Sensing Techniques for Tablet+Stylus Interaction
Ken Hinckley1, Michel Pahud1, Hrvoje Benko1, Pourang Irani1,2, Francois Guimbretiere1,3,Marcel Gavriliu1, Xiang 'Anthony' Chen1, Fabrice Matulic1, Bill Buxton1, & Andy Wilson1

1

Microsoft Research, Redmond, WA{kenh, benko, mpahud, bibuxton,
awilson}@microsoft.com

2

University of Manitoba, Dept. ofComp. Sci., Winnipeg, MB,
Canada, irani@cs.umanitoba.ca

ABSTRACT

We explore grip and motion sensing to afford newtechniques that leverage how users naturally manipulate
tablet and stylus devices during pen + touch interaction. We
can detect whether the user holds the pen in a writing grip or
tucked between his fingers. We can distinguish bare-handed
inputs, such as drag and pinch gestures produced by thenonpreferred hand, from touch gestures produced by thehand holding the pen, which necessarily impart a detectablemotion signal to the stylus. We can sense which hand grips
the tablet, and determine the screen's relative orientation to
the pen. By selectively combining these signals and using
them to complement one another, we can tailor interaction to
the context, such as by ignoring unintentional touch inputs
while writing, or supporting contextually-appropriate tools
such as a magnifier for detailed stroke work that appears
when the user pinches with the pen tucked between his
fingers. These and other techniques can be used to impartnew, previously unanticipated subtleties to pen + touch
interaction on tablets.
Author Keywords

Sensing; pen+touch; motion; grip; tablet; bimanual input
ACM Classification Keywords

H.5.2 [Information Interfaces and Presentation]: Input
INTRODUCTION

In the modern context of multi-touch tablets, pen input hasreceived renewed interest, particularly when used as a
distinct modality in tandem with touch [21,34,55]. However,many problems and ambiguities arise because the system
can't easily determine whether the user intends to interact
with the pen, with touch, or with the two in combination. As
one example, systems employ various heuristics to ignore
unintentional touch inputs associated with resting the palmon the screen while writing, but typically these come at theexpense of limiting simultaneous intentional touches
produced by the nonpreferred hand [1,2,42].
ACM acknowledges that this contribution was co-authored by an affiliateof the Canadian National Government. As such, the Crown in Right ofCanada retains an equal interest in the copyright. Reprint requests should
be forwarded to ACM, and reprints must include clear attribution to ACM
and the agency.
UIST '14, October 05 - 08 2014, Honolulu, HI, USA
Copyright is held by the owner/author(s). Publication rights licensed to
ACM.
ACM 978-1-4503-3069-5/14/10…$15.00.
http://dx.doi.org/10.1145/2642918.2647379

3

Cornell University, Information
Science Department, Ithaca, NY
francois@cs.cornell.edu

As witnessed by the proliferation in mobile sensing[7,12,19,23,24,39], there is great potential to resolve such
ambiguities using sensors, rather than foisting complexity on
the user to establish the missing context [6]. As sensors andcomputation migrate into tiny mobile devices, pens no longer
need to be conceived primarily as passive intermediaries
without a life once they move away from the display.

Figure 1. Our sensors can distinguish bare-handed (left) vs. penin-hand (right) inputs to evoke contextually-appropriate tools.

To extend this perspective, we show novel ways of evoking
contextually-appropriate tools. For example, if the user tucks
the pen while performing a pinch gesture (Figure 1, right),
this brings up a magnifying tool particularly well suited todetail work with the pen. This is sensed by detecting the Tuckgrip in combination with a hard-contact motion signal on the
pen at the same time the hand holding it contacts thetouchscreen. Performing a bare-handed pinch gesture withthe other hand, however, does not produce this pattern andcan therefore invoke a distinct behavior (Figure 1, left).
We also report observations of a rich vocabulary of naturally
occurring behaviors, including tuck vs. palm grips forstowing the pen, as well as a new class of finger extension
grips (from the hand holding the pen) for touchscreen
manipulation. That such behaviors have gone largely
unnoticed, much less actively sensed by pens and tablets,
reflects the opportunities for contextual adaptation and fresh
nuances of expression afforded by adding a few new sensors.
Overall, our contributions include the following: Observations of natural grips and usage patterns that arise
when using pen and touch together on a tablet.
 Novel hardware / software solutions that sense grip andmotion to capture the full context of stylus and tablet use.
 Using sensors to mitigate unintentional touch (from thepalm, or from the thumb when picking up the tablet), butalso to promote intentional touch by the nonpreferredhand, or via extension grips to interleave pen and touch.
 Novel contextually-appropriate tools that combine grip,
motion, and touchscreen contact, including distinct toolsfor bare-handed input, pinch input while tucking the pen,and drafting tools that the user can summon with thenonpreferred hand when the pen is poised for writing.
 Preliminary observations and user reactions arising frominitial user experience with these tools and techniques.
Collectively, these observations and novel techniques
illustrate how contextual sensors on modern stylus and tablet
devices have the potential to ameliorate ambiguities inherent
in simultaneous pen+touch interaction, while also affording
a broad design space of novel interactions.
RELATED WORK

Our research threads together themes from mobile sensing,
sensor-augmented pens, grip sensing, and pen + touch input.
Mobile Sensing on Handhelds

Tilt, pressure, and proximity sensing on mobiles enables
contextual adaptations such as detecting handedness [14],portrait/landscape detection [19], or walking vs. stationary
usage [40]. Grip sensing allows a mobile to detect how theuser holds it [53], or to use grasp to automatically engage
functions [49] such as placing a call, taking a picture, or
watching a video [24]. We adopt this perspective of sensing
natural user behavior, but bring it to pen and tablet
interaction, where the behaviors to sense—and the new
possibilities for pen+touch—remain largely unexplored.

