Interaction torque contributes to planar reaching at slow speed
- 6.8k Downloads
How the central nervous system (CNS) organizes the joint dynamics for multi-joint movement is a complex problem, because of the passive interaction among segmental movements. Previous studies have demonstrated that the CNS predictively compensates for interaction torque (INT) which is arising from the movement of the adjacent joints. However, most of these studies have mainly examined quick movements, presumably because the current belief is that the effects of INT are not significant at slow speeds. The functional contribution of INT for multijoint movements performed in various speeds is still unclear. The purpose of this study was to examine the contribution of INT to a planer reaching in a wide range of motion speeds for healthy subjects.
Subjects performed reaching movements toward five targets under three different speed conditions. Joint position data were recorded using a 3-D motion analysis device (50 Hz). Torque components, muscle torque (MUS), interaction torque (INT), gravity torque (G), and net torque (NET) were calculated by solving the dynamic equations for the shoulder and elbow. NET at a joint which produces the joint kinematics will be an algebraic sum of torque components;
NET = MUS - G - INT.
Dynamic muscle torque (DMUS = MUS-G) was also calculated. Contributions of INT impulse and DMUS impulse to NET impulse were examined.
The relative contribution of INT to NET was not dependent on speed for both joints at every target. INT was additive (same direction) to DMUS at the shoulder joint, while in the elbow DMUS counteracted (opposed to) INT. The trajectory of reach was linear and two-joint movements were coordinated with a specific combination at each target, regardless of motion speed. However, DMUS at the elbow was opposed to the direction of elbow movement, and its magnitude varied from trial to trial in order to compensate for the variability of INT.
Interaction torque was important at slow speeds. Muscle torques at the two joints were not directly related to each other to produce coordinated joint movement during a reach. These results support Bernstein's idea that coordinated movement is not completely determined by motor command in multi-joint motion. Based on the data presented in this study and the work of others, a model for the connection between joint torques (muscle and passive torques including interaction torque) and joint coordination is proposed.
KeywordsTorque Elbow Joint Muscle Torque Interaction Torque Passive Torque
Unlike the single joint movement, the dynamics of multi-joint movement is complex. Specifically, interaction torque (INT) will be included into the joint dynamics, which is arising from the movement of the adjacent joints . INT at a joint, therefore, may be regarded by the CNS as an unavoidable passive disturbance which is to be adjusted for multijoint movement coordination.
Except for movement in the horizontal plane, net torque (NET) produces joint kinematics that can be shown as an algebraic sum of muscle (MUS), interaction (INT), and gravity torque (G); NET = MUS - INT - G
Previous studies on healthy subjects have shown that INT arising during rapid multi-joint movement is of sufficient magnitude to influence movement trajectory [1, 2]. These authors have postulated that the CNS can predictively compensate or utilize INT [3, 4, 5, 6, 7]. INT in multi-joint dynamics have been investigated mainly for reaching movements [8, 9, 10, 11, 12, 13]. Studies on patients with cerebellar lesions [14, 15, 16, 17] or without proprioception [18, 19, 20] have an inability to control interaction torques, thereby resulting in kinematic deficits.
INT is dependent on joint acceleration and velocity. Motion speed has thus been considered as an essential factor for the effects of INT on multi-joint movement. However, it was pointed out qualitatively that the relative contribution of velocity was significant regardless of the movement speed . Functional role of the interaction and muscle torque for the production of planar reaching through different movement speed is still unclear.
The primary purpose of this study was to re-examine whether the effects of interaction torque on multi-joint reaching movement is significant at slow speed. Planar reach involving shoulder and elbow joints toward different targets in the sagittal plane was examined under a wide range of motion speeds.
It is known that the trajectory of reach and joint coordination have invariant characteristics irrespective of target position and movement speed . If the effect of the interaction torque was significant over a range of different speed, then a question arises as to how the relation of muscle torque between neighboring joints is adequately produced to achieve multi-joint coordination. Therefore, a secondary purpose of this study was to explore whether the coordination between muscle torques at two joints corresponds to coordinated joint movements.
