The Effects of Objectives and Constraints on Motor ...

Journal of Motor Behavior, 1992, Vol. 24, No. 2, 173-185

H. G. Williams, M. H. Woollacott, & R. Ivry Keele, S. W., Pokorny, R. A., Corcos, D. M., &Ivry, R. I. (1985). Do perception and motor production share common timing mechanisms: A correlational analysis. Acta Psychologica, 60, 173-191. Lieberman, H., &Pentland, A. (1982). Microcomputer based estimation of psychophysical thresholds: The best PEST. Behavioral Research Methods and Instrumentation, 14, 21-25. Lord, R., & Hulme, C. (1987). Kinaesthetic sensitivity of normal and clumsy children. Developmental Medicine and Child Neurology, 29, 720-725. Morns, J., &Williams, H. G. (1987). Development of central and peripheral components of reaction time in young children. Abstracts of the Annual Conference of the North American Socieryfor the Psychology ofSport and Motor Behavior, Phoenix, AZ. Pentland, A. (1980). Maximum likelihood estimation: The best PEST. Perception and Psychophysics, 28, 377-379. Poeck, K. (1986). The clinical examination for motor apraxia. Neuropsychologia, 24, 128-134. Rosenbaum, D. A., Inhoff A. W., &Gordon, A. M. (1984). Choosing between movement sequences: A hierarchical editor model. Journal of Experimental Psychology: General, 113, 372-393. Schmidt, R. A. (1982). Motor control and learning: A behavioral emphasis. Champaign, IL: Human Kinetics. Sheridan, M. R. (1981). Response programming and reaction time. Journal of Motor Behavior, 13, 161-176. Smyth, T. R., & Glencross, D. (1986). Information processing deficits in clumsy children. Australian Journal of Psychology, 38, 13-22.

Taylor, M., & Creelman, C. (1967). PEST: Efficient estimates of probability functions. Journal of the Acoustical Society of America, 41, 782-787. Taylor, D. C.,& McKinlay, I. A.(1979). Child Care, Health and Development, 5, 167-175. Williams, H. G. (1973). The Williams Gross Motor Control Test battery. Toledo, OH: University of Toledo. Williams, H. G. (1983). Perceptual-motor development in young children. Englewood Cliffs, NJ: Prentice-Hall. Williams, H. G., & Woollacott, M. H.(in press). Speed, consistency, and organization of automatic postural responses in clumsy and normal children. Advances in Research in Motor Development. Wing, A. M.(1977). Effects of type of movement on the temporal precision of response sequences. British Journal of Mathematical and Statistical Psychology, 30, 60-72. Wing, A. M. (1980). The long and short of timing in response sequences. In G. B. Stelmach & 7. Requin (Eds.), Tutorials in motor behavior. New York: North-Holland. Wing, A. M., & Kristofferson, A. B. (1973). Response delays and the timing of discrete motor responses. Perception and Psychophysics, 14, 5-12. Wolff, P. H., Gunnoe, C. E., &Cohen, C. (1983). Associated movements as a measure of developmental age. Developmental Medicine and Child Neurology, 25, 417-429.

The Effects of Objectives and Constraints on Motor Control Strategy in Reciprocal Aiming Movements Jos J. Adam Department of Movement Sciences University of Limburg

Submitted September 12, 1990 Revised March 18, 1991

~

p

~ ~

achieve), whereas the constraints of the movement arise from the extrinsic limitations imposed by the environment and from the intrinsic limitations imposed by the biomechanical and the neurophysiological characteristics of the human body (Fisk & Goodale, 1989). Constraints as determinants of movement have been studied extensively. For example, in the classic studies of Fitts (1954; Fitts &Peterson, 1964), duration of movement was shown to be systematically related to movement distance and target size. Fitts' law has generated much research, and it has been shown to hold under a variety of movement constraints involving different limbs and physical contexts and for different populations (for a review, see Keele, 1981; Meyer, Smith, &Wright, 1982). The role of objective in the control of movement, on the other hand, has received only scant attention. Marteniuk et al. (1987) were the first to investigate explicitly whether the kinematic characteristics of rapid arm movements were dependent upon the intent of the performer. Among other things, Marteniuk and coworkers found a disproportionately longer deceleration phase of a movement when subjects were asked ta pick up a disk to place it carefully in a tight-fitting well than when they were asked to pick up the same object but with the intent of throwing it into a large box. Fisk and Goodale (1989) manipulated instructions to subjects in order to vary the objective of the movement. That is, they varied the speed and accuracy demands of a pointing task by requiring the subjects to point to the target "as quickly as you can," "as accurately as you can," or both "quickly and accurately." The results showed that a significantly smaller proportion of movement time was spent de-

ABSTRACT. The goal of this study was to examine how the kinematics of reciprocal aiming movements were affected by both the objective of the movement and the constraints operating on that movement. In Experiment 1, the objective of the movement was indirectly manipulated by capitalizing on the fact that subjects determine their own accuracy and speed limits, despite uniform task instructions to move as quickly and accurately as possible. A Fitts' type reciprocal aiming paradigm was employed, in which 69 subjects were asked ta move a stylus repetitively between two spatially separated targets. Four tazget widths were orthogonally combined with four movement amplitudes, resulting in 16 conditions. Movements were made on an X-Y digitizing tablet. Based on the mean variable error produced on both targets, subjects were differentiated post hoc into three movement objective groups: speed, accuracy, and speed-plus-accuracy. Kinematic analyses revealed that the programming and execution of movements were systematically influenced by both the movement objective and the movement constraints. That is, movement time, peak velocity, dwell time, acceleration and deceleration time, normalized acceleration and normalized deceleration vaned systematically as a function of both the speed—accuracy movement objective and the movement constraints of target size and movement distance. Moreover, the consequences of changing the constraints of the movement were affected by an interaction with the objective of the movement. In Experiment 2, the objective of the movement was directly manipulated by varying speed and/or accuracy instructions to subjects. The basic results of Experiment 1 were substantiated. Overall, the results were consistent with the view that motor control is dependent upon sensory consequences. Key words: human movement, kinematics, speed and accuracy, strategies ecently, several authors have pointed out that in the study of motor control, it is important to consider both the objective and constraints of the movements (Arbib, 1985; Corcos, Gottlieb, & Agarwal, 1988; Fisk & Goodale, 1989; Marteniuk, MacKenzie, Jeannerod, Athenes, & Dugas, 1987; Nelson, 1983; Newell, 1989). The objective of the movement originates from the intentions and goals of the performer (i.e., what the performer is trying to

1 ~2

Journal of Motor Behavior

Correspondence address: Department of Movement Sciences, University of Limburg, P.O. Box 616, 6200 MD Maastricht, The Netherlands. (E-mail: JOS. ADAM @BW. RULIMBURG. NL) 1 ~3