rejection techniques require the user to bring the pen tip onor near the screen before setting the palm down, which
requires users to modify their natural movements (e.g. [55],or Microsoft Windows tablets, which turn off touch when the
pen comes in range). Our approach uses sensors to detect
when a touchscreen contact is associated with the handholding the pen, thus showing that the problem can be framed
as one of sensing appropriate contextual information.
Sensor-Augmented and Multi-DOF Stylus Input

Auxiliary tilt, roll, and other stylus degrees-of-freedom canbe combined [15] to call up menus [50] or trigger modeswitches [4] without necessarily disrupting natural use [54].
Conte [51] explores a tilt-sensitive “digital Conte crayon” forpen + touch interaction on a tabletop. In particular, Conte
explores interactions where the user orients or holds or thecrayon on the display, while other fingers from the same
hand reach out and touch the screen to pick colors or choosemodes. We consider similar capabilities where the user can
extend one or more fingers while tucking the stylus. We also
sense distinct contexts with separate functions, even when
the user holds the pen away from the screen.

Multi-touch input and inertial sensors (IMU's with 3-axis
gyroscopes, accelerometers, and magnetometers) afford new
possibilities for mobiles to discern user intent based on grasp
and motion dynamics [3]. Devices can distinguish if the user
touches the screen with the thumb vs. the index finger [12],or use grip sensing to avoid accidental screen auto-rotation[7]. Whacking [23] or jerking motions [39] offer out-of-band
signals distinct from incidental handling of a device. We
illustrate new techniques that leverage these types of motion
sensing, grip sensing, and multi-touch inputs when they are
distributed across separate pen and tablet devices.

Pens can be augmented with motion [17,48], grip [46,47],
and near-surface range sensing [28]. MTPen [46] uses grip
sensing to detect a tripod writing grip, or to invoke different
brushes. Sun et al. [47] use an integrated IMU on the pen toassist grip recognition, an approach which we adopt here,
and also sense the orientation of the tablet (e.g. horizontal vs.
drafting table). Context sensing examples have also been
proposed, such as sensing if the user forgets the pen [17]. Lee
et al. [26] employ an orientation-sensing stylus to reduce
occlusion problems. Our work goes beyond these efforts;
compared to the most closely related work (i.e. MTPen [46],FlexAura [28], and [17,21]), the main things that distinguishour contribution are our behavioral observations, the holistic
pen and tablet sensing platform, and application of newtechniques to well-considered UI challenges.

Grips and Sensing for Tablets

Synchronous Gestures and Cross-Channel Inputs

Lightweight tablets afford many new grips, movements, andsensing techniques. BiTouch and BiPad [52] demonstrates
bimanual interactions that take natural tablet grips into
account. Sensing tablet grips affords bringing up a
touchscreen keyboard in a contextually-appropriate location[8]. GroupTogether [32] senses clusters of co-located users
to support lightweight exchange of information by subtly
orienting a tablet towards another user with micro-mobility
gestures [29]. Our system is the first to implement full grip
sensing and motion sensing—on both tablet and stylus at thesame time—for pen + touch interaction.

The literature shows examples of distributed sensing
techniques such as bumping two tablets together [16] ortapping a mobile phone against a multi-touch tabletop [41].
Synchronous events or correlations across input channels canalso enable new types of gestures. The 1Line keyboard [9]uses a bezel thump as a spacebar by noting that normal
keystrokes produce a bump at the same time as the touchdown event, whereas a bezel thump arrives without acorresponding touch event. Smart-Its Friends [22] pairs two
devices when the user shakes them together. Are You With
Me? [27] uses motion signal similarities to sense if two
mobile devices are being carried by the same person, whileYour Phone or Mine? [38] correlates mobile phone motions
with depth image patches. Sensor Synaesthesia [20] andGripSense [12] combine touchscreen and motion signals.
Our research contributes cross-device and cross-channel
inputs for a distributed tablet–stylus sensing system to detect
unique contexts and behaviors that arise in pen+touch input.

Palm Detection and Unintentional Touch Handling

Palm contact can cause false activations during pen + touch
interaction [1,2,42]. For example, many iPad note-taking
applications include palm-blocking (e.g. [11,35,36]), but
details of these heuristics are unpublished and vary widely;
they often appear to rely on application-specific assumptions
about how and where the user will write. Other palm-

OBSERVATIONS OF PEN & TABLET BEHAVIORS

B2. Tuck vs. Palm for stowing the pen. Unlike previous
studies, we observed two distinct grips that users employ tostow the pen. All users exhibited the Tuck grip (pen laced
between fingers), but many also employed a Palm grip (withfingers wrapped lightly around the barrel) to stow the pen
during pauses or to afford touch interactions.
B3. Preferred pen stowing grip depends on task context. For
users that employed both Tuck and Palm grips, Tuck afforded
quick, transient touch interactions, while Palm was primarily
used if the user anticipated a longer sequence of touch
interactions. Other users always used Tuck to stow the pen.
B4. Grip vs. Pose. For each grip we observed a range of
poses, often by wrist supination (turning the palm upward).
Grasping motions with a pen therefore encompass the patternof hand contact on the barrel, as well as the 3D orientation of
the pen. We observed full palmar supination for Tuck andPalm, but only half-supination for the Writing grip.
B5. Extension Grips. We observed many grips where users
extended one or more fingers while holding the pen to touch
the screen, from both the Tuck and the Palm grips. However,
not all extensions were observed from each grip; inparticular, we did not observe any extension grips from the
Writing grip, and the common Tuck–Middle Extension Grip
did not occur with the Palm grip. (The 4-5 finger grips are
logical, but our touch gestures required two fingers at most.)

