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J Neurophysiol (February 1, 2003). 10.1152/jn.00434.2001
Submitted on Submitted 29 May 2001; accepted in final form 12 April 2002
Centre de Recherche en Sciences Neurologiques, Département de Physiologie, Université de Montréal, Montreal, Quebec H3C 3T8, Canada
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ABSTRACT |
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Monzée, Joël, Yves Lamarre, and Allan M. Smith. The Effects of Digital Anesthesia on Force Control Using a Precision Grip. J. Neurophysiol. 89: 672-683, 2003. A total of 20 right-handed subjects were asked to perform a grasp-lift-and-hold task using a precision grip. The grasped object was a one-degree-of-freedom manipuladum consisting of a vertically mounted linear motor capable of generating resistive forces to simulate a range of object weights. In the initial study, seven subjects (6 women, 1 man; ages 24-56 yr) were first asked to lift and hold the object stationary for 4 s. The object presented a metal tab with two different surface textures and offered one of four resistive forces (0.5, 1.0, 1.5, and 2.0 N). The lifts were performed both with and without visual feedback. Next, the subjects were asked to perform the same grasping sequence again after ring block anesthesia of the thumb and index finger with mepivacaine. The objective was to determine the degree to which an internal model obtained through prior familiarity might compensate for the loss of cutaneous sensation. In agreement with previous studies, it was found that all subjects applied significantly greater grip force after digital anesthesia, and the coordination between grip and load forces was disrupted. It appears from these data, that the internal model alone is insufficient to completely compensate for the loss of cutaneous sensation. Moreover, the results suggest that the internal model must have either continuous tonic excitation from cutaneous receptors or at least frequent intermittent reiteration to function optimally. A subsequent study performed with 10 additional subjects (9 women, 1 man; ages 24-49 yr) indicated that with unimpaired cutaneous feedback, the grasping and lifting forces were applied together with negligible forces and torques in other directions. In contrast, after digital anesthesia, significant additional linear and torsional forces appeared, particularly in the horizontal and frontal planes. These torques were thought to arise partially from the application of excessive grip force and partially from a misalignment of the two grasping fingers. These torques were further increased by an imbalance in the pressure exerted by the two opposing fingers. Vision of the grasping hand did not significantly correct the finger misalignment after digital anesthesia. Taken together, these results suggest that mechanoreceptors in the fingertips signal the source and direction of pressure applied to the skin. The nervous system uses this information to adjust the fingers and direct the pinch forces optimally for grasping and object manipulation.
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INTRODUCTION |
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Studies of the forces
employed in object manipulation using a precision grip have found that
the grip forces are optimally sufficient to prevent accidental slips
and yet are not so excessive as to crush a fragile object or to cause
muscle fatigue (Johansson and Westling 1984a
;
Westling and Johansson 1984
). These investigations suggested that in precision grasping, the pinch force and its rate of
application were determined by the anticipated weight and friction of
the object. It was also shown that the grip force was affected by the
margin of safety, set by the individual and based on prior experience.
A critical supporting observation was that cutaneous anesthesia of the
thumb and index finger disrupted the coordination between the grip and
lifting forces that was normally adapted to the friction between the
object and the skin, resulting in slips especially with relatively
heavier objects presenting low-friction surfaces (Johansson and
Westling 1984a
; Westling and Johansson 1984
).
Furthermore, Collins et al. (1999)
showed that cutaneous
afferents signaling contact with a target object play an important role
in triggering and regulating the finger muscle activity during
grasping. Loss of tactile sensation has also been associated with a
significant increase in the overall grip force applied to the object
both during grasping and lifting as well as during static holding.
Although initially the appropriate application of grasping and lifting
forces to a novel object depends on feedback from cutaneous afferents
of the hand, further familiarity gained through manipulatory experience
contributes to the formation of a memory trace or internal model of the
physical properties of the grasped object (Gordon et al. 1991
,
1993
; Johansson and Westling 1984b
, 1988
). The
acquired internal model not only contributes to the preprogramming of
grip and lifting forces, but also to the changes in grip forces
anticipating the tangential forces on the skin caused by the changes in
acceleration occurring during oscillatory movements of a hand-held
object (Flanagan and Wing 1993
, 1997
).
