Understanding One Handed Use of Mobile Devices
`
`Amy K. Karlson
`Human-Computer Interaction Lab
`Department of Computer Science
`A.V. Williams Building
`University of Maryland, College Park, MD 20742
`Phone: (301) 405-2662 Fax: (301) 405-6707
`akk@cs.umd.edu
`
`Benjamin B. Bederson
`Human-Computer Interaction Lab
`Department of Computer Science
`A.V. Williams Building
`University of Maryland, College Park, MD 20742
`Phone: (301) 405-2764 Fax: (301) 405-6707
`bederson@cs.umd.edu
`
`Jose L. Contreras-Vidal
`Cognitive-Motor Behavior Laboratory
`Department of Kinesiology
`Health and Human Performance Building
`University of Maryland, College Park, MD 20742
`Phone: (301) 405-2495 Fax: (301) 405-6707
`pepeum@umd.edu
`
`Karlson, A., Bederson, B. B. (2007) Understanding One
`Handed Use of Mobile Devices. Lumsden, Jo (Ed.), Handbook
`of Research on User Interface Design and Evaluation for Mobile
`Technology, Idea Group Reference, 86-101.
`
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`Petitioners Samsung and Sony Ex-1034, 0001
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`Understanding One Handed Use of Mobile Devices
`
`ABSTRACT
`
`Mobile phones are poised to be the world's most pervasive technology, already outnumbering
`land lines, personal computers and even people in some counties! Unfortunately, solutions to
`address the usability challenges of using devices on the move have not progressed as quickly as
`the technology or user distribution. Our work specifically considers situations in which a mobile
`user may have only a single hand available to operate a device. To both motivate and offer
`recommendations for one-handed mobile design, we have conducted three foundational studies:
`a field study to capture how users currently operate devices; a survey to record user preference
`for the number of hands used for a variety of mobile tasks, and an empirical evaluation to
`understand how device size, interaction location, and movement direction influence thumb
`agility. In this chapter we describe these studies, their results, and implications for mobile device
`design.
`
`INTRODUCTION
`
`The handheld market is growing at a tremendous rate; the technology is advancing rapidly and
`experts project that annual mobile phone sales will top 1 billion by 2009 (Pittet et al., 2005). To
`meet customer demand for portability and style, device manufacturers continually introduce
`smaller, sleeker profiles to the market. Yet advances in battery power, processing speed and
`memory allow these devices to come equipped with increasing numbers of functions, features,
`and applications. Unfortunately these divergent trends are at direct odds with usability: richer
`content accessed via shrinking input and output channels simply makes devices harder to use.
`The unique requirements for mobile computing only compound the problem, since mobile use
`scenarios can involve to unstable environments, eyes-free interaction, competition for attention
`resources, and varying hand availability (Pascoe, Ryan, & Mores, 2000). While each of these
`constraints requires attention in design, we are currently interested in issues of usability when a
`user only has only one hand available to operate a mobile device.
`
`Devices that accommodate single-handed interaction can offer a significant benefit to users by
`freeing a hand for the host of physical and attentional demands common to mobile activities. But
`there is little evidence that current devices are designed with this goal in mind. Small, light
`phones that are easy to control with one hand are unfriendly to thumbs due to small buttons and
`crowded keypads. Larger devices are not only harder to manage with a single hand, they tend to
`feature more (rather than larger) buttons, as well as stylus-based touchscreens whose rich
`interface designs maximize information content, but offer targets too small, and/or too distant,
`for effective thumb interaction.
`
`While it may seem obvious which features inhibit single-handed use, there has been relatively
`little systematic study of enabling technologies and interaction techniques. Most commercial and
`research efforts in one-handed device interaction have focused primarily on either a specific
`technology or task. For example, accelerometers have been explored to support tilt as a general
`input channel for handheld devices (Dong, Watters, & Duffy, 2005; Hinckley, Pierce, Sinclair, &
`Horvitz, 2000; Rekimoto, 1996), while media control (Apple, 2006; Pirhonen, Brewster, &
`Holguin, 2002) and text entry (Wigdor & Balakrishnan, 2003) have been popular tasks to
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`consider for one-handed device operation. But in the varied landscape of mobile devices and
`applications, one-handed design solutions must ultimately extend to a wide range of forms and
`functions. We began our investigation of this problem by looking at the fundamental human
`factors involved in operating a device with a single hand.