Writing Grips

Notes
Users employeda tripod grip forwriting, but withmany minor
variations [43].

Tuck Grips

A few users
tucked between
middle and ring
fingers.

Tuck

Palm Grips

Some users
Tuck or Palm,
depending on
task; others
never Palm.
S INGLE F INGER E XTENSION G RIPS FOR T OUCHSCREEN M ANIPULATION
Index
Middle
Ring
Thumb

Palm

NOT
OBSERVEDNOTOBSERVEDM ULTIPLE F INGER E XTENSION G RIPS FOR T OUCHSCREEN M ANIPULATION
Pinch
Index + Middle 4 or 5 Fingers Thumb on Tablet

Tuck

B1. Stowing the pen during touch. Users often stowed thepen [21,46] when performing touch gestures. Users only put
the pen down when they anticipated they wouldn’t need itagain for a prolonged time, or if they encountered a task thatthey felt was too awkward to perform with the pen in-hand,such as typing a lot of text using the on-screen keyboard.

C ORE P EN G RIPS AND P OSES
Half Supination Full SupinationNOTOBSERVEDFEASIBLE BUTNOT OBSERVED

Palm

Nine people (4 female, 1 left-handed) participated in theobservational study. Users interacted with a 10” Windows 8tablet, with multi-touch and an electromagnetic pen digitizer,
using OneNote to jot notes and Internet Explorer to browse
the web. We observed a wide variety of behaviors (B1-B12)
that helped inform our designs, as well as many previously
unrecognized pen grips, as illustrated in Figure 2 (some aredrawn from the literature). At present, we focus on behaviors
of right-handers; left-handers are known to exhibit a varietyof additional grips and accommodations (e.g. [13]).

Ready-to-Act

Finger LiftNOTOBSERVED(NOT STABLE?)

O THER P EN G RIPS O BSERVED
Extern. Precision Passing Grip Thumb Slide [30]

Other

Several papers identify distinct grips for tasks such as writing
and brushing [46,47], or holding tablets [8,52]. But theliterature still lacks an inventory of pen grips and postures
while interacting on a tablet with pen + touch. We therefore
sought to enumerate common grips that arise in digital penand-tablet tasks, and particularly touchscreen interactions
articulated while the pen is in hand. Our task thus spans notetaking with a pen, as well as a secondary task (web browsing)that primarily employs touch. We chose web browsing forthis secondary task because writing side-by-side withreading the web offers a compelling scenario from theliterature for digital ink (e.g. [18,44]).

Figure 2. Taxonomy of pen + touch grips. See text for details.

B6. Variation in pen grips. Users exhibited many variationsin the tripod grip for writing (see also [43]), leading tocorresponding variations in users’ resulting Tuck and Palm
grips, such as one user’s tendency to favor her ring finger for
single-touch (Figure 2, Tuck–Ring Finger Extension Grip).
B7. Re-gripping. An implicit theme of observations B1-B6
is that users shift between a variety of grips. Furthermore,users often exhibited subtle adjustments to their grasp whilewriting and handling the pen. These naturally occurring regripping behaviors appeared to be motivated by comfort,
fatigue, and functional considerations (such as reaching out
a finger during an extension grip, as in B5).
B8. Consistency in grips. Each user consistently applied thesame core pen grips in the same situations. Users also tended
to maintain whatever grip required the least effort, until aperceived interaction barrier such as fatigue or inefficiency
gave them an incentive to shift grips. Users switched tablet
grips more often when sitting than standing, perhaps because
there are few effective ways to hold a tablet while standing.
B9. Touchscreen avoidance behaviors. Users often adopted
pen grips and hand postures, such as floating the palm above
the screen while writing, or splaying out their fingers in a
crab-like posture, to avoid incidental contact with the screen.
Another form of touchscreen avoidance was perching the
thumb along the outside rim of the tablet bezel, rather thanletting it stray too close to the touchscreen when picking up
the tablet with one hand. These unnatural and potentiallyfatiguing accomodations reflect the system's inability to
distinguish the context of intentional vs. unintentional touch.

and our custom circuitry. For inertial sensing we use the
STMicroelectronics L3G4200D MEMS gyroscope as well as
a LSM303DLHC accelerometer / magnetometer module.
The capacitive grip sensor consists of a copper grid customprinted on a flexible Kapton substrate, connected to a
Cypress CY8CTMA463-60BUI touch controller. We stream
data to a host using the 2.4GHz Nordic Semiconductor
nRF24L01 transceiver operating at 2Mbps. An Atmel
XMEGA 32A4U microcontroller runs our firmware.
We stream all inertial sensors off the pen at 130Hz, and the
7×30 capacitance map (Figure 3) at 30Hz. We designed our
pen to be wireless; however, it proved difficult to change thebattery without damaging the grip sensor, so we had to add acable for power. The pen is 19cm long × 14mm diameter.

B10. Finger Lift for activating pen controls. Users activatedthe pen barrel button from the Writing grip, and then onlywith the index finger. Users held the pen still when tapping
the button. The thumb is also potentially available forcontrols from the Thumb Slide grip, as noted by [30].
B11. External Precision Grip. Users employed this grip,with the pen held toward the fingertips [30] andperpendicular to the writing surface, for precise pointing at
small targets, such as the web links in our web browsing task.

Figure 3. Example pen sensor data showing two different grips(a,b) and three example gyro signals (c,d,e). See text for details.

