Visual size cues in the programming of manipulative forces during

Exp Brain Res (1991) 83:477-482

Experimental BrainResearch 0 Springer-Verlag 1991

Visual size cues in the programming of manipulative forces during precision grip A.M.

Gordon’,

H. Forssberg ‘, R.S. Jobansson2, and G. Westling2

1 Nobel Institute for Neurophysiology and Department of Pediatrics, Karolinska ’ Department of Physiology, UmeCi University, S-901 87 UmeB, Sweden

Institute, S-104 01 Stockholm, Sweden

Received January 19, 1990 / Accepted August 24, 1990 Summary. A size-weight illusion was used to examine the role of visual cues in the programming of manipulative forces during the lifting of test objects utilizing the precision grip. Three different boxes of equal weight and unequal size were lifted. These were equipped with an instrumented grip handle to measure the employed grip force, load force (vertical lifting force), force rates and vertical movement. All fifteen subjects participating in the study reported that the smallest box was the heaviest, which is consistent with size-weight illusion predictions. However, the rate of increase of the isometric grip and load forces initially during the lift, the peaks of the grip and load force and the vertical acceleration were all found to increase with the box size. Thus, despite the conscious perception indicating a heavier weight for the small object, the motor program was scaled for a lighter weight. Yet, no differences were found in grip force during the static phase of the lift, where weight related information was apparently available via sensory feedback. Previous studies have reported, that the programming of the precision grip is based on somatosensory information gained during previous lifts (Johansson and Westling 1984, 1988a, b). The present study suggests that visual cues are integrated in the programming of manipulative forces during precision grip. Key words: Precision grip - Motor control - Motor programming - Vision - Size-weight illusion - Human

Introduction To produce a skilled movement a sequentially coordinated activation of muscles is required. It is generally assumed that such movements are controlled by motor programs which contain the appropriate muscle commands for the forthcoming movement (e.g. Keele 1968; Schmidt 1975). One fine motor skill which has recently Offprint requests to: H. Forssberg Dept. of Pediatrics, Karolinska Hospital, S-104 01 Stockholm, Sweden

been studied with regard to motor programming is the precision grip (Johansson and Westling 1984, 1988a, b; Johansson 1990). While small objects are lifted using this grip, the grip force and the load force (vertical lifting force) are scaled to allow for smooth transitions between successive phases of discretely coordinated actions (Johansson and Westling 1988a). Such phases include, but are not limited to: (a) the formation of the grip (preload phase), (b) the increase in grip and load force until the load force overcomes gravity (loading phase), (c) the lift of the object to the desired position (transitional phase), (d) the reaching of the desired position such that the object is held stationary forming a plateau in the forces (static phase), (e) the lowering of the object to the resting position (replacement phase) and (f) the decrease in forces until the object is released (unloading phase). The rate profiles of the grip and load forces during the loading phase show that the lifts are programmed in advance (Johansson and Westling 1988a). The profiles are predominately single-peaked, bell-shaped, and scaled as one force rate pulse to the target force. Thus, they resemble the “continuous” or “bell-shaped” velocity profiles described during fast programmed movements (Bizzi and Abend 1983; Brooks 1984), as well as rate profiles obtained during programmed isometric contractions (Ghez 1979; Gordon and Ghez 1984). The target force, in turn, is scaled based on the weight of the object in the previous lifts. In these experiments, the visual appearance of the object did not change, indicating that somatosensory afferent input during preceding manipulations can issue updates of the sensorimotor memory used for the scaling of the program parameters to the expected weight (see Johansson and Westling 1990). In contrast, little is known about the capacity of visual cues in the anticipatory control of the precision grip. Visual information may be used in the anticipatory control of the formation of finger grip during the reaching phase of prehension (Jeannerod 1986). It seems likely that visual information can also be used to relate the size of the object to its weight in order to anticipate the forces necessary to successfully lift the object. This would be of

