Feedback Control of Hand-Movement and Fitts' Law

Crossman, E. R. F. W.; Goodeve, P. J.

doi:10.1080/14640748308402133

Cited by 456 publications

(339 citation statements)

References 8 publications

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“…Therefore, the "open-loop" motor response cannot be viewed as entirely preplanned. Crossman and Goodeve (1983) and Keele and Posner (1968) proposed a strategy of intermittent correction by a single control mechanism to explain the speed-accuracy relationship described by Fitts (1954). However, no evidence for intermittency was found for any of the observed control mechanisms in the present study.…”

Section: Second Adjustmentcontrasting

confidence: 52%

“…Studies attempting to explain the basis of Fitt's Law (Fitts, 1954) proposed that the final limb position was reached through a process of iterative correction of response errors by the same feedback mechanism (Crossman and Goodeve, 1963;Keele, 1968). Greene (1972Greene ( , 1982 has theorized that trajectory control could be simplified by updating motor responses with a number of different control mechanisms.…”

mentioning

confidence: 99%

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Mechanisms controlling accurate changes in elbow torque in humans

Cordo¹

1987

J. Neurosci.

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This paper addresses a fundamental question of how motor commands specify target torque levels. Human subjects produced fast and accurate changes in torque with the isometric elbow joint. Visual stimuli were used to indicate target torque levels as well as to cue subjects to initiate their responses. During rapid changes in torque from one steadystate level to another, target torque was achieved through a sequence of approximations. During the first 200-250 msec of responses produced in the presence of visual feedback, 3 distinct control mechanisms were recruited to guide torque to the target level.The timing and accuracy of each control mechanism were evaluated. The first control mechanism was triggered by the visual stimulus and produced the initial rise in torque. Target torque predictability was found to strongly influence the accuracy of this control mechanism. The second control mechanism produced a corrective adjustment in torque within roughly the first 100 msec of responses. This mechanism incorporated target torque information provided by the stimulus into the response. The third control mechanism began 200-250 msec after response onset and produced corrective adjustments based on visual feedback of torque errors.The stability of the visual feedback mechanism was evaluated because of a long loop delay. Two strategies were used to control stability: low gain and information transfer between the visual feedback mechanism and the preceding (second) control mechanism.A central issue in the study of goal-directed motor activity is how motor commands specify the final position or torque. Most studies have presumed that the final position or torque is encoded in early stages of motor commands. For example, the "equilibrium point hypothesis" of limb control holds that the initial activation levels of opposing muscle groups specify the final joint position by setting muscle stiffness (Feldman, 1966a, b;Polit and Bizzi, 1979) and that the net stiffness of the joint uniquely determines the final (equilibrium) limb position. Im-

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Section: Second Adjustmentcontrasting

confidence: 52%

mentioning

confidence: 99%

Mechanisms controlling accurate changes in elbow torque in humans

Cordo¹

1987

J. Neurosci.

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“…Pointing movements with accuracy constraints show evidence of small corrective submovements (cf. Crossman and Goodeve, 1983;Novak et al, 2000) that are though to be visually mediated. Furthermore, if the size of the object to be grasped is changed suddenly during the course of the reaching movement, hand kinematics are altered at short latency (Paulignan et al, 1991), just as arm movements are modified at short latency if the location of a target is shifted suddenly (Soechting and Lacquaniti, 1983;Pelisson et al, 1986).…”

Section: Sensory Guidance Of Hand Motionmentioning

confidence: 99%

Patterns of Hand Motion during Grasping and the Influence of Sensory Guidance

2002

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This study was aimed at describing temporal synergies of hand movement and determining the influence of sensory cues on the control of these synergies. Subjects were asked to reach to and grasp various objects under three experimental conditions: (1) memory-guided movements, in which the object was not in view during the movement; (2) virtual object, in which a virtual image of the object was in view but the object was not physically present; and (3) real object, in which the object was in view and physically present. Motion of the arm and of 15 degrees of freedom of the hand was recorded. A principal components analysis was developed to provide a concise description of the spatiotemporal patterns underlying the motion. Vision of the object during the reaching movement had no influence on the kinematics, and the effect of the physical presence of the object became manifest primarily after the fingers had contacted the object. Two principal components accounted for Ͼ75% of the variance. For both components, there was a strong positive correlation in the rotations of metacarpophalangeal and proximal interphalangeal joints of the fingers. The first principal component exhibited a pattern of finger extension reversing to flexion, whereas the second principal component became important only in the second half of the reaching movement.

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“…It predicts that the time required to rapidly move to a target is a function of the distance to and the size of the target. Fitts' law has been used to model the act of pointing in both the physical world [5] and the virtual environment [10,24]. One common formulation of the law is as follows:…”

Section: Modeling Interaction Taskmentioning

confidence: 99%

Modeling object pursuit for 3D interactive tasks in virtual reality

Liu

Liere

2011

2011 IEEE Virtual Reality Conference

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Models of interaction tasks are quantitative descriptions of relationships between human temporal performance and the spatial characteristics of the interactive tasks. Examples include Fitts' law for modeling the pointing task and Accot and Zhai's steering law for the path steering task, etc. Models can be used as guidelines to design efficient user interfaces and quantitatively evaluate interaction techniques and input devices.In this paper, we introduce a 3D object pursuit interaction task, in which users are required to continuously track a moving target in a virtual environment. The entire movement of the task is broken into a tracking phase and a correction phase. For each phase, we propose a model that has been verified by two experiments. As the experimental results show, the time for the tracking phase is fixed once a task has been established, while the time for the correction phase usually varies according to some characteristics of the task. It can be modeled as a function of path length, target width and the velocity with which the target moves.The proposed model can be used to quantitatively evaluate the efficiency of user interfaces that involve the interaction with moving objects.

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Feedback Control of Hand-Movement and Fitts' Law

Cited by 456 publications

References 8 publications

Mechanisms controlling accurate changes in elbow torque in humans

Mechanisms controlling accurate changes in elbow torque in humans

Patterns of Hand Motion during Grasping and the Influence of Sensory Guidance

Modeling object pursuit for 3D interactive tasks in virtual reality

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