J. J. Adam celerating in the speed condition than in the other two conditions. Taken together, the results of these two studies seem to indicate that the objective of a movement (that is, the performer's intent), has important consequences for the kinematic properties of the movement. The main goal of the present study was to elucidate further the way in which the objective of a movement can affect its execution. In Experiment 1, manipulation of movement objective was accomplished in an indirect and post hoc manner, based on the notion of speed-accuracy tradeoff. That is, performance instructions in rapid aiming tasks often require subjects to move as quickly and accurately as possible (e.g., Glencross &Barrett, 1983; MacKenzie, Marteniuk, Dugas, Liske, & Eickmeier, 1987; Meyer, Abrams, Kornblum, Wright, &Smith, 1988). These instructions, however, are potentially very confusing, ambiguous, and in some sense even mutually exclusive, because speed and accuracy are inversely related (Fitts, 1954; Fitts & Peterson, 1964; Pachella, 1974; Pew, 1969). It is not unlikely, therefore, that subjects try to find some reasonable compromise or tradeoff between these competing objectives (Nelson, 1983). One cannot be confident, however, that subjects will reach the same compromise. This point has also been made by Corcos et al.,(1988), who proposed that human voluntary movement involves a strategy or set of internal rules imposed by the subject that affects movement outcome. They warned that "significant elements of this strategy, such as how accurately to perform the task, may not be recognized or controlled in many movement paradigms, in spite of uniform instructions to subjects and similar apparatus"(p. 255). Newell(1989) essentially made the same point when he contented that "constraints to action have to be viewed from the perspective of the performer rather than from reliance on the external physical description of the constraints"(p. 94). In Experiment 1, we asked 69 subjects to move a stylus repetitively between two circular targets of equal width, separated by a certain amplitude, as quickly and accurately as possible for 15 s. Four target widths were orthogonally combined with four amplitudes, resulting in 16 movement conditions. As argued before, the ambiguous nature of these task instructions may allow subjects to implement their own accuracy criteria and to perform according to their own accuracy standards. In other words, depending on how a subject perceives the task demands, the objective of the movement can vary from an emphasis on accuracy to an emphasis on speed. To determine individual speed and/ or accuracy biases, we devised a measure of bias toward accuracy, operationally defined by the mean variable error produced on both left and right targets, collapsed over the 16 movement conditions. Variable error(VE) is the withinsubject standard deviation of the movement spatial endpoints about their own mean and is also known as the effective target width (Welford, 1968). Based on this criterion of bias toward accuracy, we placed one thud of the subjects in the accuracy group (the 23 subjects with the lowest mean VE), one third of the subjects in the speed group (the 23 174

subjects with the highest mean VE), and one third in the speed-plus-accuracy group (the remaining 23 subjects). In summary, the object of this investigation was to study how different speed and/or accuracy biases (that is, movement objectives) might affect the kinematic properties of reciprocal aiming movements. Further, manipulation of the external constraints of movement amplitude and target size would make it possible to observe how changes in the objective of a movement interact with changes in the constraints of that movement. EXPERIMENT 1 Method Subjects Sixty-nine undergraduate students, 30 men and 39 women, of the University of Alberta participated in this study (mean age, 21.3 years; range, 18 to 31). All subjects were unpaid volunteers, wrote with their right hand, and had normal or corrected to normal vision. None of them had any experience with the experimental task or the logic behind the study. Apparatus A 60- x 60-cm X-Y digitizing tablet (Supergrid, Summagraphics Corporation), mounted on a 85-cm high table, was used in conjunction with a PDP 10/11 laboratory computer to record the Time x Coordinate data pairs. The sampling rate was 100 Hz, and measuring accuracy of the digitizing tablet was set at 0.1 mm. Procedure Subjects stood facing a table on which the X-Y digitizing tablet was mounted. They were asked to hold a stylus in a pen-grip fashion and to slide the stylus smoothly and repetitively between two identically sized circular targets as quickly and accurately as possible for a duration of 15 s. Four target widths (diameters of 3, 6, 12, and 24 mm)were orthogonally combined with four amplitudes (40, 80, 160, 320 mm), resulting in 16 movement conditions. The order of those was determined by acomputer-generated random sequence and was the same for all subjects. A separate target sheet was constructed for each condition, consisting of two equally sized circular targets horizontally separated by a given amplitude. Amplitude,was taken as the distance between the centers of the two targets. The target sheets were placed on top of the X-Y digitizing tablet and covered by a piece of clear Plexiglas. Alignment guides on the target sheets and the digitizing tablet were used to ensure correct positioning. Subjects were instructed to position themselves such that their body midline was biased toward the target opposite their right hand. In each condition, subjects were given a short familiarization period, including a 5-s practice bout. A single trial bout of 15 s was then given. At the beginning of each trial, subjects were asked to place the stylus on the right target. The subjects were instructed to start moving in response to an auditory start signal and to Journal of Motor Behavior

J.J. Adam celerating in the speed condition than in the other two conditions. Taken together, the results of these two studies seem to indicate that the objective of a movement (that is, the performer's intent), has important consequences for the kinematic properties of the movement. The main goal of the present study was to elucidate further the way in which the objective of a movement can affect its execution. In Experiment 1, manipulation of movement objective was accomplished in an indirect and post hoc manner, based on the notion of speed-accuracy tradeoff. That is, performance instructions in rapid aiming tasks often require subjects to move as quickly and accurately as possible (e.g., Glencross &Barrett, 1983; MacKenzie, Marteniuk, Dugas, Liske, & Eickmeier, 1987; Meyer, Abrams, Kornblum, Wright, &Smith, 1988). These instructions, however, are potentially very confusing, ambiguous, and in some sense even mutually exclusive, because speed and accuracy are inversely related (Fitts, 1954; Fitts & Peterson, 1964; Pachella, 1974; Pew, 1969). It is not unlikely, therefore, that subjects try to find some reasonable compromise or tradeoff between these competing objectives (Nelson, 1983). One cannot be confident, however, that subjects will reach the same compromise. This point has also been made by Corcos et al.,(1988), who proposed that human voluntary movement involves a strategy or set of internal rules imposed by the subject that affects movement outcome. They warned that "significant elements of this strategy, such as how accurately to perform the task, may not be recognized or controlled in many movement paradigms, in spite of uniform instructions to subjects and similar apparatus"(p. 255). Newell(1989) essentially made the same point when he contented that "constraints to action have to be viewed from the perspective of the performer rather than from reliance on the external physical description of the constraints"(p. 94). In Experiment 1, we asked 69 subjects to move a stylus repetitively between two circular targets of equal width, separated by a certain amplitude, as quickly and accurately as possible for 15 s. Four target widths were orthogonally combined with four amplitudes, resulting in 16 movement conditions. As argued before, the ambiguous nature of these task instructions may allow subjects to implement their own accuracy criteria and to penfarm according to their own accuracy standards. In other words, depending on how a subject perceives the task demands, the objective of the movement can vary from an emphasis on accuracy to an emphasis on speed. To determine individual speed and/ or accuracy biases, we devised a measure of bias toward accuracy, operationally defined by the mean variable error produced on both left and right targets, collapsed over the 16 movement conditions. Variable error (VE) is the withinsubject standard deviation of the movement spatial endpoints about their own mean and is also known as the effective target width (Welford, 1968). Based on this criterion of bias toward accuracy, we placed one third of the subjects in the accuracy group (the 23 subjects with the lowest mean VE), one third of the subjects in the speed group (the 23 174

Objectives and Constraints in Aiming Movements subjects with the highest mean VE), and one third in the speed-plus-accuracy group (the remaining 23 subjects). In summary, the object of this investigation was to study how different speed and/or accuracy biases (that is, movement objectives) might affect the kinematic properties of reciprocal aiming movements. Further, manipulation of the external constraints of movement amplitude and target size would make it possible to observe how changes in the objective of a movement interact with changes in the constraints of that movement. EXPERIMENT 1

~

~ ~ i

Subjects Sixty-nine undergraduate students, 30 men and 39 women, of the University of Alberta participated in this study (mean age, 21.3 years; range, 18 to 31). All subjects were unpaid volunteers, wrote with their right hand, and had normal or corrected to normal vision. None of them had any experience with the experimental task or the logic behind the study. Apparatus '


VE (mm)

350

Movements were analyzed off-line, using a nonintegrative computer program. The following dependent measures were calculated: (a) movement time (starting with the first detectable displacement and ending with the first zero displacement in one time frame of 10 ms); (b) peak velocity (largest displacement in one time frame of 10 ms); (c) acceleration time (time from initiation of a movement to that of maximum velocity); (d) deceleration time (time from maximum velocity to zero velocity at the end of the movement;(e) dwell time (ttie amount of time the effective speed of the stylus was zero during the reversal of a movement on the target); (f) variable error as a measure of movement accuracy (the within-subject standard deviation of the movement endpoints about their own mean). These dependent variables were formed from the average of the separate analyses of the individual movements to both left and right targets, for all movement conditions. Repeated-measures analyses of variance (ANOVAs), using the GeisserGreenhouse correction (Keppel, 1982) to control for violations of assumptions of homogeneity of variance and covariance, were calculated.