B12. Passing Grip. We also observed passing prehension[33] when participants passed the pen and tablet back to theexperimenter. Users tended to hold the device securely, in
more of a power grip, and extended it from their body while
keeping it level, so that their intent was clear and so that theother person could grab it from the far side.
Having observed these natural behaviors, we now turn ourattention to stylus + tablet hardware that can sense them.
Note that it is not our intention to recognize all of these grips,
or to leverage all of these behaviors, but rather to inform ourapproach and help shape many of our design decisions.
REALIZING GRIP+MOTION SENSING FOR PEN/TABLET

To support the range of context sensing techniques that weenvisioned, we designed custom hardware to augment thestylus and tablet with inertial sensors and capacitive grip
sensing, as well custom software to handle simultaneous pen+ touch events from the touchscreen.
Pen Hardware Design

A flexible capacitive grid consisting of 7×30 sensing
elements covers the entire barrel of the pen, which we wrap
in heat-shrink tubing to protect the sensor and to provide asmooth and easy-to-grip cylindrical surface for sensing. Theinterior of the pen consists of a 3D-printed case that holds a
miniature Wacom electromagnetic pen, a AAAA battery,

Figure 4. Example tablet case grip sensor data showing four
fingers reaching in from the top to grasp the tablet.
Tablet Hardware Design

The tablet case (Figure 4) covers the entire back surface andsides of the tablet. The rigid case is constructed from printed
circuit boards consisting of 44×26 capacitive sensing
elements. There is a small insensitive area (in the middle ofthe case on the back side) where the integrated circuits aremounted. The case includes the same sensor components as
the pen, except there are four touch controllers for different
parts of the capacitive grid. We stream the tablet sensor data
via USB, with the tablet's inertial sensors sampled at 100Hz
and the tablet's 44×26 capacitance map sampled at 25Hz.
Simultaneous Pen and Touch from the Touchscreen

Because by default Windows deactivates touch when the pen
comes in range (as a palm-rejection technique), we employ
the Windows Raw Input API to capture multi-touch and pen

events directly from the HID controller. Using this approach
the Samsung Series 7 Slate we use for our prototype canreport up to 8 touch contacts simultaneously with pen input.
Software Design

We time-stamp the pen / tablet sensor data on an external PC,
compute grips, and then dispatch events to the tablet for
presentation in the UI. Thus our implementaton consists of a
distributed system with four cooperating components: thestylus, the tablet case, the tablet itself, and the external PC.
Inertial Sensor Fusion

We combine the accelerometer, gyro, and magnetometerusing a direct cosine matrix algorithm ([31,37]). This
produces stable yaw, pitch, and roll values in an east-northup Earth coordinate frame, yielding the stylus orientation ina consistent reference frame relative to the tablet.
Stylus Grip Classification

At present we recognize four distinct grips: Writing, Tuck,
Palm, and No Grip (for when the stylus is not held). Per
observed behavior B4 (Grip vs. Pose), the grip recognition
considers the pattern of hand contact (capacitive grip
sensing) as well as the pose (orientation) of the stylus. We
processed the incoming data to extract salient features andthen trained a multi-class classifier to extract the stylus grips.
We performed a multi-class classification of the stylus grip
patterns by using a set of one-vs-all learners, where eachlearner was a Support Vector Machine (SVM) classifier. The
result is a probability distribution over all four grips.
We selected features for grip classification that carefully
considered the cylindrical symmetry of the stylus formfactor. Sensed grips should be agnostic to the roll angle ofthe pen; likewise, the size of the user’s hand, or a grip higher
or lower on the pen barrel, should not affect classification.
Thus we compute a normalized image invariant with respect
to grip height and roll angle. From the raw 7×30 capacitancemap, we fit the non-zero capacitance values into a 7×10
normalized image. We shift the capacitance map in the ydimension so that the first row of lit pixels corresponds to thebottom of the normalized image, and then scale the non-zero
capacitance pixels to fit in the 10 rows of the normalized
image. The features employed for grip classification
therefore include the stylus yaw and pitch angles, thenormalized grip image, as well as the normalized grip
histogram in the x and y dimensions. We also include features
for the number of lit (non-zero) pixels, and the pixel sum of
all 7×30 capacitance values from the raw capacitance map.
Grip Training Dataset Collection

We recruited nine right-handed participants (4 female), allwith prior exposure to pen/tablet use, to generate the training
dataset. Per observation B7, grip classification must accountfor transitions between grips, grasp modification duringextension grips (B5), and naturally occurring re-gripping
behaviors. With this in mind, we designed our procedure to
elicit such transitions. Our training data therefore
incorporates common transitions between grips, as well as
any re-gripping behaviors that users exhibited.

To collect all of the main grips for each user, we led users
through a script illustrating specific grips and actions toperform in each grip. These included stowing the pen using
touch (per observation B1) from both the Tuck and Palm
grips (B2). We also included different sequences of tasks tocapture the various common transitions between grips (B3).
We led users through the full range of supination for eachgrip (B4) and included transitions between Writing and thesingle-finger and two-finger extension grips (B5), witharticulation of direct-manipulation gestures such as tapping,dragging, and pinching. However, for writing tasks we did
not specify any particlar tripod grip to use, but rather let users
hold the pen naturally so that our dataset would capture
cross-user variations in Writing grips (per B6). The datacollection lasted approximately 15 minutes per user, with a
total of 1200 samples for each user, per grip, yielding a total
training dataset of 1200 × 3 grips × 9 users = 32400 samples.
Stylus Grip Recognition Accuracy

