The Experts below are selected from a list of 261 Experts worldwide ranked by ideXlab platform
Karl M Newell - One of the best experts on this subject based on the ideXlab platform.
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Visual information about past, current and future properties of irregular Target Paths in isometric force tracking
Attention Perception & Psychophysics, 2015Co-Authors: Molly M. Mazich, Breanna E. Studenka, Karl M NewellAbstract:In visual-motor tracking, information about past, current, and future properties of a Target Path can be available but, because they are typically manipulated independently, the relative contribution of these information categories to tracking performance is not well understood. The aim of the current study was to investigate the role of visual information pertaining to past, current, and future states of the Target Path in guiding isometric tracking performance as a function of the irregularity of the Target Path (sine wave, brown/pink noise, white noise). The findings from local and global properties of the force output showed that the role of visual information about the past, current, and future states of Target Paths is dependent on the regularity of the signal to be tracked. The brown/pink noise Pathway condition was most strongly influenced by future and past-future visual information for both local error properties (lead/lag, root mean square error (RMSE)) and global properties of the force output (ApEn, cross correlation). The highly irregular white noise Pathway did not benefit from past or future information and the highly regular sine wave was only influenced for the local error properties of RMSE and lead/lag. It appears that visual information about past and future tracking states is more effective with a Pathway that is middling with respect to regularity/irregularity. This is consistent with the role of visual information in tracking to be dependent on the potential adaptability for change in the dimension of the motor output.
Molly M. Mazich - One of the best experts on this subject based on the ideXlab platform.
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Visual information about past, current and future properties of irregular Target Paths in isometric force tracking
Attention Perception & Psychophysics, 2015Co-Authors: Molly M. Mazich, Breanna E. Studenka, Karl M NewellAbstract:In visual-motor tracking, information about past, current, and future properties of a Target Path can be available but, because they are typically manipulated independently, the relative contribution of these information categories to tracking performance is not well understood. The aim of the current study was to investigate the role of visual information pertaining to past, current, and future states of the Target Path in guiding isometric tracking performance as a function of the irregularity of the Target Path (sine wave, brown/pink noise, white noise). The findings from local and global properties of the force output showed that the role of visual information about the past, current, and future states of Target Paths is dependent on the regularity of the signal to be tracked. The brown/pink noise Pathway condition was most strongly influenced by future and past-future visual information for both local error properties (lead/lag, root mean square error (RMSE)) and global properties of the force output (ApEn, cross correlation). The highly irregular white noise Pathway did not benefit from past or future information and the highly regular sine wave was only influenced for the local error properties of RMSE and lead/lag. It appears that visual information about past and future tracking states is more effective with a Pathway that is middling with respect to regularity/irregularity. This is consistent with the role of visual information in tracking to be dependent on the potential adaptability for change in the dimension of the motor output.
Leigh A. Mrotek - One of the best experts on this subject based on the ideXlab platform.
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Following and intercepting scribbles: interactions between eye and hand control
Experimental Brain Research, 2013Co-Authors: Leigh A. MrotekAbstract:The smooth pursuit eye movement system appears to be importantly engaged during the planning and execution of interceptive hand movements. The present study sought to probe the interaction between eye and hand control systems by examining their responses during an interception task that included Target speed perturbations. On 2/3 of trials, the Target increased or decreased speed at various times, ranging from about 300 ms before to 150 ms after the onset of a finger movement directed to intercept the Target and was triggered by a GO signal. Additionally, the same 2D sum-of-sines Target trajectories were followed with the eyes without interception. The smooth pursuit system responded more quickly if the Target speed perturbation occurred earlier during the reaction time (i.e., near the time of the GO signal). Similarly, the finger movement began more quickly if Target speed was increased earlier during the reaction time. For early perturbation conditions, the initial direction of the finger movement matched the predicted Target intercept using the new Target speed. For perturbations occurring after finger movement, onset initial direction of finger movement did not match Target interception such that the finger Path began to curve toward the perturbed Target after about 150–200 ms. The results support the idea of an active process of visual Target Path extrapolation simultaneously used to guide both the eye and hand.
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Planning and drawing complex shapes
Experimental Brain Research, 2006Co-Authors: Martha Flanders, Leigh A. Mrotek, C.c.a.m. GielenAbstract:Arm and hand movements are generally controlled using a combination of sensory-based and memory-based guidance mechanisms. This study examined similarities and differences in visually-guided and memory-guided arm movements, and sought to determine as to what extent certain control principles apply to each type of movement. In particular, the 2/3 power law is a principle that appears to govern the formation of complex, curved hand trajectories; it specifies that the tangential velocity should be proportional to the radius of curvature raised to an exponent of 1/3. A virtual reality system was used to project complex Target Paths in three-dimensional (3D) space. Human subjects first tracked (with the tip of a handheld pen) a single Target moving along an unseen Path. The entire Target Path then became visible and the subject traced the shape. Finally, the Target shape disappeared and the subject was to draw it, in the same 3D space, from memory. Most aspects of the movements (speed, Path size, shape and arm postures) were very similar across the three conditions. However, subjects adhered to the 2/3 power law most closely in the tracing condition, when the entire Target Path was visible. Also, only within the tracing condition, there were significant differences in the value of the exponent depending on the size and the spatial orientation of the trajectory. In the tracking and drawing conditions, the exponent was greater than 1/3, indicating that subjects spent more time in areas of tight curvature. This may represent a strategy for learning and remembering the complex shape.