MT

6.5

5.5

250

4.5

goo 3.5

i 50

B: MT AS A FUNCTION OF VE VE (mm) 12.5

R=-0.84 10

5

~

Table 1 provides a summary of the main kinematic measures for the three movement objective groups, averaged over the 16 movement conditions. Significant differences between the three movement objective groups were evident for all kinematic variables (Tukey test on means, p < .O1 for all comparisons). That is, subjects biased toward accuracy systematically moved slower by reducing peak velocity and by spending more June 1992, Vol. 24, No. 2

2.5

ACCURACY

MOVEMENT OBJECTIVE

Manipulation of Movement Objective

E$'ects of Movement Objective on Kinematics

SPEED/ACCURACY

SPEED

Results

Manipulation of movement objective was established by a selective post hoc differentiation of subjects into one of three groups (speed, accuracy, or speed-plus-accuracy), based on the criterion of mean VE. The outcome of this manipulation can be seen in Figure la. The accuracy group produced very accurate but slow movements, whereas the speed group produced very fast but inaccurate movements. This speed—accuracy tradeoff phenomenon was statistically confirmed by a strong negative between-subject correlation between movement time and variable error(r = — .84)(see Figure lb). We also calculated, for the whole group of subjects, correlations for the variable movement time between all 16 movement conditions. These correlations were generally very high, with a mean correlation of .71, demonstrating that the relative position of the subjects on the speed—accuracy continuum remained constant during all 16 movement conditions.

- 7,5

O VE

300

7.5

Procedure Subjects stood facing a table on which the X-Y digitizing tablet was mounted. They were asked to hold a stylus in a pen-grip fashion and to slide the stylus smoothly and repetitively between two identically sized circular targets as quickly and accurately as possible for a duration of 15 s. Four target widths (diameters of 3, 6, 12, and 24 mm)were orthogonally combined with four amplitudes (40, 80, 160, 320 mm), resulting in 16 movement conditions. The order of those was determined by acomputer-generated random sequence and was the same for all subjects. A separate target sheet was constructed for each condition, consisting of two equally sized circular targets horizontally separated by a given amplitude. Amplitude was taken as the distance between the centers of the two targets. The target sheets were placed on top of the X-Y digitizing tablet and covered by a piece of clear Plexiglas. Alignment guides on the target sheets and the digitizing tablet were used to ensure correct positioning. Subjects were instructed to position themselves such that their body midline was biased toward the target opposite their right hand. In each condition, subjects were given a short familiarization period, including a 5-s practice bout. A single trial bout of 15 s was then given. At the beginning of each trial, subjects were asked to place the stylus on the right target. The subjects were instructed to start moving in response to an auditory start signal and to

A: SPEED-ACCURACY TRADE OFF MT (ms)

Data Analysis

Method

A 60- x 60-cm X-Y digitizing tablet (Supergrid, Summagraphics Corporation), mounted on a 85-cm high table, was used in conjunction with a PDP 10/11 laboratory computer to record the Time x Coordinate data pairs. The sampling rate was 100 Hz, and measuring accuracy of the digitizing tablet was set at 0.1 mm.

keep the stylus in contact with the Plexiglas surface. Fifteen seconds later, a second tone ended the trial. No other inforrraation was provided to the subject.

~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~~~~ ~

~ ~~~ ~

2.5

0 0

100

200

300

400

500

MOVEMENT TIME (ms) FIGURE 1.(a) Mean movement time (MT) and mean variable error (VE), for the three movement objective groups. (b) Mean movement time as a function of mean variable error, for a1169 subjects.

time in acceleration and deceleration; moreover, they produced movements with peak velocities almost half as large as those produced by subjects biased toward speed. The percentage of movement time spent in acceleration (normalized acceleration) and deceleration (normalized deceleration) also varied markedly between the three movement objective groups (see Figure 2). The speed group spent a larger proportion of movement time in acceleration than the accuracy group (52.5% versus 43.4%); correspondingly, the accuracy group spent a bigger proportion of movement time in deceleration than the speed group (56.6% versus 175

J. J. Adam

TABLE 1 Mean Values of Different Movement Characteristics for the Three Movement Objective Groups

Measures

Speed

Speedplusaccuracy

Movement time (ms) Variable error(mm) Peak velocity (cm/s) Acceleration time (ms) Deceleration time (ms) Normalized acceleration(%) Normalized deceleration(%) Dwell time (ms)

173 7.6 141 91 82 52.5 47.5 12.7

250 5.5 104 117 133 46.8 53.2 20.0

ACCELERATION /DECELERATION TIME (ms) 200 ~ ACCELERATION (ms) 0 DECELERATION (ms)

Accuracy

F(2, 66)

p

334 3.6 78 145 189 43.4 56.6 28.4

56.8 128.4 69.5 65.7 47.6 38.4 38.4 33.4

.001 .001 .001 .001 .001 .001 .001 .001

47.5%). Dwell time was also affected by movement objective. The accuracy group spent more time dwelling on the target than the speed-plus-accuracy group, which, in turn, spent more time than the speed group on the target. The above results provide clear evidence that the kinematic features of reciprocal aiming movements are influenced by the movement objective.

150

Effects of Movement Constraints on Kinematics goo

50

SPEED

SPEED/ACCURACY

ACCURACY

MOVEMENT OBJECTIVE

NORMALIZED ACC./ DEC.(%) 60 ~ NORM. ACC.(%)

55

o NORM oE~ ~%~

50

45

40 SPEED

SPEED/ACCURACY

ACCURACY

MOVEMENT OBJECTIVE

FIGURE 2.(a) Mean absolute acceleration and deceleration time for the three movement objective groups. (b) Mean normalized acceleration and deceleration time for the three movement objective groups.

176

The effects of the movement constraints, target size and amplitude, on the main movement kinematics are presented in Tables 2 and 3, respectively. Decreasing target size as well as increasing amplitude resulted in progressively longer movement times, longer dwell times, longer acceleration and deceleration phases, and larger proportions of movement time spent in deceleration. However, whereas increasing amplitude resulted in larger peak velocities, decreasing target size resulted in smaller peak velocities. Interaction Between Movement Objective and Movement Constraints For almost all kinematic variables, significant two-way interactions were found between movement objective and movement amplitude(p < .O1) and between movement objective and target size (p < .25).' Some of these interactions are illustrated in Figures 3 and 4, where the kinematic variables movement time, dwell time, deceleration time, and normalized deceleration are depicted for the three movement objective groups as a function of target size and movement amplitude, respectively. In general, these interactions indicated that the main effects of target size and amplitude were magnified when the intent of the performer was to be accurate instead of fast. That is, when speed was the main movement objective, target size and amplitude exerted much less influence on the kinematic parameters than when the movement goal was to be accurate. Discussion The purpose of this study was to determine the effects of movement objective and movement constraints on the kiJournal of Motor Behavior

Objectives and Constraints in Aiming Movements

J. J. Adam

TABLE 2 Mean Values of Different Movement Characteristics for the Four Target Size Conditions

TABLE 1 Mean Values of Different Movement Characteristics for the Three Movement Objective Groups

Measures

Speed

Speedplusaccuracy

Movement time (ms) Variable error(mm) Peak velocity (cm/s) Acceleration time (ms) Deceleration time (ms) Normalized acceleration(%) ~ Normalized deceleration(%) Dwell time (ms)

173 7.6 141 91 82 52.5 47.5 12.7

250 5.5 104 117 133 46.8 53.2 20.0

ACCELERATION /DECELERATION TIME (ms) 200 ~ ACCELERATION (ms) D DECELERATION (ms) 150

Tazget size(mm) Accuracy

F(2, 66)

p

334 3.6 78 145 189 43.4 56.6 28.4

56.8 128.4 69.5 65.7 47.6 38.4 38.4 33.4

.001 .001 .001 .001 .001 .001 .001 .001

47.5%). Dwell time was also affected by movement objective. The accuracy group spent more time dwelling on the target than the speed-plus-accuracy group, which, in turn, spent more time than the speed group on the target. The above results provide clear evidence that the kinematic features of reciprocal aiming movements are influenced by the movement objective. Effects of Movement Constraints on Kinematics

100

50 SPEED

SPEED/ACCURACY

ACCURACY

MOVEMENT OBJECTIVE

NORMALIZED ACC./ DEC. (~o) 60 NORM. ACC.(%) 55

0 NORM. DEC.(%)

50

45

40 SPEED

SPEED/ACCURACY

ACCURACY

MOVEMENT OBJECTIVE

FIGURE 2.(a) Mean absolute acceleration and deceleration time for the three movement objective groups. (b) Mean normalized acceleration and deceleration time for the three movement objective groups.