A10-fold cross-validation using the collected grip training
dataset yielded an overall accuracy of 88% for the userindependent model. We also conducted a separate follow-up
study with nine additional right-handed users, none of whom
contributed to the training dataset. The task required users towrite as well as perform specified touch gestures (tap, drag,and pinch) while holding the pen in the Tuck and Palm grips(i.e. it did not employ the same protocol used to collect thetraining dataset, to provide greater ecological validity). We
assessed 8100 total samples (9 users × 3 grips × 300 samples
at 250ms intervals) from the new users. This yielded userindependent grip recognition accuracy of 93% for the
Writing grip, 93% for Tuck, and 77% for Palm. The relatively
low recognition rate for the Palm grip appeared to stem fromseveral users’ tendency to hold the pen very lightly in this
grip, resulting in a somewhat inconsistent pattern of contactsensed by the capacitive grip array. However, the system wasstill able to distinguish Writing vs. non-writing grips (i.e.
Tuck or Palm) with 97% accuracy. Since the interaction
techniques described below do not depend on any distinction
between the Tuck vs. Palm grips, we proceeded with thisuser-independent grip model, which works well enough even
without collecting training data for newly-encountered users.
GRIP + MOTION INTERACTION TECHNIQUES

Building on the behaviors we observed and the griprecognition capability detailed above, our goal was toexplore the design space of sensing techniques for tablet +stylus interaction. We explicitly sought to investigate
techniques in the foreground of attention, such as new
gestures made possible by additional degrees-of-freedom, as
well as background sensing techniques that use context toautomatically sense natural user behavior [6].
We pursued these goals in the context of a simple sketching
application because we felt this would best showcase ourideas. Although sketching is a different scenario than thewriting side-by-side with reading the web task used togenerate observations B1-B12, we felt that the converse—

conducting behavioral observations on an already-existing
sketching application—would not have yielded the samerichness of observations. The behavioral study thus served asa point of departure, with insights that we now apply to oursketching application. It includes annotation, panning, andzooming capabilities representing a broad sample of popular
pen-based applications (such as Microsoft OneNote, or Paper
by FiftyThree [11]), and thereby provides various examples
that illustrate the utility of our approach.
Pen Orientation Sensed Relative to the Tablet

Our inertial sensor fusion allows us to maintain a common
reference frame relative to the tablet. We employ this tabletrelative orientation at the grip-recognition phase, as well as
in the interpretation of the pen motion (such as for the
airbrush tool, described later). It is important to emphasize
here that we only can sense the orientation of the stylus
relative to the tablet. Inertial sensing cannot reliabily
determine the (x,y) translation or z-altitude of the pen without
resort to some other absolute external reference.
PALM ‘REJECTION’ AS A PROBLEM OF CONTEXT

Sensing unintentional palm contact is a difficult problem
because, at the onset of touch, there is often insufficient
information to distinguish what type of touch is occuring. A
palm might be recognizalbe as a touch with a large contact
area, but such contacts always start small and may take awhile to pass a certain size threshold. Also, someunintentional touches (such as contact produced by the
knuckles) may never turn into a “large” contact. This strategy
therefore necessitates delays (introduces lag) in processing
touch events, and still may fail to detect many contacts [1,2].
Recently, Schwarz et al. demonstrated probabilistic palm
rejection using the touch events after the palm makes contact
with the screen [42]. Our approach is complementarybecause its cues (that the pen is held in a Writing grip or not)arrive before the hand touches down, or coincident with handcontact (in the form of the ‘bump’ motion signal).
To increase stability and avoid fatigue, users naturally rest
their hand on the writing surface, but (per behavior B9),current tablet users are forced to adopt touchscreen
avoidance behaviors. Simply sensing that the user is holding
the pen is not sufficient to address this problem because
people stow the pen while using touch (B1) and employ
various extension grips to touch the screen (B5). Stylus
orientation is also insufficient because each grip can beassociated with a range of wrist supinations (B4) and because
users hold the pen in a variety of ways (B6).
However, since unintentional touch primarily occurs
incident to writing, sensing the Writing grip itself is a
powerful cue, particularly because the user typically adopts
a writing grip prior to resting his hand on the display. Hence,a highly conservative palm-rejection algorithm could simply
reject any touch that occurs when the pen is held in the
Writing grip. This, however, would preclude intentional
touches made by the nonpreferred hand whenever the pen isheld in the writing grip, which eliminantes many desirable
scenarios (e.g. panning and zooming with the nonpreferredhand), as well as simultaneous pen + touch gestures [21].
With our sensors, we noticed that when the user plants his
hand on the screen, it simultaneously induces acorresponding signal on the pen’s motion sensors. (Thetablet’s motion sensors also pick up some of this motion, but
at present we do not rely on this signal because it is damped
somewhat by the greater mass of the tablet.)The stylus motion exhibits a characteristic hard-contact
profile similar to that seen with bump, whack, and thump
gestures in other contexts ([9,16,23,41]). We look for a peak(using the second order finite difference [9] on the threecombined axes of the accelerometer or gyro) that exceeds aminimum threshold within a 10-sample window. We also
know exactly when to look for this signal because the palm
produces a bump at the same time that the touchscreen
detects the new contact. We can identify this peak within amaximum of 56ms after the touch-down event in the worst
case (including all network delays).
This allows us to employ a resonable movement thresholdfor the bump signal, while also trivially rejecting othermotion signals that do not occur coincident to a new
touchscreen contact. However, our approach can and will
miss subtle contacts, such as accidentally brushing the screenwith a pinky, or if the user tries to fool the sensors by setting
his hand down gently, for example. Nonetheless, we find our
detection scheme works well for most normal pen
interactions during writing.
For as long as the detected palm contact persists, we flag any
new touches as a “palm” if they land within a 300 pixel
radius. We found it helpful to provide feedback of the initial
palm detection by playing a brief “radar circle” animation,centered on the palm-down location, that fades as it expands.
This provides non-distracting feedback that confirms to theuser that the palm contact was successfully detected. Without
this feedback, the user may be left with a nagging uncertainty
as to whether or not their palm has triggered an undesired
action (such as calling up a menu, or leaving behind an ink
trace) that is currently occluded by the hand.
Note that the Paper app by FiftyThree provides a Pencil
hardware accessory [11] that activates a palm-blocking
feature. However, the user must explicitly provide thecontext that the Pencil is in use by holding it on the screen topair it. Paper’s palm blocking further appears to only operate
when the Pencil tip is actually in contact with the screen,
which prevents it from sensing natural palm contact as thehand approaches. Hence, our context-sensing approachworks very differently and can detect many types of palm
contact that Paper and other related approaches [42] cannot.
Permitting Intentional Touch

