We present a system for identifying contact fingers
using vibration as a modality of communication.
Vibration allows data communication through computing devices
or the human body with low-cost transmitters and receivers.
In this research, we transmit encoded vibrations to identify contact fingers instead of transmitting complex data sequences.
The use of vibration enables cost-effective communication between a user and a device.
Our system includes two ring-shaped transmitters and a touch surface with a microphone receiver.
An encoded vibration emitted by one finger travels through the finger and then the surface.
Only the vibration(s) from the contact finger(s) reaches the receiver, and we can identify the contact finger(s).
We transmit on-off keying (OOK) sequences to make the communication robust to external sound noise.
Basically, each finger is augmented with a unique carrier frequency,
which is carefully selected by considering auditory and tactile perception.
Therefore, recognizing contact fingers corresponds to identifying carrier frequencies from the captured data.
To demodulate the encoded vibration sequences, we use cross-correlation that measures the similarity between two sequences.
Here, we illustrate the results of the cross-correlations.
An OOK sequence generates unique patterns when it is cross-correlated with other OOK sequences.
We observe one prominent main peak and two side peaks only when two OOK sequences have the same carrier frequency.
The detailed demodulation process is illustrated in our paper.
For successful vibratory communication, a vibration needs to travel through a series of channels.
Therefore, we investigated the vibration characteristics of the channels involved: the hand and the surface of a tablet.
Designing robust data communication takes substantial time and effort.
As a systematic approach, we built a testbed to simulate
the propagation of encoded vibration sequences from the transmissibility data.
In this simulation, we extensively tested our modulation and demodulation methods to verify the effects of design parameters.
To consolidate the simulation results, we verified the selected communication protocols at two places, the laboratory and a cafe.
The resulting highest accuracy in each place was 93 % and 90.5 %, respectively.
The best-performing protocol was repeating a 50-ms long pulse three times and wearing rings on the thumb and middle fingers.
We demonstrated the effectiveness of our vibratory communication as a finger identification method with a touch screen.
Our system achieved over 91 % accuracy in identifying seven contact states
enumerated from three fingers while wearing only two actuator rings with the aid of a touch screen.
Additionally, we conducted a supplemental study of everyday objects by attaching a wireless earbud as the receiver.
We have created applications for finger-aware touch interaction with our system.
Our concept is beneficial for diversifying touch interaction
on touch-sensitive surfaces with a microphone,
e.g., tablets and wearable devices,
and everyday surfaces by attaching a microphone.
We envision that the practical applicability of our system can enrich touch interactions in various computing contexts and devices.