176

The effects of the movement constraints, target size and amplitude, on the main movement kinematics are presented in Tables 2 and 3, respectively. Decreasing target size as well as increasing amplitude resulted in progressively longer movement times, longer dwell times, longer acceleration and deceleration phases, and larger proportions of movement time spent in deceleration. However, whereas increasing amplitude resulted in larger peak velocities, decreasing target size resulted in smaller peak velocities. Interaction Between Movement Objective and Movement Constraints For almost all kinematic variables, significant two-way interactions were found between movement objective and movement amplitude(p < .O1) and between movement objective and target size (p < .25).' Some of these interactions are illustrated in Figures 3 and 4, where the kinematic variables movement time, dwell time, deceleration time, and normalized deceleration are depicted for the three movement objective groups as a function of target size and movement amplitude, respectively. In general, these interactions indicated that the main effects of target size and amplitude were magnified when the intent of the performer was to be accurate instead of fast. That is, when speed was the main movement objective, target size and amplitude exerted much less influence on the kinematic parameters than when the movement goal was to be accurate. Discussion The purpose of this study was to determine the effects of movement objective and movement constraints on the kiJournal of Motor Behavior

Measures Movement time (ms) Variable error(mm) Peak velocity (cm/s) Acceleration time (ms) Deceleration time(ms) Normalized acceleration(%) Normalized deceleration(%) Dwell time (ms)

3

6

12

24

F(3, 198)

p

332 4.6 86 141 190 46.5 53.5 30.0

284 4.9 94 129 155 49.2 50.8 22.3

226 5.8 112 112 114 52.1 47.9 16.0

169 7.0 138 89 80 54.5 45.5 12.2

293.1 91.6 300.9 278.3 214.1 145.3 145.3 138.1

.001 .001 .001 .001 .001 .001 .001 .001

TABLE 3 Mean Values of Different Movement Characteristics for the Four Movement Amplitude Conditions Amplitude(mm) Measures Movement time (ms) Variable error(mm) Peak velocity (cm/s) Acceleration time (ms) Deceleration time (ms) Normalized acceleration(%) Normalized deceleration(%) Dwell time (ms)

40

80

160

320

F(3,198)

p

120 3.1 67 62 58 54.0 46.0 17.6

179 4.7 93 87 92 51.7 48.3 18.8

281 6.9 119 130 151 49.5 50.5 20.6

430 7.6 151 191 238 46.9 53.1 24.4

988.2 169.0 415.3 1498.3 606.8 153.5 153.5 35.1

.001 .001 .001 .001 .001 .001 .001 .001

nematic properties of reciprocal aiming movements. The objective of the movement was inferred post hoc and was based on the functional behavior of subjects in terms of their movement accuracy. That is, despite uniform instructions to move as accurately and quickly as possible, subjects determined their own accuracy limits and movement speed. Hence, the 69-subject pool was differentiated into one group of subjects who emphasized speed at the cost of accuracy, another group who emphasized accuracy at the cost of speed, and a third group who emphasized both. How were these different movement objectives manifested in the kinematic parameters of the generated movements? First of all, the speed group produced movements with twice as large peak velocities as those of the accuracy group (140.9 versus 77.7 cm/s, respectively). Second, acceleration time and deceleration time were longer for the accuracy group than for the speed group. As well, acceleration time was longer than deceleration time for the speed group (91.1 versus 82.3 ms, respectively), whereas for the accuracy group, deceleration time was longer than acceleration time (188.8 versus 145.0 ms, respectively). Expressed in terms of proportion of movement time, the speed June 1992, Vol. 24, No. 2

group spent 47.5% of their movement time in acceleration and 52.5% in deceleration, whereas the accuracy group spent 43.4% in acceleration and 56.6% in deceleration. Third, the analysis of dwell tune indicated that the subjects biased toward speed remained on the target for only short periods of time (12.7 ms), whereas subjects biased toward accuracy maintained target contact over twice as long (28.4 ms) periods of time. Taken together, the above results justify the conclusion that the objective of reciprocal aiming movements has important consequences for its kinematic control parameters. A similar conclusion has been reached by Marteniuk et al. (1987) for discrete grasping movements, and by Fisk and Goodale (1989) for discrete pointing movements. Variations in the constraints target size and amplitude were found to affect all kinematic measures. Striking was the finding that as the task constraints demanded more precise movements, subjects increasingly spent more time decelerating than accelerating. This finding is in agreement with previous studies examining the effects of target size on rapid, goal-directed movements (MacKenzie et al., 1987; Marteniuk et al., 1987; Milner & Ijaz, 1990). 177

J. J. Adam

DWELL TIME

MOVEMENT TIME 600MT (ms)

60DT (ms)

500

50

MOVEMENT OBJECTIVE — SPEED ~ SPEED/ACCURACY Q QQ

4O

300

30

200

20

100

10 0

0 3 TARGET SIZE (mm)

3

24

DECELERATION TIME 300

~ ACCURACY

TARGET SIZE (mm)

24

NORMALIZED DECELERATION 60ND (%)

DEC T. (ms)

250 55 200 50

150 100

45 50 40


24

3

TARGET SIZE (mm)

24

FIGURE 3. Mean movement time, dwell time, deceleration time, and normalized deceleration time, as a function of tazget size, for the three movement objective groups.

Moreover, it was found that as the task constraints demanded longer movements, subjects increasingly spent more time decelerating than accelerating. This finding is not in agreement with data reported by MacKenzie et al. (1987). Employing a discrete tapping task and a similar range of amplitudes and target sizes, they found that amplitude had no effect on the proportion of movement time spent in deceleration. This discrepancy perhaps may be related to the fact that in the present experimental conditions, subjects made reciprocal sliding movements over the sur-

face of a digitizer, whereas in MacKenzie et al. (1987), subjects performed discrete tapping movements; that is, in MacKenzie et al. (1987), subjects started from a home position and moved through the air to collidé with a specified 178

target zone. In this situation, the movement is not completely self-terminating, in that part of the deceleration action is accomplished passively through target collision. In the present experimental paradigm, on the other hand, no downward collision with the target area was allowed, creating the need for active control of the whole deceleration phase. The present finding that subjects increasingly spent more time decelerating than accelerating, with increasing amplitude, may indicate that the substantially larger peak velocities associated with longer movements require longer decelerative control to achieve intended endpoint accuracy (see, for a similar argument, Milner & Ijaz, 1990). The present study not only demonstrated the effects of movement objective and movement constraints on the exeJournal of Motor Behavior


J.J. Adam

600MT (ms)

60 DT (ms)

5OO

5O

DWELL TIME

MOVEMENT TIME

DWELL TIME

MOVEMENT TIME

60 DT (ms)

600MT (ms)

MOVEMENT OBJECTIVE

MOVEMENT OBJECTIVE rj~~j~

-- SPEED

~— SPEED ~- SPEED/ACCURACv

~ SPEED/ACCURACY

400

40

30

300

30

200

20

200

20

100

10

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O

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~ ACCURACY

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350DEC. T. (ms) 300

250 55

55

250

200 200 150

50

50 150

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45 50

O

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TARGET SIZE (mm)

24

FIGURE 3. Mean movement time, dwell time, deceleration time, and normalized deceleration time, as a function of target size, for the three movement objective groups.

