Skinput: appropriating the body as an input surface

By Chris Harrison, Desney S. Tan, Dan Morris. International Conference on Human Factors in Computing Systems, 2010

704 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/ba7d6b7c0fec3468085d927151695cd563428638

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

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In Human-Computer Interaction

Citations in the corpus

UX Design Innovation: Challenges for Working with Machine Learning as a Design Material (2017, background): “skin into a touch interface [27] to gesture recognition [50].”
Combining multiple depth cameras and projectors for interactions on, above and between surfaces (2010, background): “Examples include immersive virtual experiences [14], on-demand augmentations and interactive displays [18], multi-user collaborations [4], and adapting the user’s body as an interactive surface with acoustically sensed interactions [9].”
OmniTouch: wearable multitouch interaction everywhere (2011, background): “Also of note is Skinput [8], which uses bio-acoustics to detect finger tap events on the skin.”
Interacting with Soli: Exploring Fine-Grained Dynamic Gesture Recognition in the Radio-Frequency Spectrum (2016, neutral): “6% [13], 85% [29]).”
We Can Hear You with Wi-Fi! (2014, background): “Further, it has detection delay because the sensor must first record the sound and process it, then transmit it to the receiver.”
3D Gestural Interaction: The State of the Field (2013, background): “[23], uses a set of sensors worn as an armband to detect acoustical signals transmitted through the skin [18].”
Whole-home gesture recognition using wireless signals (2013, background): “Inertial sensing and other on-body sensing methods on the other hand, require the users to wear multiple sensors or carry a device such as a wrist band [7, 14, 12].”
Digits: freehand 3D interactions anywhere using a wrist-worn gloveless sensor (2012, background): “…different dimensions, such as limiting hand tracking to 2D input only [9, 26], focusing on ﬁngertips or other speciﬁc parts of the hand [20, 37], only supporting interactions through surfaces and other tangible mediators [5, 11, 12], or supporting a small discrete set of hand gestures [15, 34, 35].”
3D Tracking via Body Radio Reflections (2014, background): “These include devices that the person needs to hold (such as the Nintendo Wii [4]) or wear (e.g., on-body sensors such as wristbands [1, 14, 17]).”