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Manual tracking in three dimensions
Experimental Brain Research, 2006Co-Authors: Leigh A. Mrotek, C.c.a.m. Gielen, Martha FlandersAbstract:Little is known about the manual tracking of Targets that move in three dimensions. In the present study, human subjects followed, with the tip of a hand-held pen, a virtual Target moving four times (period 5 s) around a novel, unseen Path. Two basic types of Target Paths were used: a peanut-shaped Cassini ellipse and a quasi-spherical shape where four connected semicircles lay in orthogonal planes. The quasi-spherical shape was presented in three different sizes, and the Cassini shape was varied in spatial orientation and by folding it along one of the three bend axes. During the first cycle of Cassini shapes, the hand lagged behind the Target by about 150 ms on average, which decreased to 100 ms during the last three cycles. Tracking performance gradually improved during the first 3 s of the first cycle and then stabilized. Tracking was especially good during the smooth, planar sections of the shapes, and time lag was significantly shorter when the tracking of a low-frequency component was compared to performance at a higher frequency (−88 ms at 0.2 Hz vs. −101 ms at 0.6 Hz). Even after the appropriate adjustment of the virtual Target Path to a virtual shape tracing condition, tracking in depth was poor compared to tracking in the frontal plane, resulting in a flattening of the hand Path. In contrast to previous studies where Target trajectories were linear or sinusoidal, these complex trajectories may have involved estimation of the overall shape, as well as prediction of Target velocity.
Koji Iida - One of the best experts on this subject based on the ideXlab platform.
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A search game when a search Path is given
European Journal of Operational Research, 2000Co-Authors: Ryusuke Hohzaki, Koji IidaAbstract:Abstract In this paper, we investigate a search game in discrete time and space. A searcher is given a search Path in advance and his look on the Path is determined by a randomized look strategy. A Target selects a Path from some options. The searcher gains a value on the detection of the Target but expends search cost by the look. A pay-off function of the game for the searcher is the expected reward which is defined as the expected value minus the expected search cost. First, we show a recursive relation for the conditional optimal look strategy of the searcher given a Target Path. We prove its NP-completeness, though it looks simple, and clarify some characteristics of the solution. Then our original continuous game is converted to a matrix game. From these facts, we consider a relationship between the game and the one-sided optimizing problem and examine some examples.
Martha Flanders - One of the best experts on this subject based on the ideXlab platform.
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Planning and drawing complex shapes
Experimental Brain Research, 2006Co-Authors: Martha Flanders, Leigh A. Mrotek, C.c.a.m. GielenAbstract:Arm and hand movements are generally controlled using a combination of sensory-based and memory-based guidance mechanisms. This study examined similarities and differences in visually-guided and memory-guided arm movements, and sought to determine as to what extent certain control principles apply to each type of movement. In particular, the 2/3 power law is a principle that appears to govern the formation of complex, curved hand trajectories; it specifies that the tangential velocity should be proportional to the radius of curvature raised to an exponent of 1/3. A virtual reality system was used to project complex Target Paths in three-dimensional (3D) space. Human subjects first tracked (with the tip of a handheld pen) a single Target moving along an unseen Path. The entire Target Path then became visible and the subject traced the shape. Finally, the Target shape disappeared and the subject was to draw it, in the same 3D space, from memory. Most aspects of the movements (speed, Path size, shape and arm postures) were very similar across the three conditions. However, subjects adhered to the 2/3 power law most closely in the tracing condition, when the entire Target Path was visible. Also, only within the tracing condition, there were significant differences in the value of the exponent depending on the size and the spatial orientation of the trajectory. In the tracking and drawing conditions, the exponent was greater than 1/3, indicating that subjects spent more time in areas of tight curvature. This may represent a strategy for learning and remembering the complex shape.
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Manual tracking in three dimensions
Experimental Brain Research, 2006Co-Authors: Leigh A. Mrotek, C.c.a.m. Gielen, Martha FlandersAbstract:Little is known about the manual tracking of Targets that move in three dimensions. In the present study, human subjects followed, with the tip of a hand-held pen, a virtual Target moving four times (period 5 s) around a novel, unseen Path. Two basic types of Target Paths were used: a peanut-shaped Cassini ellipse and a quasi-spherical shape where four connected semicircles lay in orthogonal planes. The quasi-spherical shape was presented in three different sizes, and the Cassini shape was varied in spatial orientation and by folding it along one of the three bend axes. During the first cycle of Cassini shapes, the hand lagged behind the Target by about 150 ms on average, which decreased to 100 ms during the last three cycles. Tracking performance gradually improved during the first 3 s of the first cycle and then stabilized. Tracking was especially good during the smooth, planar sections of the shapes, and time lag was significantly shorter when the tracking of a low-frequency component was compared to performance at a higher frequency (−88 ms at 0.2 Hz vs. −101 ms at 0.6 Hz). Even after the appropriate adjustment of the virtual Target Path to a virtual shape tracing condition, tracking in depth was poor compared to tracking in the frontal plane, resulting in a flattening of the hand Path. In contrast to previous studies where Target trajectories were linear or sinusoidal, these complex trajectories may have involved estimation of the overall shape, as well as prediction of Target velocity.
