scalable and can be applied to almost any surface as electrodes can be clear and applied easily everywhere. When compared to mechanical means of feedback electrovibration has some noticeable advantages. Some advantages electrovibration has include being more salable for large interfaces, producing no noise when active, and being more reliable than physical parts. Simulations, like writing or painting, and rubbing interactions, for picture editing, are just some of the many applications electrovibration.


Methods - Studies were conducted to observe what users perceive when touching the TeslaTouch surface to validate its use as an effective form of feedback:
1) 10 participants were asked to touch the TeslaTouch in 4 different configurations and give their feedback reagarding their experiences. This study will help the researchers decide what settings to adjust to achieve certain textures.
2) The absolute detection thresholds were determined by 10 participants touching a screen split into 2 sections and determining which had a tactile stimulus. The stimulus would be randomly chosen from 5 frequencies and the participants' choices decided how much the intensity, dB, would change. If a user chose right the intensity decreased and vica versa if a user chose wrong but after so many trials the scale of the change decreased so as to narrow down the threshold.
3) The frequency and amplitude discrimination thresholds were calculated by 7 participants choosing the unique surface from a set of 3 that had a test stimuli and 2 identical reference stimuli with intensity of 15 dB higher than the absolute detection threshold.


Results - The results of the methods mentioned above will help with determining what bounds to use and what factors affect the feeling:
1) The low frequency settings were viewed as being rougher than the high frequency settings. Amplitude changes in the high frequency settings changed how smooth or "waxy" the surface the felt while amplitude changes in the low frequency settings affected the perceived stickiness the surface possessed. 
2) The absolute detection thresholds were found to be severely affected by the frequency levels although a reliable figure was found to use in the following tests.
3) While the discrimination threshold was kept constant, frequency was found to severely affect user perception with the lower frequencies resulting in far more JNDs than the higher frequencies. Amplitude was found to be independent of frequency resulting in clear results.


Conclusion - The researchers conclude by stating that they have shown that electrovibration is a viable option for touch feedback in the future and that the abstract nature of the technology will allow for many applications to be uniquely implemented with it.


Discussion


I think the researchers successfully proved their hypothesis that electrovibration is a viable form of feedback for touch interfaces. The most interesting part of this research to me is the abstract nature of the tool which, unlike physical vibration which can only be vibrated at different intensities, has the potential to be used in many different ways such as simulating stick surfaces as opposed to bumpy surfaces or waxy surfaces. I think this technology has a future in the mobile tablet industry if more research is put into it and people start using it as the appeal for a device that supports this would be very high among the public in my opinion.

