7.1 Introduction and goals for the studies

7.2 Experiment 1: Qualitative analysis of handwriting and sketching

The handwriting and sketching studies emphasize qualitative results. Through subject observation and videotape analysis, my pilot studies quickly led to qualitative insights with immediate application to interface design, but I found it was difficult to formalize these results. There are many interacting within and between-subjects factors that must be carefully controlled to produce a clean quantitative result, but many of these factors (which are outlined in section 7.2.1) have little or no relevance to interface design. As a result I decided that discovering, understanding, and measuring or controlling for these factors in formal experimental designs was beyond the intended scope of this thesis.

The handwriting and sketching studies individually consisted of 6 rounds of experimental work with small numbers of subjects. In total, 29 right-handed subjects (9 friends and colleagues and 20 subjects drawn from the psychology department's subject pool) participated. Each round of experimental work tested one or more variants of the experimental tasks of (1) filling a page with handwriting, (2) filling out a form, (3) sketching an object in the environment, or (4) drawing a circle. Rather than focusing on the specific details of each round of tests, this discussion pools my observations across all subjects, and gives the specifics of the experimental tasks where appropriate.

7.2.1 Handwriting

The left hand can participate in manipulation of the page when the user is writing on dictation or from memory (such as when writing a memorized sentence or during composition of original prose). For example, of 4 subjects whom I asked to write a memorized phrase on every third line of a college-ruled page, all 4 subjects used the left hand to initially orient the page, and 3 of the 4 subjects used the left hand in a dynamic role to reposition the page at least once during the actual writing. The fourth subject used her left hand to lean on the desk and prop up her head. Most people can write unimanually if necessary, and a few even prefer to do so. In this regard, the task of writing on an already selected line is probably an oversimplified representation of the tasks of interest to interface designers. Nonetheless, even for such a simple task, most people do prefer to use both hands.

As part of the experimental protocol, subjects filled out a questionnaire with 14 questions on preferred hand usage (fig. 7.1). Subjects did not realize that this doubled as an experimental task which I captured on videotape¹. Filling out a form is an interesting variant of the handwriting task, because it involves the same basic motor skills, but the task contains both macrometric and micrometric components. Answering a single question requires a small movement to "fill in the blank", but moving to the next question requires a potentially large movement to another area of the page.

Figure 7.1 Questionnaire for the "filling out a form" task.

By analyzing the videotapes, I counted the number of times that 7 subjects moved the page while filling out the questionnaire. Five subjects moved the page at least once; 2 subjects did not move the page at all, while 2 subjects moved the page for essentially every item on the questionnaire (12 or more movements for 14 questions). When subjects moved the page, they moved it in a specific pattern: the preferred hand holding the pen stayed in a very small working area, while the nonpreferred hand shifted the page to bring the work to the preferred hand. Clearly, the nonpreferred hand helps to reduce the working volume of the preferred hand to a small, comfortable, well-practiced region.

In unpublished work, Athenes [6][7] (working with Guiard) has found that all of the following factors can influence the speed of handwriting²:

• Handedness: There are three distinct classes of handwriters: right handers, left-handed inverters, and left-handed non-inverters (fig. 7.2). Each class has its own distinct handwriting strategy [72][6].
• Paper weight: Heavier paper has more friction with the desk surface and is easier to use unimanually.
• Paper size: Extremely small pages, such as post-it notes, are difficult to write on because the nonpreferred hand can hardly help at all.
• Line Position on the Page: The lower the position on the page, the more important the contribution of the nonpreferred hand.
• Margin Size: The closer the pen gets to the edge of the paper, the more difficult it is to write with one hand. As suggested by the above list, isolating the "true" contribution of the nonpreferred hand to handwriting tasks requires consideration of many mundane factors and is an almost impossible endeavor. Many similar factors influence the drawing and sketching tasks discussed below. This is why the present studies emphasize my qualitative findings.

  

  Figure 7.2 Writing posture of left-handed inverters and non-inverters [6].

