Investigating Wrist Deflection Scrolling Techniques for Extended
Reality
Jacqui Fashimpaur

Amy Karlson

Tanya R. Jonker

jacquiwithaq@meta.com
Meta Inc., Reality Labs Research
Redmond, Washington, USAakkarlson@meta.com
Meta Inc., Reality Labs Research
Redmond, Washington, USA

tanya.jonker@meta.com
Meta Inc., Reality Labs Research
Redmond, Washington, USA

Hrvoje Benko

Aakar Gupta

benko@meta.com
Meta Inc., Reality Labs Research
Redmond, Washington, USAaakar.hci@gmail.com
Meta Inc., Reality Labs Research
Redmond, Washington, USA

Figure 1: (a) Flexion and Extension, which is one of the axes of wrist defection. This is the primary input to our scrolling
techniques. (b) An example XR interface that supports scrolling and selection, used in our study to teach participants thescrolling techniques. (c) Two postures in which we evaluated our scrolling techniques, arm-in-front and arm-at-side.

ABSTRACTScrolling in extended reality (XR) is currently performed using
handheld controllers or vision-based arm-in-front gestures, whichhave the limitations of encumbering the user’s hands or requiring a
specifc arm posture, respectively. To address these limitations, weinvestigate freehand, posture-independent scrolling driven by wrist
defection. We propose two novel techniques: Wrist Joystick, whichuses rate control, and Wrist Drag, which uses position control. In
an empirical study of a rapid item acquisition task and a casualbrowsing task, both Wrist Drag and Wrist Joystick performed on
par with a comparable state-of-the-art technique on one of the twotasks. Further, using a relaxed arm-at-side posture, participantsretained their arm-in-front performance for both wrist techniques.
Finally, we analyze behavioral and ergonomic data to provide design insights for wrist defection scrolling. Our results demonstratethat wrist defection provides a promising method for performant

scrolling controls while ofering additional benefts over existing
XR interaction techniques.

CCS CONCEPTS• Human-centered computing → Interaction techniques; Mixed/ augmented reality; Virtual reality.

KEYWORDS
scrolling, wrist defection, freehand, wristband, extended reality,
virtual reality, position control, rate control, user study
ACM Reference Format:
Jacqui Fashimpaur, Amy Karlson, Tanya R. Jonker, Hrvoje Benko, and Aakar
Gupta. 2023. Investigating Wrist Defection Scrolling Techniques for Extended Reality. In Proceedings of the 2023 CHI Conference on Human Factors
in Computing Systems (CHI ’23), April 23–28, 2023, Hamburg, Germany. ACM,
New York, NY, USA, 16 pages. https://doi.org/10.1145/3544548.3580870

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https://doi.org/10.1145/3544548.3580870

INTRODUCTION

Scrolling is an essential form of digital interaction. In XR (an umbrella term for virtual, augmented, and mixed reality), scrollingis often performed using joysticks or touchpads on controllers or
mid-air gestures that are detected by hand tracking via camerason the headset [22, 32, 38]. Common mid-air scrolling techniques
include touching and dragging the virtual content directly (as if itwere a touch-screen) or raycasting towards the UI and holding apinch gesture to drag the content at the point of intersection. TheseCHI ’23, April 23–28, 2023, Hamburg, Germany

techniques can be efective but they each sufer from at least oneof the following problems:(1) Encumbrance. Techniques that require users to carry physicalcontrollers are impractical in some situations (e.g., runningerrands wearing an all-day XR device) and there are tasks
where it is important for the user’s hands not to be occupied(e.g., using XR to assist with assembling something).
(2) Constrained Arm Posture. Sensing capabilities and interaction designs can both introduce constraints on the user’s arm
posture. For example, hand-tracking cameras are sensitive to
occlusion, while techniques that involve raycasting towards
or touching a virtual interface are sensitive to the interface’s
location, distance, and size. Techniques that require a specifc arm posture are limited to contexts where that positionis possible: one may not be able to e.g. hang their arm by
their side when seated or outstretch their arm in a crowded
space. Additionally, techniques that require users to holdtheir arms in front of them can be fatiguing during lengthy
interaction sessions[11, 20], and are socially unacceptable inmany contexts [42].

These issues often present a trade-of for XR interactions: users caneither hold a device and provide input to any interface in any arm
posture, or use freehand interactions and introduce posture constraints. To advance adoption of XR and applications to a broader
range of tasks and contexts, there is a need for XR interaction
techniques that are both freehand and arm-posture independent.
A scrolling technique with these properties could enable users toe.g. navigate a grocery list while shopping, or choose from a few
music options while walking, with ease and minimal interferencewith their primary task.
One promising solution could be to drive interactions with wrist
defection, the angle between one’s hand and their forearm. Thisvalue is independent of one’s arm posture, and wrist-worn opticalsensors have shown to be a practical way to measure it without
encumbering one’s hands [15, 16, 44], so this presents an attractive
and yet unexplored solution for scrolling controls and XR input
in general. In fact, overall, scrolling in extended reality has notreceived much attention in the literature. As such, in the present
work, we explore the design of XR scrolling techniques driven bywrist defection.
We propose two novel scrolling techniques (i.e., Wrist Joystickthat uses rate control and Wrist Drag that uses position control) andassess their viability, relative strengths, and ergonomic properties.
In a user study with 24 participants, we compared the two wrist
techniques with each other and with state-of-the-art analogs (i.e.,Controller Joystick and Arm Drag) on task performance and user
behavior. The wrist techniques were evaluated in two diferent
postures: seated with one’s arm on an armrest and standing with
one’s arm by their side.
The results indicated that neither wrist technique was strictly
better than the other: participants were able to perform a continual browsing task more efciently using Wrist Joystick, whereas
they could perform a rapid target acquisition task more efciently
using Wrist Drag. Both techniques performed comparably to their

Fashimpaur et al.

state-of-the-art counterpart on their better task using an arm-infront posture, and this performance was retained when participants transferred to an arm-at-side posture. These results support
the idea that wrist defection could enable efective freehand andposture-independent scrolling for XR. Furthermore, our analyses of
behavioral and ergonomic metrics ofer design insights for future
development of wrist defection interactions.
Thus this paper contributes:• Two novel wrist defection scrolling techniques, one basedon rate control and another based on position control.
• An investigation comparing the two techniques with eachother and with two state-of-the-art XR scrolling techniques,
which demonstrated the viability of both wrist techniques
while highlighting their relative strengths and weaknesses.
• Design insights for wrist defection interactions based on
behavioral analyses.
Posture-independent wrist defection, sensed by a wristband,
could present a practical solution to achieve fexible freehand XR
input. Our work lays the foundation for this by showing its efcacy
for scrolling interactions and revealing behavior patterns that are
specifc to this form of input.

2

RELATED WORKThis research was informed by prior research in the areas of scrollinginteraction design, freehand input, and wrist angle input. Also of
relevance is literature related to interactions with properties similar
to scrolling, such as position and rate control transfer functions.