Book Reading: Gang Leader for a Day

     Gang Leader for a Day answered some questions I had concerning the topic and raised many more. Among those answered was how people get trapped in the projects of major cities and, even more important, how they manage to survive there. Some questions this book has me asking now are how objective can an observer remain when participation becomes necessary to continue observing and what is the state of poor neighborhoods in 21st century America.
     My first thoughts on this book concern the subject being studied, low-income housing. Sudhir explores this world by diving into it head first when he meets JT in one of the buildings within his territory. Throughout the book I gradually became more aware of the environment Sudhir was studying mainly because Sudhir decided to go further than JT in his studying and branched off into the community on his own. In a way I was learning about the projects at the same time Sudhir was in the book which is an interesting way to present information given that most instructional books are told by someone that clearly already understands everything being said making it harder to pick up from a beginner's perspective. Mrs. Bailey helped in learning about this setting the most as she was the director of the community. What I quickly picked up on was that the whole system is unregulated in the projects and selfishness is allowed to run freely leading to some of the most corrupt individuals being put in power. The most interesting elements I got from Mrs. Bailey were actually from everyone else's view of her. Anytime Sudhir talked to anybody that he wasn't studying, he learned something new about the people he was studying like Mrs. Bailey's "death grip" on the residents of Robert Taylor. If someone made any money they surely owed some of it to Mrs. Bailey and JT was more than happy to loan foot soldiers to here cause at any time because she helped him in return, and so the vicious cycle continues. JT and Mrs. Bailey loved to talk about how the police and government were ruining people's lives but they were actually doing just as bad. I would've liked to have seen Sudhir study some of the residents in more detail than he does but I have a feeling that the reason this didn't happen is because JT and Mrs. Bailey didn't want that at all.
     The horror stories presented in this book regarding some of the people's lives were truly terrifying but the hopeful stories were just as potent in the opposite way. For all of the rapes and shootings mentioned in this book, their was an equal amount of success stories such as Autry running the boys and girls club at one of the other Robert Taylor homes. It was especially interesting to see how the women worked together to get things done such as pitching in to have a certain number of working showers and kitchens between many families.
     Some of the book's most interesting moments were the ones in which Sudhir took an active role in the gang or community such as being gang leader for a day. The physically involving actions, like the stairwell with Bee-Bee or helping Price when he got shot, were the ones which I think confused everybody the most because after them people treated him differently. The more social actions, like teaching the women how to write or Sudhir's "school"-turned-babysitting job, offered a diverse look at the residents of the communities affected by JT and Mrs. Bailey. As an ethnographer, Sudhir may have been overstepping his bounds here but each action got him deeper into the community and gang so I'm not sure this question can ever really be answered. When it works out, like this, and an ethnographer accomplishes his goals through participation people will think positively of it but, when an ethnographer gets hurt or worse from involvement people will turn against it. In either sense the outcome can never be predicted and the risk will always be high.
     The last question I have is one that I do not have an answer to yet but I am more motivated than ever to really look for some answers. The state of the poor in America in this century is not really known by me or most of the people that I affiliate with which tells me that the social divide in this country is not in a good place. I'm not sure if we're any better off than we were than at the time of this book but I am interested in looking nonetheless.
     Overall, I think this book provided me with a great look into a part of this country that I have no experience with and also showed what ethnography can do to expose information in the best way. While methods can be controversial much can be learned through risky behavior and we can all learn something from each other.

Paper Reading #13: Combining multiple depth cameras and projectors

Combining Multiple Depth Cameras and Projectors for Interactions On, Above, and Between Surfaces


Authors - Andrew D. Wilson and Hrvoje Benko 


Authors Bios - Andrew D. Wilson is a researcher at Microsoft Research and has a PhD from MIT Media Laboratory.
Hrvoje Benko is a researcher at Microsoft Research and has a PhD from Columbia University.


Venue - This paper was presented at the UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.


Summary


Hypothesis - In this paper, the researchers will develop a system capable of making non-instrumented surfaces interactive using a series of projectors and cameras. The hypothesis is that this system, called LightSpace, will explore more capabilities of depth cameras and help lead us to a future in which even the smallest corner of a room will be interactive.


Content - 4 interactions that will be implemented in this system include simulated interactive surfaces (support hand gestures and touch input), through-body transitions between surfaces (ability to touch 2 surfaces to transfer objects), picking up objects (ability to carry an object in a user's hand), and spatial menus (use human as interactive surface). 


Methods - The researchers built their system using 3 InFocus projectors and 3 PrimeSense depth cameras mounted on a single aluminum truss and aimed so as to maximize effectiveness. The depth cameras use 2 types of cameras and a light source to accurately form a 3D model of what is being viewed. All cameras contribute to a single system-stored 3D representation of the test area to eliminating the need to know which camera is located where. The cameras are calibrated individually using 3 points of reference and them the projectors are inserted into the 3D grid created by the camera calibration. The interactive surfaces must be designated by identifying 3 corners of the surface in question and the surface must be rectangular, flat, and immobile. A virtual camera's view is created by using the data collected by all 3 cameras in order to form an overall view of the interactive area to better analyze what is being performed. Connectivity of two objects by a person is detected by checking for intersecting images with the interactive surfaces. Picking up and dropping objects is handled by simply checking what a user is touching. The spatial menu implementation can easily be applied to other spatial objects in the future. The system was demoed to an audience of 800 at a special event.


Results - The demo showed that a maximum of 6 users could use the system at any one time to any real effect although, any more than 3 users slowed the system down considerably. Whenever actions were not detected by the cameras, it was usually because some object or person was blocking the view which brought the question of camera placement back to the creators' minds. Some unique interactions were also discovered during the demo such as objects transferring between surfaces because users with those objects shook hands. Future plans for the system mostly center around making the system more robust and removing limiting requirements. 