• Unimanual Restricted (UR): Subjects were instructed to keep their left hand in their lap. The page was also taped to the desk surface so that it would not move (either accidentally or by the subject's intent) during the task.
• Bimanual Restricted (BR): Subjects were instructed to keep their left hand on the desk surface, but the page was again taped to the desk surface so that the page could not be rotated. Subjects were allowed to position and move the left hand as desired.
• Bimanual Free (BF): Subjects were instructed to perform the task in "whatever way comes naturally." The page was not secured to the desk surface.

  Figure 7.3 Examples of circles drawn versus individual pen strokes³.

  As expected, in the BF condition most subjects did naturally use their left hand to rotate the page and thereby extend the working range of the right hand. This strategy allowed subjects to repeatedly draw an almost identical stroke until the circle was complete. Subjects would perform most of the work on the left hand side of the page. To illustrate this tendency, I placed transfer paper (carbon paper) on the back of a specially prepared desk blotter; subjects sketched a circle (fig. 7.3, top row) on a page on top of this blotter. The transfer paper captured the impression of the subject's pen strokes relative to the blotter (fig. 7.3, bottom row). As the examples shown in figure 7.3 demonstrate, most of the arcs are in the same direction and take up a small area relative to the size of the circle itself. Note that figure 7.3 shows examples from two separate subjects performing slightly different tasks (subject A had 4 registration marks to guide the drawing of each circle, while subject B had 8 such registration marks).

  In the BR and UR conditions where rotating the page was not possible, subjects often had difficulty in the upper right-hand quadrant of the circle. This is exactly the point where the inflection of the circle goes against the natural biomechanical curves generated by the wrist and fingers of the right hand. To compensate for this biomechanical awkwardness, subjects would try to move their entire torso relative to the page to produce a better angle for the action of the right hand. Having the left hand in the lap, as required by the UR condition, made it even more difficult for subjects to counter-rotate their body to adjust for the fixed page. As one subject commented, "I usually put my hand on the table for support." Thus, the UR condition reveals that the left hand normally plays a postural role as well.

  There was a tendency for the bimanual conditions (especially the BF condition) to produce better quality results (the circle looked better), as self-assessed by the subjects or by an independent judge. However, the overall difference between conditions was not that impressive. The times to complete the task varied tremendously between subjects; some who were in a hurry would complete every circle in 20 seconds, no matter how bad they looked, while others would spend 3 minutes perfecting their work every time. Thus, the experimental tasks did not adequately control for time/accuracy trade-offs.

  While the above results suggest that using both hands for sketching tasks may have some benefits, using a second hand might also be a liability, because each hand occludes part of the circle that the subject is sketching: the subject loses the overall context of the entire circle. In the UR condition, subjects seemed to have more difficulty precisely controlling hand movements, but they could see more of the circle, since their right hand (for at least half of the time) is to the right of the circle and does not occlude it at all. In the BF condition, it was easier to make the outside of the circle "smooth," but it was harder to make it truly circular. When subjects tried to draw free-hand circles in the BF condition without any registration marks to guide their work, many of the resulting circles were egg-shaped.

  

  Figure 7.4 An example two-handed application [59] using the Active Desk.

  The same issue arises in interface design when using both hands for direct input on a large display surface such as the Active Desk (fig. 7.4). In unpublished work, Buxton tried to reproduce the results of Kabbash [95] using direct input on the Active Desk display. Kabbash (as originally discussed in section 2.6.2.2 on page 36) found that users could connect and color a series of randomly appearing dots much faster with the two-handed ToolGlass technique [15] than with one-handed techniques; Kabbash produced these results using indirect input devices in conjunction with a standard monitor. But on the Active Desk, Buxton found that the targets would sometimes randomly appear in parts of the display occluded by the user's arms, causing subjects to become extremely confused. Thus, interface designs which use two hands for direct input need to be aware of the problems introduced by occlusion of the display surface and potential problems caused by the resulting loss of context⁴.

