We introduce in this paper GestuRING, a gesture dataset and tool for the web meant to support
design of ring-based gesture input.
We focus on ring devices because rings can detect a variety of gesture types, such as
taps and touches on the ring s surface, hand poses and mid-air gestures, but also body-referenced
and on-body input.
Also, despite an exciting area with many promises for innovations in wearable interactions,
research on input techniques for smart rings lacks structured knowledge and readily-available
resources for designers to systematically attain such innovations.
Existing research on ring-based gesture input is scattered in the scientific literature
in a landscape that mixes contributions from wearable computing, human motion sensing,
gesture recognition, and interaction devices and techniques.
Our goal is to structure this fragmented landscape and to provide resources to foster design
and engineering of interactive systems employing ring gestures.
To this end, our contributions are multiple:
We report results from a systematic literature review on ring gesture input that included
84 papers addressing this topic.
By analyzing the results reported in those papers, we catalogued nearly 1,000 ring gestures
and identified 579 mappings between ring gestures and system functions.
Also, we deliver our findings as actionable resources for practitioners.
GestuRING, our web-based tool features a searchable dictionary of ring gestures with companion
YouTube videos and numerical data files to illustrate the gestures.
In this paper, we employ an operational definition of a ring gesture as any action that can be
performed with or on a smart ring or any movement of a body part that can be detected by the
ring.
This definition comes from a 2018 paper on user-defined gestures with smart rings.
Based on this definition, a ring device can be seen as a finger-augmentation device that
has the form factor of a ring.
However, we found that this definition was not enough to describe all the prototypes
that we came across in the scientific literature and that were described by their authors as
rings.
Hence, we introduce in this paper new terminology.
Namely, ring-like devices are not restricted by the ring form factor and enable the same
kind of gesture interactions as a ring.
Also, ring-ready devices are devices that can take multiple forms in order to serve
multiple purposes and among these forms they can also take the form factor of a ring and
be worn and used as such.
Together, rings, ring-like, and ring-ready devices constitute a distinct family of wearables
for finger augmentation.
Please see our paper for more details and examples for these device categories.
For our systematic review, we followed best practices from the literature and identified
more than 400 papers in several scientific databases.
Of these, a number of 84 papers met our requirements for gesture input with ring devices.
We found that most of the contributions from the literature were about artifacts, such
as new ring devices, that were often accompanied by empirical results from user studies and
evaluations.
We also found two datasets and two survey contributions.
Most of the devices that we encountered in the scientific literature fell into the first
category of our ring taxonomy, that is finger augmentation with a ring form factor device.
However, the rest of the 20% of the devices deviated from the ring form factor by either
augmenting more parts of the finger in the case of ring-like devices or by targeting
multiple forms and purposes, as in the case of ring-ready devices.
Please see our paper for specific examples.
Most of the rings were intended to be worn on the index finger.
An interesting result is that in 23% of the cases, combinations of fingers were targeted
by the ring devices that we surveyed, such as two rings worn on the index and middle
fingers, respectively.
Regarding the technology to detect gestures, we found inertial sensing implemented in almost
half of the devices from the literature, followed by video cameras, pressure and magnetic sensing.
From each paper, we extracted the gesture set, if available.
Overall, we identified a total number of 579 mappings between ring gestures and system
functions.
The most frequently occurring gesture types were free-hand, mid-air, and touch input on
the ring surface, respectively.
A noteworthy result from this analysis is that the average size of the gesture sets
presented in the papers that we examined was of just 8.1, showing small size vocabularies
for gesture-based user interfaces for rings.
We used our results to develop GestuRING, a tool for ring gesture input that makes the
findings of our systematic literature review actionable for practitioners and readily available
on the web.
GestuRING provides access to a dataset of 579 gesture-to-function mappings, such as
rotating the ring across the finger to navigate a one-dimensional menu or, as shown in this
video, ring gestures to interact with content displayed on a smartwatch.
Moreover, GestuRING includes a YouTube video library that illustrates the gestures from
the literature and also numerical data for those gestures that we recorded using an accelerometer
attached to the index finger.
More details are available in our paper about the design of our systematic literature review
study, findings on ring gestures, and details about GestuRING including examples of use
cases.
Thank you for your attention.