Conclusion - The researchers conclude by saying they have presented a system that is capable of transitioning the user space from a single computer to the entire room around them.


Discussion


I think the researchers prove their hypothesis that depth cameras provide a viable option in creating more interactivity in currently non-interactive environments by simply bringing in a somewhat portable system that can then calibrate to that space. I think the future in this study could produce great results that lead some day to an interactive classroom followed by the elusive "smart" house. The only faults I can find with this work is that the use of an external system, as opposed to an internal one, can be very limited by the location of objects and users if a standard for depth camera positioning is not established by an extensive study on the topic.

Paper Reading #12: Enabling beyond-surface interactions for interactive surface with an invisible projection

i-m-Flashlight

Enabling Beyond-Surface Interactions for Interactive Surface with An Invisible Projection


Authors - Li-Wei Chan, Hsiang-Tao Wu, Hui-Shan Kao, Ju-Chun Ko, Home-Ru Lin,
Mike Y. Chen, Jane Hsu, Yi-Ping Hung


Authors Bios - Li-Wei Chan is a PhD student at the National Taiwan University and researches with the Image and Vision Lab and iAgent.
Hsiang-Tao Wu is now a researcher at Microsoft Research Asia but previously attended the National Taiwan University.
Hui-Shan Kao, Ju-Chun Ko, Home-Ru Lin were students at the National Taiwan University during the time of this paper.
Mike Y. Chen is an assistant professor at the National Taiwan University specializing in human-computer interaction and mobile computing.
Jane Hsu is a professor at the National Taiwan University and focuses on multi-agent systems and web technologies.
Yi-Ping Hung is a professor at the National Taiwan University and researches human-computer interaction among other things.


Venue - This paper was presented at the UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.


Summary


Hypothesis - In this paper, researchers propose using Infrared (IR) projectors to allow 3D interactions with traditional 2D tabletop surfaces. The hypothesis is that through the use of IR projectors, invisible markers can be created to allow for an entirely new set of interactions with touch surfaces interacting in the 3rd dimension.


Content - The researchers first had to build the devices to be used seeing as most of what is needed is not currently available on the market. The IR projector was built by upgrading a DLP projector and the table had to be made with the diffuser layer above the touch-glass because the touch-glass would reflect on observers and degrade the light. Detecting multi-touch was implemented using a combination of touch recognition and the Diffused-Illumination(DI) method in a clever way by simulating backgrounds, inspecting suspected objects in a region of interest (ROI) by projecting white regions onto it, and smoothing out feedback with a Kalman filter. Due to the camera and projectors being independent systems, it was necessary to use software synchronization to keep the cameras from feeding old data to the projectors. 


Methods - 3 applications were developed including:
1) i-m-Lamp - Ordinary lamp structure with IR camera and pico-projector instead of a light bulb. Users move the lamp to point at an area of interest like a particular part of a map. The tabletop surface masks its projection at that location and the pico-projector takes over by projecting the same data shown on the tabletop beforehand only with more detail than before.
2) i-m-Flashlight - Mobile version of the i-m-Lamp allowing for quicker examination of certain areas of interest like those found on paintings.
3) i-m-View - A 3D viewer that lets a tablet, or tablets, view a 3D model of whatever 2D image is being shown on the tabletop surface. The boundaries of the tabletop surface are clearly denoted on these tablet devices to keep users aware of the system they are using.


Results - 5 users were asked to use the 3 systems to perform certain actions and provide feedback:
1) The i-m-Lamp was found to be the most stable of the devices and proper use was described as moving the lamp to a desired location to then search nearby for information.
2) The i-m-Flashlight was used more quickly and was found to be effective in finding information from a variety of locations in quick succession but a problem was encountered if users moved the device too close or too far from the table.
3) The i-m-View became lost when users tried to look up at tall buildings focusing the device away from the tabletop. Users also wanted touch actions enabled on the tablet for easy manipulation as well as a portrait mode. The i-m-View also immersed the users too much in the tablet, as expected, and made them unaware of the real scene on the table.


Conclusion - The researchers conclude by noting that they had accomplished the goal of creating a 3D interactive environment through the use of IR cameras and projectors. They also discussed future work in fixing problems found during testing and adding more features requested by users.