  As a final example, during one experimental session, I asked two subjects with minors in art to sketch an object which I placed at the rear of the desk surface. Although these subjects were allowed to use both hands, neither subject rotated the page while they were capturing the general outline of the object. However, once they started to shade it and "overstrike" some of their initial strokes, they began to frequently rotate the page with the left hand. Thus, when drawing an object from the environment, rotating the page is a detriment because it would require a mental rotation to align the page and the environment; but when attention is focused primarily on the page itself, these subjects found rotating the page to be a natural and efficient task strategy.

  Although these two subjects had some artistic skill, this was not the case for most of the subjects which I recruited for these studies. I speculate that for skilled artists performing a sketching task, using the left hand to rotate the page or otherwise assist the activities of the right hand is even more important than for unskilled subjects. When asked directly about this issue, one professional artist (who was not a participant in this study) commented, "I can't draw unless I can rotate the page."

Furthermore, as illustrated by the impressions of individual pen strokes relative to the desk (fig. 7.3), when the left hand helps to manipulate the page, the patterns of hand use are quite consistent and predictable across subjects. By dynamically positioning and orienting the page, the nonpreferred hand extends the working range of the "sweet spot" for the preferred hand.

There are problems which these studies do not address. Many uninteresting factors obscure the time, precision, or postural advantages (if any) of using two hands for these tasks, and a formal experiment would need to control for these factors. The tasks which I tested were also somewhat open-ended, and did not adequately control for time/accuracy trade-offs. This, in addition to the large between-subject variability in terms of handwriting speed, artistic ability, and so forth, means that these studies were not well suited to produce quantitative results.

7.3 Experiment 2: Cooperative bimanual action

Furthermore, when physical constraints guide the tool placement, this fundamentally changes the type of motor control required. The task is tremendously simplified for both hands, and reversing roles of the hands is no longer an important factor. Thus, specialization of the roles of the hands is significant only for skilled manipulation.

Figure 7.5 A subject performing the experimental task.

7.3.2 Introduction

The present experiment was motivated by my experiences with the props-based interface. Informally, I observed that the operation of the interface was greatly simplified when both hands were involved in the task. But the early design stages had to consider many possible ways that the two hands might cooperate. An early prototype allowed users to use both hands, but was still difficult to use. The nonpreferred hand oriented the doll's head, and the preferred hand oriented the cross-sectioning plane, yet the software did not pay any attention to the relative placement between the left and the right hands. Users felt like they were trying to perform two separate tasks which were not necessarily related.

I modified the interface so that relative placement mattered. The software interpreted all motion as relative to the doll's head in the user's nonpreferred hand, resulting in a far more natural interaction: users found it much easier to integrate the action of the two hands to perform a cooperative task. Informally, this suggests that two-handed coordination is most natural when the preferred hand moved relative to the nonpreferred hand. The current experiment formalizes this hypothesis and presents some empirical data which suggests right-to-left reference yields quantitatively superior and qualitatively more natural performance.

Beyond this specific example, interface designers in general have begun to realize that humans are two-handed, and it is time to develop some formal knowledge in support of such designs. In this spirit, the present experiment, which analyzed right-handed subjects only, contributes the following pieces of such formal knowledge:

• The experimental task, which represents a general class of 3D manipulative tasks involving a tool and a reference object, requires an asymmetric contribution of the two hands.
• For such tasks, performance is best when the right hand operates relative to the left. Reversing the roles of the hands significantly reduces performance both in terms of time and accuracy.
• When physical constraints help to perform the task, the type of motor control required fundamentally changes. This is as an especially telling finding for virtual manipulation, where the user is often equipped with a glove offering no haptic feedback, and speaks strongly for the possible benefits of using either passive or active haptic feedback (using either "props" or a force-feedback arm akin to the Phantom [147], respectively).
• Specialization of the roles of the hands is significant only for skilled manip-ulation. This does not imply that two-handed input will be ineffective for tasks which afford symmetric manipulation, but instead restricts the scope of tasks where asymmetry factors will have important design implications.
• These findings are quite robust with respect to a subject's level of motor skill. Given the wide range of skill exhibited by the participants, it is remarkable that all 16 showed the above effects to some extent.
• Qualitatively, these results held despite the strong tendency for subjects to adopt coping strategies which attempted to maintain the natural roles for the hands. For example, when roles were reversed, some subjects tried to hold the tool stationary in the left hand while moving the target object to meet it. Clearly, the constraints of the task limited the effectiveness of this strategy. The study only included right-handed subjects because hand usage patterns in left-handers tend to be somewhat more chaotic than those in right-handers, which complicates experimental design. The issues posed by handedness are surprisingly complicated [69][74], and without a clear understanding of bimanual action in right-handers, it seems premature to address the unique behavioral strategies employed by left-handers. For example, as shown in figure 7.2 on page 136, left-handers can adopt at least one of two distinct postures, inverted or non-inverted, for handwriting. Nonetheless, I speculate that left-handers should exhibit a similar (but less consistent) pattern of findings to those reported here for right-handers.

