A kinematic theory of rapid human movement. Part IV: a formal mathematical proof and new insights

A few years ago a kinematic theory was proposed to study and analyze rapid human movements. The theory relies on a model of a synergy made up of two neuromuscular systems, one agonist and the other antagonist to the movement. Representing these systems with lognormal impulse responses, it is predicted that the velocity profile of a fast movement will be described by a delta-lognormal equation. So far, many studies have been conducted to test and empirically validate the theory. This paper presents an extended mathematical proof of the model. The proof is based on the Central Limit Theorem under the assumption that a law of proportionate effect governs the cumulative time delays of a sequence of dependent subprocesses constituting a neuromuscular system. Furthermore, a detailed interpretation of the parameters of the delta-lognormal equation, in terms of movement time and amplitude, response time and time delays, is discussed, providing new insights into the properties of the model with respect to neuromuscular system activity and movement generation.     

A kinematic theory of rapid human movements: Part III. Kinetic outcomes

This paper describes the kinematic and kinetic properties of simple rapid movements using a single and unique framework based on a delta-lognormal law (Plamondon 1993a,b, 1995a,b). Predictions concerning isotonic measurements are made using the properties of acceleration profiles, as described by the first time derivative of the delta-lognormal law. Predictions dealing with isometric measurements are directly analyzed using the delta-lognormal law, after demonstrating the experimental equivalence between isometric forces and virtual velocity profiles. The theory is also used to make statistical predictions about the variability of numerous kinematic and kinetic variables. The overall approach can be viewed as if, at some level of representation, the central nervous system were planning, executing and evaluating simple rapid movements in terms of momentum and energy instead of forces. The unifying perspective provided by the theory constitutes a powerful tool with which to study and analyze movements under numerous experimental conditions, using a single analytical law. Received: 13 November 1996 / Accepted in revised form: 6 November 1997     

A kinematic theory of rapid human movements

 This paper proposes a kinematic theory that can be used to study and analyze rapid human movements. It describes a synergy in terms of the agonist and antagonist neuromuscular systems involved in the production of these movements. It is shown that these systems have a log-normal impulse response that results from the limiting behavior of a large number of interdependent neuromuscular networks, as predicted by the central limit theorem. The delta log-normal law that follows from this model is very general and can reproduce almost perfectly the complete velocity patterns of an end-effector. The theory accounts for the invariance and rescalability of these patterns, as well as for the various observations that have been reported concerning the change in maximum and mean velocities, time to maximum velocity, etc., under different experimental conditions. Movement time, load effects, and control strategies are discussed in a companion paper. Received: 15 February 1993/Accepted in revised form: 15 September 1994     

Kinematic invariants during cyclical arm movements

It has been observed that the motion of the arm end-point (the hand, fingertip or the tip of a pen) is characterized by a number of regularities (kinematic invariants). Trajectory is usually straight, and the velocity profile has a bell shape during point-to-point movements. During drawing movements, a two-thirds power law predicts the dependence of the end-point velocity on the trajectory curvature. Although various principles of movement organization have been discussed as possible origins of these kinematic invariants, the nature of these movement trajectory characteristics remains an open question. A kinematic model of cyclical arm movements derived in the present study analytically demonstrates that all three kinematic invariants can be predicted from a two-joint approximation of the kinematic structure of the arm and from sinusoidal joint motions. With this approach, explicit expressions for two kinematic invariants, the two-thirds power law during drawing movements and the velocity profile during point-to-point movements are obtained as functions of arm segment lengths and joint motion parameters. Additionally, less recognized kinematic invariants are also derived from the model. The obtained analytical expressions are further validated with experimental data. The high accuracy of the predictions confirms practical utility of the model, showing that the model is relevant to human performance over a wide range of movements. The results create a basis for the consolidation of various existing interpretations of kinematic invariants. In particular, optimal control is discussed as a plausible source of invariant characteristics of joint motions and movement trajectories.     

A model of handwriting

The research reported here is concerned with hand trajectory planning for the class of movements involved in handwriting. Previous studies show that the kinematics of human two-joint arm movements in the horizontal plane can be described by a model which is based on dynamic minimization of the square of the third derivative of hand position (jerk), integrated over the entire movement. We extend this approach to both the analysis and the synthesis of the trajectories occurring in the generation of handwritten characters. Several basic strokes are identified and possible stroke concatenation rules are suggested. Given a concise symbolic representation of a stroke shape, a simple algorithm computes the complete kinematic specification of the corresponding trajectory. A handwriting generation model based on a kinematics from shape principle and on dynamic optimization is formulated and tested. Good qualitative and quantitative agreement was found between subject recordings and trajectories generated by the model. The simple symbolic representation of hand motion suggested here may permit the central nervous system to learn, store and modify motor action plans for writing in an efficient manner.     