It might be expected that once acquired, the internal model based on
knowledge of an object's inertial and frictional properties would
compensate for any loss of cutaneous sensation from local anesthesia
(Jenmalm and Johansson 1997
; Johansson and
Westling 1984a
). However, it seems that when subjects are asked
to grasp a familiar object with anesthetized fingers, the grip forces
were consistently excessive despite extensive prior experience with the
object (Häger-Ross and Johansson 1996
;
Jenmalm and Johansson 1997
; Johansson and
Westling 1984a
; Johansson et al. 1992
;
Westling and Johansson 1984
). Certainly, the absence of
a sense of friction explains why grip forces are higher during the
first few lifts of a familiar object and any additional uncertainty
about slips induced by changes in acceleration would further encourage
the use of greater grip forces. As further evidence of the CNS's
capacity to compensate for the loss of cutaneous feedback,
Johansson and Westling (1984a)
reported that when
subjects alternatively lifted the same object with an anesthetized and
un-anesthetized hand, the grip force in the insensate hand was
influenced by the experience of the sensate hand. It would seem,
therefore, that prior tactile experience helps to reduce excessive grip
forces on subsequent trials without tactile feedback. That is, one
could hypothesize that repeated practice with grasping the same object
with anesthetized fingers should lead to some grip force reduction
based on the internal model of the object's inertial properties. The
objective of this study was to examine the capacity of an acquired
internal model to compensate for the loss of normal cutaneous sensation after digital anesthesia.
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METHODS |
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Task
The subjects were seated comfortably with the right arm abducted at about 30°, the elbow flexed at about 90°, and the forearm resting on a firm, supporting surface. At a signal from the experimenter, the subjects were instructed to grasp a metal tab between the thumb and index finger and to lift it about 2.5 cm and maintain this position stationary for 4 s. Certain trial blocks were conducted without visual feedback, and although the subjects were not blindfolded, they were not able to turn the head such that peripheral vision of the arm was available. A 1.0-kHz tone signaled to the subject that the armature had been lifted to the desired height between 1.5 and 3.5 cm. At the conclusion of testing with intact sensation, anesthesia with mepivacaine of the thumb and index was achieved by a ring-block infiltration of the digital nerves around the metacarpal-interphalangeal joint at the base of each finger. Infiltration continued until all sensation in the two fingers was gone, indicated by complete insensitivity to skin contact with a camelhair brush and Semmes-Weinstein monofilaments. The loss of cutaneous sensation was repeatedly verified throughout testing. In general, the local anesthesia lasted for about 2 h, but in a few subjects, supplementary injections were required before the conclusion of testing.
Statistical analysis
In general, the data were evaluated using either t-tests for paired comparisons, correlation coefficients, or one or two-way analyses of variance. The peak force on each trial during the dynamic lifting phase was identified and averaged, and the forces and torques were averaged over the last 500 ms on each trial to obtain a mean value for the static phase.
Apparatus
The apparatus used in the present experiment was modified and
improved after preliminary experiments suggested the presence of forces
other than those involved with grasping and lifting. The device shown
in Fig. 1 is the improved version of a
similar apparatus used in an earlier study (Cadoret and Smith
1996
). The one-degree-of-freedom armature was set in a
compressed air bushing that allowed near frictionless movement in the
vertical direction. The voltage applied to the coil provided a range of
resistive forces opposing lifting. Flat rectangular grasping surfaces
for the thumb and index finger were attached to a horizontal strut mounted at 90° to one end of the armature. A load cell measured the
total compression or grip force between the index and thumb, and a
second load cell mounted on the armature measured the vertical or
lifting force on the armature.