For truly bimanual movement, most psychology and motor behavior experiments have studied tasks which require concurrent but relatively independent movement of the hands. Example tasks include bimanual tapping of rhythms [44][134][185] and bimanual pointing to separate targets [87][117][184]. Since the hands are not necessarily working together to achieve a common goal, it is uncertain if these experiments apply to cooperative bimanual action.⁵

There are a few notable exceptions, however. Buxton and Myers [27] demonstrated that computer users naturally use two hands to perform compound tasks (positioning and scaling, navigation and selection) and that task performance is best when both hands are used. Buxton [29] has also prepared a summary of issues in two-handed input.

Kabbash [95] studied a compound drawing and selection task, and concluded that two-handed input techniques, such as ToolGlass [15], which mimic everyday "asymmetric dependent" tasks yield superior overall performance. In an asymmetric dependent task, the action of the right hand depends on that of the left hand [95][67]. This experiment did not, however, include any conditions where the action of the left hand depended on the right hand.

Guiard performed tapping experiments with a bimanually held rod [69]. Subjects performed the tapping task using two grips: a preferred grip (with one hand held at the end of the rod and the other hand near the middle) and a reversed grip (with the hands swapping positions). The preferred grip yielded better overall accuracy, but had reliably faster movement times only for the tapping condition with the largest amplitude. Guiard also observed a distinct partition of labor between the hands, with the right hand controlling the push-pull of the rod, and the left hand controlling the axis of rotation.

A number of user interfaces have provided compelling demonstrations of two handed input, but most have not attempted formal experiments. Three-dimensional virtual manipulation is a particularly promising application area. Examples previously described in chapter 2 include the Virtual Workbench [138], 3Draw [141], Worlds-in-Miniature [164], PolyShop [1], and work by Shaw [149] and Multigen, Inc. [121]. There is also some interest for teleoperation applications [163]. In two dimensions, examples include Toolglass and Magic Lenses [15], Fitzmaurice's Graspable User Interface [59] (shown in figure 7.4 on page 139), and Leganchuk's bimanual area sweeping technique [108]. Bolt [17] and Weimer [180] have investigated uses of two hands plus voice input. Hauptmann [76] showed that people naturally use speech and two-handed gestures to express spatial manipulations.

7.5 The Experiment

For the Hard task, the subject must mate the tool and the target object so that the tool touches only the target area (fig. 7.7). The target area is wired to a circuit that produces a pleasant beep when touched with the tool; if the tool misses the target area, it triggers an annoying buzzer which signals an error. The target area is only slightly larger than the tool, so the task requires dexterity to perform successfully. I instructed each subject that avoiding errors was more important than completing the task quickly.

For the Easy task, the subject only has to move the tool so that it touches the bottom of the rectangular slot on the target object. The buzzer was turned off and no "errors" were possible: the subject was allowed to use the edges of the slot to guide the placement. In this case, the subject was instructed to optimize strictly for speed.

Each subject performed the Hard and the Easy task using two different grips, a Preferred grip (with the left hand holding the target object and the right hand holding the tool) and a Reversed grip (with the implements reversed). This resulted in four conditions: Preferred Hard (PH), Preferred Easy (PE), Reversed Hard (RH), and Reversed Easy (RE).