The point of no return in planar hand movements: an indication of the existence of high level motion primitives

Previous psychophysical studies have sought to determine whether the processes of movement engagement and termination are dissociable, whether stopping an action is a generic process, and whether there is a point in time in which the generation of a planned action is inevitable (“point of no return”). It is not clear yet, however, whether the action of stopping is merely a manifestation of low level, dynamic constraints, or whether it is also subject to a high level, kinematic plan. In the present study, stopping performance was studied while nine subjects, who generated free scribbling movements looking for the location of an invisible circular target, were requested unexpectedly to impede movement. Temporal analysis of the data shows that in 87% of the movements subsequent to the ‘stop’ cue, the tangential motion velocity profile was not a decelerating function of the time but rather exhibited a complex pattern comprised of one or more velocity peaks, implying an unstoppable motion element. Furthermore, geometrical analysis shows that the figural properties of the path generated after the ‘stop’ cue were part of a repetitive geometrical pattern and that the probability of completing a pattern after the ‘stop’ cue was correlated with the relative advance in the geometrical plan rather than the amount of time that had elapsed from the pattern initiation. Altogether, these findings suggest that the “point of no return” phenomenon in humans may also reflect a high level kinematic plan and could serve as a new operative definition of motion primitives.     

Seeing Circles and Drawing Ellipses: When Sound Biases Reproduction of Visual Motion

The perception and production of biological movements is characterized by the 1/3 power law, a relation linking the curvature and the velocity of an intended action. In particular, motions are perceived and reproduced distorted when their kinematics deviate from this biological law. Whereas most studies dealing with this perceptual-motor relation focused on visual or kinaesthetic modalities in a unimodal context, in this paper we show that auditory dynamics strikingly biases visuomotor processes. Biologically consistent or inconsistent circular visual motions were used in combination with circular or elliptical auditory motions. Auditory motions were synthesized friction sounds mimicking those produced by the friction of the pen on a paper when someone is drawing. Sounds were presented diotically and the auditory motion velocity was evoked through the friction sound timbre variations without any spatial cues. Remarkably, when subjects were asked to reproduce circular visual motion while listening to sounds that evoked elliptical kinematics without seeing their hand, they drew elliptical shapes. Moreover, distortion induced by inconsistent elliptical kinematics in both visual and auditory modalities added up linearly. These results bring to light the substantial role of auditory dynamics in the visuo-motor coupling in a multisensory context.     

A neural model for generating and learning a rapid movement sequence

 In this article, a neural model for generating and learning a rapid ballistic movement sequence in two-dimensional (2D) space is presented and evaluated in the light of some considerations about handwriting generation. The model is based on a central nucleus (called a planning space) consisting of a fully connected grid of leaky integrators simulating neurons, and reading an input vector Ξ (t) which represents the external movement of the end effector. The movement sequencing results in a succession of motor strokes whose instantiation is controlled by the global activation of the planning space as defined by a competitive interaction between the neurons of the grid. Constraints such as spatial accuracy and movement time are exploited for the correct synchronization of the impulse commands. These commands are then fed into a neuromuscular synergy whose output is governed by a delta lognormal equation. Each movement sequence is memorized originally as a symbolic engram representing the sequence of the principal reference points of the 2D movement. These points, called virtual targets, correspond to the targets of each single rapid motor stroke composing the movement sequence. The task during the learning phase is to detect the engram corresponding to a new observed movement; the process is controlled by the dynamics of the neural grid. Received: 16 March 1995/Accepted in revised form: 25 July 1995     

A role for the cerebellum in the control of limb movement velocity

Accepting, rejecting or modifying the many different theories of the cerebellum's role in the control of movement requires an understanding of the signals encoded in the discharge of cerebellar neurons and how those signals are transformed by the cerebellar circuitry. Particularly challenging is understanding the sensory and motor signals carried by the two types of action potentials generated by cerebellar Purkinje cells, the simple spikes and complex spikes. Advances have been made in understanding this signal processing in the context of voluntary arm movements. Recent evidence suggests that mossy fiber afferents to the cerebellar cortex are a source of kinematic signals, providing information about movement direction and speed. In turn, the simple spike discharge of Purkinje cells integrates this mossy fiber information to generate a movement velocity signal. Complex spikes may signal errors in movement velocity. It is proposed that the cerebellum uses the signals carried by the simple and complex spike discharges to control movement velocity for both step and tracking arm movements.     

