Capacitive Fingerprinting

Project Members

Chris Harrison (Carnegie Mellon University)
Munehiko Sato (University of Tokyo)
Ivan Poupyrev (Disney Research Pittsburgh)

At present, touchscreens can differentiate multiple points of contact, but not who is touching the device. In this work, we consider how the electrical properties of humans and their attire can be used to support user differentiation on touchscreens or any other touch interface.

We propose a novel sensing approach based on Swept Frequency Capacitive Sensing, a technique investigated in Electrostatic Vibration sensing technology, that we proposed and investigated earlier. Electrostatic Vibration measures the impedance of a user to the environment by sweeping across a range of AC frequencies. Different people have different bone densities and muscle mass, they wear different clothes and footwear, and so on. This, in turn, yields different impedance profiles, which allows attribute touch events and multitouch gestures to a particular user. We refer to this technology as Capacitive Fingerprinting. Note that this technology does not require any instrumentation of the user or the environment.

Capacitive Fingerprinting has many interesting implications for interactive design, including personalization, collaborative interaction on touch surfaces, security and others. Our evaluation of this novel sensing approach demonstrate that the technique has considerable promise and further investigations are required.

Capacitive Fingerprinting is part of the broader investigation of Swept Frequency Capacitive Sensing techniques in touch and gesture interaction that is conducted by the Haptics Team at Disney Research Pittsburgh.


A Swept Frequency Capacitive Sensing signal is applied to the touch panel. The resulted impedance profiles will be different for different users. This allows us to know who is touching the the touch screen at each moment of time.

Using Capacitive Fingerprinting we can allow each user to draw with the own color, without the need to switch colors every time they use a shared touch surface.

Capacitive Fingerprinting has also great potential in shared gaming applications.

A machine-learning classification and categorization algorithms are used to determine which specific user is touching the screen at each moment of time. Note, that no instrumentation of the user or environment is necessary.

With Capacitive Fingerprinting the system also allows to provide user-specific undo functions in teh drawing applications: only the drawings owned by the user will be affected.

These are just few possible applications of Capacitive Fingerprinting technology.


Capacitive Fingerprinting- Exploring User Differentiation by Sensing Electrical Properties of the Human Body-Thumbnail

Capacitive Fingerprinting: Exploring User Differentiation by Sensing Electrical Properties of the Human Body
October 7, 2012
ACM Symposium on User Interface Software and Technology (ACM UIST) 2012
Paper File [pdf, 4.27 MB]

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