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A lightweight (9.4 g) six-axis force-and-torque sensor (Nano-6-axis force and torque transducer; ATI Industrial Automation, Garner, NC) was added to measure side to side (x axis), up and down (y axis), and pushing and pulling (z axis) forces. The three force traces were fed to a proprietary analog-to-digital converter with 16-bit precision at a conversion rate of 250 Hz, which was used to calculate the three torque components. The inset above the force transducer in Fig. 1 indicates the directions of the x, y, and z linear forces. The curved arrows indicate the planes about the x, y, and z axes of the clockwise or counterclockwise rotational forces that have been called the x, y, and z torques. With this arrangement, the vertical load cell essentially replicated the y-axis force measurement. However the length of the strut bearing the grasping tabs provided a significant lever arm and contributed to the x-axis torque shown in Fig. 6G, which will be discussed later. In contrast, the grip-force load cell measured the sum of the compression forces exerted by the thumb and index together, whereas the x-axis force output from the force and torque sensor measured the force differential between the two fingers. Taken together, these two measures made it possible to calculate the force exerted by the index and thumb separately.
Finally, two high-resolution (67 points/cm2), ultra-thin (0.1 mm), pressure-sensitive surfaces from Tekscan Pressure Measurement Systems were added to each of the finger pads to record the pressure distribution under the thumb and index finger at a frequency of 100 Hz. During stationary holding, the position of the fingers did not change, allowing the position of the center of pressure under each finger to be calculated with accuracy.
Subjects and parameters investigated
The ethics committee of the Faculty of Medicine of the Université de Montréal approved the experimental protocol, and a total of 20 right-handed subjects (17 women and 3 men) signed informed consent forms and volunteered to participate in this study. Experiment one focused on the effects of friction on grip forces applied before and after digital anesthesia. Three subjects (2 women, 1 man; ages 24-56 yr) performed 10-trial blocks of the lift-and-hold task with smooth metal and emery paper textures, with three resistive forces (0.5, 1.0, and 2.0 N), with and without visual feedback, and finally with and without digital anesthesia. Four subjects (4 women, ages 24-28 yr) performed the task with 25-trial blocks with the two textures, with a 1.5-N resistive force, and with and without visual and cutaneous feedback. The slip force, or point at which the object slipped from the grasp, was measured for each surface on a separate block of trials in which the subjects were required to first lift and hold the object and then gradually release until the resistive force caused it to slip from the grasp. The coefficient of friction was determined as the average ratio of the grip-to-load force at the moment of slip. The emery paper surface had an approximate coefficient of friction against the skin of about 1.74, whereas the smooth metal had an approximate coefficient of friction of about 0.73.
Experiment two focused on the forces exerted by the hand in a total of 10 additional subjects (9 women, 1 man; ages 24-49 yr) who were tested with a simpler protocol focusing on the effects of local anesthesia, vision, and resistive force. These subjects were first tested on all conditions with sensation intact and then later after blocking the digital nerves to the thumb and index finger with mepivacaine. Each condition of resistive force (0.5, 1.0, and 2.0 N) and visual feedback were presented in 25-trial blocks in a balanced order randomizing the sequence of resistive force and visual feedback conditions.
A third part of this study focused on different control conditions
designed to provide a better understanding of the results. Three
additional subjects provided unique data. The first was a healthy
25-yr-old man naïve to the purpose of the experiment who was
asked to perform a series of lift-and-hold movements with his fingers
deliberately misaligned on the grasp surface. The second was a healthy
26-yr-old woman who performed two blocks of 25 trials initially using a
self-selected grip force and then later deliberately exerting a 9.0-N
grip force that was similar to the mean force used by subjects with the
fingers anesthetized. Finally, a third subject was a 50-yr-old woman
suffering from a polysensory neuropathy of both cutaneous and
proprioceptive afferents (Forget and Lamarre 1987
,
Simoneau et al. 1999
).