Moreover, it was found that as the task constraints demanded longer movements, subjects increasingly spent more time decelerating than accelerating. This finding is not in agreement with data reported by MacKenzie et al. (1987). Employing a discrete tapping task and a similar range of amplitudes and target sizes, they found that amplitude had no effect on the proportion of movement time spent in deceleration. This discrepancy perhaps may be related to the fact that in the present experimental conditions, subjects made reciprocal sliding movements over the surface of a digitizer, whereas in MacKenzie et al. (1987), subjects performed discrete tapping movements; that is, in MacKenzie et al. (1987), subjects started from a home position and moved through the air to collidé with a specified 178

45

target zone. In this situation, the movement is not completely self-terminating, in that part of the deceleration action is accomplished passively through target collision. In the present experimental paradigm, on the other hand, no downward collision with the target area was allowed, creating the need for active control of the whole deceleration phase. The present finding that subjects increasingly spent more time decelerating than accelerating, with increasing amplitude, may indicate that the substantially larger peak velocities associated with longer movements require longer decelerative control to achieve intended endpoint accuracy (see, for a similar argument, Milner & Ijaz, 1990). The present study not only demonstrated the effects of movement objective and movement constraints on the exeJournal of Motor Behavior

O

40

AMPLITUDE (mm)

320

40

40

AMPLITUDE (mm)

320

FIGURE 4. Mean movement time, dwell time, deceleration time, and normalized deceleration time, as a function of amplitude, for the three movement objective groups.

cution of reciprocal aiming movements but it also showed that variations in the movement objective interacted with variations in the movement constraints in their effects upon movement kinematics. For instance, the normalized deceleration data as a function of target size (see Figure 3) indicated that the speed group tended to vary the relative duration of the deceleration phase according to target size, with longer durations at smaller target sizes. The range of this variation, however, was limited (from 44.0% to 47.5%). This effect was much more pronounced for subjects biased toward accuracy: They showed a range three times as large, from 47.3% to 59.3%. The analysis of dwell time also indicated clearly that the objective of the movement interacted with the constraints of the movement. SubJune 1992, Vol. 24, No. 2

jects biased toward speed demonstrated similar and minimal dwell times in all movement conditions. Subjects biased toward accuracy, on the other hand, dwelled systematically on the target, according to target size and, to a lesser extent, according to amplitude. That is, the smaller the targets the longer the dwell times, and the longer the amplitude the longer the dwell times. In conclusion, for the reciprocal aiming paradigm, the consequences of changing the constraints of the movement are affected by an interaction with the objective of the movement. One possible caveat in the above experiment concerns the manipulation and, therefore, interpretation of movement objective. We realize that the indirect and post hoc manipulation of movement objective made the study correlational 179

,J. J. Adam rather than experimental. To counteract the possible claim that our manipulation of movement objective reflects some kind of individual difference (e.g., strength) instead of the strategic intent to be accurate and/or fast, we conducted a second experiment in which movement objective was directly manipulated by varying instructions to subjects.

ment objective groups in Experiment 1. From Figure 5, it is clear that movement time and VE are indeed inversely related, such that subjects trade movement speed for endpoint accuracy to form aspeed—accuracy tradeoff continuum.

EXPERIMENT 2

Significant differences between the two instruction conditions were evident for all kinematic variables (p < .O1). These findings are summarized in Table 4. As in Experiment 1, when the movement objective was to be accurate instead of fast, subjects produced longer movement times with smaller peak velocities, spent a larger proportion of movement time decelerating than accelerating, and they spent more time dwelling on the target.

In this experiment, we manipulated movement objective experimentally by changing the instructions as to how accurately or rapidly subjects were required to execute reciprocal aiming movements. Using awithin-subject design, we varied the instructions to subjects from a condition emphasizing speed to a condition in which movement accuracy was the main movement goal. Method Subjects The subjects were 20 students, 10 male and 10 female, of the University of Limburg (mean age, 25.7 years; range, 21 to 32). They were all unpaid volunteers, wrote with their right hand, and had normal or corrected to normal vision. Apparatus A 61- x 91-cm X-Y digitizing tablet (Scriptel Corporation), mounted on a 80-cm high table, was used in conjunction with a MS-DOS AT computer to record Timex Coordinate data pairs. Sampling rate was 70 Hz, and spatial accuracy of the digitizing tablet was set at 0.1 mm. Procedure Four movement amplitudes (40, 80, 160, and 320 mm) were factorially combined with two target sizes (3 and 24 mm), resulting in eight movement conditions. Subjects had to perform these eight movement conditions under two instructions. In the accuracy instruction condition, subjects were explicitly asked to emphasize accuracy rather than speed, and in the speed instruction to emphasize speed rather than accuracy. The order in which subjects received these two instruction conditions was counterbalanced; half of the subjects performed the eight movement conditions under the accuracy instruction first, and the other half performed the eight movement conditions under the speed instruction first. Order of movement conditions within the instruction conditions vaned randomly. Otherwise, the procedure was the same as in Experiment 1. Results Manipulation of Movement Objective In the speed condition, subjects moved faster than in the accuracy condition (280 versus 468 ms); correspondingly, in the speed condition, subjects were less accurate than in the accuracy condition (VE of 4.5 and 2.8 mm, respectively). These results are presented in Figure 5, together with the mean movement times and VEs of the three move180

Effects of Movement Objective on Kinematics

Effects of Movement Constraints on Kinematics The effects of the movement constraints—amplitude and target size—on the principal movement characteristics are presented in Table 5. Increasing movement amplitude as well as decreasing target size was manifested in progressively longer movement times, longer dwell times, larger acceleration and deceleration phases, and larger proportions of movement time spent in deceleration. These results replicate exactly those found in Experiment 1. Interaction Between Movement Objective and Movement Constraints For all kinematic parameters, movement objective and movement amplitude, and movement objective and target size, interacted significantly (p < .O1). Some of these interactions are shown in Figures 6 and 7, where the kine-

SPEED-ACCURACY TRADE OFF EXPERIMENT 1 and 2 500

VE (mm)

MT (ms)

450

~ MT

o vE

400

~5 ~

350

05 5.5

300 - 4.5

250 ~

200 ~ 50

,~sP

,sP.iac. z~sP ,~Aa MOVEMENT OBJECTIVE

~ z Ac.

3.5 2.5

FIGURE 5. Mean movement time (MT) and mean variable error (VE), for the three movement objective groups in Experiment 1 and for the two movement objective conditions in Experiment 2. Note: The numbers 1 and 2 in the values on the x-axis refer to Experiments 1 and 2, respectively; SP. stands for speed as movement objective and AC. for accuracy as movement objective.