Subjects were required to hold both objects in the air during manipulation (fig. 7.5), since this is typically what is required when manipulating virtual objects. Subjects were allowed to rest their forearms or wrists on the table, which most did.

Figure 7.6 Configuration for Experiment 2.

7.6 Experimental hypotheses

The specific hypotheses for this experiment are as follows:

H1: The Hard task is asymmetric and the hands are not interchangable. That is, the Grip (preferred, reversed) used will be a significant factor for this task.

H2: For the Easy task, the opposite is true. Reversing roles of the hands will not have any reliable effect.

H3: The importance of specialization of the roles of the hands increases as the task becomes more difficult. That is, there will be an interaction between Grip (preferred, reversed) and Task (easy, hard).

H4: Haptics will fundamentally change the type of motor control required.

7.6.1 Subjects

7.6.2 Experimental procedure and design

The experiment began with a brief demonstration of the neurosurgical props interface to engage subjects in the experiment. I suggested to each subject that he or she should "imagine yourself in the place of the surgeon" and stressed that, as in brain surgery, accurate and precise placement was more important that speed. This made the experiment more fun for the subjects, who would sometimes joke that they had "killed the patient" when they made an error.

Figure 7.7 Dimensions of the plate tool, the stylus tool, and target areas.

There were two tools, a plate and a stylus, and three target objects, a cube, a triangle, and a puck (figs. 7.7, 7.8). Using multiple objects helped to guarantee that the experimental findings would not be idiosyncratic to one particular implement, as each implement requires the use of slightly different muscle groups. Also, the multiple objects served as a minor ruse: I did not want the subjects to be consciously thinking about what they were doing with their hands during the experiment, so they were initially told that the primary purpose of the experiment was to test which shapes of input devices were best for two-handed manipulation.

Figure 7.8 Dimensions of the Cube, Triangle, and Puck target objects.

The subject next performed a practice session for the Hard task, during which I explained the experimental apparatus and task. This session consisted of 6 practice trials with the Preferred grip and 6 practice trials with the Reversed grip⁶.

For the experimental trials, a within-subjects latin square design was used to control for order of presentation effects. For each of the four experimental conditions, subjects performed 24 placement tasks, divided into two sets of 12 trials each. Each set included two instances of all six possible tool and target combinations, presented in random order. There was a short break between conditions.

For the Hard task, the dependent variables were time (measured from when the tool is picked up until it first touches the target area) and errors (a dichotomous pass / fail variable). For the Easy task, since no errors were possible, only time was measured.

7.6.3 Details of the experimental task and configuration

Two platforms were used, one to hold the tools and one to hold the target objects (fig. 7.6). The tool platform was instrumented with electrical contact sensors, allowing the apparatus to detect when the tool was removed from or returned to the platform. Returning the tool to the platform (after touching the target) ended the current trial and displayed a status report. The subject initiated the next trial by clicking a footpedal.

Figure 7.9 Sample screen showing experimental stimuli.

Each subject was seated so that the midline of his or her body was centered between the two platforms. The tool platform was flipped 180º during the Reversed conditions, so that the plate was always the closest tool to the objects. The platforms were positioned one foot back from the front edge of the desk, and were spaced 6" apart.

Figure 7.8 shows the dimensions for the cube, triangle, and puck target objects. Each object was fitted with an identical target (fig 7.7, right) which was centered at the bottom of the rectangular slot (0.75" deep by 0.375" wide) on each object. The objects were machined from delrin (a type of plastic) and wrapped with foil so they would conduct electricity. The target area and the foil were wired to separate circuits; some capacitance was added to each circuit to ensure that even slight contacts would be detected.

When using the plate, subjects were instructed to use the entire 0.5" wide tip of the plate to touch the target. For the stylus, the subject was told to touch the rounded part of the target area (the stylus was thicker than the other parts of the target, as shown in figure 7.7, and thus only the central rounded part of the target area could be touched without triggering an error).