Ten right-handed healthy adults (five males and five females) gave an informed consent to participate in this study. All protocols were approved by the Review Board of Tohoku Bunka Gakuen University. They had no neurological, musculoskeletal, or visual disorders by self-report. The subject's age ranged from 20 to 22 years (average 21 yrs).
The subjects sat on a stool with their shoulder 0° flexed, 0° adducted and 0° outward rotated. Their right elbow joint and hand were flexed 90° and at a middle position to supination and pronation, respectively. The subjects were asked to reach their right hand by pointing at a small target in the sagittal plane while keeping their trunk in the initial position. Each target was 1 cm in width and wrapped around a stick of 1.5 cm diameter that stood in front of the right shoulder joint. The subjects were verbally instructed to reach at fast, natural (comfortable), and slow speed. Accuracy of the pointing was not required.
Subjects were allowed to practice several times by reaching at T45 to familiarize themselves with the task. All subjects first reached to T60 under a slow speed condition, and then target and motion speed were randomly assigned. The subjects performed a total of 15 trails (5 targets × 3 speeds).
Data collection and analysis
Adhesive infra-red reflex markers were placed on the acromion, the lateral epicondyle of the humerus, and middle point between styloid process of the ulnaris and radius of the right arm, and positions were collected using a three-dimension motion analysis device (ELITE puls, BTS, 50 Hz). Position data of each joint was smoothed with a cutoff frequency of 3 Hz for natural and slow speed conditions, and 1 Hz for the very slow speed condition using a second order Butterworth filter . Using these position data, joint angle, velocity, and acceleration were calculated for the shoulder and elbow joints.
Since the angular velocity profile had always a single peak, peak angular velocity was calculated for each joint in each trial. The onset and termination of movement were determined at the time where the angular velocity of the shoulder or elbow exceeded 5% of its peak. The duration from the onset to the termination of movement was defined as movement time (MT).
Trajectory curvature index
Wrist path was quantified by curvature index (I = d/L) determined as the ratio of maximum path deviation (d) from a straight line (L) connecting the initial and final points of the wrist trajectory. A deviation under the straight line was evaluated as positive.
Calculation of torque components
The dynamic equations for two-linked rigid bodies composed of the upper and lower arms were used to calculate the joint torque components (i.e., MUS, NET, INT, and G for the shoulder and elbow joint)(Additional file 1). Anthropometric data were estimated from the height and weight of each subject .
Absolute torque impulse
The magnitude of each torque component was quantified by calculating absolute torque impulse during movement time. The G at the joints is a function of the angle and load, and is independent of movement speed (see Additional file 1). Because this study aimed to examine dynamic changes in muscle torque components, we calculated the "dynamic muscle torque" . Dynamic muscle torque (DMUS) was the residual muscle torque after removing the gravitational component. The impulse of DMUS was similarly calculated.
We quantified the relative contributions of DMUS and INT to NET as follows . In a period during which the INT was in the same direction as NET, the INT impulse was evaluated as positive, while when the INT was in the opposite direction to NET, the INT impulse was evaluated as negative. The total sum of the positive and negative INT impulses over movement time was divided by the absolute impulse of NET to yield a contribution index of INT to NET in each trial. Similarly, the positive and negative impulses of the DMUS were summed to yield a contribution index of DMUS to NET. The sum of both indexes was always 1.
Movement time (MT)
Movement time [ms]
Joint angular velocity
Although NET and interaction torque (INT) were small at slow speed, the relation between DMUS and NET was preserved for all speed conditions at both joints. That is, DMUS utilized (in the shoulder) or compensated (in the elbow) INT in order to generate the required joint movement.
Relative contribution of muscle and interaction torques to NET torque
The contribution index for elbow INT changed with the target (F = 167.17, p < 0.01) and was always positive and greater than 1, while the DMUS contribution index changed to negative with target height (F = 166.56, p < 0.01) (Figure 9B). Similar to the shoulder, there was no significant effect on the speed condition. The positive contribution of DMUS was found only in T45. In order to produce NET, there was a counteractive relationship between DMUS and INT at the elbow (i.e., the excess INT had to be counteracted by DMUS in order to generate the required NET). Interestingly, the DMUS contribution exhibited almost zero at T45 or T60, regardless of the movement speed. Specifically, the muscle torque was used only to cancel the gravity. In sum, the relative contribution of INT and DMUS to NET was not dependent on reaching speed at every target, both for the shoulder and elbow joints.
