Segmentation and coupling in complex movements.

Viviani, Paolo; Cenzato, Marco

doi:10.1037/0096-1523.11.6.828

Cited by 134 publications

(149 citation statements)

References 34 publications

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“…Figure 5a shows the v-r plots for three sizes of ellipses taken from one representative subject. For the small ellipse, the uniform slope k appears to indicate one movement segment, in agreement with Viviani and Cenzato (1985). However, for larger ellipses the single slope splits into two slopes suggesting two segments.…”

Section: Power Law and Velocity Gain Factorsupporting

confidence: 77%

“…If the power law holds, the data lie on a straight line through the origin with the slope expressing the velocity gain factor k. During one elliptic cycle the continuous trajectory traverses the same linear slope four times. Importantly, if the data lie on more than one line throughout one elliptic cycle, this has been interpreted as evidence for different segments (Viviani, 1986;Viviani and Cenzato, 1985). Figure 5a shows the v-r plots for three sizes of ellipses taken from one representative subject.…”

Section: Power Law and Velocity Gain Factormentioning

confidence: 99%

“…Additionally, Viviani and Cenzato (1985) and Viviani (1986) investigated the role of the proportionality constant k as a means to reveal movement segmentation: as k is approximately constant during extended parts of the movement and only shifts abruptly at certain points of the trajectory, it was interpreted as an indicator for segmented control. Since the magnitude of k also appears to correlate with the average movement velocity in a movement segment, k was termed the "velocity gain factor."…”

Section: Introductionmentioning

confidence: 99%

“…Since the magnitude of k also appears to correlate with the average movement velocity in a movement segment, k was termed the "velocity gain factor." Viviani and Cenzato (1985) found that planar elliptical drawing patterns are characterized by a single k and, therefore, consist of one unit of action. However, in a fine-grained analysis of elliptic patterns of different eccentricities, Wann , Nimmo-Smith, and Wing ( 1988) demonstrated consistent deviations from this result.…”

Section: Introductionmentioning

confidence: 99%

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Segmentation of endpoint trajectories does not imply segmented control

Sternad¹,

Schaal²

1999

Experimental Brain Research

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Abstract:While it is generally assumed that complex movements consist of a sequence of simpler units, the quest to define these units of action, or movement primitives, still remains an open question. In this context, two hypotheses of movement segmentation of endpoint trajectories in 3D human drawing movements are re-examined: (1) the strokebased segmentation hypothesis based on the results that the proportionality coefficient of the 2/3 power law changes discontinuously with each new "stroke", and (2) the segmentation hypothesis inferred from the observation of piecewise planar endpoint trajectories of 3D drawing movements. In two experiments human subjects performed a set of elliptical and figure-8 patterns of different sizes and orientations using their whole arm in 3D. The kinematic characteristics of the endpoint trajectories and the seven joint angles of the arm were analyzed. While the endpoint trajectories produced similar segmentation features as reported in the literature, analyses of the joint angles show no obvious segmentation but rather continuous oscillatory patterns. By approximating the joint angle data of human subjects with sinusoidal trajectories, and by implementing this model on a 7-degree-of-freedom anthropomorphic robot arm, it is shown that such a continuous movement strategy can produce exactly the same features as observed by the above segmentation hypotheses. The origin of this apparent segmentation of endpoint trajectories is traced back to the nonlinear transformations of the forward kinematics of human arms. The presented results demonstrate that principles of discrete movement generation may not be reconciled with those of rhythmic movement as easily as has been previously suggested, while the generalization of nonlinear pattern generators to arm movements can offer an interesting alternative to approach the question of units of action.

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Section: Power Law and Velocity Gain Factorsupporting

confidence: 77%

Section: Power Law and Velocity Gain Factormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Segmentation of endpoint trajectories does not imply segmented control

Sternad¹,

Schaal²

1999

Experimental Brain Research

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“…2/3-PL evolves with age during childhood (Sciaky et al 1987;Viviani and Schneider 1991) and interacts in subtle ways with the spontaneous tendency to modulate the average velocity as a function of movement size (Viviani and McCollum 1983;Viviani and Cenzato 1985;Viviani et al 2009). …”

Section: Showed That V(t) Is Approximately Proportional To the Cubic mentioning

confidence: 99%

Drawing ellipses in water: evidence for dynamic constraints in the relation between velocity and path curvature

et al. 2016

Self Cite

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Several types of continuous human movements comply with the so-called Two-Thirds Power Law (2/3-PL) stating that velocity (V) is a power function of the radius of curvature (R) of the endpoint trajectory. The origin of the 2/3-PL has been the object of much debate. An experiment investigated further this issue by comparing two-dimensional drawing movements performed in air and water. In both conditions, participants traced continuously quasi-elliptic trajectories (period T = 1.5 s). Other experimental factors were the movement plane (horizontal/vertical), and whether the movement was performed free-hand, or by following the edge of a template. In all cases a power function provided a good approximation to the V-R relation. The main result was that the exponent of the power function in water was significantly smaller than in air. This appears incompatible with the idea that the power relationship depends only on kinematic constraints and suggests a significant contribution of dynamic factors. We argue that a satisfactory explanation of the observed behavior must take into account the interplay between the properties of the central motor commands and the visco-elastic nature of the mechanical plant that implements the commands

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Biomechanical Insights into Neural Control of Movement

Zernicke

Smith

1996

Comprehensive Physiology

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The sections in this article are: Analytical Techniques and Terms Biomechanics Terminology Dynamics Variables Single vs. Multiple Degrees of Freedom Free‐Body Diagram Dynamics Techniques Insights from Inverse Dynamics Equations of Motion Anthropometric Data Predictions Using an Inverse Dynamics Model Control of Different Locomotion Forms Swing‐Phase Dynamics Stance‐Phase Dynamics Insights for Neural Control of Locomotion Role of Dynamics in the Control of Arm Movements Limb Postural Dynamics Intersegmental Dynamics Change with Practice Changes in Limb Dynamics During Development Spontaneous Kicking Behaviors Acquisition of Reaching Concluding Remarks

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Segmentation and coupling in complex movements.

Cited by 134 publications

References 34 publications

Segmentation of endpoint trajectories does not imply segmented control

Segmentation of endpoint trajectories does not imply segmented control

Drawing ellipses in water: evidence for dynamic constraints in the relation between velocity and path curvature

Biomechanical Insights into Neural Control of Movement

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