7.6.4 Limitations of the experiment

Second, the accuracy measurements yield a dichotomous pass / fail outcome. Thus, the apparatus captures no quantitative information about the magnitude of the errors made when the subjects missed the target in the Hard conditions. Even given these limitations, the experimental results are quite decisive. Therefore, I decided to leave resolution of these issues to future work, and to demonstrate some effects with the simplest possible experimental design and apparatus.

7.7 Results

A straightforward analysis of the Hard task shows a strong lateral asymmetry effect. For both the plate and the stylus tools, 15/16 subjects performed the task faster in the PH condition than in the RH condition (significant by the sign test, p < .001). The difference in times is not due to a time / accuracy trade-off, as 15/16 subjects (using the plate) and 14/16 subjects (using the stylus) made fewer or the same amount of errors in the PH condition vs. the RH condition.

For the Easy task, as predicted by Hypothesis 2, the lateral asymmetry effect was less decisive. For both the plate and the stylus tools, 11/16 subjects performed the task faster in the PE condition than in the RE condition (not a significant difference by the sign test, p > .20). For at least one of the tools, 6/16 subjects performed the task faster in the RE condition vs. the PE condition.

Figure 7.10 summarizes the mean completion times and error rates. No errors were possible in the Easy conditions. In the Hard conditions, the relatively high error rates resulted from the difficulty of the task, rather than a lack of effort. I instructed subjects that "avoiding errors is more important than speed," a point which I emphasized several times and underscored by the analogy to performing brain surgery.

Condition	Mean	Std. dev.	Error rate
Preferred Easy (PE)	0.76	0.15	--
Reversed Easy (RE)	0.83	0.19	--
Preferred Hard (PH)	2.33	0.77	43.9%
Reversed Hard (RH)	3.09	1.10	61.1%

Figure 7.10 Summary of mean completion times and error rates.

7.7.1 Qualitative analysis

I observed three patterns of strategies in experimental subjects when they were performing the Hard task:

• Maintaining natural roles of hands: In the RH condition, some subjects tried to perform the task by "holding the [left-hand] tool steady and bringing the [right-hand] object to meet it."
• Tool stability: Also in the RH condition, many subjects adjusted their left-hand grip to be as close to the tip of the tool as possible. This helped to reduce the effect of any left-hand unsteadiness.
• Having the right view of the objects: The target was at the bottom of a slot, so there was a restricted set of views where the subject could see the target. For the Hard task, subjects often performed the task with edge-on or overhead views, sometimes holding one eye closed to get the best view of the tool tip and target. Subjects usually performed the RH task differently than the PH task. When using the Preferred grip, the left hand would first orient the object, and the right hand would then move in with the tool, so that at the time of contact the target object was usually stationary and only the tool was in motion. But in the Reversed grip, there often were several phases to the motion. The right hand would first orient the object, and the left hand would approach with the tool; but then the left hand would hesitate and the right hand would move towards it. During actual contact with the target, both the tool and the object were often in motion.

  At first glance, it would seem that the primary difference between the RH and the PH conditions was the left hand's unsteadiness when handling the tools. For at least some of the subjects, however, it also seemed that the right hand had difficulty setting the proper orientation for the action of the left hand. So the right hand was best at fine manipulation, whereas the left hand was best at orientating the target object for the action of the other hand.

  For the Easy tasks, subjects performed the task quickly and without much concentration, since they could rely on the physical constraints of the slot to guide the tool. Subjects were divided about whether or not the RE task was unnatural. Some thought it was "definitely awkward," others thought it was "fine." At least one subject preferred the Reversed grip; this preference was confirmed by a small Reversed grip advantage in the quantitative data.

  Finally, when switching to the Hard task after performing a block of the Easy task, subjects often took several trials to adjust to the new task requirements. Once subjects became used to relying on physical constraints, it required a conscious effort to go back. To assist this transition, I instructed subjects to "again emphasize accuracy" and to "focus initially on slowing down."