478

particular relevance in specifying the motor program parameters during manipulative interactions with less familiar objects. It is well known that alterations in the usual size-weight relationships may lead to an illusion in whit the smaller object is perceived to be the heaviest whe I! objects of varying size and equal weight are lifted (Charpentier 1891). The present study was designed to examine the extent to which visual size information influences the scaling of the motor program parameters. A size-weight illusion was used to also determine the influence of the subject’s weight perception on the scaling of the force parameters. If the programming of the precision grip is influenced by visual size cues and not the subject’s weight perception, then it would be expected that the rate profiles of the grip and load forces during the loading phase are influenced by the size of the lifted object. This would imply that weight information “estimated” on the basis of the objects size is used in a manner similar to weight information acquired via somatosensory modalities during previous handling of the object. Material

and methods

Fifteen healthy right-handed subjects participated in the study (13 female and 2 male, age 23 to 47 years). None had previous experience with the experimental task, nor were they familiar with the hypothesis being tested. Subjects were replaced if they could not demonstrate fine manipulatory control of the precision grip resulting in exceedingly high grip force values which the instrument could not measure (above 30 N). As a consequence, two subjects were replaced. The subjects were positioned behind a table on which the objects to be lifted rested, such that the lift mainly involved an elbow flexion.

Apparatus and data acquisition The test objects were three wooden boxes each weighing 0.83 kg. They were all painted a flat gray and measured 16 x 16 x 16 cm (small box), 20 x 20 x 20 cm (medium box), and 25 x 25 x 25 cm (large box). Thus, the ratios between volumes of the three boxes were approximately 1: 2: 4. Two strips of plastic were attached to the top of each box which an instrumented grip handle could be easily slid into. As shown in Fig. 1, the parallel grip surfaces (35 mm x 35 mm) were situated at the top of the object. The surface material used for the grip was fine sandpaper (no. 200) and the total weight of the grip instrument and each box was 1.03 kg. The boxes were placed on an adjustable platform and positioned such that the starting position of the handle was identical for each box. The instrumented grip handle was a modified version of one described earlier (Westling and Johansson 1984). Its vertical displacement was measured (DC-l .5 kHz) using infra-red light emitting diodes which were attached to the side of the handle and projected towards an appropriately located light-sensitive photoresistor (United Detector Technology, X/28), which sensed the position of the diodes. Both grip and load forces were measured by transducers located in the handle of the grip instrument (DC-160 Hz). Signals from the handle led through a 12 bit A/D converter sampling at 400 Hz for each channel to a microcomputer (IBM PC-AT).

Procedure Subjects were randomly assigned to three groups of five subjects, each group beginning with a different size box. The task required

Fig. 1. Schematic drawing of the grip instrument. A grip plates with fine sand paper surfaces cover strain-gauge force transducers for measurement of grip force and load force, B infra-red light emitting diodes, C interchangeable box, D lightposition sensitive photoresistor subjects to lift the boxes to a predetermined height (10 cm from the platform), maintain the lift for 3-4 s, replace and release the object. The object was grasped from above with the right hand using the precision grip (between the thumb and forefinger; see Fig. 1). Following a demonstration by the experimenter, the subject lifted one box five times. Thereafter, the boxes were randomly presented with the only restrictions being that the first lift consisted of the same box as the practice trials and that all blocks of three trials contained each box. The boxes were changed by sliding the grip instrument out of the track on one box into the track of another. Each possible order of the three boxes was presented to each subject, resulting in eighteen trials, six trials of each box (plus the five practice trials). The time between each lift was approximately 10 seconds. Following the experiment, subjects were asked to rate the weight of the boxes from the heaviest to the lightest.

Data analysis Using a twenty point numerical differentiation, grip force rate (dGF/dt), load force rate (dLF/dt), vertical velocity (dPOS/dt) and acceleration (dzPOS/dtz) were computed from the grip force, load force and position signals. A graphics terminal was used and these time derivatives, as well as the grip and load forces, were measured

419

at their positive peaks, and the data points (time and amplitude) were stored for statistical analysis. The mean and median values were similar, indicating that the distributions of the various measures were not appreciably skewed. A 3 x 3 (Box Sizex Group) analysis of variance (ANOVA) was then performed on each dependent measure. The main effect for group and the box x group interaction was non-significant for all dependent measures (p> 0.05). A post-hoc analysis using the Newman-Keuls method was performed, at the 0.05 level for all ANOVAs which yielded a significant main effect for box size.

