Devices with significant computational power and capabilities can now be easily carried on our bodies.
However, their small size typically leads to limited interaction space (e.g., diminutive screens, buttons, and jog wheels) and consequently diminishes their usability and functionality.
Since we cannot simply make buttons and screens larger without losing the primary benefit of small size, we consider alter- native approaches that enhance interactions with small mo- bile systems.
One option is to opportunistically appropriate surface area from the environment for interactive purposes. For example, [10] describes a technique that allows a small mobile device to turn tables on which it rests into a gestural finger input canvas.
However, tables are not always present, and in a mobile context, users are unlikely to want to carry appropriated surfaces with them (at this point, one might as well just have a larger device). However, there is one surface that has been previous overlooked as an input canvas, and one that happens to always travel with us: our skin.
Appropriating the human body as an input device is appealing not only because we have roughly two square meters of external surface area, but also because much of it is easily accessible by our hands (e.g., arms, upper legs, torso).
Furthermore, proprioception – our sense of how our body is configured in three-dimensional space – allows us to accurately interact with our bodies in an eyes-free manner.
For example, we can readily flick each of our fingers, touch the tip of our nose, and clap our hands together without visual assistance.
Few external input devices can claim this accurate, eyes-free input characteristic and provide such a large interaction area.
In this paper, we present our work on Skinput – a method that allows the body to be appropriated for finger input using a novel, non-invasive, wearable bio-acoustic sensor.
The contributions of this paper are:
. 1) We describe the design of a novel, wearable sensor for bio-acoustic signal acquisition (Figure 1).
. 2) We describe an analysis approach that enables our sys- tem to resolve the location of finger taps on the body.
Devices with significant computational power and capabilities can now be easily carried on our bodies.
However, their small size typically leads to limited interaction space (e.g., diminutive screens, buttons, and jog wheels) and consequently diminishes their usability and functionality.
Since we cannot simply make buttons and screens larger without losing the primary benefit of small size, we consider alter- native approaches that enhance interactions with small mo- bile systems.
One option is to opportunistically appropriate surface area from the environment for interactive purposes. For example, [10] describes a technique that allows a small mobile device to turn tables on which it rests into a gestural finger input canvas.
However, tables are not always present, and in a mobile context, users are unlikely to want to carry appropriated surfaces with them (at this point, one might as well just have a larger device). However, there is one surface that has been previous overlooked as an input canvas, and one that happens to always travel with us: our skin.
Appropriating the human body as an input device is appealing not only because we have roughly two square meters of external surface area, but also because much of it is easily accessible by our hands (e.g., arms, upper legs, torso).
Furthermore, proprioception – our sense of how our body is configured in three-dimensional space – allows us to accurately interact with our bodies in an eyes-free manner.
For example, we can readily flick each of our fingers, touch the tip of our nose, and clap our hands together without visual assistance.
Few external input devices can claim this accurate, eyes-free input characteristic and provide such a large interaction area.
In this paper, we present our work on Skinput – a method that allows the body to be appropriated for finger input using a novel, non-invasive, wearable bio-acoustic sensor.
The contributions of this paper are:
. 1) We describe the design of a novel, wearable sensor for bio-acoustic signal acquisition (Figure 1).
. 2) We describe an analysis approach that enables our sys- tem to resolve the location of finger taps on the body.
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