J. J. Adam


rather than experimental. To counteract the possible claim that our manipulation of movement objective reflects some kind of individual difference (e.g., strength) instead of the strategic intent to be accurate and/or fast, we conducted a second experiment in which movement objective was directly manipulated by varying instructions to subjects.

ment objective groups in Experiment 1. From Figure 5, it is clear that movement time and VE are indeed inversely related, such that subjects trade movement speed for endpoint accuracy to form aspeed-accuracy tradeoff continuum. E$'ects of Movement Objective on Kinematics

EXPERIMENT 2 In this experiment, we manipulated movement objective experimentally by changing the instructions as to how accurately or rapidly subjects were required to execute reciprocal awning movements. Using awithin-subject design, we varied the instructions to subjects from a condition emphasizing speed to a condition in which movement accuracy was the main movement goal. Method Subjects The subjects were 20 students, 10 male and 10 female, of the University of Limburg (mean age, 25.7 years; range, 21 to 32). They were all unpaid volunteers, wrote with their right hand, and had normal or corrected to normal vision. Apparatus A 61- x 91-cm X-Y digitizing tablet (Scriptel Corporation), mounted on a 80-cm high table, was used in conjunction with a MS-DOS AT computer to record Timex Coordinate data pairs. Sampling rate was 70 Hz, and spatial accuracy of the digitizing tablet was set at 0.1 mm. Procedure

Significant differences between the two instruction conditions were evident for all kinematic variables (p < .O1). These findings are summarized in Table 4. As in Experiment 1, when the movement objective was to be accurate instead of fast, subjects produced longer movement times with smaller peak velocities, spent a larger proportion of movement time decelerating than accelerating, and they spent more tine dwelling on the target. Effects of Movement Constraints on Kinematics The effects of the movement constraints-amplitude and target size-on the principal movement characteristics are presented in Table 5. Increasing movement amplitude as well as decreasing target size was manifested in progressively longer movement times, longer dwell times, larger acceleration and deceleration phases, and larger propartions of movement time spent in deceleration. These results replicate exactly those found in Experiment 1.

matic variables-movement time, dwell time, deceleration time, and normalized deceleration time-are presented for the two instruction conditions as a function of target size and movement amplitude, respectively. As in Experiment 1, compared with the speed condition, decreasing target size and increasing amplitude disproportionally affected all movement parameters in the accuracy condition. Again, this pattern of results is the same as that found in Experiment 1. Discussion The aim of Experiment 2 was to substantiate the main findings of Experiment 1, by using a direct and experimental manipulation of movement objective instead of one that was indirect and correlational. The results demonstrated that when movement objective was directly varied by means of task instructions emphasizing either speed or accuracy, the kinematic properties of the resulting movements were very similar to those of Experiment 1. This successful replication bolsters our post hoc, between-subject manipulation of movement objective in Experiment 1, and, therefore, we may be more confident that the results of that experiment regarding the effects of movement objective on the kinematics of reciprocal aiming movements are valid.

Interaction Between Movement Objective and Movement Constraints

TABLE 4 Mean Values of Different Movement Characteristics for the Two Instruction Conditions

For all kinematic parameters, movement objective and movement amplitude, and movement objective and target size, interacted significantly (p < .O1). Some of these interactions are shown in Figures 6 and 7, where the kine-

Measures Movement time (ms) Variable error(mm) Peak velocity (cmis) Acceleration time (ms) Deceleration rime (ms) Normalized acceleration(%) Normalized deceleration(%) Dwell time (ms)

Four movement amplitudes (40, 80, 160, and 320 mm) were factorially combined with two target sizes (3 and 24 mm), resulting in eight movement conditions. Subjects had to perform these eight movement conditions under two instructions. In the accuracy instruction condition, subjects were explicitly asked to emphasize accuracy rather than speed, and in the speed instruction to emphasize speed rather than accuracy. The order in which subjects received these two instruction conditions was counterbalanced; half of the subjects performed the eight movement conditions under the accuracy instruction first, and the other half performed the eight movement conditions under the speed instruction first. Order of movement conditions within the instruction conditions varied randomly. Otherwise, the procedure was the same as in Experiment 1.

Speed

Accuracy

F(1, 19)

p

280 4.5 127 142 138 53.9 46.1 24.6

468 2.8 91 204 264 481 51.9 56.2

108.1 98.6 170.5 109.4 92.3 91.2 91.2 103.5

.001 .001 .001 .001 .001 .001 .001 .001

TABLE 5 Mean Values of Different Movement Characteristics for the Two Target Size Conditions and the Four Movement Amplitude Conditions Target size (mm) Measures

Results

Movement time (ms) Variable error(mm) Peak velocity (cm/s) Acceleration time (ms) Deceleration time (ms) Normalized acceleration(%) Normalized deceleration(%) Dwell time (ms)

Manipulation of Movement Objective In the speed condition, subjects moved faster than in the accuracy condition (280 versus 468 ms); correspondingly, in the speed condition, subjects were less accurate than in the accuracy condition (VE of 4.5 and 2.8 mm, respectively). These results are presented in Figure 5, together with the mean movement times and VEs of the three move180

GENERAL DISCUSSION The results of these experiments imply that movement objective (speed and/or accuracy bias) interacts strongly with the movement constraints of target size and movement distance on the kinematic makeup of rapid reciprocal aiming movements. When the intent of the performer is to make accurate movements, the resulting movement profiles and, in particular, the normalized deceleration and acceleration phases as well as the dwell times depend heavily upon the size of the targets and the distance between them. When the intent of the performer is to move rapidly instead of accurately, the resulting movement profiles also depend on these external constraints, but in a less pronounced manner. What are the implications of these results for motor control theory? Clearly, the present findings are not compatible with the concept of invariance in relative time, which supports aview of motor control in which a general motor program produces specific movements by adjusting a scalable parameter in the time domain (e.g., Meyer et al., 1982; Munhall, Ostry, & Parush, 1985). The analyses of the proportions of movement time spent in acceleration and deceleration indicate that as the task constraints or the movement objective (or both) changes, the symmetry of the movement, that is, the ratio of acceleration to deceleration,


June 1992, Vol. 24, Rlo. 2

Amplitude(mm)

3

24

F(1, 19)

p

40

80

160

320

F(3, 57)

p

528 2.3 74 228 103 46.5 53.5 63.7

220 5.0 145 117 299 54.9 45.1 17.6

387.1 141.1 248.2 479.9 249.3 115.2 115.2 148.4

.001 .001 .001 .001 .001 .001 .001 .001

197 2.6 63 98 99 53.6 46.4 36.5

287 3.3 92 135 152 51.6 48.4 38.9

433 4.4 118 197 235 49.6 50.4 44.6

579 4.5 165 260 319 48.0 52.0 42.9

311.6 28.0 242.8 347.3 217.5 43.2 43.2 4.61

.001 .001 .001 .001 .001 .001 .001 .OS

181

J.J. Adam

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FIGURE 6. Mean movement time, dwell time, deceleration time, and normalized deceleration time, as a function of target size, for the two movement objective conditions.

does not remain constant but changes as well. Generally, the nature of these changes aze such that as the perceived precision demands increase, the resulting movements are characterized by disproportionally larger deceleration than acceleration phases and by larger dwell times. We suggest that this strategy may allow feedback information concerning endpoint accuracy to be monitored and used for adjustments of movements in order to optimize their accuracy. Similar results and interpretations have been published by Carlton (1980), Grossman and Goodeve (1983), MacKenzie et al. (1987), Marteniuk et al. (1987), and Milner and Ijaz (1990). What kind of motor control models, then, are supported 1 g2

by the results of this study? In general, the present findings seem to be most easily resolved by a theory of motor control that views motor planning in terms of sensory consequences (Abbs, Gracco, &Cole, 1984; Arbib, 1981, 1985; Cole & Abbs, 1986; Marteniuk et al., 1987). Cole and Abbs (1986) have stated explicitly that motor planning can be seen "in terms of the multimodel sensory experience associated with successful accomplishment of intended [italics added] motor tasks" (p. 1420). Furthermore, they argue that "the planning of motor góals [italics added] in terms of sensory consequences is fundamentally pragmatic and task specific [italics added]"(p. 1420). A similar view has been expressed by Arbib (1985), who Journal of Motor Behavior


J. J. Adam

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~O

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FIGURE 6. Mean movement time, dwell time, deceleration time, and normalized deceleration time, as a function of target size, for the two movement objective conditions.