20 N

GRIP

FORCE

LOAD

(N)

FORCE

10 N

0

i 0

(N)

15 N/S 0 1

60 N/S

Results LOAD RATE

All fifteen subjects reported the smallest box to be the heaviest, which is consistent with the size-weight illusion (Charpentier 1891). Twelve of the subjects reported the large box to be the lightest, while three reported the medium box to be the lightest. The grip force, load force, and vertical position signals of each box, together with the corresponding time derivatives are illustrated in Fig. 2 (single subject, trials averaged for each box size). During the loading phase, the rates of both the isometric grip and load force generation increased with box size. Likewise, the grip and load force peaks, as well as the vertical acceleration of the object, increased with box size. Table 1 shows means and standard deviations for the dependent measures as a function of box size. Figure 3a shows grip force rate in relation to load force for one subject for the first lift of the large box when it had been preceded by the six initial lifts with the small box. The scaling of the grip force rate towards a larger load force target (solid curve) indicates that the subject expected a somewhat heavier weight. In contrast, Fig. 3b shows another subject on the small box when it immediately followed the presentation of the six initial lifts with the large box. The small initial peak suggests that the subject programmed the grip force and load force to a lower expected weight. When the lift-off did not occur at the anticipated load force the parallel force increase continued. The increase occurred slowly and disconTable

1.

FORCE (N/S)

0 i 220 MM/S

0

PosrnoN

100 MM

/z

(MM)

Influence of box size on average grip force, load force, grip force rate (dGF/dt), load force rate (dLF/dt), vertical velocity (dPOS/dt), and vertical position as a function of time for one typical subject. All six trials of the small box (- - - ), medium box (-.-.-.), and the large box () are averaged and superimposed. The data averaging was synchronized at the onset of grip force. The weight of the grip instrument and each box (1.03 kg) was kept constant throughout the experiment. The force rate, velocity, and acceleration curves are presented using a 20 point numerical differentiation. Note that a mismatch between the load force and position curves occurs and is due to the process of averaging the curves Fig. 2.

tinuously, as seen by the multiple peaks in grip force rate, until the load force overcame gravity and the vertical movement began. This is similar to an unexpected change to a heavier weight without changing the lifted objects’ visual appearance (Johansson and Westling 1988a). One might expect a strong effect at the first change of box size

Descriptive statistics of dependent measures as a function of box size

Dependent measure Peak grip force (N) Peak grip force (N) (first trial block) Peak grip force (N) (last trial block) Static grip force (N) Grip force rate (N/s)

(peak)

Load force rate (N/s)

Small

Medium

13.81 13.04

(4.29) (3.95)

14.28 13.93

(4.32) (5.26)

15.11

(4.91) (4.78)

13.03

(4.32)

13.40

(4.18)

14.96

(5.50)

10.66 (3.20)

10.12 66.16

(2.92) (32.84)

10.54

(2.92)

(35.57)

76.28

(40.33)

60.61

(20.49)

61.73

(20.26)

67.09

(23.84)

0.29

(peak)

Acceleration (m/s2) (peak) Loading phase (ms)

15.24

65.39

(peak)

Vertical velocity (m/s)

Large

(0.53)

1.14 (0.35) 450

(168)

0.28

(0.44)

1.25 (0.40) 441

WO

0.30

(0.54)

1.39 (0.48) 368

(149)

Numbers represent means and standard deviations (parentheses) of the individual means (n = 6 trials for each box size) for all subjects (n= 15). The mean peak grip force for the first and last trial block (i.e. the first and last lift of each box size) was calculated separately

480

phase. Since the weight was constant, and thereby the force required to overcome gravity, the duration of the loading phase was inversely proportional to the average load force rate. A 3 x 3 (Box Size x Group) ANOVA on this duration indicated a main effect only for box size (F (2,24) = 6.86, p < 0.05). The post-hoc analysis showed that the loading phase for the large box was significantly shorter than for both the small and medium boxes, while the difference between the small and medium boxes was not statistically significant (p > 0.05). Pearson correlations between peak load force rate and the duration of the loading phase over all 18 trials for each subject ranged from -0.27 to -0.85. The mean correlation (r= - 0.65) was significant when the correlations for each subject were averaged using Fischer Z transformations 0, < 0.05).