Development and validation of a 3-D model to predict knee joint loading during dynamic movement

The purpose of this study was to develop a subject-specific 3-D model of the lower extremity to predict neuromuscular control effects on 3-D knee joint loading during movements that can potentially cause injury to the anterior cruciate ligament (ACL) in the knee. The simulation consisted of a forward dynamic 3-D musculoskeletal model of the lower extremity, scaled to represent a specific subject. Inputs of the model were the initial position and velocity of the skeletal elements, and the muscle stimulation patterns. Outputs of the model were movement and ground reaction forces, as well as resultant 3-D forces and moments acting across the knee joint. An optimization method was established to find muscle stimulation patterns that best reproduced the subject's movement and ground reaction forces during a sidestepping task. The optimized model produced movements and forces that were generally within one standard deviation of the measured subject data. Resultant knee joint loading variables extracted from the optimized model were comparable to those reported in the literature. The ability of the model to successfully predict the subject's response to altered initial conditions was quantified and found acceptable for use of the model to investigate the effect of altered neuromuscular control on knee joint loading during sidestepping. Monte Carlo simulations (N = 100,000) using randomly perturbed initial kinematic conditions, based on the subject's variability, resulted in peak anterior force, valgus torque and internal torque values of 378 N, 94 Nm and 71 Nm, respectively, large enough to cause ACL rupture. We conclude that the procedures described in this paper were successful in creating valid simulations of normal movement, and in simulating injuries that are caused by perturbed neuromuscular control.     

Towards reasoning and coordinating action in the mental space

Unlike a purely reactive system where the motor output is exclusively controlled by the actual sensory input, a cognitive system must be capable of running mental processes which virtually simulate action sequences aimed at achieving a goal. The mental process either attempts to find a feasible course of action compatible with a number of constraints (Internal, Environmental, Task Specific etc) or selects it from a repertoire of previously learned actions, according to the parameters of the task. If neither reasoning process succeeds, a typical backup strategy is to look for a tool that might allow the operator to match all the task constraints. This further necessitates having the capability to alter ones own goal structures to generate sub-goals which must be successfully accomplished in order to achieve the primary goal. In this paper, we introduce a forward/inverse motor control architecture (FMC/IMC) that relaxes an internal model of the overall kinematic chain to a virtual force field applied to the end effector, in the intended direction of movement. This is analogous to the mechanism of coordinating the motion of a wooden marionette by means of attached strings. The relaxation of the FMC/IMC pair provides a general solution for mentally simulating an action of reaching a target position taking into consideration a range of geometric constraints (range of motion in the joint space, internal and external constraints in the workspace) as well as effort-related constraints (range of torque of the actuators, etc.). In case, the forward simulation is successful, the movement is executed; otherwise the residual "error" or measure of inconsistency is taken as a starting point for breaking the action plan into a sequence of sub actions. This process is achieved using a recurrent neural network (RNN) which coordinates the overall reasoning process of framing and issuing goals to the forward inverse models, searching for alternatives tools in solution space and formation of sub-goals based on past context knowledge and present inputs. The RNN + FMC/IMC system is able to successfully reason and coordinate a diverse range of reaching and grasping sequences with/without tools. Using a simple robotic platform (5 DOF Scorbot arm + Stereo vision) we present results of reasoning and coordination of arm/tool movements (real and mental simulation) specifically directed towards solving the classical 2-stick paradigm from animal reasoning at a non linguistic level.     

Linear ensemble-coding in midbrain superior colliculus specifies the saccade kinematics

Recently, we proposed an ensemble-coding scheme of the midbrain superior colliculus (SC) in which, during a saccade, each spike emitted by each recruited SC neuron contributes a fixed minivector to the gaze-control motor output. The size and direction of this 'spike vector' depend exclusively on a cell's location within the SC motor map (Goossens and Van Opstal, in J Neurophysiol 95: 2326-2341, 2006). According to this simple scheme, the planned saccade trajectory results from instantaneous linear summation of all spike vectors across the motor map. In our simulations with this model, the brainstem saccade generator was simplified by a linear feedback system, rendering the total model (which has only three free parameters) essentially linear. Interestingly, when this scheme was applied to actually recorded spike trains from 139 saccade-related SC neurons, measured during thousands of eye movements to single visual targets, straight saccades resulted with the correct velocity profiles and nonlinear kinematic relations ('main sequence properties' and 'component stretching'). Hence, we concluded that the kinematic nonlinearity of saccades resides in the spatial-temporal distribution of SC activity, rather than in the brainstem burst generator. The latter is generally assumed in models of the saccadic system. Here we analyze how this behaviour might emerge from this simple scheme. In addition, we will show new experimental evidence in support of the proposed mechanism.     