Discussion


I think the researchers accomplished their goal of creating a 3D interactive surface using invisible markers and the applications helped prove that but where this would fit in in the general public remains a mystery. This system is too bulky by itself and would need a good reason to exist. I can see this applied to Air Traffic Control systems. The table could display general airplane symbols and show direction but to get more data, the controller can highlight it with a device similar to the i-m-Flashlight. Because of things like this, I can see this technology developing and maybe even finding a niche somewhere.

Paper Reading #11: Multitoe

Multitoe: High-Precision Interaction with Back-Projected Floors Based on High-Resolution Multi-Touch Input


Authors - Thomas Augsten, Konstantin Kaefer, René Meusel, Caroline Fetzer, Dorian Kanitz, Thomas Stoff, Torsten Becker, Christian Holz, and Patrick Baudisch


Authors Bios - Thomas Augsten is a master student in IT systems engineering at Hasso Plattner Institute
Konstantin Kaefer is a master student at Hasso Plattner with interest in human-computer interaction
René Meusel, Caroline Fetzer, Dorian Kanitz, and Thomas Stoff were all undergraduate researchers at Hasso Plattner Institute at the time of this project.
Torsten Becker is a graduate student at Hasso Plattner Institute specializing in human-computer interaction.
Christian Holz is a PhD student at Hasso Plattner Institute working with Patrick Baudisch in human-computer interaction.
Patrick Baudisch is a professor at Hasso Plattner Institute and chair of the Human-Computer Interaction Lab.


Venue - This paper was presented at the UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.


Summary


Hypothesis - In this paper, researchers argue that current tabletop computers are limited in size and could be made better if they were bigger. To accommodate bigger displays, the researchers propose using the floor as the surface to interact with increasing the size limit greatly. The hypothesis put forth by the researchers is that the floor can be a sizable, productive interactive surface if combined with the right technology and designed thoughtfully.


Contents - In order to propose an effective design of an interactive floor surface, a prototype was built by the researchers. They decided to use a combination of Front Diffuse Illumination (Front DI), gives position of feet by analyzing shadows, and Frustrated Total Internal Reflection (FTIR), makes pressure visible, to interpret user input. The floor was made of several tiles that consisted of many different materials and Rosco projection screens to display images. To keep costs down, the researchers decided to only build one tile that could sense user input. 


Several tests were done in determining what features to support. Those tests and results are shown below with numbers like "3)" denoting corresponding trials and results.


Methods - 1) The researchers asked 30 participants to activate 2 paper buttons taped to the floor and not activate the others. The manner in which they activated the buttons was observed as well as what was done in the non-activation. 
2) Invoking menus needed to be location independent due to the inherent size of floors and observations from the previous study was used in determining results.
3) A method for selecting and dragging objects was needed so 20 participants were asked to stand on a grid of "buttons" and tell an experimenter which ones were selected based on how they were standing.
4) Selecting a button needs to be precise so the researchers conducted a study that had 24 participants select, or what they perceived as select, a button with a crosshair in the center using 4 different methods (free-form, big-toe, tip of shoe, and ball of the foot). Studying this data, the researchers found what specific pressures were present when users made "selections" allowing for the development of a natural selection process.
5) Choosing the correct size for the smallest elements was also important to the researchers so they had 26 participants type a specified sentence 2 times on 3 differently sized keyboards and recorded the accuracy.


Results - 1) The researchers found tapping to be the most intuitive activation input and walking was used the most often in ignoring the others therefore tapping was used in this prototype. 
2) Jumping seemed to be the most appealing input to invoke menus as users can jump anywhere when a menu is needed.
3) Most participants described the entire area under their shoe as being pressed therefore the Front DI component (described earlier) was used for determining object selection.
4) Results varied in the free-from method and accuracy greatly improves when telling users what method to use but the researchers did not want to alienate users so the end decision was to support all type but have users set their method by performing an easy machine training step.
5) As expected, as button size decreased error rates increased and the majority of users liked the largest keyboard the best.


Conclusion - The researchers conclude by saying they demonstrated why floor surfaces are viable touch interfaces and even introduced the concept of identity recognition based on sole patterns and that research will continue in this field and they will continue to build on the prototype shown in this paper by looking into building a smart room capable of monitoring the well-being of the people inside.