Of course, the whole point of this approach is to permit
simultaneous intentional touches, even when the palm is
resting on the screen. With the above criteria, any new touch

that occurs away from the palm (which is not accompanied
by a bump on the pen) represents a true intentional touch.
Our current implementation uses the first two additional
touches that are not flagged as a palm contact to support thestandard pinch-to-zoom gesture. Palm contact is ignored anddoes not interfere with pan/zoom, even if the palm moves.
However, because we still track the palm—rather thanoutright ‘rejecting’ it per se—our approach also can support
techniques that use the palm location as an input, such as tohelp correctly orient menus [5] or to anchor objects [45].
DIFFERENTIATING PEN-IN-HAND VS. BARE HAND INPUTThe Magnifier Tool vs. Full Canvas Zoom

The functionality of our Magnifier Tool (Figure 1) was
inspired by FiftyThree's Paper application [10]. Paper
invokes a focus-plus-context magnifier (known as the“loupe”) which is especially well suited to sketching tasks
where the user wants to make a few detailed strokes without
losing the overall context of the workspace. Unlike Paper,
we support both the Magnifier and Full-Canvas Zooming bysensing how the user is interacting with the pen and tablet.
When the user stows the pen (via Tuck or Palm, per B2), we
recognize this grip. If the user then brings two fingers into
contact with the display, we check the stylus for acorresponding “bump” that occurs at the same time as thetouch. When we see this combined stylus bump + two-finger
touch, it brings up the Magnifier Tool. Users found theappearance of the tool in this context natural and appealing.
If we see a two-finger touch without any corresponding
bump on the stylus, we instead infer that the user made thetouch with their other (nonpreferred) hand, which is notholding the pen. This then triggers the standard two-finger
pan and zoom interaction to allow full canvas zoom (rather
than the focus-plus-context Magnifier Tool).
The Magnifier zooms only the region of the canvas under thecircular tool. The magnifier interactively resizes itself
according to the spread between the user’s two fingers. The
user may also touch down a finger on the border of theMagnifier to drag it to a new location. A single finger tap, or
pen stroke, anywhere outside of the Magnifier dismisses it,
leaving the canvas undisturbed at its original zoom level.
Note that, since we employ a minimum motion threshold todetect the bump signal, if the user touches their fingers down
very lightly the stylus may not detect a motion signal
sufficient to exceed this threshold. Nonetheless, our current
thresholds are sufficient to detect the motions produced whenusers naturally bring their fingers to the screen with the pen
stowed. Yet the way the sensing works thus affords an
explicit work-around, by touching lightly, a noteworth pointthat crops up again in the informal evaluation reported near
the end of this paper.
The Pen Controls

As another example, a single-finger tap while the pen isstowed brings up a small in-place palette containing the Pen

Controls, allowing the user to change modes, or to modifiy
the pen color and stroke thickness, without making a roundtrip to a toolbar docked at the edge of the workspace. This
example again takes advantage of the bump generated on thestylus when the user taps the touchscreen from an extension
grip, using any single finger to make touchscreen contact(per B5). The tools appear next to the finger. The user may
then interact with the radial menus using either pen or touch,as studies have consistently found that users expect pen andtouch to be interchangable for UI controls [21,34].
FURTHER DIFFERENTIATING INPUTS BY PEN GRIP
The Drafting Tools

Our inspiration for the Drafting Tools arose from theobservation that users often maintain the Writing grip
between bursts of writing activity. For example, during
pauses users often rotate the wrist away from the screen, tobring the pen into the Writing–Half Supination pose (B4).
We reasoned, therefore, that the Writing grip itself represents
an interesting context that might be explicitly supported byproviding various Drafting Tools that take into account thatthe user is holding the pen in a ready-to-write posture.
The user calls up the drafting tools explicitly, by touching
down a single finger of the nonpreferred hand (recognized
by a single touch without a corresponding bump signal on
the stylus). If the pen is held in the Writing grip, this brings
up a small palette that currently offers two pen + touch toolmodes, an Airbrush and a Compass, although we envision
placing additional tools here (such as a straightedge, a french
curve [25], pen + touch tape drawing [21], and so forth).
The current Drafting Tool is invoked as soon as the user
touches down his finger; currently, the Airbrush is the initialdefault mode. The user can then tap on another tool (such as
the Compass) to change modes. All drafting tools are
implemented as spring-loaded modes; the mode ismaintained only so long as the user holds down his finger.