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RESULTS |
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Experiment one
In the initial study, seven subjects were asked to perform repeated grasp, lift, and hold sequences against four resistive forces (0.5, 1.0, 1.5, and 2.0 N) and two surface textures (emery paper and smooth metal). Table 1 shows the average grip forces applied during the static holding. Two 2-way analyses of variance (ANOVA) were used to test the effects of resistive force, texture, and anesthesia on peak grip force, and two additional analyses of variance were used to test the effects of resistive force, texture, and anesthesia on mean static grip force. A 2-way ANOVA of the effects of resistive force [F(1,3) = 147.696, P < 0.001] and digital anesthesia [F(1,3) = 226.143, P < 0.001] found both variables to have a significant effect on peak grip force. A similar 2-way ANOVA for the effects of texture [F(1,1) = 109.497, P < 0.001] and digital anesthesia [F(1,1) = 206.550, P < 0.001] found both variables also to have a significant effect on peak grip force. Identical 2-way ANOVAs were used to evaluate the impact of resistive force, texture, and anesthesia on mean static grip force. Resistive force [F(1,3) = 160.068, P < 0.001] and anesthesia [F(1,3) = 344.720, P < 0.001] were significant main effects, and in a separate 2-way ANOVA, texture [F(1,1) = 103.662, P < 0.001] and anesthesia [F(1,1) = 269.331, P < 0.001] were found to be significant main effects.
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The mean grip forces for 10 trials lifting three opposing forces are illustrated for one subject in Fig. 2A. With the fingers anesthetized, the grip force increased substantially. However, even without cutaneous feedback, this subject applied a greater mean grip force when lifting a greater resistive force, suggesting that some awareness of the required lifting force must have been available to the subject, probably from proprioceptive feedback, since no difference was found with or without visual feedback. Paradoxically, despite substantially increased grip force after digital anesthesia, most subjects initially dropped the object due to the inappropriate coordination of the grasping and lifting forces during the first few trials, particularly with the highest resistive force. No doubt these unrecoverable slips would have occurred even more frequently if we had used resistive forces equivalent to the 400- to 800-g weights used in most similar studies.
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The same seven subjects were asked to grasp, lift, and hold the uncovered smooth metal grasping tabs or the same tabs covered with emery paper, contacting the fingers. The local anesthesia resulted in a substantial increase in both the dynamic and static grip force for all subjects. Figure 2B shows the increase in mean grip force after digital anesthesia for a single subject lifting a 1.5-N resistance. The grip force increase was greater for the smooth metal surface than for the emery paper surface.
A 2-way ANOVA found that both surface texture [F(1,1) = 6.12, P < 0.014] and digital anesthesia
[F(1,1) = 134.49, P < 0.001] significantly affected the latency between the grip force onset and the
initiation of the load force. Both these observations are in agreement
with earlier studies by Johansson and Westling (1984a)
.
Figure 3A illustrates the
10-trial mean grip and load forces employed to lift a smooth metal
object offering a 1.0-N resistance with and without digital anesthesia
for a single subject. Figure 3B shows a single lifting trial
after digital anesthesia. In both parts of Fig. 3, the traces have been
aligned on the onset of grip force. Without cutaneous feedback, the
onset of lifting was delayed by several hundred milliseconds.
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Experiment two
DIGITAL ANESTHESIA AND THE PREPROGRAMMING OF GRIP AND LIFTING FORCES. The grip forces used to lift three resistances of 0.5, 1.0, and 2.0 N were tested in 10 additional subjects. As in experiment one, the onset of lifting was significantly delayed without cutaneous feedback. A 2-way ANOVA indicated that both resistive force [F(1,2) = 231.00, P < 0.001] and anesthesia [F(1,2) = 783.25, P < 0.001] were significant factors in determining the static grip force. The interaction was not significant. Table 2 shows that the static grip forces after anesthesia were significantly greater than with intact sensation. The smaller load forces of 0.5 and 1.0 N produced force and torque patterns similar to the 2.0-N load force, although they were of smaller magnitude. The patterns were the same both with intact tactile sensation and after digital anesthesia, and for this reason, they will not be described in further detail.
