Each and every year we are witnessing smaller and smaller computers being realest on the market. More and more PDA and mobile computers as well as GPS devices are being sold each and every day. They performance as well as number of different uses increases. No wonder that the concept of a real wearable computer is being discussed and researched so often. Wearable computers are not equivalent to small computers anymore, they aim to become a new paradigm in computing.
Companies all around the world as well as universities invest money in developing both hardware and software that is suppose to change a small computer that we carry with us into a real ubiquitous technology. One of the biggest problems that still has to be faced is the user interface of devices like that.
Interfacing a small device like that in a efficient way is a problem by itself. B. Thomas, K. Grimmer, J. Zucco, and S. Milanese in their work “Where Does the Mouse Go? An Investigation into the Placement of a Body-Attached TouchPad Mouse for Wearable Computers” discuss in depth a problem not only of a size of the interface device but its placement during various situations.
They not only perform a set of experiments that is suppose to measure the efficiency of each position of an input device but also consider them in various situations.
The only reason why I mention this particular research is because how ineffective are the standard ways of interfacing based on a keyboard, mouse and WIMP interface. Not only times of reaction are to big for every day usage also the input devices themselves due to human limitations have to be of a significant size. Moreover what might be obvious they require hand usage what makes them useless in some applications, because they can not be simply used while driving or during other activity that requires both hands.
That is why to speak about ubiquitous computing we have to forget about traditional interfaces and focus on other solutions that are less consuming not only physically but also mentally.
So what are the other solutions? First one that came to my mind was sound. Asim Smailagic in his article “An evaluation of audio-centric CMU wearable computers” focuses on the systems that already have been developed and their implementation and accuracy.
Systems presented by the author prove to have very high accuracy as well. But the error introduced by the voice recognition is still too big for everyday use. Not to mention the fact that the research considering efficiency was based on well defined tasks only and it is difficult to tell on that basis what will be the efficiency for new undefined tasks.
When talking about vocal interfaces it is worth mentioning that it is not only voice based control. Yong Xu , Mingjiang Yang, Yanxin Yan, Jianfeng Chen in the paper “Wearable Microphone Array as User Interface” describe the usage of sound as a tool for detecting context of the usage of the wearable equipment.
A big advantage of systems like that is the fact that they can be easily used by people with movement disabilities. But a serious disadvantage is that sometimes voice commands are even slower than manual commands and not always sounds can be used for control.
The other method for control of the wearable devices are gestures. There is a big amount of research describing usage of finger tracking (like the one by Sylvia M. Dominguez, Trish Keaton, Ali H. Sayed “Robust Finger Tracking for Wearable Computer Interfacing”) gesture and head movement tracking (M. Hanheide, C. Bauckhage, G. Sagerer Combining Environmental Cues & Head Gestures Interact with Wearable Devices).
Using that interfacing system interaction is much more faster, discreet and easier. This technology combined with aye tracking techniques can not only be used by disabled but requires much less effort from a human being.
But still to call this technology pervasive active human involvement has to be as small as possible. Computer should be aware not only of the context of usage adjusting interfaces and behavior to the particular situations but also should be able to learn from our behavior. Learning patterns, customs and our hobbies. It should be able to anticipate our actions and be able to suggest possible solutions to everyday problems involving us as little as possible.