`
`In this chapter, we report on three studies conducted to understand different aspects of one-
`handed mobile design requirements. We first ran a field study to capture the extent to which
`single-handed use is currently showing up “in the wild”. Second, we polled users directly to
`record personal accounts of current and preferred device usage patterns. The results from these
`studies help motivate one-handed interface research, and offer insight into the devices and tasks
`for which one-handed techniques would be most welcomed. Finally, we performed an empirical
`evaluation of thumb tap speed to understand how device size, target location, and movement
`direction influence performance. From these results we suggest hardware-independent design
`guidelines for the placement of interaction objects. Together our findings offer foundational
`knowledge in user behavior, preference, and motor movement for future research in single-
`handed mobile design.
`
`BACKGROUND
`
`The physical and attentional demands of mobile device use was perhaps first reported for
`fieldworkers (Kristoffersen & Ljungberg, 1999; Pascoe, Ryan, & Mores, 2000), from which
`design recommendations for minimal-attention and one-handed touchscreen interface designs
`emerged (Pascoe et al., 2000). Though well suited to the directed tasks of fieldwork, the
`guidelines do not generalize to the varied and complex personal information management tasks
`of today’s average user. Research of the effects that mobility has on attention and user
`performance continues (Oulasvirta, Tamminen, Roto, & Kuorelahti, 2005), as well as how these
`factors can be replicated for laboratory study (Barnard, Yi, Jacko, & Sears, 2005).
`
`Several approaches for one-handed device interaction have been proposed. Limited gestures sets
`have been explored for mobile application control with both the thumb (Apple, 2006; Karlson,
`Bederson, & SanGiovanni, 2005; Pascoe et al., 2000) and index finger (Pirhonen et al., 2002),
`but none have specifically considered ergonomic factors. Since text entry remains the input
`bottleneck for mobile devices, many are working on improvements, and some targeting one-
`handed use. Peripheral keyboards for one-handed text entry are available, such as the Twiddler
`(Lyons et al., 2004), but the mobile device itself must be supported by another hand, desk or lap,
`which violates our definition of one-handed device control. Text entry on phone keypads is
`generally performed with a single thumb, but methods to improve input efficiency have focused
`on reducing the number of key presses required, such as T9 word prediction, rather than by
`improving ergonomics by optimizing button sizes, locations, or movement trajectories.
`Accelerometer-augmented devices allow for the device’s spatial orientation to serve as an input
`channel, and have been shown to support one-handed panning (Dong, Watters, & Duffy, 2005),
`scrolling (Rekimoto, 1996), and text entry (Wigdor & Balakrishnan, 2003). However, the coarse
`level of control tilt offers, and the potential for confusion with the normal movements of mobile
`computing necessarily limit the viability of tilt for generalized input.
`
`Scientists in the medical community have studied the biomechanics of the thumb extensively for
`the purposes of both reconstruction and rehabilitation. The structure of the thumb is well
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`understood (Barmakian, 1992), but only now are scientists beginning to reliably quantify the
`functional capabilities of the thumb. Strength has been the traditional parameter used to assess
`biomechanical capabilities, and recent research has established the effect movement direction has
`on thumb strength (Li & Harkness, 2004). Unfortunately, only standard anatomical planes have
`been considered, which excludes movements toward the palm that are typical of mobile device
`interaction. As a complement to force capabilities, others have looked at range as a characteristic
`of thumb movement. Kuo, Cooley, Kaufman, Su and An (2004) have developed a model for the
`maximal 3D workspace of the thumb and Hirotaka (2003) has quantified an average angle for
`thumb rotation. The experimental conditions for these studies, however, do not account for
`constraints imposed by holding objects of varying size, such as alternative models of handheld
`device.
