Reading #29: Scratch Input Creating Large, Inexpensive, Unpowered and Mobile Finger Input Surfaces

COMMENTS ON OTHERS:

           Jonathan 

SUMMARY

              In this paper, the authors provide a new input technique that allows small devices to appropriate existing, large, passive surfaces such as desks and walls, for use as a kind of input device. This Scratch Input technique operates by listening to the sound of “scratching” (e.g., with a fingernail) that is transmitted through the surface material. This signal can be used to recognize a vocabulary of gestures carried out by the user. The proposed sensor is simple and inexpensive, and can be easily incorporated into mobile devices, enabling them to appropriate whatever solid surface they happen to be resting on. Alternately, it can be very easily deployed, for example, to make existing walls or furniture input-capable.

            To capture sound transmission through solid materials, authors proposed to use a modified stethoscope. This is particularly well suited to both amplifying sound and detecting high frequency noises. This is attached to a generic microphone, which converts the sound into an electrical signal. In this particular implementation, the signal is amplified and connected to a computer through the audio-input jack. Scratch Input’s non-spatial property gives it a significantly different character from many other surface input techniques and does preclude some uses. Results indicate participants were able to achieve an average accuracy of 89.5%. As hypothesized, accuracy suffered as gesture complexity grew. Gestures with two of fewer motions achieved accuracies in excess of 90%. 

DISCUSSION

            The Scratch Input, an acoustic-based finger input technique that can be used to create large, inexpensive and mobile finger input surfaces. This can allow mobile devices to appropriate surfaces on which they rest for gestural input. This revealed that Scratch Input is both easy to use and accurate on a variety of surfaces. Foremost, most mechanical sensors are engineered to provide relatively flat response curves over the range of frequencies that is relevant to signal. This is a desirable property for most applications where a faithful representation of an input signal – uncolored by the properties of the transducer – is desired. However, because only a specific set of frequencies is conducted through the arm in response to tap input, a flat response curve leads to the capture of irrelevant frequencies and thus to a high signal-to-noise ratio.