does not remain constant but changes as well. Generally, the nature of these changes are such that as the perceived precision demands increase, the resulting movements are characterized by disproportionally larger deceleration than acceleration phases and by larger dwell times. We suggest that this strategy may allow feedback information concerning endpoint accuracy to be monitored and used for adjustments of movements in order to optimize their accuracy. Similar results and interpretations have been published by Carlton (1980), Grossman and Goodeve (1983), MacKenzie et al. (1987), Marteniuk et al. (1987), and Milner and Ijaz (1990). What kind of motor control models, then, are supported 182

by the results of this study? In general, the present findings seem to be most easily resolved by a theory of motor control that views motor planning in terms of sensory consequences (Abbs, Gracco, &Cole, 1984; Arbib, 1981, 1985; Cole & Abbs, 1986; Marteniuk et al., 1987). Cole and Abbs (1986) have stated explicitly that motor planning can be seen "in terms of the multimodel sensory experience associated with successful accomplishment of intended [italics added] motor tasks" (p. 1420). Furthermore, they argue that "the planning of motor góals [italics added] in terms of sensory consequences is fundamentally pragmatic and task specific [italics added]"(p. 1420). A similar view has been expressed by Arbib (1985), who Journal of Motor Behavior

40

AMPLITUDE (mm)

320

45

40

AMPLITUDE (mm)

320

FIGURE 7. Mean movement time, dwell time, deceleration time, and normalized deceleration time, as a function of amplitude, for the two movement objective conditions.

has postulated a model of overt behavior in terms of a continuing action—perception cycle, where perceptual activity is embedded in and directed by the organism's continuing interaction with its environment. In Arbib's (1985) words: "As the organism moves in a complex environment, making, executing, and updating plans, it must stay tuned to its spatial relationship with its immediate environment... . As action continues, the current plan may continue to be executed simply with tuning or updating of parameters" (pp. 64-65). The tuning or updating of coordinated perceptual and motar control programs in reciprocal aiming tasks may be accomplished most economically in the deceleration phase of the movement(Beaubaton &Hay, 1982; CarlJune 1992, Vol. 24, No.2

ton, 1981; Marteniuk et al., 1987; Milner & Ijaz, 1990) and in the reversal portion of the movement, that is, during dwell time. It is interesting to speculate on the functional significance of dwell time. At least two interpretations seem possible: One relates dwell time to visual feedback processing time and the other to programming time. The visual feedback processing time hypothesis holds that dwell time reflects the time needed to assess the discrepancy between intended endpoint accuracy and actual endpoint accuracy. The programming time hypothesis, on the other hand, claims that dwell time reflects the time needed to program the next movement to be made. In other words, whereas the feed183

J. J. Adam back processing time hypothesis relates dwell time to the evaluation of ajust-completed movement, the programming time hypothesis relates dwell time to the preparation of a future movement. The present data do not discriminate between these two hypotheses; more experimentation is needed. Currently, experiments are being carried out in our laboratory to investigate these possibilities. Although not the aim of this study, examination of the linear relationship between movement time and Fitts' index of difficulty, that is, the logarithm of the ratio of amplitude and target size (Fitts, 1954; Fitts &Peterson, 1964), reveals for Experiment 1 that Fitts' law accounted for 72%, 86%, and 92% of the variance for the speed-, speed-plusaccuracy-, and accuracy-biased subjects, respectively. Substituting the subjective target size (i.e., effective target size or the standard deviation of the movement endpoints around their own mean) for the objective target size in the calculation of the index of difficulty (Welford, 1968; Meyer et al., 1988) resulted in accounted variances of 89%, 97%, and 99% for low-, medium-, and high-accuracy-biased subjects. Clearly, Fitts' law best fits the movements produced by subjects who are biased toward accuracy. This is not surprising as one considers that Fitts himself was not ambiguous in his task instructions; he explicitly asked subjects to "emphasize accuracy rather than speed" (Fitts, 1954, p. 384). In conclusion, we would like to emphasize that the results of this study clearly demonstrate that subjects may do identically defined tasks in different ways. In pazticulaz, ambiguous task instructions, such as to move as quickly and accurately as possible, are vulnerable to different strategic interpretations varying from an emphasis on accuracy to an emphasis on speed. The present research, therefore, strongly validates Newell's (1989) contention that constraints to action have to be viewed from the perspective of the performer rather than from reliance on the external, physical description of the constraints. ACKNOWLEDGMENTS The author acknowledges the theoretical contributions of Ian Humphreys and Bob Wilberg; I would also like to thank Foppe ten Hoor, Wynne Lee, Christine MacKenzie, and two anonymous reviewers for useful comments on an earlier draft of this paper. Thanks are extended to Aggi Bronkhorst, Marion de Vreede, and Harry Wandler for technical assistance.

NOTE 1. The only exception was for the variable peak velocity in the interaction between movement objective and target size (p > .2).

REFERENCES Abbs, J. H., Gracco, V. L., &Cole, K. J. (1984). Control of multimovement coordination: Sensorimotor mechanisms in speech motor programming. Journal of Motor Behavior, 16, 195-231. Arbib, M. A. (1981). Perceptual structures and distributed motor control. In V. B. Brooks (Ed.), Handbook of physiology: Sec. 1. The nervous system: Uol. 2. Motor control. Pt 2(pp. 14481480). Bethesda, MD: American Physiological Association. 184

Arbib, M. A. (1985). Scheuras for the temporal organization of behavior. Human Neurobiology, 4, 63-72. Beaubaton, D., &Hay, L. (1982). Integration of visual cues in rapid goal-directed movements. Behavioral Brain Research, 5, 92-93. Brooks, V. B. (1986). The neural basis of motor control. New York: Oxford University Press. Carlton, L. G. (1980). Movement control characteristics of aiming responses. Ergonomics, 23, 1019-1032. Cazlton, L. G.(1981). Processing visual feedback information for movement control. Journal of Experimental Psychology: Human Perception and Performance, 7, 1019-1030. Cole, K. J., & Abbs, J. H. (1986). Coordination of three-joint digit movements for rapid, finger-thumb grasp. Journal ofNeurophysiology, 55, 1407-1423. Corcos, D. M., Gottlieb, G. L., & Agarwal, G. C. (1988). Accuracy constraints upon rapid elbow movements. Journal of Motor Behavior, 20, 255-272. Grossman, E. R. F. W., & Goodeve, P. J. (1983). Feedback control of hand-movement and Fitts' law. Quarterly Journal ofExperimental Psychology, 35A, 251-278. Original work presented at the meeting of the Experimental Psychology Society, Oxford, England, July 1963. Fisk, J. D., & Goodale, M. A.(1989). The effects of instructions to subjects on the programming of visually directed reaching movements. Journal of Motor Behavior, 21, 5-19. Fitts, P. M.(1954). The information capacity of the human motor system in controlling the amplitude of the movement. Journal ofExperimental Psychology, 47, 381-391. Fitts, P. M., &Peterson, J. R. (1964). Information capacity of discrete motor responses. Journal ofExperimental Psychology, 67, 103-112. talencross, D., &Barret, N. (1983). Programming precision in repetitive tapping. Journal of Motor Behavior, I5, 191-200. Keele, S. W. (1981). Behavioral analysis of movement. In V. B. Brooks (Ed.), Handbook of physiology: Sec. 1. The nervous system: Uol. 2. Motor control. Pt 2(pp. 1391-1414). Bethesda, MD: American Physiology Association. Keppel, G. (1982). Design and analysis. Englewood Cliffs, NJ: Prentice-Hall. MacKenzie, C. L., & Marteniuk, R. G. (1985). Motor skill: Feedback, knowledge, and structural issues. Canadian Journal ofPsychology, 39, 313-337. MacKenzie, C. L., Marteniuk, R. G., Dugas, C., Liske, D., & Eickmeier, B. (1987). Three-dimensional movement trajectories in Fitts' task: Implications for control. Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 39A, 629-647. Marteniuk, R. G., MacKenzie, C. L., Jeannerod, M., Athenes, S., & Dugas, C.(1987). Constraints on human arm movement trajectories. Canadian Journal ofPsychology, 41, 365-378. Meyer, D. E., Abrams, R. A., Kornblum, S., Wright, C. E., & Smith, J. E. K. (1988). Optimality in human motor performance: Ideal control of rapid aimed movements. Psychological Review, 95, 340-370. Meyer, D. E., Smith, J. E. K., &Wright, C. E. (1982). Models for the speed and accuracy of aimed movements. Psychological Review, 89, 449-482. Milner, T. E., & Ijaz, M. M.(1990). The effect of accuracy constraints on three-dimensional movement kinematics. Neuroscience, 35, 365-374. Munhall, K. G., Ostry, D. J., & Parush, A.(1985). Characteristics of velocity profiles of speech movements. Journal of Experimental Psychology: Human Perception and Performance, 11, 457-474. Nelson, W. L. (1983). Physical principles for economies of skilled movements. Biological Cybernetics, 46, 135-147. Journal of Motor Behavior