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DIGITAL ANESTHESIA AND ADDITIONAL FORCES AND TORQUES. In general, with tactile sensation intact, all subjects applied forces relatively efficiently during lifting and holding with minimal force expenditure in directions other than grasping or lifting (i.e., relatively small off-axis forces). The single exception was the x-axis torque noted in METHODS (seen in Fig. 6G) that represented a mechanical characteristic of the apparatus due to the 6.4- to 7.0-cm lever arm, dependent on the position of the fingers rather than a feature of grip force application by the subject. This x-axis torque was unaffected by digital anesthesia in all subjects as shown by a 2-way ANOVA [F(1,2) = 0.22, P > 0.64].
With the fingers anesthetized, a t-test for paired comparisons indicated a significant increase in the absolute z-axis torque for the last 500 ms of static holding in 9/10 subjects and a significant (P < 0.001) increase in absolute y-axis torque for 7/10 subjects during the same period. However, the average increase in y-axis torque (from 47 to 107 N-mm) was much greater than the mean increase in z-axis torque (from 7.6 to 18.0 N-mm). In addition, two linear forces were also significantly increased after the digital anesthesia. The x-axis force representing the force balance between the index and thumb increased in 6/10 subjects, and the z-axis force representing a force pushing away or pulling toward the subject increased significantly (P < 0.001) in 5/10 subjects. The mean forces and torques with and without cutaneous feedback are displayed in Table 3.
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FINGER MISALIGNMENT AND Y- AND Z-AXES TORQUES. Tekscan high-resolution, pressure-sensitive surfaces were used to provide evidence of the misalignment of the fingertips after digital anesthesia. Figure 7 illustrates a three-dimensional (3-D) reconstruction of the area of contact pressure under the thumb and index finger during 500 ms of static holding of a 2.0-N resistive load during three trials with tactile sensation intact and after digital anesthesia. The upper portion of Fig. 7 illustrates the finger-pressure cones exerted prior to the injection of local anesthesia during three separate trials. The increased finger pressure after digital anesthesia is indicated by the greater height of these pressure cones (Fig. 7, middle). Software algorithms from Tekscan were used to determine the precise horizontal and vertical coordinates of the center of pressure for each finger during stationary holding. The difference between the centers of pressure of the thumb and index finger in the horizontal and vertical planes determined the lever arm contributing to the y-axis and z-axis torques, respectively.
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TACTILE ANESTHESIA AND FINGER ALIGNMENT.
The horizontal and vertical misalignment of the two centers of pressure
was noted for all subjects before and after digital anesthesia.
Correlation coefficients were calculated between the alignment errors
and the mean steady-state y- and z-axes torques for the first and last five trials in each condition, with and without
the digital anesthesia. Table 4 shows the
correlations between the horizontal alignment distance and the
y-axis torque and the vertical alignment distance and the
z-axis torque. These correlations ranged from
r = 0.14 (n = 20, not significant) to r = 0.95 (n = 20, P < 0.001). However, a significant correlation was found for at least one
of the two axes for all 10 subjects, indicating that, in general, the
finger misalignment significantly contributed to the y- and
z-axes torques. The y- and z-axes
torques together would have produced a resultant torque
(Tr) on the fingers calculated as
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EFFECT OF DELIBERATELY MISALIGNED FINGER PRESSURE. To substantiate the causal link between finger alignment and the y- and z-axes torques, we asked an additional naïve male subject with cutaneous sensation intact to perform a series of 10 lifts against a 2.0-N resistive force with the fingers aligned and then deliberately misaligned by about 20 mm in either the horizontal or vertical directions. Figure 9A shows that when the fingers were accurately aligned, there was practically no z-axis torque, and the y-axis torque was rather small. In contrast, Fig. 9B shows that when the fingers were misaligned in the vertical direction, a significant z-axis torque appeared with the same small amount of y-axis torque. Figure 9C shows that misalignment in the horizontal direction caused a significant y-axis torque with negligible z-axis torque. Although not illustrated, the deliberate finger misalignment was also accompanied by a significant increase in the grip force.