2.1

Scrolling Interaction Design

Scrolling behaviour modeling and scrolling technique development
has been an important and well studied topic for computers andhand-held devices [2, 21, 33, 36, 41, 50, 57]. In these literatures, mostcontinuous scrolling techniques use either “rate control” or “position control.” With rate control, the user’s input directly indicatesthe desired scrolling velocity. For example, a list might scroll fasterthe more a joystick is tilted in the corresponding direction. This
type of control can be low-efort in that it allows content to scroll
continuously without additional user movement, but it can makeprecise targeting difcult [6, 27, 48]. It is well suited to isometricdevices with self-centering mechanisms, and sufers signifcant
performance decreases without them [8, 56].
In contrast, position control enables the user to directly control
the scroll position. For example, dragging a fnger across a touch
screen might move scrollable content to a new position whose ofset
is the same as the fnger’s. Mouse scroll wheels and touchpads
also fall into this category. In general, position-controlled scrolling
techniques have been found to provide users with precise control ofscrollable content, but they often require "clutching" [34, 57], where
the user must disengage from position control (such as by lifting
their fnger), reset their position, and re-engage to keep scrollingin the same direction. Touchscreens and touchpads often reduce
the need for clutching by supporting fick interactions, in which
scrollable content behaves like an object with momentum and canbe “thrown” some distance using a quick drag and release [1, 12, 39].

Investigating Wrist Deflection Scrolling Techniques for Extended Reality

Most common scrolling techniques ft into one of these twocategories, but others have been proposed, such as “inertial control,” where the scrollable content behaves as if it has momentum
and is sliding on a surface being tilted by the user [35, 53]. In
extended reality, some commercial controllers have joysticks for
rate-controlled scrolling (e.g., Meta Quest Touch Controllers [38]),
while others have touchpads for position-controlled scrolling (e.g.,
HTC Vive Controllers [22]). These devices encumber the user’shand(s), making them impractical or inconvenient for portable use,
and motivating freehand alternatives.

2.2 Freehand Scrolling
Though several techniques have been proposed for mid-air freehand
pointing and selection [19, 23, 51], or discrete command gesture detection [5, 31], research specifcally investigating freehand scrollingis sparse. Boundless Scroll [47] used a tracking system around a
touchscreen to enable users to continue dragging after their fnger
left the edge of a device, however it specifcally targeted touchscreen devices and does not necessarily extend to XR scrolling.
Many XR devices support freehand interactions using cameras
contained in the headset and computer vision algorithms. A common approach to scrolling with these systems is to use freehand
pointing interaction (i.e., a ray cast out from the user’s hand onto avirtual interface) in combination with a sustained pinch to “grab,”“drag”, and “throw” scrollable content. Such vision-based techniques
are convenient in that they require no additional devices aside froma headset, but they are sensitive to lighting conditions and occlusion. Additionally, they require a user to hold their arm out in frontof them. This is not only conspicuous [42] but also fatiguing [11],with extended use leading to the “gorilla arm efect” [20].
To counter these challenges, some researchers have proposed
methods for freehand arm-at-side input; however, to date, none ofthese have been evaluated for scrolling interaction. Gunslinger [30],for example, used 3D cameras mounted on both thighs to track handposes, and had a vocabulary of gestures for two-handed interaction
with a wall display. WatchTrace [45] used a smartwatch’s gravity
sensor data to detect arm-at-side arm gestures. These techniques,
while useful, were limited to standing, arm-at-side postures (thoughGunslinger supported simultaneous touch interaction). ARPads [4]experimented with multiple arm positions for indirect pointing in
AR, but each position required a diferent 3D camera placement
and had a diferent virtual target plane, as opposed to a single
technique being posture-independent. Gestures involving one’s 3D
hand pose [26] could be detected in any arm posture, but presented
a much harder tracking problem than detecting the angle of thewrist, without necessarily providing any added value for scrolling.
Our work demonstrates that wrist defection is sufcient to drive
efective freehand scrolling.

2.3 Wrist Angle Input
The wrist is a dexterous joint that can rotate on the axis of theforearm (i.e., pronation/supination), on the axis pointing out of thepalm (i.e., radial deviation/ulnar deviation), and on the axis perpendicular to those (i.e., fexion/extension, Fig. 1a). Extensive researchhas demonstrated the expressiveness of wrist angles as a form of
input [12, 16, 18, 35, 40, 49, 52]. Rahman et al. [40], for example,

CHI ’23, April 23–28, 2023, Hamburg, Germany

found that users could comfortably control their fexion/extension
with a precision of roughly 5°. Tsandilas et al. [49] argued that thewrist can be viewed as isotonic around its neutral position andelastic when defected past a certain range.
To capitalize on the fexibility of the wrist, some have proposedusing the reorientation of handheld devices as a proxy for wrist
input. For example, device tilting has been explored for text entry [54], pointing [48, 49, 53], and scrolling [12, 35, 36, 41]. Thesemethods have proved compelling, but they occupied the user’shand. Smartwatches [10, 17] and rings [18] are alternatives for tiltbased interaction using built-in gravity sensors. However, all ofthese tilting techniques rely on an object’s orientation relative toa user’s environment rather than relative to the user’s forearm,which means the user must constrain their orientation. Wrist defection input, as considered in the present research, circumvents
this challenge and allows users to fexibly transition between any
arm posture.
Several sensing techniques have been proposed to detect wrist
defection, including multiple IMUs [55], magnetic sensors [52],stretch sensors [46], and optical sensors [15, 16, 44]. RotoWrist [44]specifcally demonstrated continuous wrist defection estimation
using optical time-of-fight sensors. The same apparatus and approach was used to estimate wrist angles for our techniques. Theseprior works demonstrate the potential of wrist defection sensing
for wristband devices, but did not investigate scrolling input. Fukui
et al’s [13] work compared several arm-in-front scrolling techniquesthat were driven by forearm pronation and supination rather thandefection. Our work investigates fexion-extension wrist angles
for both arm-in-front and arm-at-side postures for extended reality
use cases.

3

PROPOSED TECHNIQUE DESIGNSWe implemented several prototype scrolling techniques, iterating
separately on rate control and position control prototypes until
we had one preferred design of each type (these control types aredescribed in Section 2.1). We chose to use fexion-extension as the
input angle because it allows for a much larger dexterous input
range than radial and ulnar deviation [40, 43].
During our iterative design process, we conducted two qualitative pilot studies. In the frst study, we gathered feedback from fve
participants in order to narrow down our approaches with a few
high-level design decisions. Each participant tried each of eight
diferent wrist-defection scrolling prototypes for several minutes
on a sample list (Fig. 1b). They then ranked them by preference andprovided qualitative feedback. In the second study, we deployed the
top two techniques and collected feedback from four participants todetermine the best gain functions and constant values. We systematically switched the type of gain function or adjusted the value ofa constant, and asked participants whether it had gotten better orworse. This continued until we found locally optimal values, which
we averaged across the four participants for our user study. Herein
we describe the designs of the fnal techniques as well as several
key decisions that were made during the prototyping process. The
specifc constant parameters used in the prototypes are describedin appendix A.