`
`FIELD STUDY
`
`One motivation for our research in single-handed mobile designs was our assumption that people
`already use devices in this manner. Since current interaction patterns, whether by preference or
`necessity, are predictive of future behavior, they are likely to be transferred to new devices. This
`suggests that designs should become more accommodating to single-handed use, rather than less,
`as the current trend seems to be. To capture current behavior, we conducted an in situ study of
`user interaction with mobile devices. The study targeted an airport environment for the high
`potential of finding mobile device users and ease of access for unobtrusive observation.
`
`Field Study Method
`
`We observed 50 travelers (27 male) at Baltimore Washington International Airport’s main
`ticketing terminal during a six hour period during peak holiday travel. Because observation was
`limited to areas accessible to non-ticketed passengers, seating options were scarce. We expected
`to observe the use of both Personal Digital Assistants (PDAs) and cell phones since travelers are
`likely to be coordinating transportation, catching up on work, and using mobile devices for
`entertainment purposes. Since most users talk on the phone with one hand, we recorded only the
`cell phone interactions that included keypad interaction as well. All observations were performed
`anonymously without any interaction with the observed.
`
`Note that while any subject observation without consent presents a legitimate question for ethical
`debate, in our research we follow the federal policy on the protection of human research subjects
`(Department of Health and Human Services, 2005) as a guideline. The policy states that the
`observation of public behavior is not regulated if the anonymity of the subjects is maintained and
`that disclosure of the observations would not put the subjects at risk in terms of civil liability,
`financial standing, employability, or reputation. Since we were interested in capturing natural
`behavior, did not record identifying characteristics, and consider phone use while standing,
`walking and sitting relatively safe activities, we did not obtain subject consent.
`
`Field Study Measures
`
`For each user observed, we recorded sex, approximate age, and device type used: candy bar
`phone, flip phone, Blackberry, or PDA. A “candy bar” phone is the industry term for a
`traditional-style cellular phone with a rigid rectangular form, typically about 3 times longer than
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`wide. For phone use, we recorded the hand(s) used to dial (left, right or both) and the hand(s)
`used to speak (left, right or both). We also noted whether users were carrying additional items,
`and their current activity (selected from the mutually exclusive categories: walking, standing, or
`sitting).
`
`Field Study Results
`
`Only two users were observed operating devices other than mobile phones - one used a PDA and
`the other a Blackberry. Both were seated and using two hands. The remainder of the discussion
`focuses on the 48 phone users (62.5% flip, 37.5% candy bar). Overall, 74% used one hand for
`keypad interaction. By activity, 65% of one handed users had a hand occupied, 54% were
`walking, 35% were standing, and 11% were sitting. Figure 1 presents the distribution of subjects
`who used one vs. two hands for keypad interaction, categorized by the activity they were
`engaged in (walking, standing, or sitting). The distribution of users engaged in the three activities
`reflects the airport scenario where many more people were walking or standing than sitting. It is
`plain from Figure 1 that the relative proportion of one handed to two handed phone users varied
`by activity; the vast majority of walkers used one hand, about two-thirds of standers used one
`hand, but seated participants tended to use two hands. However, we also recorded whether one
`hand was occupied during the activity, and found walkers were more likely to have one hand
`occupied (60%), followed by standers (50%), and finally sitters (25%), which may be the true
`reason walkers were more likely than standers to use one hand, as well as why standers were
`more likely than sitters to use one hand. Regardless of activity, when both hands were available
`for use, the percentage of one vs. two handed phone users was equal.
`
`Figure 1. Airport Field Study - number of hands used for keypad interaction by activity.