Coordination between torque components and kinematics
Correlate coefficients between peak angular velocity and torque impulse.
PV s – iNETs
PV e – iINTs
PV s – iDMUSs
PV e – iNETe
PV s – iINTe
PV e – iDMUSe
Kinematic invariance of reach and kinetic contributions
The experimental setting adopted in the present study was designed to simulate every day reaching in which subjects performed forward reaching in a vertical plane. Reaching targets differed both in direction and distance. The distance increased as the target got higher from T45 to T105 (Figure 2), but movement time remained the constant among targets (Table 1) because of a corresponding increase in the velocity of reach. Since increases in shoulder velocity with higher targets were compensated by decreases in elbow velocity (Figure 4), movement time was kept constant independent of the target position. The changes in angular velocity were directly related to the amount of net torque (iNET) required for reaching in the shoulder and elbow (Figure 8).
In addition, differences in target direction corresponded to gravity torque loaded on the both joints. Whereas gravity torque on the shoulder joint increased steadily with the target height, gravity on the elbow changed little (Figure 8). The effect of gravity on the trajectory generation has been examined by some researchers. A series of studies by Papaxanthis et al. showed that the direction of pointing movement was a determinant for arm trajectory generation in a vertical plane [26, 27, 28, 29]. The result of the present study is in agreement with their result, that is, the linearity of hand trajectory varied with the direction of reach. In particular, the trajectories of reaching movement to upper targets in this study, i.e., T90 and T105, were curved more greatly than the lower targets. This result implies that gravity affects the trajectory in vertical reaching.
Further, the present study suggests gravity and interaction torque both relate to wrist trajectory generation in multijoint movement. If the absolute magnitude of interaction torque was a major factor for trajectory generation, changes in the linearity of wrist trajectory would appear under different speed conditions. While the magnitude of the interaction torque (iINT) decreased as the reach got slower (Figure 8), the linearity of trajectory to a target was independent of the speed. Because of the speed-independency of the trajectory, it is suggested that the interaction torque contributed to the trajectory formation even at slow speed. This point will be discussed below.
Speed is independent of the relative contribution of interaction torque to net torque
We believe that the most remarkable finding of this study was that the contribution of INT to NET was important when reaching at slow speed. The contribution index of INT to NET was independent of speed for every target in the shoulder and elbow joints (Figure 9). As the velocity of reach decreases, the magnitude of INT and NET at the joints also decrease. This relation might be the reason for the fact that the relative contribution of INT to NET was independent of the speed. A recent study from our laboratory examined squatting and also showed the same speed-independency of the relative contribution of INT to NET (manuscript in preparation). It has been postulated that the speed of reaching is crucial for the effects of interaction torque, and therefore may be negligible for multi-joint movements at slow speed . Consequently, most recent studies have examined the effects of INT on fast movements.
Messier et al.  reported that patients with complete loss of proprioception experience a deficit in accuracy during slow reaching, and also suggested that the proprioceptive information providing cues for the predictive control of interaction torque is important, even when interaction torques are very small. Also, Hollerbach and Flash  demonstrated qualitatively that the effects of interaction torque may be relatively independent of speed. Our result is consistent with these works and suggests that the contribution of interaction torque to multi-joint movement may be significant irrespective of speed.
Direction-specific interaction torque
The contribution index of INT consistently depended on the target direction at both joints. This result is consistent with data presented in previous studies demonstrating that the magnitude of INT gradually changes with the direction of reaching [9, 10, 12]. As a larger shoulder flexion was required for the elbow extension (e.g., reaching toward T105), the contribution of iDMUS became more dominant than that of INT at the shoulder, while the INT contributed excessively to NET at the elbow. In contrast, when reaching toward T45 the contribution of INT became dominant when compared to iDMUS at the shoulder. The dependence of INT on the target position shown in our study could be attributed to changes in the joint angular velocities of the shoulder and elbow joints. For instance, the peak angular velocity at the shoulder during reaching toward T105 was faster than the others (see Figure 4), thus resulted in more interaction torque produced at the elbow (Figure 8).