Automatic versus voluntary motor imitation: effect of visual context and stimulus velocity

Automatic imitation is the tendency to reproduce observed actions involuntarily. Though this topic has been widely treated, at present little is known about the automatic imitation of the kinematic features of an observed movement. The present study was designed to understand if the kinematics of a previously seen stimulus primes the executed action, and if this effect is sensitive to the kinds of stimuli presented. We proposed a simple imitation paradigm in which a dot or a human demonstrator moved in front of the participant who was instructed either to reach the final position of the stimulus or to imitate its motion with his or her right arm. Participants' movements were automatically contaminated by stimulus velocity when it moved according to biological laws, suggesting that automatic imitation was kinematic dependent. Despite that the performance, in term of reproduced velocity, improved in a context of voluntary imitation, subjects did not replicate the observed motions exactly. These effects were not affected by the kind of stimuli used, i.e., motor responses were influenced in the same manner after dot or human observation. These findings support the existence of low-level sensory-motor matching mechanisms that work on movement planning and represent the basis for higher levels of social interaction.     

Vulnerable window for conduction block in a one-dimensional cable of cardiac cells, 1: single extrasystoles

Spatial dispersion of refractoriness, which is amplified by genetic diseases, drugs, and electrical and structural remodeling during heart disease, is recognized as a major factor increasing the risk of lethal arrhythmias and sudden cardiac death. Dispersion forms the substrate for unidirectional conduction block, which is required for the initiation of reentry by extrasystoles or rapid pacing. In this study, we examine theoretically and numerically how preexisting gradients in refractoriness control the vulnerable window for unidirectional conduction block by a single premature extrasystole. Using a kinematic model to represent wavefront-waveback interactions, we first analytically derived the relationship (under simplified conditions) between the vulnerable window and various electrophysiological parameters such as action potential duration gradients, refractoriness barriers, conduction velocity restitution, etc. We then compared these findings to numerical simulations using the kinematic model or the Luo-Rudy action potential model in a one-dimensional cable of cardiac cells. The results from all three methods agreed well. We show that a critical gradient in action potential duration for conduction block can be analytically derived, and once this critical gradient is exceeded, the vulnerable window increases proportionately with the refractory barrier and is modulated by conduction velocity restitution and gap junctional conductance. Moreover, the critical gradient for conduction block is higher for an extrasystole traveling in the opposite direction from the sinus beat than for one traveling in the same direction (e.g., an epicardial extrasystole versus an endocardial extrasystole).     

The role of the plant properties in point-to-point arm movements: a robustness study

In recent papers we demonstrated by means of a modeling study that the smoothness of hand paths and the bell-shaped character of hand velocity profiles which have been experimentally observed in point-to-point arm movements can be largely attributed to the biomechanical properties of the arm rather than to specific planning by the central nervous system. In this paper we present a study of the robustness of our earlier results comprising two goals: (i) the determination of the range of model parameters for which such observations remain valid, (ii) the identification of possible relationships between model parameters and kinematic variables. The results of this study imply three conclusions: (i) the valid range of the tested model parameters (namely the main muscle parameters) is large, (ii) the modeled phenomena are well behaved in that parametric changes do not give rise to bifurcations or other behavioral discontinuities in the analyzed ranges, (iii) there exist precise relationships between certain muscle parameters and the time course of the hand velocity. These results point out that the phenomena observed in our previous work are indeed robust and can lead to useful insights into the mechanisms comprising the regulatory action of the central nervous system as well as into the design principles for biologically inspired artificial arms. Received: 4 December 1995 / Accepted in revised form: 6 November 1996     

A model of the variation of water potential and diameter within a woody axis cross-section under transpiration conditions

 The spatio-temporal variation of water potential and the corresponding changes in diameter in a woody axis cross-section have been modelled. The two-dimensional space model is based on the assumption that the water flux is regulated by Darcy’s law which leads to a diffusion type equation. This equation takes into account the water movements to and from the xylem vessels in space and time. The water potential of the vessels being given, a numerical solution provided the values of the water potential variations of the wood and peripheral elastic tissues in the woody axis cross-section throughout the day. By specifying that the predawn water potential equilibrates throughout the whole section, this study enabled us to determine a range of satisfactory values of parameters. A first validation was given by an application of the model to a peach-tree. It was performed by comparing the calculated variations in diameter of a trunk to those which were measured. In conclusion we discuss some physiological consequences of the model. Received: 25 January 1997 / Accepted: 13 October 1997