`
`Analysis of Field Study
`
`Although Figure 1 suggests a relationship between user activity and keypad interaction behavior,
`it is unclear whether activity influences the number of hands used, or vice versa. Furthermore,
`since the percentage of users with one hand occupied correlates with the distribution of one-
`handed use across activities, hand availability, rather than preference, may be the more
`influential factor in the number of hands used to interact with the keypad. While use scenario
`certainly impacts usage patterns, the fact that users were as likely to use one hand as two hands
`when both hands were available suggests that preference, habit and personal comfort also play a
`role. Regardless of scenario, we can safely conclude that one-handed phone use is quite
`common, and thus is an essential consideration in mobile phone design.
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`Generalizability. The choice of observation location may have biased our results from those
`found in the general population since travelers may be more likely to be: 1) carrying additional
`items; 2) standing or walking; and 3) using a phone vs. PDA. Different environments,
`information domains, populations, and scenarios will yield unique usage patterns. Our goal was
`not to catalogue each possible combination, but to learn what we could from a typical in-transit
`scenario.
`
`WEB SURVEY
`
`While informative for a preliminary exploration, shortcomings of the field study were a) a lack
`of knowledge about motivation for usage style; b) the limited types of devices observed
`(phones); and c) the limited tasks types observed (assumed dialing). To broaden our
`understanding of device use over these dimensions, we designed a survey to capture user
`perceptions of, preferences for and motivations surrounding their own device usage patterns.
`
`Survey Method
`
`The survey consisted of 18 questions presented on a single web page which was accessed via an
`encrypted connection (SSL) from a computer science department server. An introductory
`message informed potential participants of the goals of the survey and assured anonymity.
`Notification that results would be posted for public access after the survey period was over
`provided the only incentive for participation. Participants were solicited from a voluntary
`subscription mailing list about the activities of our laboratory. In addition the solicitation was
`propagated to one recipient’s personal mailing list, a medical informatics mailing list, and a link
`to the survey was posted on two undergraduate CS course web pages.
`
`Survey Measures
`
`For each participant, we collected age, sex and occupation demographics. Users recorded all
`styles of phones and/or PDAs owned, but were asked to complete the survey with only one
`device in mind - the one used for the majority of information management tasks. We collected
`general information about the primary device, including usage frequency, input hardware, and
`method of text entry. We then asked a variety of questions to understand when and why people
`use one vs. two hands to operate a device. We asked users to record the number of hands used
`(one and/or two) for eighteen typical mobile tasks, and then to specify the number of hands (one
`or two) they would prefer to use for each task. Three pairs of activities were designed to
`distinguish between usage patterns for different tasks within the same application, which we
`differentiated as “read” (email reading, calendar lookup, and contact lookup) vs. “write” (email
`writing, calendar entry, and contact entry) tasks. Users then recorded the number of hands used
`for the majority of device interaction and under what circumstances they chose one option over
`the other. Finally, users were asked how many hands they would prefer to use for the majority of
`interactions (including no preference), and were also asked to record additional comments.
`
`Survey Results
`
`Two hundred twenty-nine participants (135 male) responded to the survey solicitation. One male
`participant was eliminated from the remaining analysis because his handheld device was
`specialized for audio play only, leaving 228. Median participant age was 38.5 years. Participant
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`occupations reflectedhe channels for solicitation, with 25% in CS, IT or engineering, 23%
`students of unstated discipline, 20% in the medical field, 10% in education, and the remainder
`(21%) from other professional disciplines.
`
`Devices owned. The three most common devices owned were flip phones (52%), small candy bar
`phones (23%) and Palm devices without a Qwerty keyboard (20%). Palm devices with an
`integrated Qwerty keyboard were as common as Pocket PCs without a keyboard (14%). Since
`interaction behavior may depend on device input capabilities, we reclassified each user’s primary
`device into one of four general categories based on the device’s input channels: (i) keypad-only
`(51%) are devices with a 12-key numeric keypad but no touchscreen, (ii) TS-no-qwerty (23%)
`are devices with a touchscreen but no Qwerty keyboard, (iii) TS-with-qwerty (21%) are devices
`with a touchscreen as well as an integrated Qwerty keyboard, and finally (iv) qwerty-only (5%)
`are devices with an integrated Qwerty keyboard but no touchscreen. For users with multiple
`devices, we derived their primary device type from the text entry method reported.