The role of interaction torque and dynamic muscle torque
For every target, flexion DMUS and flexion INT always contributed in an additive fashion to flexion movement at the shoulder (i.e., INT assisted the shoulder movement). In other words, DMUS utilized the INT to produce a specific shoulder movement over a range of movement speeds. This can especially be seen by the contribution of DMUS to joint movement during T105 reaching. On the other hand, the contribution of DMUS also counteracted elbow movement. Because the INT overwhelmingly contributed to net torque production, DMUS was forced to compensate for the magnitude of the INT. Interestingly, when reaching to T45 and T60 the contribution of the DMUS to NET was quite low and the joint motion was produced solely by passive interaction torques caused by the shoulder joint.
Our results were consistent with the "shoulder-centered pattern"  or "leading joint hypothesis" , in which shoulder muscle torque predominates in the production of movement while the elbow muscles play a minor role. The torque profiles at the elbow (Figure 7) showed that DMUS was generated prior to NET. This result is consistent with the notion that the central nervous system (CNS) can predict coming interaction torque during multi-joint movement in a feed-forward manner [3, 4, 5, 6, 8, 31].
Implications for multi-joint coordination
The trajectory of reach examined in the present study was always linear to each target and the linearity was preserved regardless of movement speed (Figure 2). The linear trajectory of reach has been generally observed in planar reaching, except in the extreme margins of the work space . Therefore, the angular movements of joints involved in reaching should be also coordinated so that a linear trajectory is produced. This inter-joint coordination is demonstrated in Figure 3 for our reaching task. The relationship between shoulder and elbow joints is the result of inverse kinematics from the linear trajectory.
The question then arises as to how muscular torque acts on each joint in order to produce coordinated joint movement, or "By what rule has the CNS selected an appropriate muscle activation pattern to achieve the inter-joint coordination?" . If interaction torque can be neglected in multi-joint reaching, then the inter-joint coordination should closely correspond to the invariant relationship between the muscle torques of each joint. However, the joint net torque that produces inter-joint coordination cannot be determined solely by muscle torque (or dynamic muscle torque), because of the essential contribution of INT to NET. Consequently, muscle torques per se may be variable from trial to trial without corresponding to joint kinematics. This indeterminacy of muscle torque is indeed demonstrated in Figure 10 and Table 2 for the elbow joint in our reaching task. Also, the dynamic muscle torque could not predict the elbow peak velocity. In addition, the elbow muscle torque was opposed to the direction of the elbow movement.
Gottlieb et al. [32, 33] previously reported data indicating that shoulder and elbow torques keep a linear relation in averaged trials of their reaching task (i.e., "linear synergy"). Based on this data, Gottlieb et al. postulated that the CNS uses a single command that is transmitted to the muscle at two joints in a predetermined proportion, thereby reducing the degree of freedom for movement. However, their later work failed to provide evidence that shows the generality of "linear synergy" for reaching . Their studies on elbow muscle torque appeared to show linear relationship with shoulder torque, but it was often opposed to the direction of elbow movement depending on the target direction. The central command must designate the direction of elbow torque in this case, thereby requiring an additional degree of freedom.
The relative contributions of interaction torque to net torque were independent of reaching speed. Effect of the interaction torque was significant in reaching movement even at slow speeds. Muscle torque at the two joints was not adequately related to each other to produce coordinated joint movement. These results support Bernstein's idea on the multi-joint coordination.
We thank Dr. Kazutoshi Kudo and Dr. Tomoyuki Matsuo for helpful comments.