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EFFECT OF EXCESSIVE GRIP FORCE. A second control was carried out to determine what effect excessive grip force would have by itself. A naïve female subject with cutaneous sensation intact was asked to perform a series of 10 lifts against a 2.0-N resistive force using the force of her own choosing, and then a second series of 10 lift-and-hold trials using a 9.0-N grip force that was about the average force used by subjects with anesthetized fingers. The mean misalignment distance under the control condition was 1.83 mm compared with 2.27 mm using excessive grip force, but an F test indicated that this difference was not statistically significant. However the y-axis torque increased from an average of 19.0 to 119.3 N-mm [F(1,18) = 37.134, P < 0.001], and the z-axis torque increased from an average of 3. 3 to 13.0 N-mm [F(1,18) = 9.798, P < 0.001].
GRASPING LIFTING AND HOLDING IN A PATIENT WITH A POLYSENSORY
NEUROPATHY.
We compared the grasping and holding performance of healthy subjects
after digital anesthesia with a 50-yr-old female patient, G. L.,
suffering from a polysensory neuropathy involving the afferent fibers over the entire body below the nose. The patient has a complete
loss of touch, pressure, and kinesthesia in the limbs, neck, and trunk,
and her condition has been stable for more than 20 yr (Forget
and Lamarre 1987
, Simoneau et al. 1999
). G. L. was asked to perform the grasp, lift, and hold task, both with and without visual control. In the condition without vision, she was allowed to view the position of her hand and the manipulandum between
trials. G. L. appeared to use a single default grip force since
object fragility was not a constraint. Her grip force was about the
same for the three resistive forces and two surface textures. She
increased her grip force further when performing the task without
visual feedback. Figure 7 (bottom) shows the 3-D
reconstruction of the pressure cones under the thumb and index finger
exerted by G. L. during static holding on three grasping trials
under visual control. The mean offset distance of the center of
pressure was greater than the mean distance in control subjects with
intact cutaneous sensation and was similar to the mean offset distance
in subjects after digital anesthesia. Figure 7 also shows that G. L. had a significant force imbalance favoring the index finger. In
addition, G. L. also had an unusually large finger skin contact
area, and this behavior may have reflected a compensatory strategy to
cope with losing the sense of friction on the fingers by spreading the
contact over a wider area of semi-compliant skin to increase the
friction with the grasped object.
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DISCUSSION |
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In the first experiment we were able to replicate several
observations from earlier studies of object manipulation after digital anesthesia. Specifically we confirmed that anesthetizing the thumb and
index fingers disrupted the preprogramming of grip and load forces. The
grip force onset and the initiation of the lifting force were
temporally dissociated, resulting in a significant increase in the
duration of the preloading phase (Johansson and Westling
1984a
; Westling and Johansson 1984
). We also
confirmed that the capacity to optimally adapt grip forces to the
simulated weight and surface friction of a manipulated object was
severely impaired by the loss of cutaneous sensation. However the most striking effect shown by all subjects in this study was the use of
vastly excessive grip forces during both lifting and holding, which had
also been reported in many previous studies (Häger-Ross and Johansson 1996
; Jenmalm and Johansson 1997
;
Johansson and Westling 1984a
; Johansson et al.
1992
; Westling and Johansson 1984
).
There are probably several reasons for the grip force increases after
digital anesthesia. First, local anesthesia reduces the rate of
sweating and lowers the skin-object friction, which is known to
influence grip force (Edin et al. 1992
; Johansson and Westling 1984b
; Smith et al. 1997
). However,
reduced friction due to dryness of the skin was only one factor
contributing to the higher sustained grip forces after digital
anesthesia. A second factor was the inadvertent and unconscious
application of forces and torques, which would have required increased
grip force to prevent the fingers from slipping on the grasping tabs.