a

GRIP FORCE RATE (N/S)

b

Transitional phase

4N

LOAD

FORCE (N)

3a, b. Grip force rate as a function of load force for a a typical subject on the first lift of the large box (-) following the last of six initial trials with the small box (---), b another subject who displayed more drastic differences, on the first lift of the small box (---) following the last of six initial lifts of the large box (-) Fig.

since the subjects would presumably predict the large box to be the heaviest on the basis of previous experience from various everyday situations. However, the box size effects were consistent throughout the series of lifts as seen by the mean grip force values for the first and last block of trials (Table I), suggesting a continuous visual effect. Loading phase

A two factorial (Box Size x Group) ANOVA on peak grip force rate revealed only a main effect for box size (F(2,24) = 11.87, p < 0.05). The post-hoc analysis revealed no significant difference between the small and medium boxes while the grip force rate for the large box was significantly greater than both. A corresponding ANOVA and post-hoc analysis of the peak load force rate indicated a significant difference between the small, medium, and large boxes (F(2,24) = 7.02, p < 0.05). Within-subject correlations (Pearson rs) were computed between peak grip force rate and peak load force rate. These correlations ranged from 0.35 to 0.89 and a significant correlation (r = 0.69) was obtained when the coefficients were averaged over subjects using the Fischer Z transformation (p < 0.05). The average rate of grip force and load force also increased with box size during the loading phase. This was revealed by an analysis of the duration of the loading

The higher load force rate for the larger boxes at lift-off caused a greater load force overshoot as seen in the peak load force (F(2,24) = 4.12, p < 0.05), and thereby also a faster vertical acceleration (F(2,24) = 11.21, p < 0.05). The post-hoc analyses revealed no significant differences between the small and medium boxes. Yet the peak load force and acceleration for the large box was significantly greater than that for the smaller boxes. In agreement with the parallel weight scaling of the grip and load forces (see Johansson 1990), differences in the peak grip forces were also seen between each box (F(2,24) = 8.60, p < 0.05). The differences between the medium box and the small or large box (Table 1) were, however, not statistically significant, whereas the grip force peak for the small box was significantly less than the grip force peak for the large box 01~0.05). Yet, 12 out of the 15 subjects exhibited successive increases in peak grip force for the small, medium and large boxes, respectively. Static phase

The grip force during the static phase of the lift, in which the object is held stationary in air, was measured as the mean force during a 2 s period starting 0.5 s after the peak grip force. An ANOVA (Box Size x Group) on the static grip forces failed significance (p > 0.05) for grip force. The similarity of the means (Table 1) suggests that somatosensory information now had overruled visual biases and the grip force was purely adjusted to the weight of the object. Discussion Anticipatory control of precision grip

Precise manipulation is not only based on predetermined programs which constrain and reduce the degrees of freedom and provide adequate manipulative strategies. The physical properties of the object must also, in an anticipatory fashion, be integrated in the controlling process of the manipulated objects. There is evidence that