CHI ’23, April 23–28, 2023, Hamburg, Germany

Fashimpaur et al.

Figure 2: (a) Transfer function for the Wrist Joystick technique. (b) A diagram of example actions possible with the Wrist
Drag technique. (i) The user ficks the scrollable content and it starts to slide. (ii) The user interrupts the slide by grabbing thecontent again. (iii) The user drops the content without ficking it. (iv) The user ficks the list again and it slows to a stop on its
own.

3.1 Rate Control: Wrist Joystick
Wrist Joystick uses rate control and is inspired by scrolling witha physical joystick. It works in the following manner: Prior tousing the technique the frst time, the user completes a calibration
routine that determines their comfortable range of wrist fexionand extension, and their neutral wrist angle position. Then whenusing the technique, the user makes a thumb-to-index fnger pinch
gesture to activate scrolling, and releases their pinch to deactivate it.
While scrolling is activated, the content will scroll at a rate related
to the angle of the user’s wrist fexion/extension (Fig. 2a).
While most joysticks have an automatic re-centering mechanism, marking a clear neutral position, there is no such distinct
boundary in wrist motion. Therefore, in Wrist Joystick, there is asmall “neutral zone” around their calibrated neutral wrist angle inwhich the content does not move. Outside of this zone, the wrist
angle is converted to a proportion from the edge of the neutral zone
to the user’s maximum comfortable point of fexion/extension. This
proportion is cubed and the result is used to interpolate between aminimum scrolling speed and a maximum scrolling speed.
3.1.1 Fixed vs Relative Ofset. Wrist Joystick measures the user’s
wrist angle with respect to a calibrated fxed neutral point, so each
wrist defection angle always maps to the same scrolling speed.
Another option would have been to use a relative ofset, where
the neutral point would be reset whenever scrolling was activated.
Participants in our frst pilot study reported that with the relativeofset they would often forget where they had started their pinch
gesture, making it difcult to self-center and locate the slowest
speeds. Participants would also frequently reach the limits of theirwrist fexion/extension and fnd that they had not given themselvesroom to reach the scroll speeds they wanted, adding frustration
when scrolling to a distant target. Therefore, we used the ofset
from a fxed point.
3.1.2 Transfer Function. The transfer function (Fig. 2a) is similar
to the one used for pure rate control pointing by Tsandilas [49],
who observed that “transfer functions that grow rapidly around thezero position ... are sensitive to input precision”. We made similar
observations, but found that adding a neutral angle zone with aspeed of 0 and then interpolating from a higher minimum speed
improved user control for precise scrolling. We theorize that thisis because speeds very close to 0 are not useful, even for precise
scrolling, so adding this discontinuity devotes a wider range ofwrist angles to the moderately slow speeds that users are interested
in.

3.2

Position Control: Wrist Drag

Wrist Drag is our position control technique and is analogous totouch-screen drag and fick interactions [1, 12, 39]. The user begins
a pinch gesture to “grab” scrollable content and then changes the
fexion/extension angle of their wrist to move the content a constantdistance for every degree they have traveled. When the user releases
their pinch, the content stays in its new position. If its speed at
the time of release is higher than a certain threshold, the content
will continue moving as if with momentum, gradually slowing toa stop with simulated friction (Fig. 2b). The friction is a simple
combination of exponential decay and linear decay. In particular,
the content’s scrolling speed at frame n (�� ) is determined by theexpression
�� = ��−1 − Δ� ((���−1 ) + �)
where � and � are constants and Δ� is the time in seconds between
two frames. When the sliding speed falls below a threshold, it
automatically drops to zero. This is used to prevent lists that don’tsmoothly animate between items from advancing after they appear
to be stopped.

4

USER STUDY

Wrist-defection based scrolling techniques such as the ones we’vedeveloped above have not been explored as a method for interface
control for XR, and yet they are promising because they enable
freehand interaction and ofer fexibility in arm position. Thus, toexplore their potential, we conducted a user study towards thefollowing goals: a) Explore potential performance trade-ofs forInvestigating Wrist Deflection Scrolling Techniques for Extended Reality

our freehand, posture-independent techniques when compared tostate-of-the-art controller and hand-tracking based techniques. b)
Determine whether or not the wrist defection techniques perform
well in the arm-at-side posture. c) Assess the relative merits of rate
control and position control for wrist defection input. d) Analyze
wrist scrolling behaviors and ergonomic behaviors to ofer design
insights for future development.

4.1 Apparatus
To detect users’ angles of wrist fexion and extension agnostic ofheadset camera coverage, we used the same approach as RotoWrist[44] (i.e., eight time-of-fight (ToF) IR light modules distributed
around a wristband as in Figure 3a). RotoWrist was found to achievea cross-user median tracking error of 5.9° in fexion/extension. To
detect pinch and release gestures, a pair of electrodes were strapped
to the thumb and index fnger respectively, similar to [25] (Fig. 3a).
We conducted the study in virtual reality, using an Meta Quest 2
for the display [38].

4.2 Participants
Twenty-four right-handed participants were recruited to participate
in the study (i.e., 12 male, 11 female, 1 non-binary, aged 24-54). Outof 5, they reported a median familiarity of 3 with virtual reality
headsets, 4 with joystick controllers, and 1.5 with "mid-air gestureinteractions."

CHI ’23, April 23–28, 2023, Hamburg, Germany

hand, ray, or reticle in VR to avoid distraction and because theother techniques had no visual component. Users were able to grab
and scroll even if their reticle position was outside the boundsof the scrollable interface so they did not need to worry about
pointing in exactly the right place. For all tasks, clicking signalled
the completion of the goal regardless of the reticle position.
4.3.3 Postures. All four techniques were evaluated in an arm-infront posture, with participants seated and their arm resting on anarmrest (Fig. 1c, left). We selected this posture because we wereconcerned that arm fatigue from prolonged arm extension may
impact scrolling behavior over the course of the study duration[11, 20]. We had several variables to balance, so we wanted tominimize the efect of fatigue and enable valid comparisons ofscrolling behaviors under close-to-ideal circumstances. Participants
were instructed to keep their elbows on the armrest throughout
all arm-in-front trials. When using the wrist defection techniques,participants were also advised to keep their palms facing down, toencourage proper fexion and extension movement, but this was
not enforced beyond regular reminders.
Because arm-posture independence is one motivation for wrist
defection interactions, we included a fnal condition evaluating
the wrist techniques in a standing arm-at-side posture (Fig. 1c,right). Arm-at-side posture creates an indirect mapping between
wrist movement and scrolling movement, and so it is possible thatscrolling performance might sufer when the technique is carriedout with one’s arm by their side.