- 3.Flanagan JR, Wing AM: The role of internal models in motion planning and control: Evidence from grip force adjustments during movements of hand-held loads. J Neurosci 1997, 17: 1519–1528.Google Scholar
- 4.Gribble PL, Ostry DJ: Compensation for interaction torques during single- and multi-joint limb movement. J Neurophysiol 1999, 82: 2310–2326.Google Scholar
- 5.Hore J, Watts S, Tweed D: Prediction and compensation by an internal model for back forces during finger opening in an overarm throw. J Neurophysiol 1999, 82: 1187–1197.Google Scholar
- 6.Hore J, Watts S, Leschuk M, MacDougall : Control of finger grip forces in overarm throws made by skilled throwers. J Neurophysiol 2001, 86: 2678–2689.Google Scholar
- 8.Sainburg RL, Ghez C, Kalakanis D: Intersegmental dynamics are controlled by sequential anticipatory, error correction, and postural mechanisms. J Neurophysiol 1999, 81: 1045–1056.Google Scholar
- 9.Sainburg RL, Kalakanis D: Differences in control of limb dynamics during dominant and nondominant arm reaching. J Neurophysiol 2000, 83: 2661–2675.Google Scholar
- 10.Koshland GF, Galloway JC, Nevoret-Bell CJ: Control of the wrist in three-joint arm movements to multiple directions in the horizontal plane. J Neurophysiol 2000, 83: 3188–3195.Google Scholar
- 11.Almeida GL, Corcos DM, Hasan Z: Horizontal-plane arm movements with direction reversals performed by normal individuals and individuals with Down syndrome. J Neurophysiol 2000, 84: 1949–1960.Google Scholar
- 14.Bastian AJ, Martin TA, Keating JG, Thach WT: Cerebellar Ataxia: Abnormal control of interaction torques across multiple joints. J Neurophysiol 1996, 76: 492–509.Google Scholar
- 15.Bastian AJ, Zackowski KM, Thach WT: Cerebellar Ataxia: Torque deficiency or torque mismatch between joints? J Neurophysiol 2000, 83: 3019–3030.Google Scholar
- 17.Cooper SE, Martin JH, Ghez C: Effects of inactivation of the anterior interpositus nucleus on the kinematic and dynamic control of multijoint movement. J Neurophysiol 2000, 84: 1988–2000.Google Scholar
- 18.Sainburg RL, Ghilardi MF, Poizner H, Ghez C: Control of limb dynamics in normal subjects and patients without proprioception. J Neurophysiol 1995, 73: 820–835.Google Scholar
- 20.Messier J, Adamovich S, Berkinblit M, Tunik E, Poizer H: Influence of movement speed on accuracy and coordination of reaching movements to memorized targets in three-dimensional space in a deafferented subject. Exp Brain Res 2003, 150: 399–416.Google Scholar
- 21.Soechting JF, Lacquaniti F: Invariant characteristics of a pointing movement in man. J Neurosci 1981, 1: 710–720.Google Scholar
- 23.Winter DA: Biomechanics and motor control of human movement. John Wiley & Sons, New York; 2005.Google Scholar
- 24.Gottlieb GL, Song Q, Almeida GL, Hong D, Corcos D: Directional control of planar human arm movement. J Neurophysiol 1997, 78: 2985–2998.Google Scholar
- 25.Flash T, Hogan N: The coordination of arm movements: an experimentally confirmed mathematical model. J Neurosci 1985, 5: 1688–1703.Google Scholar
- 28.Papaxanthis C, Pozzo T, Schieppati M: Trajectories of arm pointing movements on the sagittal plane vary with both direction and speed. Exp Brain Res 2003, 148: 498–503.Google Scholar
- 32.Gottlieb GL, Song Q, Hong D, Corcos DM: Coordinating two degrees of freedom during human arm movement: Load and speed invariance of relative joint torques. J Neurophysiol 1996, 76: 3196–3206.Google Scholar
- 33.Gottlieb GL, Song Q, Hong D, Almeida GL, Corcos DM: Coordinating movement at two joints: A principle of linear covariance. J Neurophysiol 1996, 75: 1760–1764.Google Scholar
- 34.Bernstein N: The coordination and regulation of movements. Pergamon Press; 1967:104–113.Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.