481

relevant program parameters are defined via a robust, but easily updated, internal neural representation of relevant physical properties of objects, or categories of objects, that have been previously manipulated (Johansson 1990). Grip force and load force are scaled in parallel when the programming of the forces is based upon the weight of the object (Johansson and Westling 1988a). In contrast, the grip force is scaled in relation to the load force when the programming is based upon the friction (Johansson and Westhng 1984). The importance of an anticipatory scaling of the force development during the loading phase for a well coordinated transition between the loading phase and the static phase of the lift is obvious. Sensory information about the weight is not gained until the start of the vertical movement after the loading phase and there is a relatively long time (> 0.1 s) between the movement feedback and when the motor commands can be changed to appropriately control the forthcoming phase. Subjects in this experiment demonstrated the influence that visual cues have on the programming of the loading and transitional phases of the lift. Both grip force and load force were scaled towards a higher expected weight for the. larger objects, even though the weight of the three objects was identical. It seems as if the programming of the lift based on the objects size shares common functional elements with the programming based on previous experiences of the weight of the object while its visual appearance is kept constant (Johansson and Westling 1988a). Since the grip force and load force are scaled in parallel towards a target weight, it may be that the anticipatory control based on visual size cues operates over the same mechanism as the scaling of the force parameters due to weight. But in addition, it includes a transformation based on a predicted relationship between the visual size cues and the weight of the object derived from previous somatosensory experience. Interestingly, the proposed internal weight representation used in the anticipatory control does not appear to be related to the subject’s conscious perception of the weight of the object. While all subjects reported the smallest box to be the heaviest, visual information influenced force production throughout the experiment causing them to scale toward a smaller targeted force for the small box. While the dynamic phase of the lift is programmed prior to response initiation, the force coordination during the static phase can be influenced by peripheral feed back. Microneurography has shown that once the object starts to move there are somatosensory signals available that may automatically terminate the parallel force increase after a ca. 0.1 s latency (Johansson and Westling 1990). This somatosensory information seems to override the visual bias and allow for a proper control of static forces. Moreover, it apparently efficiently issues updates of the proposed internal neural representation of the object (Johansson and Westling 1990). Roles of vision

The effects of vision are relatively small when they are compared to the effects of changing the weight of the

object by approximately the same ratio (1: 2: 4) while keeping the visual appearance constant (Johansson and Westling 1988a). On the other hand, vision seems to be used to identify the object and call up the appropriate internal representation of the weight of the current object, which forms the basis for the programming of the lift. In that respect, vision is a very strong source of feedforward information since it is capable of identifying the object prior to the first contact. For less familiar objects, the programming of a lift is most likely based on the predicted relationship between the size and weight of the object (cf. Claparede 1901). Gachoud et al. (1983) proposed that such a size-weight representation must relate the properties of the object to those of other objects. The necessary density associated with the object may be internally represented for such objects. Indeed, studies by Harshfield and DeHardt (1970) in which objects of equal weight and size were perceived differently due to the material (e.g. balsawood, steel) indicate that visual cues also are used to estimate the density of the object. The present data indicate that information derived from visual cues may influence the programming of the dynamic phase of the lift, even if the information is not accurate. While the three boxes may be internally represented as individual objects, there is still an effect from the visual size information. This is consistent with other research contending that vision generally is a strong afferent source and can often even dominate over kinesthetic feedback (Gibson 1933; Kinney and Luria 1970; Klein and Posner 1974; Pick, Warren and Hay 1969 ; Rock and Harris 1966). Weight sensation

The contribution of various sources of information including the afferents from skin, joints and muscles to weight sensation is only partly understood. Gandevia and McCloskey (cf. 1977) have suggested that weight perception of a lifted object is more dependent on the centrally generated motor command than on the afferent response evoked by the weight itself. It seems as if the size-weight illusion occurs because of a mismatch between the expected and the actual weight of the object (Claparede 1901; Martin and Muller 1899; Davis and Roberts 1976) since actual sensory information from erroneously programmed lifts is different from the expected sensory information. In our experiment, we demonstrate that the smaller boxes cause a weaker motor output while the larger causes a stronger motor output. The different forces programmed for the boxes leads to different sensory information between the lifts, resulting in different perception of the boxes. The stronger motor output during a lift of the large box results in a shorter loading phase and a faster acceleration, which may aid to the perception of “lightness.” Acknowledgements. A.G was supported by a grant from the Fulbright Commission. This study was supported by the Swedish Medical Research Council (projects 4X-5925, 4P-8885 and 14X-

482 08667), the Stiftelsen Sven Jerrings Fond, the First of Mayflower Annual Campaign for Children’s Health, the Stiftelsen Solstickan, the Sunnerdahls Handikappfond, the Samverkansnamnden, the Norra Sjukvardsregionen, and the University of Umea. The authors also wish to thank Hiroshi Kinoshita, Ann-Christin Eliasson, and Tommy Nord for technical assistance. .

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