4.3 Scrolling Techniques
We evaluated the two wrist techniques alongside state-of-the-art
rate and position control XR scrolling techniques, which we refer to
as Controller Joystick (Section 4.3.1) and Arm Drag (Section 4.3.2).
These are analogous to Wrist Joystick and Wrist Drag respectively,
so by analyzing the ways in which they difer we hoped to identify
trade-ofs and insights specifc to wrist defection scrolling.
4.3.1 Controller Joystick. The Meta Quest Touch Controller’s thumbstick/joystick is used to drive scrolling. When the joystick is in its
neutral position, the scrollable content does not move. When it isofset from that position, the content’s position changes at a rate
related to the vertical ofset of the joystick. The same minimum
speeds, maximum speeds, and interpolation function as the Wrist
Joystick technique are used (Fig. 2a), with the width of the “neutralzone” always being 0 because the joystick’s auto-centering makes
it easy to return to exactly its neutral position.
4.3.2 Arm Drag. This technique is similar to the one used to scroll
with hand tracking in the Meta Quest 2 [38]. A reticle position isdefned where the Quest’s default hand tracking driven raycast
intersects with the plane of the scrollable interface. When the user
begins pinching, they “grab” the scrollable content at the current
reticle position. Then, any vertical movement of the reticle position “drags” the content with it until the user releases their pinch.
From this point, it has identical ficking and sliding behavior to theWrist Drag technique (Fig. 2b), with the same simulated friction
parameters.
Pinches were detected using the same apparatus as the wrist
techniques, which was more robust to diferent hand poses thanthe vision-based pinch detection. Also, we did not show the user’s

4.4

Scrolling Tasks

Diferent scrolling methods may perform diferently depending on
the nature of the scrolling task. To capture a broader picture of
our techniques’ performance, we considered two task types (Fig.
3b and 3c). The frst task, Reciprocal Selection, emphasized thefast acquisition of a target in a known location. The second task,
Counting, resembled a more casual browsing task in which the userneeds to pay attention to the content as they scroll through it.
Both tasks involved a list interface that was vertically scrollable
and moved smoothly without any snapping. The lists were positioned 2 meters in front of the participant at whatever height theparticipant deemed most comfortable. Both tasks included a "click"gesture to indicate completion. For all freehand techniques thisgesture was a double-pinch (that is, two quick pinch and releasemotions within a short time) and for the Controller Joystick this gesture was pulling the controller’s trigger button. To avoid accidental
scrolling when the user pinches to select (i.e., the "Heisenberg Effect" [3]), a 0.15 second delay was added to all freehand techniques
between the start of pinching and the list’s movement. The dragtechniques would override this delay if the user moved the list morethan 20cm in that time, such as when performing a fick. These
values were determined in our second pilot study.
4.4.1 Reciprocal Selection Task. This task was a variant of theFitts’ reciprocal tapping task that has been used in prior research[21, 50]. Participants were shown a vertically scrollable list of boxes
numbered from 1 to 200, with two white arrows fxed in the center
pointing inward, and a virtual viewport that was 140 centimeterstall (Fig. 3b). The boxes all had the same height and were blue

CHI ’23, April 23–28, 2023, Hamburg, Germany

Fashimpaur et al.

Figure 3: (a) The user study apparatus consisted of a wristband with eight time-of-fight IR light modules pointed towards thehand, and two electrode fnger straps for the thumb and forefnger. (b) The Reciprocal Selection task involved scrolling backand forth between two targets as quickly as possible. Here it is shown with a 30 centimeter target size. (c) The Counting task
involved counting the number of cats that appeared in a list of photos of animals (photos omitted here).
except for one target which was orange. The target number was
also displayed in a box next to the list. To vary the level of precision
required, small (15 centimeters) and large (30 centimeters) target
heights were used.
Participants were instructed to scroll until the target box was
between the central arrows, then perform a click to select the target.
When they selected the target, it turned blue and they were given
a new target. The users could not proceed to the next trial until
they had selected correctly. Within a given trial, the targets would
alternate between 50 and a larger number for 10 total selections (i.e.
“phases”). Each phase consisted of a single scrolling and clicking
task which started with a prompt and ended with a double pinch.
Participants were told to alternate between selecting these twotargets as quickly and accurately as possible. Small (30 centimeter),medium (270 centimeter), and long (960 centimeter) distances wereused. Each block of the Reciprocal Selection task consisted of one
10-phase trial for each possible Target Size and Scroll Distance pair.
4.4.2 Counting Task. This task was inspired by prior research [12]and was designed to simulate the smooth scrolling and cognitive
load of real-world browsing tasks. Participants were shown a gridof 33 rows of 3 photos (Fig. 3c). The set of photos were manually
selected from The Oxford-IIIT Pet Dataset [37]. Most of these photos
were of dogs, but some (anywhere from 6 to 14, chosen randomly)
were of cats. Each list contained a randomly selected subset of dogs
and a randomly selected subset of cats (with the appropriate numberof each), shufed into a random order. Participants were asked toscroll to the bottom of the list and count the number of cats asquickly and accurately as possible. They performed a click gesture
to reveal the list and begin the timing, and clicked again to hide
the list and stop the timer. After the list was hidden, they reported
the number of cats they counted. Each block of the Counting task
consisted of one such trial.

4.5 Design and Procedure
A repeated-measures design with within-subjects factors was used.
The independent variables were Technique (Arm Drag, Wrist Drag,
Wrist Joystick, Controller Joystick) and Task (Reciprocal Selection
and Counting). Within the Reciprocal Selection task, we also varied

Target Size (15 and 30 centimeters) and Scroll Distance (30, 270, and960 centimeters). For the wrist techniques, we included a second
posture condition for a total of two Postures (arm-in-front and armat-side).
The study consisted of four back-to-back sessions with brief (i.e.,less than fve minute) breaks in between, lasting approximately
two hours total. Each session was dedicated to a single scrolling
technique. At the start of a session, participants could practice withthe technique for as long as they wanted, and they completed one
practice trial before their frst block of each task. After all arm-infront blocks in a session, participants completed a qualitative survey
about the technique. For the wrist techniques they completed asecond survey after the arm-at-side blocks. After all four sessions,participants completed a fnal survey comparing the Techniques,
Tasks, and Postures.
Across participants we counterbalanced the presentation of Technique as well as the order of the 6 Size x Distance pairs in each blockof the Reciprocal Scrolling task. We did not counterbalance Task order; instead we always presented 2 blocks of the Reciprocal Scrollingtask followed by 3 blocks of the Counting task. We also did notcounterbalance Posture for the wrist techniques; participants frst
completed all arm-in-front trials and a survey about them, then theytransitioned to the arm-at-side posture and completed 1 additional
block of the Reciprocal Scrolling task, 3 blocks of the Counting task,
and an additional survey. This was done so that all four techniques
could be compared in the arm-in-front posture without any learning
efects from arm-at-side trials, since some techniques did not havethis condition. Each Task x Posture combination was considered
independently, as our goal was not to directly compare these witheach other but instead to see how our techniques performed in
multiple contexts.
Thus the fnal experiment design was:
• Arm-in-Front, Reciprocal Selection: 4 Techniques x 2
Blocks x 3 Distances x 2 Sizes x 10 Phases• Arm-in-Front, Counting: 4 Techniques x 3 Blocks• Arm-at-Side, Reciprocal Selection: 2 Techniques x 1 Blockx 3 Distances x 2 Sizes x 10 Phases• Arm-at-Side, Counting: 2 Techniques x 3 Blocks

Investigating Wrist Deflection Scrolling Techniques for Extended Reality

CHI ’23, April 23–28, 2023, Hamburg, Germany

Figure 4: Results for the Reciprocal Selection task. Error bars represent 95% CI, * denotes a signifcant diference. (a) Mean error
rate for each technique and posture. (b) Mean scroll times by technique, posture, and target distance. (c) Subjective scores for
the Reciprocal Selection task.