`
`Current usage patterns. Of the 18 activities users typically perform with devices, 9 were
`performed more often with one hand, 6 more often with two hands, and 3 were performed nearly
`as often with one vs. two hands. Figure 2a displays these results, with the shaded backgrounds
`grouping the activities preferred with one, either or two hands. Upon inspection, all of the
`“reading” activities were performed more often with one hand (top) and all “writing” activities
`with two hands (bottom). Considering users’ device types, we notice that with the exception of
`gaming, owners of keypad-only devices were more likely to use one hand regardless of activity,
`owners of TS-no-qwerty were more likely to use two-hands for most activities, and those owning
`Qwerty based devices were more likely to use two hands when performing writing tasks, but not
`reading tasks.
`
`Overall, 45% of participants stated they use one hand for nearly all device interactions, as
`opposed to only 19% who responded similarly for two hands. Considering device ownership,
`however, users of touchscreen-based devices were more likely to use two hands “always” than
`they were one hand (Figure 3). When participants use one hand, the majority (61%) perceive
`they do so whenever the interface supports it, the reason cited by only 10% of those who use two
`hands. Device form dictated usage behavior when the device was too small for two hands, too
`large for one hand, or when large devices could be supported by a surface and used with one
`hand. Participants cited task type as a reason for hand choice, primarily as a trade off between
`efficiency and resources usage: 14% of users selected one hand only for simple tasks (conserving
`resources), while 5% selected two hands for entering text, gaming, or otherwise for improving
`the speed of interaction (favoring efficiency). Finally, according to respondents, the majority of
`two-handed use occurs when it is the only way to accomplish the task given the interface (63%).
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`Figure 2. Web Survey – Number of hands (a) currently used and (b) preferred (1 hand is shown
`as solid, 2 hands is shown as striped) for 18 mobile tasks as a percentage of the observed
`population. Hand usage for each task is broken down by device type (TS = touchscreen).
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`Figure 3. Web Survey - The frequency and reasons for one (solid) and two (striped) handed
`device use, broken down by device type.
`
`Hand preferences. When asked how many hands users preferred to use while performing the
`same 18 tasks, one hand was preferred overwhelmingly to two hands for all tasks (Figure 2b).
`The activities with the closest margin between the number of participants who preferred one vs.
`two hands were playing games (13%) and composing email (16%). With one exception
`(gaming), the activities for which more than 14% of users stated a preference for two hands were
`“writing” tasks (e.g., those that required text entry): text entry, contact entry, calendar entry,
`email writing, and text messaging, in decreasing order. Even so, except for users of TS-with-
`qwerty devices, the majority of users stated a preference for using one hand, regardless of task or
`device owned. Users of TS-with-qwerty devices preferred two hands for text messaging, email
`composition, and text entry. Based on these data, it is consistent that 66% of participants stated
`they would prefer to use one hand for the majority of device interaction, versus 9% who would
`prefer two hands for all interaction. Twenty-three percent did not have a preference and 6 users
`did not respond.
`
`Survey Summary
`
`Considering current usage patterns only, there is no obvious winner between one and two handed
`use. Excluding phone calls, the number of activities for which a majority of respondents use one
`(7) vs. two hands (6) is nearly balanced. However, device type certainly influences user
`behavior; users of keypad-only devices nearly always use one hand, while users of touchscreen
`devices more often favor two hands, especially for tasks involving text entry. But user
`justifications for hand choice indicate that the hardware/software interface is to blame for much
`two-handed use occurring today. Most use one hand if at all possible and only use two hands
`when the interface makes a task impossible to do otherwise. Other than gaming, tasks involving
`text entry are the only ones for which users may be willing to use two hands, especially when the
`device used provides an integrated Qwerty keyboard. It seems, therefore, that the efficiency
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`gained by using two hands for such tasks is often worth the dedication of physical resources,
`which is also true of the immersive gaming experience.