Despite the fact that the subjects were fully familiarized with the
modest range of resistive forces offered by the apparatus, after
digital anesthesia, they nonetheless applied excessive grip forces
without apparent adaptation on over 25 trials. Moreover, the anesthesia
produced a significant disturbance in the correlation between the grip
and load forces and the preprogramming of the grip and load force rates
without any apparent tendency toward improvement. The anesthetized
subjects showed some grip force modulation with different resistive
forces presumably on the basis of proprioceptive feedback, whereas in
contrast, the patient with the polysensory neuropathy showed no
modulation of grip force with the various resistive forces. These
results are surprising considering the several studies demonstrating
anticipatory grip force control driven from an internal model of the
object (Flanagan and Wing 1993
, 1997
) or from motor
memories (Gordon et al. 1993
). On the basis of
these studies, one might have predicted a significant degree of
compensation as a result of the experience acquired with the normal
tactile sensation prior to the anesthesia. However, the results of this
study indicate that the preprogramming of the grip and load force rates
was severely disrupted by the local anesthesia. Instead, the data from
this study suggest that the internal model requires either continuous
tonic excitation from cutaneous receptors, or at the very least,
frequent intermittent reiteration to function optimally.
Jenmalm and Johansson (1997)
also found that changing
the angle of flat grasping surfaces from parallel to various positive and negative cambers substantially changed the grip forces in close
correlation with the net tangential-to-normal force ratio on the skin.
In this case, vision of the grasping surfaces was sufficient to produce
some compensation for the loss of tactile sensation from digital
anesthesia, probably because the tapered surfaces provided a
recognizable visual stimulus associated with either a substantial
increase or decrease in required grip force. The authors noted,
however, that despite some adaptation, the subjects with anesthetized
fingers invariably used "considerably stronger horizontal
forces " than the same subjects tested with normal digit sensitivity.
With cutaneous sensation intact, all subjects in the present study generated only very small forces in directions other than those intended for grasping and lifting. After digital anesthesia, the x- and z-axis linear forces arising from the force imbalance between the fingers and from pushing or pulling were significantly increased. In addition, significant off-axis torques appeared in the horizontal (y axis) and frontal (z axis) planes. However, it is important to emphasize that some of these extraneous forces might not have occurred on a freely moving object because they would have resulted in movement of the object that the subject could have corrected visually. Yet, because of the stationary nature of the apparatus in this study and coupled with the lack of pressure sensation from the fingers, substantial linear forces occurred during grasping about which the subjects were apparently unaware.
After local anesthesia, tangential forces arose because the pinch forces applied by each finger were no longer applied in a perfectly perpendicular manner between two completely aligned centers of pressure. Instead, each finger applied a vector that was partially tangential to the grasping surface, and together they created a tangential torque. This misapplication of the pinch meant that the measured grip force was closer to the slip point because of a substantial increase in the net tangential force and torque on the fingers.
The fixed nature of the manipulandum in this study compared with the
"free-standing" characteristic of test objects used in most other
studies of digital anesthesia raises an important question about the
generality of the results of this study. One advantage of our apparatus
is that it allowed us to demonstrate excessive force and misdirected
torques with much lower loads (i.e., 0.5-2.0 N) than previous studies.