4.6 Measures
The primary metric for the Reciprocal Selection task was scroll
time, which was measured as the duration starting from the frst
movement in a phase until the start of the correct click gesture.
The primary metric for the Counting task was scroll time, which
was measured starting from the moment the list of photos was
revealed until the start of the click gesture indicating completion.
We also report on the percentage of errors, subjective scores, andother metrics such as total wrist movement to help us understanduser behaviors.

5 RESULTS
We frst discuss task performance and subjective scores for the
Reciprocal Selection task followed by the Counting task. We thenpresent participants’ overall preference rankings. For readability,
all statistics and some results are provided in appendix A. Tables
2, 3, and 4 contain the results of our analyses on error rates, taskcompletion time, and subjective scores, respectively.

5.1 Reciprocal Selection Task
Overall, Wrist Drag performed better than Wrist Joystick at thistask, having consistently faster scroll times and occasionally lower
error rates. Wrist Drag’s arm-in-front performance was also comparable with Arm Drag’s. However Controller Joystick, which enablesprecise fnger-level movements, generally outperformed all othertechniques and was reported to be the least physically and mentally
demanding. Looking at the mean scroll times in the arm-at-side
posture, both wrist techniques retain their scroll time performancefrom the arm-in-front posture.
Note that arm-at-side trials may have benefted from learning
efects, since they always took place after arm-in-front trials. For
this reason we avoid direct analysis across postures and observe
only that performance was retained: it did not noticeably sufer
when users transitioned to an indirect arm-at-side posture, which

is promising evidence that wrist defection techniques can support
posture-independent interaction.
5.1.1 Errors & Outliers. In the arm-in-front posture, the rate oferroneous phases where an incorrect target was selected was 1.5%of all phases (Fig. 4a). There were no signifcant diferences between
diferent techniques. In the arm-at-side posture, this rate was 2.7%,
and the error rate for Wrist Drag was signifcantly lower than Wrist
Joystick, although both rates were fairly low. For the scroll time
analysis, we removed these erroneous phases. We further removed
outliers outside three standard deviations which constituted 2.7%of all phases in the arm-in-front posture and 1.3% in the arm-at-side
posture.
5.1.2 Scroll Time. For the arm-in-front posture, a 4-way RM-ANOVA
was conducted to analyze the mean task completion time for theTechnique, Block, Distance, and Size variables (Fig. 4b and 9). Mainefects were found for all four variables. The efects of Distance,
Size, and Block were along expected lines given Fitts’ Law andlearning efects, and are not discussed since our focus is on the effects relating to Technique. 2-way interactions were found between� ��ℎ����� × �������� and � ��ℎ����� × ����. No 3-way or 4-way
efects were found, nor were any other 2-way efects found.
We further analyzed simple main efects of � ��ℎ����� for each�������� and ���� level and conducted pairwise comparisons with
Bonferroni corrections where signifcant simple main efects were
found. The results revealed that Controller Joystick had signifcantly lower scroll times than the other three techniques for the
270 and 960 distances. Arm Drag and Wrist Drag mostly had similar performance to each other, with Arm Drag having a higher
scroll time for only the 270 distance. Wrist Joystick had signifcantly higher scroll times than the other three techniques for the
30 and 960 distances and higher scroll time than Wrist Drag andController Joystick for the 270 distance. For both target sizes, themain efects of � ��ℎ����� were similar to those for the 960 distance:
Wrist Joystick had signifcantly higher scroll times than the other

CHI ’23, April 23–28, 2023, Hamburg, Germany

Fashimpaur et al.

Figure 5: (a) Mean scroll times for the Counting task in terms of technique and posture (error bars represent 95% CI, * denotes asignifcant diference). (b) Subjective scores for the Counting task. (c) Subjective rankings of the four scrolling techniques forthe arm-in-front posture and the two wrist scrolling techniques for the arm-at-side posture. Some participants expressed no
preference in the arm-at-side posture; we represent them with gray.
three techniques and Controller Joystick had signifcantly lower
scroll times than the other techniques.
Our results for the arm-at-side posture were very similar to armin-front. We conducted a 3-way RM-ANOVA for mean scroll time
for the Technique, Distance, and Size variables (Fig. 4b and 9a) (there
was only 1 block for arm-at-side), and found main efects for all
three variables, with the efects of Size and Distance being along
expected lines. No 2-way or 3-way efects were found, but pairwise
comparisons with Bonferroni adjustments showed that the Wrist
Drag technique once again had a signifcantly lower scroll timethan the Wrist Joystick technique.
5.1.3 Subjective Scores. For the arm-in-front posture, a non-parametricFriedman ANOVA test found a signifcant efect of Technique on the�ℎ������ ������ and ������ ������ (Fig. 4c). Pairwise Wilcoxon
tests showed that Controller Joystick had signifcantly lower physical and mental demand than the other three techniques. No othersignifcant efects were found. For the arm-at-side posture, Wilcoxon
signed-rank tests found no signifcant efects of Technique on any
subjective measure.

5.2 Counting Task
This task showed a reversal from the previous one: Wrist Joystick
was faster than Wrist Drag in both postures. It also had lower
physical demand and higher satisfaction in the arm-at-side posture.
This could be because with Wrist Joystick, the user could simply
keep their wrist still to scroll smoothly, while Wrist Drag required
constant movement that could have cost energy or focus. Wrist
Joystick also had comparable performance with both state-of-theart techniques. Once again, both wrist techniques retained theirarm-in-front performance in the arm-at-side posture.
5.2.1 Task Completion Time. A 1-way RM-ANOVA found a signifcant efect of Technique on task completion time for the armin-front posture (Fig. 5a). Pairwise comparisons with Bonferroni
adjustments showed that Wrist Drag took signifcantly longer thanWrist Joystick and Controller Joystick. For the arm-at-side posture,
Wrist Drag again had signifcantly longer scroll times than Wrist
Joystick.
5.2.2 Subjective Scores. Non-parametric Friedman tests showedsignifcant efects of Technique on Physical Demand and Satisfaction for the arm-in-front posture (Fig. 5b). Pairwise Wilcoxon tests
showed that participants reported that the Wrist Drag technique
had signifcantly higher physical demand and signifcantly lower
satisfaction than Controller Joystick. For arm-at-side, Wrist Drag
had signifcantly higher physical demand and lower satisfaction
than Wrist Joystick. No other signifcant efects were found.