Factor	F statistic	Significance
Grip	F(1,15) = 38.73	p < .0001
Task	F(1,15) = 66.60	p < .0001
Tool	F(1,15) = 5.22	p < .05
Object	F(2,30) = 3.33	p < .05
Grip 5 Task	F(1,15) = 24.83	p < .0005
Tool 5 Task	F(1,15) = 16.57	p < .001
Object 5 Task	F(2,30) = 2.52	p < .10, n.s.
Grip 5 Task 5 Tool	F(1,15) = 5.11	p < .05

Figure 7.11 Significance levels for Main effects and Interaction effects.

Overall, the preferred Grip was significantly faster than the reversed Grip and the easy Task was significantly faster than the hard Task. The Tool and Object factors were also significant, though the effects were small. The plate Tool was more difficult to position than the stylus: this reflects the requirement that the subject must align an additional degree of freedom with the plate (rotation about the axis of the tool) in order to hit the target. The cube Object was somewhat more difficult than the other Objects.

Figure 7.12 The Task X Grip interaction.

The ANOVA revealed a highly significant Grip 5 Task interaction, which suggests that the difference between the Preferred and the Reversed grips increases as the task becomes more difficult. This speaks eloquently in favor of Hypothesis 3: the importance of specialization of the roles of the hands increases as the task becomes more difficult (fig. 7.12).

There was also a significant three-way Grip 5 Task 5 Tool interaction (fig. 7.15). This indicates that the extent of the Grip 5 Task interaction varied with the tool being used (there was a larger distinction between the preferred and reversed postures with the stylus). Finally, the Tool 5 Task interaction (fig. 7.13) was significant and the Object 5 Task interaction approached significance. This suggests that the Tools and Objects differed only for the hard Task, not the easy Task.

Figure 7.13 Tool X Task interaction.

Figure 7.11 reported pooled effects across the easy and hard Task and the preferred and reversed Grip. Based on the experimental hypotheses, I also compared the individual experimental conditions. These are summarized below in figure 7.14.

Contrast	F statistic	Significance
PE vs. RE	F(1,15) = 3.94	p < 0.10, n.s.
PH vs. RH	F(1,15) = 33.56	p < 0.0001

Figure 7.14 Significance levels for comparisons of experimental conditions.

Figure 7.15 The Task X Grip X Tool interaction.

The Grip factor is significant for the Hard task (PH vs. RH), but not the Easy task (PE vs. RE). This supports Hypothesis 1: the task is asymmetric and reversing the roles of the hands has a significant effect. The Grip factor is also nearly significant for the Easy task (PE vs. RE), suggesting that Grip probably is a minor factor even in this case. This partially supports Hypothesis 2; reversing the roles of the hands has a much smaller effect for the easy task, but the study cannot confidently conclude that there is no effect.

7.7.3 Possibility of Order or Sex biases

There was a small, but significant, main effect of Sex, along with several significant interactions (fig. 7.16). Although this experiment was not designed to detect sex differences, this finding is consistent with the literature, which suggests that females may be better at some dexterity tasks [74].

Factor	F statistic	Significance
Sex	F(1,14) = 5.55	p < .05
Tool 5 Sex	F(1,14) = 12.80	p < .005
Task 5 Sex	F(1,14) = 5.23	p < .05
Tool 5 Task 5 Sex	F(1,14) = 20.90	p < .0005

Figure 7.16 Overall sex difference effects.

To ensure that Sex is not a distorting factor, separate analyses were performed with N=8 male and N=8 female subjects. This is a less sensitive analysis, but the previous pattern of results still held: Grip, Task, and the Grip 5 Task interaction were all significant for both groups (fig. 7.17). Males tended to be more sensitive to which Tool was being used for manipulation, which accounts for the Tool 5 Sex and Tool 5 Task 5 Sex interactions (fig. 7.16). The Task 5 Sex interaction results from females being faster than males for the Hard task, but not the Easy task. Therefore, on the basis of these analyses, one can confidently conclude that the differences between the experimental conditions are not biased by Order or Sex effects.

MALES
Factor	F statistic	Significance
Grip	F(1,7) = 13.69	p < .01
Task	F(1,7) = 44.59	p < .0005
Grip 5 Task	F(1,7) = 9.24	p < .02
FEMALES
Factor	F statistic	Significance
Grip	F(1,7) = 29.93	p < .001
Task	F(1,7) = 47.41	p < .0005
Grip 5 Task	F(1,7) = 24.79	p < .002

Figure 7.17 Results of separate analyses for males and females.