Figure 5. Airbrush tool. The nonpreferred hand indicates whereto spray, while the pen orientation defines the conic section. The
drafting tools palette (upper left) indicates the current mode.
Airbrush Tool

The Airbrush initially shows cursor feedback, as a graydashed ellipse, of where the airbrush will spray if the user
starts the paint flow. The user indicates where the airbrush
tool should spray by the position of the (nonpreferred hand)finger. This is necessary because (as noted previously)
inertial sensing cannot determine the absolute (x,y,z) locationof the pen tip above the tablet, only a 3D orientation relativeto the tablet. The relative sensing of the stylus orientation canbe demonstrated by rotating the tablet, rather than the stylus,
as shown in the accompanying video figure.
The user controls the spray ellipse by changing the azimuthand elevation angles of the pen with respect to the tablet
surface. The user can hold the pen well above the tablet
screen, making it easy to angle the pen as desired, unlike aprevious exploration of an airbrush-like tool [47] which did
not employ the stylus tilt angles, likely because it is difficult
to reorient the pen while also keeping it within the limited~15mm proximity sensing range of the tablet.
The user turns the paint flow on and off by tapping theirindex finger on the barrel of the pen (further detailed below).
When the user activates the spray, the feedback changes to abold red dashed ellipse to give clear feedback of the shape ofthe spray being produced. In our current prototype, we then“spray” highly transparent ellipses onto the canvas, which is
sufficient for our proof-of-concept implementation.
Compass Tool

The Drafting Tools palette also includes a Compass, which
supports a pen + touch mode where the pen is constrained to
draw circular arcs centered about the current location of thefinger (again of the nonpreferred hand). None of the extra
degrees-of-freedom of the stylus are required by this mode.
Single-Tap Virtual Pen Barrel Button

Mechanical pen barrel buttons are convenient for menus andswitching modes, but they force the user to hold the stylus in
a particular grip [46] so that the finger can reach the button.
They also can suffer from problems of accidental activation
if the user mistakenly presses the button while writing.
To address these problems Song et al. [46] implement a
virtual pen barrel button based on double-tap or finger slide
motions, sensed through capacitive grip on the pen barrel. It
is difficult to support single-tap interactions using capacitive
grip alone, because many false single-touch contacts can begenerated when the user shifts grips on the pen. Our system
overcomes this limitation and successfully supports singletap activation of a virtual barrel button by strategicallycombining all of the stylus sensing channels.
To identify candidate tap events, we look for a bump signal
from the finger tap (Figure 3c) at the same time that a new
touch contact appears on the capacitance image map.
However, this cannot filter out all false positives produced
by re-gripping the pen, because shifting grips can also
produce bump signals coincident with new finger contacts.
To filter these out, we rely on our observation that users holdthe pen still to maintain a stable tripod grasp when they lift
the index finger to tap on the barrel (per observation B10).
We therefore look at the ongoing accelerometer and gyrosignals and compute a simple time-decaying motion signal
similar to that employed by Hinckley et al. [19] to determine
whether a mobile device is moving or held still. We then only

accept candidate tap events that occur when the stylus is notmoving, which effectively filters out any false contacts.
Note that the stylus must remain in a new moving (or not
moving) state for at least 100ms. Otherwise, the pen barrel
tap itself can trigger brief activation of a “moving” signal,
which of course would thwart recognition of the barrel tap.
TABLET GRIP DETECTION TECHNIQUESWe use capacitive grip sensing on the back and sides of thetablet case to detect a number of additional contexts.
Thumb Menu and Handedness Detection

While we have so far focused on interactions involving thepen, there are many instances where the user picks up andholds a tablet with both hands, making the pen unavailable.
We use grip to sense which hand the user is holding the tablet
with. We then use this to summon a Thumb Menu at theappropriate side of the tablet, which allows the user toactivate various buttons and menus directly with the thumb.
If the user grasps the tablet with a second hand, we leave theThumb Menu visible at the side where it first appeared.
If we observe the user grasping the pen while holding thetablet with one hand, we can immediately infer the user’s
handedness, although we do not yet use this to customize
how menus appear, since our grip recognition is currently
only trained for right-handed users.
Detecting Unintentional Thumb Contact

When the Thumb Menu first appears, it fades in over a 1.5
second interval; if the user lets go of the tablet it fades out
after 350ms. The purpose of this animation feedback is topresent the Thumb Menu in a tentative state, so that if theuser’s thumb strays onto the touchscreen while picking up
the tablet, the menu can be ignored. We infer that a thumb isan unintentional touch if it occurs coincident with a new hand
grip on the corresponding back portion of the tablet case. We
then detect the thumb as an unintentional contact, and freeze
the fade-in of the Thumb Menu if the unintentional thumbcontact overlaps it. This feedback indicates to the user thatthe thumb contact has been recognized, but intercepted toprevent accidental activation of the menu. The user can thenintentionally interact with the Thumb Menu, if desired,simply by lifting the thumb and bringing it back down on themenu. The fade-in animation then completes.
If the user does not place the thumb on the screen when
picking up the tablet, the fade-in also serves as secondary cue
that the Thumb Menu is fully ready for use. Since accidental
activation mainly tends to occur when the user first grasps
the tablet, after a few seconds elapse we assume that any
hand contact with the screen was intentional. This therefore
illustrates how our detection scheme blocks unintentional
touch, while also allowing intention touches to get through,unlike the simple thumb-blocking heuristics on the iPad
Mini, for example, which ignore any hand contact near theedge of the screen in certain applications.