J. J. Adam back processing time hypothesis relates dwell time to the evaluation of ajust-completed movement, the programming time hypothesis relates dwell time to the preparation of a future movement. The present data do not discriminate between these two hypotheses; more experimentation is needed. Currently, experiments are being carried out in our laboratory to investigate these possibilities. Although not the aím of this study, examination of the linear relationship between movement time and Fitts' index of difficulty, that is, the logarithm of the ratio of amplitude and target size (Fitts, 1954; Fitts &Peterson, 1964), reveals for Experiment 1 that Fitts' law accounted for 72%, 86%, and 92% of the variance for the speed-, speed-plusaccuracy-, and accuracy-biased subjects, respectively. Substituting the subjective target size (i.e., effective target size or the standard deviation of the movement endpoints around their own mean) for the objective target size in the calculation of the index of difficulty (Welford, 1968; Meyer et al., 1988) resulted in accounted variances of 89%, 97%, and 99% for low-, medium-, and high-accuracy-biased subjects. Clearly, Fitts' law best fits the movements produced by subjects who are biased toward accuracy. This is not surprising as one considers that Fitts himself was not ambiguous in his task instructions; he explicitly asked subjects to "emphasize accuracy rather than speed" (Fitts, 1954, p. 384). In conclusion, we would like to emphasize that the results of this study clearly demonstrate that subjects may do identically defined tasks in different ways. In particular, ambiguous task instructions, such as to move as quickly and accurately as possible, are vulnerable to different strategic interpretations varying from an emphasis on accuracy to an emphasis on speed. The present research, therefore, strongly validates Newell's (1989) contention that constraints to action have to be viewed from the perspective of the performer rather than from reliance on the external, physical description of the constraints. ACKNOWLEDGMENTS The author acknowledges the theoretical contributions of Ian Humphreys and Bob Wilberg; I would also like to thank Foppe ten Hoor, Wynne Lee, Christine MacKenzie, and two anonymous reviewers for useful comments on an earlier draft of this paper. Thanks are extended to Aggi Bronkhorst, Mazion de Vreede, and Harry Wandler for technical assistance. NOTE 1. The only exception was for the variable peak velocity in the interaction between movement objective and target size (p > .2). REFERENCES Abbs, J. H., Gracco, V L., &Cole, K. J. (1984). Control of multimovement coordination: Sensorimotor mechanisms in speech motor programming. Journal of Motor Behavior, 16, 195-231. Arbib, M. A.(1981). Perceptual structures and distributed motor control. In V. B. Brooks (Ed.), Handbook of physiology: Sec. 1. The nervous system: Vol. 2. Motor control. Pt 2 (pp. 14481480). Bethesda, MD: American Physiological Association. 184

Arbib, M. A. (1985). Scheuras for the temporal organization of behavior. Human Neurobiology, 4, 63-72. Beaubaton, D., &Hay, L. (1982). Integration of visual cues in rapid goal-directed movements. Behavioral Brain Research, 5, 92-93. Brooks, V. B. (1986). The neural ~iasis of motor control. New York: Oxford University Press. Carlton, L. G. (1980). Movement control characteristics of aiming responses. Ergonomics, 23, 1019-1032. Cazlton, L. G.(1981). Processing visual feedback information for movement control. Journal of Experimental Psychology: Human Perception and Performance, 7, 1019-1030. Cole, K. J., & Abbs, J. H. (1986). Coordination of three-joint digit movements for rapid, finger-thumb grasp. Journal ofNeurophysiology, 55, 1407-1423. Corcos, D. M., Gottlieb, G. L., & Agarwal, G. C. (1988). Accuracy constraints upon rapid elbow movements. Journal of Motor Behavior, 20, 255-272. Grossman, E. R. F. W., & Goodeve, P. J. (1983). Feedback control of hand-movement and Fitts' law. Quarterly Journal ofExperimental Psychology, 35A, 251-278. Original work presented at the meeting of the Experimental Psychology Society, Oxford, England, July 1963. Fisk, J. D., & Goodale, M. A.(1989). The effects of instructions to subjects on the programming of visually directed reaching movements. Journal of Motor Behavior, 21, 5-19. Fitts, P. M.(1954). The information capacity of the human motor system in controlling the amplitude of the movement. Journal ofExperimental Psychology, 47, 381-391. Fitts, P. M., &Peterson, J. R. (1964). Information capacity of discrete motor responses. Journal ofExperimental Psychology, 67, 103-112. Glencross, D., &Barret, N. (1983). Programming precision in repetitive tapping. Journal of Motor Behavior, 15, 191-200. Keele, S. W. (1981). Behavioral analysis of movement. In V. B. Brooks (Ed.), Handbook of physiology: Sec. 1. The nervous system: Uol. 2. Motor control. Pt 2(pp. 1391-1414). Bethesda, MD: American Physiology Association. Keppel, G. (1982). Design and analysis. Englewood Cliffs, NJ: Prentice-Hall. MacKenzie, C. L., & Marteniuk, R. G. (1985). Motor skill: Feedback, knowledge, and structural issues. Canadian Journal ofPsychology, 39, 313-337. MacKenzie, C. L., Marteniuk, R. G., Dugas, C., Liske, D., & Eickmeier, B. (1987). Three-dimensional movement trajectories in Fitts' task: Implications for control. Quarterly Journal of Experirrcental Psychology: Human Experimental Psychology, 39A, 629-647. Marteniuk, R. G., MacKenzie, C. L., Jeannerod, M., Athenes, S., & Dugas, C. (1987). Constraints on human arm movement trajectories. Canadian Journal ofPsychology, 41, 365-378. Meyer, D. E., Abrams, R. A., Kornblum, S., Wright, C. E., & Smith, J. E. K. (1988). Optimality in human motor performance: Ideal control of rapid aimed movements. Psychological Review, 95, 340-370. Meyer, D. E., Smith, J. E. K., &Wright, C. E. (1982). Models for the speed and accuracy of aimed movements. Psychological Review, 89, 449-482. Milner, T. E., & Ijaz, M. M.(1990). The effect of accuracy constraints on three-dimensional movement kinematics. Neuroscience, 35, 365-374. Munhall, K. G., Ostry, D. J., & Parush, A.(1985). Characteristics of velocity profiles of speech movements. Journal of Experimental Psychology: Human Perception and Performance, 11, 457-474. Nelson, W. L. (1983). Physical principles for economies of skilled movements. Biological Cybernetics, 46, 135-147. Journal of Motor Behavior

Newell, K. M.(1989). On task and theory specificity. Journal of Motor Behavior, 21, 92-96. Pachella, R. G. (1974). The interpretation of reaction time in information-processing reseazch. In B. H. Kantowitz (Ed.), Human information processing: Tutorials in performance and cognition (pp. 41-82). Hillsdale, NJ: Erlbaum. Pew, R. W. (1969). The speed-accuracy operating chazacteristic. Attention and Performance II. Acta Psychologica, 30, 16-26. Welford, A. T. (1968). Fundamentals of skill. London: Methuen. Submitted February 20, 1990 Revised March 7, 1991

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