`
`While most users can imagine the ideal of single-handed text entry, enabling single-handed input
`may not be enough - throughput is also important. Ultimately, it is clear that interface designers
`of all device types should make one-handed usability a priority, and strive to bridge the gap
`between current and desired usage patterns.
`
`THUMB MOVEMENT STUDY
`
`The third component of our exploration was an examination of thumb movement in the context
`of mobile device interaction. As input technologies and device forms come and go,
`biomechanical limitations of the thumb will remain. Although the thumb is a highly versatile
`appendage with an impressive range of motion, it is most adapted for grasping tasks, playing
`opposite the other four fingers (Bourbonnais, Forget, Carrier, & Lepage, 1993). Hence thumb
`interaction on the surface of today’s mobile devices introduces novel movement and exertion
`requirements for the thumb – repetitive pressing tasks issued on a plane parallel to the palm. We
`believe a fundamental understanding of thumb capabilities when holding a device can help guide
`the placement of interaction targets for both hardware and software interfaces designed for one-
`handed use. Although we can make reasonable guesses about thumb capabilities, empirical
`evidence is a better guide. Since no strictly relevant studies have yet been conducted, we have
`developed a study to help us understand how device form and task influences thumb mobility
`
`Since thumb tapping is the predominant means of interaction for keypad-based devices, and has
`also proven promising for one-handed touchscreen use (Karlson et al., 2005), we focused our
`investigation on surface tapping tasks. We hypothesized that the difficulty of a tapping task
`would depend on device size, movement direction, and surface location of the interaction. We
`captured the impact of these factors on user performance by using movement speed as a proxy
`for task difficulty – under the assumption that harder tasks would be performed more slowly than
`easier tasks.
`
`Equipment
`
`Device models. For real devices, design elements such as buttons and screens communicate to
`the user the “valid” input areas of the device. We instead wanted outcomes of task performance
`to suggest appropriate surface areas for thumb interaction. We identified four common handheld
`devices to represent the range of sizes and shapes found in the market today: (1) a Siemens S56
`candy bar phone measuring 4.0 x 1.7 x 0.6 in (10.2 x 4.3 x 1.5 cm); (2) a Samsung SCH-i600 flip
`phone measuring 3.5 x 2.1 x 0.9 in (9 x 5.4 x 2.3 cm); (3) an iMate smartphone measuring 4 x
`2.0 x 0.9 in (10.2 x 5.1 x 2.3 cm) and (4) an HP iPAQ h4155 Pocket PC measuring 4.5 x 2.8 x
`0.5 in (11.4 x 7.1 x 1.3 cm). These devices are shown in the top row of Figure 4. We refer to
`these as simply SMALL, FLIP, LARGE, and PDA. To remove the bias inherent in existing
`devices, we created a 3D model of each device, removing all superficial design features. The
`models were developed using Z Corp.’s (http://www.zcorp.com/) ZPrinter 310 3D rapid
`prototyping system. Device models were hollow, but we reintroduced weight to provide a
`realistic feel. Once “printed” and cured, the models were sanded and sealed to achieve a smooth
`finish.
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`Phones
`
`Models
`
`(d)
`(c)
`(b)
`(a)
`Figure 4. Devices we chose to represent a range of sizes and forms (top row) together with their
`study-ready models (bottom row): (a) SMALL, (b) FLIP, (c) LARGE, and (d) PDA.
`
`Target design. A grid of circular targets 1.5 cm in diameter was affixed to the surface of each
`device. Circles were used for targets so that the sizes would not vary with direction of movement
`(MacKenzie & Buxton, 1992). The target size was selected to be large enough for the average-
`sized thumb, while also providing adequate surface coverage for each device. The grid
`dimensions for each device were: SMALL (2x5), FLIP (3x4), LARGE (3x7) and PDA (4x6), as
`shown in the bottom row of Figure 4.