Tablet Handoff: Passing the Tablet to Another User

We explored one final interaction, that of passing a tablet toanother user as a way to offer an alternative, more physicalsemantic of sharing content with another user [18], much as
observed during device micro-mobility [29,32]. Studies ofpassing prehension [33] and our observations (B12) indicate
a characteristic sequence of motions. A user extends theobject to offer it, while holding it level. He maintains his grip
until the other person has firmly grasped the object. The
person passing the object then lets go.
We employ our sensors to detect these states, using the tablet
case grip sensing to determine when each user is grasping thedevice, and the tablet orientation to determine if the tablet islevel. When these conditions are met, a special annotation
layer peels over the tablet, as if a transparency or a sheet ofvellum had been dropped over the display. The other user isthen free to annotate the content, but not to make digitalcopies or navigate to other documents or files. This is a very
different and much more limited form of sharing than thedigital transfer of information supported by other crossdevice information transfer techniques (e.g. [32]). We do not
trigger Tablet Handoff when a single user holds the display
up with two hands; during such interactions, users angle thetablet towards themselves, and thus it is not level.

Figure 6. Handing off the tablet drops down a layer for thatuser’s annotations (shown by a page curl animation).
PRELIMINARY USER EVALUATION

Magnifier Tool: Users quickly understood the Magnifier,and were able to easily call it up. A couple of users performed
an initial interaction with a light touch that the system could
not detect, but they quickly adapted to making a moredeliberate gesture that could be sensed. This suggests anopportunity to improve the detection by making it moresensitive to fine motions, but on the other hand users
sometimes leveraged this range of expression to intentionallybypass the Magnifier. For example, one user stated he could
employ this when using his tablet one-handed to selectively
call up the Magnifier, or instead invoke pinch-to-zoom.
Pen Controls: Users were easily able to call up the pen
controls by tapping with the pen tucked. However, users
commented that depending on what they were doing with thepen, this could sometimes require them to change grips justto call up the tools. Several users proposed bringing up the
pen controls using the virtual pen barrel button instead. We
find this an interesting suggestion, but it is unclear where to
bring up the menu if the pen is out of range when tapped.
Drafting Tools and the Airbrush: Users found the basic idea
of calling up pen-specific drafting tools when they were
holding the pen ready-to-write to be intuitive. Users foundusing the airbrush fun and exciting, but several commented
that tapping the pen barrel to turn it on and off would disturb
the location of the spray ellipse. Users also had a mixed
reaction to the need to indicate where to spray by holding
down a finger, because “your non-dominant had is doing thedrawing, which is a little odd” as one participant commented.
Thumb Menu / Detecting Unintentional Thumb Contact:
These capabilities resonated particularly well with our test
users, and many felt strongly that it was natural to bring up amenu near to the thumb while also guarding against
unintended thumb contact. Several users suggested
improving the technique by using the location of the sensed
grip to position the Thumb Menu closer to the thumb.

We ran an informal study with 8 people (3 female, all righthanded, 23-51 years old, mean 37). All participants were
office workers with previous experience on pen-operated
devices with touch. To focus on preliminary user reactions,rather than how the techniques should reveal themselves, theexperimenter demonstrated each technique, after which test
users tried it themselves. Each session lasted 60-90 minutes.

Overall Reactions: On the whole test users were excited by
the system (commenting “it’s like magic” and “this system
is very cool, hopefully someday I can use it.”) Users foundthe palm detection to be the most useful capability, as all had
previously experienced this problem firsthand. The virtual
barrel button was the lowest ranked feature, perhaps because
its only demonstrated use was to turn on / off the Airbrush.

Detecting Unintentional Palm Contact: The sensors
detected many instances of palm contact that would not bepicked up by approaches that require proximity of the pen tip
to the display. However, there were still instances where theuser brushed the screen or touched down lightly (e.g. with apinky finger) that the sensors were not able to detect. Users
were excited about the technique because many had sufferedfalse touch inputs. One user commented he would easily getin the habit of landing with a “heavy” palm to ensure thesensors could always pick up motion. Users also appreciatedthe ability to pinch-to-zoom with the nonpreferred handwhen the palm was already resting on the display.

CONCLUSION: CHALLENGES, LIMITS, & FUTURE WORK

Although the present research makes considerable progresson many issues in sensing for stylus+tablet interaction, anumber of challenges and limitations remain to be addressed:
 The thickness and length of our stylus prototype, as wellas the presence of a tether for power, limit our ability to
deploy it for truly mobile use and to observe a wider rangeof naturally-occurring behaviors with pen and tablet.
 Our current techniques for sensing pen-in-handinteractions require detecting some minimum force
motion-signal threshold on the accelerometer and/or
stylus. With more sophisticated signal-processing

techniques, or by combining the signal from the tablet’s
motion sensors as well, it may be possible to make thesystem more sensitive, but very soft touches likely
represent an inherent challenge for this type of approach.
 Our observations and techniques need to be extended forleft-hand users, to situational impairments such as
mobility (i.e. walking) and one-handed interaction, and ingeneral to a wide variety of other human accessibility
concerns that our system does not yet address adequately.
Nonetheless, we have contributed a number of techniquesthat demonstrate how stylus and tablet sensing allows us to
tailor pen+touch interaction to the context, such as byameliorating unintentional palm contact while writing, yetstill allowing full articulation of intentional touches by thenonpreferred hand. We can also combine these modalities tosupport contextually-appropriate tools, such as the Magnifier
Tool, Drafting Tools (e.g. airbrush), and the Thumb Menu,
all depending on how the user holds the tablet and pen.
A common theme in our techniques is the many ways that
motion sensing, grip sensing, and multi-touch from thetouchscreen can be combined to reinforce one another, bothto avoid false positives as well as to help extract specificsignals that would otherwise be difficult to isolate from asingle sensing modality. Collectively, these techniques
illustrate some of the compelling ways that grip and motion
sensing afford contextual awareness in pen computing, andthereby open up the potential for a rich new space of
expression for tablets using natural pen + touch interaction.
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