5.3

Ranking Preferences

In the fnal survey, participants were asked to rank all four scrolling
techniques in order of their preference (Fig. 5c). Participants had
no strong agreement about which techniques they most preferred.
The Controller Joystick technique looks somewhat more preferred(e.g., "Controller joystick was familiar therefore easy to do”, P4), andArm Drag seems to be least preferred. When asked which wrist
technique they preferred for arm-at-side scrolling, 14 participants
said Wrist Joystick, 7 said Wrist Drag, and 3 said they were similar.
Both wrist techniques were thought to be more fun, intuitive, andeasy than the other by diferent participants (e.g., “I really enjoyed
the wrist drag because it was less work to put in, yet it had a familiar
feeling to swiping on a device”, P1 and “I loved how easily you canrev up and slow down with wrist joystick. It made it feel like I wascompletely in control.”, P20).

6ANALYZING AND IMPROVING WRISTTECHNIQUESThe performance results show that both wrist scrolling techniques
can perform comparably with an analogous state-of-the-art technique for a particular task, and they can retain that performanceeven in the arm-at-side posture. These are encouraging results withrespect to the viability of freehand, posture-independent scrolling

Investigating Wrist Deflection Scrolling Techniques for Extended Reality

CHI ’23, April 23–28, 2023, Hamburg, Germany

Figure 6: Various behavior metrics from the user study (error bars represent 95% CI). (a) Number of total drag and fick gestures
for Arm Drag and Wrist Drag. (b) Proportion of time spent going backwards (that is, opposite the direction from the starting
point to the target) in the Reciprocal Selection task for Controller Joystick and Wrist Joystick. (c) Total amount of wrist
movement for Wrist Drag and Wrist Joystick in both tasks.
using wrist defection. However, the results also show that Wrist
Drag does not perform as well in the Counting task and Wrist
Joystick does not perform as well on the Reciprocal Selection task.
Therefore, in this section, we analyze scrolling behaviors from thefollowing three perspectives to gain insights on how to improve
wrist defection scrolling: a) Wrist Joystick vs Controller Joystick
behavior, b) Wrist Drag vs Arm Drag behavior, c) Wrist Drag andWrist Joystick ergonomics.

6.1 Wrist Joystick Compared with Controller
Joystick
There was a signifcant gap in performance between Wrist Joystick and Controller Joystick for the Reciprocal Selection task. Thiswas despite both techniques using the same gain function with thesame range of speeds. One reason for this could be the Controller
Joystick’s high input precision and accuracy, but rate control techniques are not necessarily very sensitive to input precision [49].
Another reason could be that participants had less intuitive controlof Wrist Joystick (e.g., "I would defnitely just prefer the controller
joystick over the wrist joystick as it is less work and easier to control.",P21). We analyzed the time spent traveling in the wrong direction
for both techniques and found that participants spent a signifcantly
larger chunk of each trial traveling in the wrong direction with
Wrist Joystick. This could be due to mistakes during the initial wrist
defection or correcting overshooting mistakes (Fig. 6b).
To learn more about the diference in user behavior with thesetechniques, we compared the amount of time spent with the joystickand the wrist at each angle of defection (Fig. 7). With the controller,
participants primarily made use of the most extreme angles andangles very close to zero, with almost no time spent in between. In
contrast, Wrist Joystick shows a much more even spread of input
values with diferent peaks depending on the target distance. With
this technique, participants seem to have spent more time gradually
accelerating and decelerating.

Part of this could be due to the extremely minimal movement
required to fully defect the Controller Joystick. But another potential reason is the lack of feedback from the Wrist Joystick about thecurrent angle of defection. Physical joysticks have an elastic force
pulling them back towards the center, and this has been shown
to improve the performance of rate control interactions [8, 56].
Without this, participants may have been less confdent quickly
changing their wrist angle, instead relying on their observation of
the list’s movement.
One potential solution to improve Wrist Joystick is to generate
haptic feedback within the wristband based on the user’s amountof defection to increase their intuition of the input space. Anothersolution would be to reduce the need for precise continuous control
in the frst place. This could be done by adding support for a discrete
gesture to "nudge" the scrollable content by a fxed distance (likethe height of one list item). Users could then use this gesture when
making short movements or fnal corrections without ever needing
to quickly access slow scroll speeds.

6.2

Wrist Drag Compared with Arm Drag

Wrist Drag had similar task completion times to Arm Drag, despite it having a much more limited input space, which suggeststhat the additional degrees of freedom supported by mid-air hand
tracking do not necessarily improve performance for this type of
one-dimensional scrolling. The two position control techniques also
showed similar movement patterns in the Reciprocal Selection task,
including similar numbers of drag/fick actions (Fig. 6a). However,in the Counting task, where it was not very practical to fick the list,
participants used signifcantly more drag/fick actions with Wrist
Drag than with Arm Drag. It appears that, when scrolling slowly,
participants make use of more of their input range to reduce theneed for clutching. In such cases where extended slow browsing
is required, it could then be useful to increase Wrist Drag’s input
range however possible, such as with a curved wrist defection path

CHI ’23, April 23–28, 2023, Hamburg, Germany

Fashimpaur et al.

Figure 7: Mean percentages of time spent with the wrist or joystick at diferent defection angles for three scrolling techniquesin the Reciprocal Selection task. In order to better show patterns, angles are expressed as a percentage of the user’s total range
in that direction (for the wrist techniques this was calibrated whenever a new wrist condition was started and posture waschanged). Note that the Controller Joystick graphs have a signifcantly larger x-axis scale than those of the wrist techniques.
(see Section 6.3.2) or even a complete circle that removes the needfor clutching, similar to an iPod’s scroll wheel [33, 50].

6.3 Wrist Ergonomics
Wrist defection is a valuable form of input because it can be freehand and posture-independent. We investigate multiple ergonomic
metrics here with the goal of optimizing our wrist techniques aswell as other wrist defection-based interactions.
6.3.1 Amount of Wrist Movement. We measured the total wrist
movement (i.e., cumulative degrees rotated) for both wrist techniques across both tasks (Fig. 6c). This revealed that participants
moved their wrist signifcantly more with Wrist Drag than with
Wrist Joystick in both tasks, with the diference increasing overlonger scroll durations. In the Counting task, where fick gestures
were not suitable, participants moved an average of over 7 times
more with Wrist Drag. As P11 said, "for long scrolling it was lessintense on my wrist to do the wrist joystick". The need for constant
movement in some situations is an inherent drawback of position
control, and constant fexion/extension movement can be particularly uncomfortable [7, 24]. One potential improvement, then,could be to use a hybrid of position and rate control such as theones proposed for pointing by Casiez et al. [9] and Tsandilas etal. [49], where the content can scroll autonomously under certain
circumstances.
6.3.2 Time Spent Deflected. We measured the total percentage oftime participants spent with their wrist at every angle of defection
for both wrist techniques. Figure 7 shows these distributions for
the Reciprocal Selection task and reveals very diferent patterns
for the two techniques. Because Wrist Drag was based on relative
movement, participants had some freedom as to their absolute wrist
angle. For all distances they generally seemed to prefer keeping
their wrist extended (such as after a fick upwards) over keeping

it fexed. With Wrist Joystick, they did not have as much freedom
and spent a large portion of time at certain defection angles while
the list scrolled to their target. This may have been uncomfortable,
especially while holding a thumb-to-fnger pinch [7, 24]. P18 said
"my wrist slightly fatigued in the fully fexed and extended positions
on the longer scrolls with the pinching". One way to mitigate this issue
could be to provide a way for the user to scroll without sustained
pinching (such as using a single pinch and release to toggle thescroll mode instead).