`
`Measurement. A typical measurement strategy for tapping tasks would involve a surface-based
`sensor to detect finger contact. Unfortunately, due to the number and variety of device sizes
`investigated, no technical solution was found to be as versatile, accurate or affordable as
`required. Instead we used Northern Digital Inc.’s OPTOTRAK 3020 motion analysis system
`designed for fine-grained tracking of motor movement. The OPTOTRAK uses 3 cameras to
`determine the precise 3D coordinates of infrared emitting diodes (IREDs). Three planar IREDs
`attached to the surface of each device defined a local coordinate system, and a fourth IRED
`provided redundancy (see Figure 4, bottom row). The spatial positions of two markers affixed to
`each participant’s right thumb were then translated with respect to the coordinate system of the
`device to establish relative movement trajectories. Diode positions were sampled at 100Hz, and
`data were post processed to derive taps from thumb minima.
`
`Software. Data collection and experiment software was run on a Gateway 2000 Pentium II with
`256 MB of RAM running Windows 98.
`
`Participants
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`Twenty participants were recruited via fliers posted in our Department of Computer Science,
`with the only restriction that participants be right-handed. Participants (15 male) ranged in age
`from 18 to 35 years with a median age of 25 years. Participants received $20 for their time.
`
`Design
`
`For each target on each device (SMALL, FLIP, LARGE, and PDA), users performed all
`combinations of distance (1 or 2 circles) x direction ( ,
`,
`,
`) tasks that could be supported
`by the geometry of the device. For example, SMALL could not accommodate trials of distance 2
`). Note that the grid layout results in actual distances that
`circles in the directions (
`,
`,
`differ between orthogonal trials (
`) and diagonal trials (
`,
`,
`), which we consider explicitly
`in our analysis. For LARGE and PDA, trials of distance 4 circles were included as the geometry
`permitted. Finally each device included a
` and
` trial to opposite corners of the target grid. For
`each device, a small number of trials (1 for SMALL, LARGE and PDA, 3 for FLIP), selected at
`random, were repeated so as to make the total trial count divisible by four. The resulting number
`of trials for each device were: SMALL (32), FLIP (48), LARGE (108), and PDA (128). Since the
`larger devices had more surface targets to test, they required more trials.
`
`Tasks
`
`Users performed reciprocal tapping tasks in blocks as follows. For SMALL and FLIP, trials were
`divided equally into 2 blocks. For the LARGE and PDA, trials were divided equally into 4
`blocks. Trials were assigned to blocks to achieve roughly equal numbers of distance x direction
`trials, distributed evenly over the device. Trials were announced by audio recording so that users
`could focus attention fully on the device. Users were presented with the name of two targets by
`number. For example, a voice recording would say “1 and 3”. After 1 second, a voice-recorded
`“start” was played. Users tapped as quickly as possible between the two targets, and after 5
`seconds, a “stop” was played. After a 1.5 second delay the next trial began. Trials continued in
`succession to the end of the block, at which point the user was allowed to rest as desired, with no
`user resting more than 2 minutes. Device and block orders were assigned to subjects using a
`Latin Square, but the presentation of within-block trials was randomized for each user.
`
`Procedure
`
`Each session began with a brief description of the tasks to be performed and the equipment
`involved. Two IRED markers were then attached to the right thumb with two-sided tape. One
`diode was placed on the leftmost edge of the thumb nail, and a second on the left side of the
`thumb. The orthogonal placement was intended to maximize visibility of at least one of the
`diodes to the cameras at all times. The two marker wires were tethered loosely to the
`participant’s right wrist with medical tape.
`
`The participant was seated in an armless chair, with the device held in the right hand, and the
`OPTOTRAK cameras positioned over the right shoulder. At this point the participant was given
`more detailed instruction about the tasks, and informed of the error conditions that might occur
`during the study: if at any point fewer than three of the device-affixed IREDs or none of the
`thumb IREDs were visible to the cameras, an out-of-sight error sound would be emitted, at
`which point he or she should