7.8 Discussion

H1: The Hard task is asymmetric and the hands are not interchangable. This hypothesis was supported by the overall Grip effect and the Preferred Hard vs. Reversed Hard contrast, both of which were highly significant. This suggests that maniplation is most natural when the right hand works relative to the left hand.

There are several qualities of the experimental task which may have led to the lateral asymmetry effects:

• Mass asymmetry: When holding the tool, some subjects had visible motor tremors in the left hand; but when they held the target object, the greater mass helped to damp out this instability.
• Having the right view of the objects: As mentioned previously, in the Reversed condition, some subjects tried to hold the tool at a fixed orientation in the left hand and move the target object to the tool. But as the subject moved the target object, he or she would no longer have the best view to see the target, and performance would suffer.
• Referential task: The task itself is easiest to perform when the manipulation of one object can done relative to a stationary object held in the other hand. Under virtual manipulation, one can overcome some of these factors (such as mass asymmetry), but not all of them. For example, many virtual manipulation tasks (such as the neurosurgeon's task of cross-sectioning volumetric medical image data) will require a specific view to do the work and will have a referential nature.

  H2: For the Easy task reversing roles of the hands will not have any reliable effect. The Grip effect was much smaller for the Easy task, but was significant at the p < 0.10 level, so one cannot confidently conclude there was no Grip effect. Nonetheless, for practical purposes, lateral asymmetry effects are much less important here.

  H3: The importance of specialization of the roles of the hands increases as the task becomes more difficult. The predicted Grip 5 Task interaction was highly significant, offering strong evidence in favor of H3.

  H4: Haptics fundamentally change the type of motor control required. Taken together, the experimental evidence for H1-H3 further suggests that the motor control required for the Easy conditions, where there was plentiful haptic feedback in the form of physical constraints, fundamentally differed from the Hard conditions.

  The evidence in support of this final hypothesis underscores the performance advantages that are possible when there is haptic feedback to guide the task. Subjects devoted little cognitive effort to perform the Easy task, whereas the Hard task required concentration and vigilance.

  This suggests that passive haptic feedback from supporting surfaces or active haptic feedback from devices such as the Phantom [147] can have a crucial impact for some tasks. This also underscores the difficulty of using a glove to grasp a virtual tool: when there is no physical contact, the task becomes a hand-eye coordination challenge, requiring full visual attention. With haptic feedback, it can be an automatic, subconscious manipulation, meaning that full visual attention can be devoted to a high-level task (such as monitoring an animation) instead of to the "tool acquisition" sub-task. For example, the PolyShop VR application [1] (fig. 2.5 on page 18) uses a physical drafting table as a support surface for 2D interactions, allowing the user to just touch the table to make selections.

  These issues underscore the design tension between physical and virtual manipulation. The design challenge is find ways that real and virtual objects can be mixed to produce something better than either can achieve alone.

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  ¹ I told subjects about the video camera during the experimental debriefing. I obtained signed consent forms from each subject before analyzing the tapes. Subjects had the right to request that the tape be erased immediately.

  ² I would like to acknowledge private communication in which Yves Guiard discussed these issues.

  ³ The circles shown in this figure were 7.5 inches in diameter (outer circle) and 7.0 inches (inner circle) as originally drawn by the subject.

  ⁴ A simple reformulation of Buxton's experiment to produce targets at predictable locations did manage to reproduce the results from Kabbash. I would like to acknowledge personal communication during which Bill Buxton discussed this experiment on the Active Desk.

  ⁵ For bimanual rhythm tapping, conceptually the two hands are working together to produce a single combined rhythm. This task, however, does not address the hypothesis of right-to-left reference in bimanual manipulation.

  ⁶ This also doubled as a lateral preferences assessment, to ensure that each subject actually did prefer the "Preferred" grip to the "Reversed" grip.

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  Copyright © 1996, Ken Hinckley. All rights reserved.