6.3.3 Wrist Movement Path. We created density plots for each participant to show the wrist defection positions that they occupied
during any trial with a wrist technique, including their radial andulnar deviation (a subset is in Figure 8, however all 24 are in Figure
10 in the appendix). We observed that several participants moved
their wrist along a path that was fairly consistent but not exemplaryof perfect fexion/extension (as they were instructed to do). Their
movement was often tilted diagonally (as with P1) or followed acurved path (as with P15). Several participants commented thatthey would have rather angled their arm ("it would be a little better
if you accounted for the fact that some people’s wrists naturally facediagonally outward rather than straight out when standing naturally
and its a bit hard to keep your wrists straight facing.", P20). Thissuggests that there is an opportunity for personalization, where if
an algorithm could explicitly or implicitly adapt to a participant’s
preferred path of motion, a larger range of input values could be captured in their comfort zone. As there are similar movement shapes
across sessions and postures for the same participant (though sometimes translated after recalibration, as with P23), there is thus thepotential for reusable, personalized models.

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CHI ’23, April 23–28, 2023, Hamburg, Germany

Figure 8: Density plots of the wrist angles of four participants (all tasks and postures, both wrist techniques). The graph’s axes
are analogous to the motion of the right wrist when viewed from a frst-person perspective. The ideal behavior is a perfectvertical line indicating that the user’s hand only moves along fexion-extension without any deviation, but many participants
demonstrated tilted or curved shapes instead.

7 DISCUSSION
Our study is the frst in-depth evaluation of scrolling techniques
based on wrist defection angles. This kind of input is distinctive
because it is freehand but defned relative to the user’s arm rather
than the world (as with device tilting) or an interface (as withray casting). This approach gives the user the fexibility to control
any interface in any arm posture, which would reduce friction in
many extended reality scenarios. Our results demonstrate that wrist
defection is an efective input modality for XR scrolling in botharm-in-front and arm-at-side postures.
Though our wrist techniques did not match the physical Controller Joystick in terms of participant preference or reciprocal
selection speed, they may be a desirable alternative to vision-based
ray casting in situations requiring freehand interaction. In both of
our study’s tasks, one wrist technique performed comparably to
Arm Drag in an arm-in-front posture, and both techniques retained
their task performance in an arm-at-side posture which Arm Dragcannot support. This added fexibility could enable users to perform quick selections or extended browsing without the social or
ergonomic costs associated with holding their arm out in front ofthem [11, 20, 42], or the friction of changing their arm posture atall.
Besides verifying the feasibility of wrist defection scrolling, ourstudy compared two wrist scrolling techniques (i.e., Wrist Joystickand Wrist Drag, that use rate control and position control respectively) for two kinds of scrolling tasks. In the Reciprocal Selectiontask, which involved rapid and precise scrolling, Wrist Drag hadsignifcantly better performance than Wrist Joystick. But in theCounting task, that involved slow sustained scrolling, Wrist Joystick
not only outperformed Wrist Drag but also required signifcantly
less wrist movement.
Our fndings are generally consistent with previous researchcomparing these control orders in other contexts [6, 14, 27, 35,48], but we gain additional insight about wrist defection input inparticular through examining behavioral metrics and comparing
with analogous state-of-the-art techniques. Both wrist techniques
were very similar to their state-of-the-art counterpart in the task
for which they were strongest. But the ways in which they diferedfrom their analog in their weakest task indicate potential paths toimprove performance. For example, participants using the Wrist

Joystick seemed to be more cautious changing their wrist angle
than they were with the Controller Joystick, and had signifcantly
slower scroll times in the Reciprocal Selection task. Wrist Joystick
may improve with additional feedback (such as haptics) to the user
about their current wrist defection state. Finally, by analyzing
wrist movement over time, we identifed several ways in which theergonomics of wrist defection impact users’ preferred movements.
These fndings can inform future development of wrist defection
interactions.

7.1

Application for Extended Reality

We envision wrist defection scrolling as a practical interaction technique for virtual, augmented, and mixed reality devices. Though
our study was conducted in a purely virtual environment, we expect
our fndings would mostly extend to AR and MR scenarios as well.
The diferences that would arise, such as increased environmental
distractions and users’ ability to see their own hands, present interesting research questions but do not negate our evidence that users
can learn and apply wrist movement alone for efective interaction
in new computing environments.
A practical XR system would also need to support more interactions than just scrolling and selection. Because both of our proposed
techniques require a sustained pinch gesture to activate scrolling,
they could easily be implemented alongside interactions that are
based only on movement and quick pinches, such as previously proposed methods of pointing, text entry, and discrete gestures using
wrist defection [15, 16, 44], though these haven’t been evaluatedin XR. Our techniques could also complement a vision-based hand
tracking system, such as by using hand tracking for complex tasks
like 3D object manipulation, and using wrist defection scrollingwhen it would be more convenient (e.g., a quick selection from a list
while waiting in line) or comfortable and discreet (e.g., browsing a
news feed on the bus).

7.2

Limitations and Future Work

Our study explored a range of scrolling task parameters and techniques, but there remains room for more detailed investigationand optimization of wrist defection scrolling in future work. Somepotential improvements to each technique are proposed in Section

CHI ’23, April 23–28, 2023, Hamburg, Germany

6. Further research could also quantitatively optimize transfer functions through approaches like those in [1, 29, 39], or augment thesetechniques with other technology like gaze tracking [28], which isfeasible in an XR headset. Comparisons with more scrolling techniques (e.g., mobile devices) and evaluations for more use cases(e.g., scrolling in two dimensions, scrolling with lists that snap into
place, scrolling while walking, or scrolling in conjunction withother interactions) could provide additional insights.
One important factor that we did not measure in this work iseach technique’s impact on fatigue and discomfort over time. We
predict that use of the wrist scrolling techniques in an arm-at-side
posture would result in lower fatigue than extended use of midair
interactions [11, 20], and in Section 6 we identifed potential sourcesof discomfort for each wrist technique. It would be valuable to verify
and expand on these ideas through a user study with longer sessions
and no arm rest.
This work also did not investigate the impact of sensing accuracy. There have been several proposed methods for measuring
a person’s wrist defection [15, 16, 44, 46, 52, 55], and our wrist
scrolling techniques could be implemented with any of them. It’s
possible that more accurate wrist angle input could improve performance with our techniques or enable the same performance withless wrist movement. It would be useful to evaluate our techniques’
performance with diferent kinds of sensing hardware and withdiferent levels of accuracy, to get a clearer idea of how afordable,
comfortable, and usable a realistic product could be.