These data imply that manipulating a freely moving object with
anesthetized fingers would result in substantial tilting and rotating
of the object although the extraneous linear forces in the x
and z axes observed with our fixed manipulandum would be
easily corrected by visual feedback. In a companion paper (Augurelle et
al. 2003
), it was found that, although subjects adapted relatively well
to holding an object stationary against gravity, when the object was
repeatedly accelerated and decelerated in oscillatory movements, it was
frequently dropped, presumably as a result of tilting beyond a critical
point. Why then, was this tilting not reported in earlier published
accounts of the effects of finger anesthesia (Cole and Abbs
1988
, Johansson and Westling 1984a
)? Possibly
because the centers of gravity of the objects used by both Cole
and Abbs (1988)
and Johansson and Westling (1984a)
were so far below the misaligned fingers that an
enormous torque would have been required to tilt the object to any
appreciable degree. Also, the objects in both these studies were not
truly free-standing but constrained either by cables (Cole and
Abbs 1988
) or by small holes cut into a table top
(Johansson and Westling 1984a
). Similarly, Edin
et al. (1992)
reported significant object tilting due to
different coefficients of friction beneath each finger, but the degree
of tilt had to be calculated because it was "barely
noticeable, " given the low center of gravity.
In this study, vision would only have been useful to insure the proper
alignment of the fingers. However, both the healthy subjects after
digital anesthesia and the deafferented patient with years of practice
in developing visual compensatory strategies failed to use visual
feedback to correct the finger alignment in precision grasping, perhaps
because the alignment discrepancy was too small to be visually
apparent. How the loss of touch sensation at the fingertips leads to
this misalignment of the fingertips during pinching is still not
entirely clear. Correct finger alignment is partly a proprioceptive
function that should be served by muscle spindles and tendon organs.
Edin (1992)
has shown that in hairy skin, SAI and SAII
skin afferents are highly sensitive to stretch and may also play an
important role in the kinesthesia of the hand. However, as anyone who
has attempted the manipulation of small objects wearing gloves can
attest, accurate placement of the fingers is clearly affected by the
loss of skin sensation.
The high density of skin mechanoreceptors in the fingertips probably provides an accurate image of the pressure vectors generated by the object in contact with the grasping digits. Some form of associative learning could establish a link between the direction of pressure on the fingertips when handling familiar objects and the necessary opposition force required from the intrinsic hand muscles. Nevertheless as noted above, memory representations or internal models cannot anticipate either the location or the direction of the pressure vectors without the presence of skin afferent input.
An important issue arising from this study is whether the increased grip force after digital anesthesia is the cause or the effect of inefficient grasping. Increased grip force certainly contributed causally and significantly to the off-axis forces and torques in this study. However, the increased grip force itself may have been a response to the increased slipperiness of the skin and the inadvertent increased tangential loading on the skin. The subject with intact sensation grasping with deliberately excessive grip force demonstrated that even with a small lever arm, large unintended torques can occur, and this effect is exacerbated by any misalignment of the fingers. We would therefore speculate that the increased grip force after digital anesthesia results not only from the loss of the sense of pressure on the skin, but also from the inability to estimate the direction and magnitude of tangential force vectors and consequent failure to appropriately direct the apposition forces of the thumb and index finger. Certainly cutaneous afferents play an important role in adapting grip and lifting forces to surface friction and object weight, but our results also suggest that, in addition, cutaneous mechanoreceptors make an important contribution to guiding the direction of pinch force vectors effectively.
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ACKNOWLEDGMENTS |
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We gratefully acknowledge the technical assistance of L. Lessard, J. Jodoin, C. Gauthier, and C. Valiquette. We also thank D. Bourbonnais for insight in the interpretation of the data and R. Dykes for critical comments on the manuscript. We benefited from constructive criticism received from T. Milner, A. Prochazka, and S. Scott.
This research was supported by a grant to Groupe de Recherche en Sciences Neurologiques from the Canadian Institutes for Health Research Council and to the Groupe de Recherche sur le Système Nerveux Central from the Fonds pour la Formation des Chercheurs et l'Aide à la Recherche (FCAR) and the Fonds de la Recherche en Santé du Quebec-FCAR Santé program.
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FOOTNOTES |
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Address for reprint requests: A. M. Smith, Centre de Recherche en Sciences Neurologiques, Département de Physiologie, Université de Montréal, C.P. 6128 Succursale Centre ville, Montreal, Quebec H3C 3T8, Canada (E-mail: allan.smith{at}umontreal.ca).
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