Discussion


I think the researchers support their hypothesis that floor interfaces are plausible replacements to similar tabletop devices and provide much larger spaces for interaction. I think this paper is particularly interesting because tabletop surfaces have yet to really prove themselves in the real world and presented here is an alternative choice for interaction. I also think it was cool that they used foot gestures to play a game showing real world potential right from the start.

Paper Reading #10: Sensing foot gestures from the pocket

Sensing foot gestures from the pocket


Authors - Jeremy Scott, David Dearman, Koji Yatani, Khai N. Truong


Authors Bios - Jeremy Scott is a graduate student at MIT and received his Bachelor's from the University of Toronto.
David Dearman is a PhD student at the University of Toronto.
Koji Yatani is a PhD student at the University of Toronto interested in interactive systems.
Khai Truong is an associate professor at the University of Toronto specifically interested in human-computer interaction.


Venue - This paper was presented at the UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology.


Summary


Hypothesis - In this paper, researchers discuss a way to use foot gestures to perform tasks in a mobile environment and develop a system that supports this. In doing so, they hope to prove their hypothesis that such a system can learn over time from users to recognize more accurately in addition to the primary goal of allowing users to perform tasks without having to focus on visual input and visual feedback.



Methods - The researchers decided the first thing to do was study possible foot gestures that could be used in the product. The four gestures explored were dorsiflexion, Plantar flexion, heel rotation, and toe rotation. Participants were asked to hold down a button on a mouse and perform one of these gestures rotating to a specified angle from the start position and releasing to indicate completion. The setup consisted of 6 Motion Capture cameras and a laptop, informing the participant of what task was to be performed and recording information received from the cameras. Participants began the study with the training phase that consisted of 156 gestures and visual feedback informing the user of their progress. Next, the testing phase began with no visual feedback and 468 gestures. Lastly, participants were interviewed and asked to rank the gestures in order of preference. A second study was conducted using the same procedure and equipment later in testing the researchers' machine learning algorithms by using different number of users' data as training data and the rest as test data. Also heel rotation and Plantar flexion were the only 2 gestures tested due to the results of the first study (see below). 2 different classification procedures were used for the machine learning portion of this study. Leave-one-participant-out (LOPO) consisted of using all but one of the particpants' data as training data and then testing on the remaining participant. Within-participant (WP) consisted of a single user performing a gesture many times with all but one of those trials used as training data and the remaining trial used as test data.


Results - The initial study found raising the heel, or Plantar flexion, to be the most accurate and preferred gesture for vertical angles. Plantar flexion also showed a consistent error rate across all angles whereas the other gestures increased in error as the angle increased. Among the rotation gestures, both heel and toe rotation were comparable in regards to error and range but heel rotation was greatly preferred by the participants. The second study tested gesture recognition using a phone located in a front pocket, back pocket, and hip mount which resulted in successful recognition 50.8%, 34.9%, and 86.4% of the time respectively.  Higher percentages resulted when the algorithm only had to determine which gesture type was being performed (heel rotation or Plantar flexion).

Contents - The researchers developed a program to recognize foot gestures using data collected with a phone's accelerometer. The workflow for the program consisted of a user wearing a phone in a pocket, initiating the system by placing a foot at the origin and performing a double tab, and performing the desired gesture which would then be recognized by the system and executes the desired command. To optimize this method, the recognition algorithm would have to be very robust and able to adapt to an individual so the researchers integrated machine learning into the workflow and did several quick tests to help develop the machine learning algorithm. They found 34 features that could be used in gesture recognition and implemented them into an initial application that was used in the second study.


Conclusion - The researchers conclude that foot gestures are a viable option for user input. Because the WP procedure worked significantly better than LOPO, the researchers also conclude that this type of program would be best implemented by learning from an individual user before use by that person.


Discussion


I think the researchers achieved their goal of proving the viability of using foot gestures as input and they mostly convinced me of this in their testing. I would have also liked to have seen a framework built that other developers could use to begin using this technology in real-world applications because I think the usefulness of this ability is still questionable to most people. Nevertheless this technology could prove crucial in the future of device interfacing and help make device interfacing a very transparent and non-feedback dependent task.