8 CONCLUSION
In this paper, we presented two scrolling techniques for extended
reality that are driven by wrist defection gestures. Wrist defection
input is not only practical to sense with a wristband, but can be
simultaneously freehand and arm posture-independent, creating
lower friction than existing XR input methods. In a user study
with 24 participants, we confrmed the viability of both techniquesin multiple arm postures and showed their relative strengths andweaknesses. By comparing ergonomic and behavioral metrics withstate-of-the-art analogs, we provided design insights specifc towrist-defection input. This work lays the foundation for further
research into this promising form of XR interaction.

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A

APPENDIXCHI ’23, April 23–28, 2023, Hamburg, Germany

Fashimpaur et al.

Constant

Reciprocal Selection Task Counting Task

Joystick Max Speed (cm/s)
Joystick Min Speed (cm/s)
Wrist Drag Rate (cm/degree)
Exponential Friction Constant �Linear Friction Constant �
Minimum Flick Speed (cm/s)
Minimum Slide Speed (cm/s)
Freehand Scrolling Activation Delay (s)

350
30
1.75
0.8
120
90
10
0.15

160
30
1.5
0.9
120
90
2
0.15

Table 1: The constant parameters used in the study. In some cases they difer between tasks, the way diferent interfaces often
set their own scroll rates. Values for both tasks were determined in our second qualitative pilot study.

Front
Reciprocal
SelectionSide

ANOVA on Technique� (2.332, 53.627) = 1.169
� > 0.05, � 2 = 0.048
� (1, 23) = 6.432
� < 0.05, � 2 = 0.219

Table 2: The results of our analysis on error rate in the Reciprocal Selection task.

Figure 9: Additional results for the Reciprocal Selection task. Error bars represent 95% CI, * denotes a signifcant diference. (a)Mean scroll times by technique, posture, and target size. (b) Mean scroll times by technique and block.

Investigating Wrist Deflection Scrolling Techniques for Extended Reality

Efect
Techniqe
Block
Distance

Arm-in-Front

Reciprocal Selection Task

Size
Techniqe ×
Block

Techniqe ×
Distance

Techniqe ×
SizeDistance
Size

Front

Techniqe ×
Distance
Techniqe ×
Size
Techniqe

Side

Counting Task

Arm-at-Side

Techniqe

Techniqe

CHI ’23, April 23–28, 2023, Hamburg, Germany

ANO VA on Scroll Time 1-way ANOVA for Simple Main Efects
Pairwise Results� (3, 60) = 32.039
� < 0.001, � 2 = 0.616
NA due to interaction efects� (1, 20) = 41.478
� < 0.001, � 2 = 0.675[Skip]
� (1.265, 25.299) = 1012.655
� < 0.001, � 2 = 0.981
NA due to interaction efects
� (1.000, 20.000) = 182.530
� < 0.001, � 2 = 0.901
NA due to interaction efects
� (1.981, 39.621) = 1.694
� > 0.05, � 2 = 0.078
D = 30: � (1.681, 38.660) = 17.507
WJ > AD, CJ, WD
� < 0.001, � 2 = 0.432(� < 0.05 for these)� (3.899, 77.987) = 10.819
D = 270: � (3, 69) = 30.464 CJ < AD, WD, WJ; WD < AD, WJ
� < 0.001, � 2 = 0.351
� < 0.001, � 2 = 0.570(� < 0.05 for these)
D = 960: � (3, 69) = 27.373 WJ > AD, CJ, WD; CJ < AD, WD
� < 0.001, � 2 = 0.534(� < 0.05 for these)
S = 15: � (3, 69) = 39.873 WJ > AD, CJ, WD; CJ < AD, WD
� (2.373, 47.453) = 7.332
� < 0.001, � 2 = 0.634(� < 0.05 for these)2
� < 0.005, � = 0.268
S = 30: � (3, 69) = 29.513 WJ > AD, CJ, WD; CJ < AD, WD
� < 0.001, � 2 = 0.562(� < 0.05 for these)� (1, 23) = 7.653
WD < WJ� < 0.05, � 2 = 0.250
NA� (1.384, 31.829) = 611.993[Skip][Skip]
� < 0.001, � 2 = 0.964
NA[Skip]
� (1, 23) = 37.886
� < 0.001, � 2 = 0.622
� (1.693, 38.936) = 1.084
� > 0.05, � 2 = 0.045
� (1, 23) = 1.223
� > 0.05, � 2 = 0.050
NAWD > CJ, WJ
� (2.069, 47.592) = 5.734
NA� < 0.005, � 2 = 0.200(� < 0.05 for these)� (1, 23) = 8.227
� < 0.01, � 2 = 0.263

WD > WJ(� < 0.05 for these)

Table 3: The results of our ANOVA analysis on task completion time. D = Distance, S = Target Size, CJ = Controller Joystick,
WJ = Wrist Joystick, AD = Arm Drag, WD = Wrist Drag. Signifcant stats are bolded. For a signifcant 2-way interaction efect,
multiple 1-way ANOVA tests were conducted for simple main efects. Greenhouse Geisser correction was applied wherever
sphericity was violated. Posthoc pairwise comparisons included Bonferroni adjustments. [Skip] denotes that we do not include
posthoc analyses for Block, Distance or Size main efects, since those efects were along expected lines and our focus was onefects relating to Technique.

Front
Reciprocal
Selection
Side
Front
Counting
Side

Mental Demand (MD)MD Pairwise Physical Demand (PD)PD Pairwise
Satisfaction (S) S Pairwise
� 2 (23, 3) = 14.965 CJ < AD, WD, WJ
� 2 (23, 3) = 15.039 CJ < AD, WD, WJ
� 2 (23, 3) = 7.645
� < 0.005
� < 0.005
� > 0.05
� 2 (23, 1) = 0.077
� 2 (23, 1) = 2.250
� 2 (23, 1) = 0.000
� > 0.05
� > 0.05
� > 0.05
� 2 (23, 3) = 13.135
WD > CJ � 2 (23, 3) = 17.262
WD < CJ� 2 (23, 3) = 6.676
� > 0.05
� < 0.005
� < 0.005
� 2 (23, 1) = 1.143
� 2 (23, 1) = 4.765
WJ < WD� 2 (23, 1) = 9.000 WJ > WD
� > 0.05
� < 0.05
� < 0.005

Table 4: The results of our Friedman test analysis on subjective scores. Pairwise comparisons were done using Wilcoxon tests.

CHI ’23, April 23–28, 2023, Hamburg, Germany

Fashimpaur et al.

Figure 10: All 24 participants’ density plots for 2D wrist angles across all tasks and postures with both wrist defection techniques(multiple sessions with diferent calibrations). The graph’s axes are analogous to the motion of the right wrist when viewed
from a frst-person perspective (i.e., down and up are fexion and extension respectively, left and right and radial and ulnar
deviation). The ideal behavior is a perfect vertical line indicating that the user’s hand only moves along fexion-extension
without any deviation, but many participants demonstrated curved or tilted paths instead.