Electromagnetic tracking of motion in the proximity of computer generated graphical stimuli: A tutorial

Electromagnetic motion-tracking systems have the advantage of capturing the tempo-spatial kinematics of movements independently of the visibility of the sensors. However, they are limited in that they cannot be used in the proximity of electromagnetic field sources, such as computer monitors. This prevents exploiting the tracking potential of the sensor system together with that of computer-generated visual stimulation. Here we present a solution for presenting computer-generated visual stimulation that does not distort the electromagnetic field required for precise motion tracking, by means of a back projection medium. In one experiment, we verify that cathode ray tube monitors, as well as thin-film-transistor monitors, distort electro-magnetic sensor signals even at a distance of 18 cm. Our back projection medium, by contrast, leads to no distortion of the motion-tracking signals even when the sensor is touching the medium. This novel solution permits combining the advantages of electromagnetic motion tracking with computer-generated visual stimulation.

[1]  W. Prinz.  Perception and Action Planning , 1997 .

[2]  R. Hampton,et al.  Monkeys Recall and Reproduce Simple Shapes from Memory , 2011, Current Biology.

[3]  Joo-Hyun Song,et al.  Target selection for visually-guided reaching in macaque , 2010 .

[4]  Wolfgang Prinz,et al.  Modes of Linkage Between Perception and Action , 1984 .

[5]  R. B. Freeman,et al.  Cognition and Motor Processes , 1983 .

[6]  Linda Jeffery,et al.  Race-specific norms for coding face identity and a functional role for norms. , 2010, Journal of vision.

[7]  Craig S. Chapman,et al.  “Real-time” obstacle avoidance in the absence of primary visual cortex , 2009, Proceedings of the National Academy of Sciences.

[8]  Emanuel Todorov,et al.  Efficient computation of optimal actions , 2009, Proceedings of the National Academy of Sciences.

[9]  D. H. Mellor,et al.  Real time , 1981 .

[10]  Konrad Paul Kording,et al.  Review TRENDS in Cognitive Sciences Vol.10 No.7 July 2006 Special Issue: Probabilistic models of cognition Bayesian decision theory in sensorimotor control , 2022 .

[11]  M. Ernst.  Learning to integrate arbitrary signals from vision and touch. , 2007, Journal of vision.

[12]  Jörn Diedrichsen,et al.  Bimanual interference associated with the selection of target locations. , 2003, Journal of experimental psychology. Human perception and performance.

[13]  H. Deubel,et al.  Visual attention during the preparation of bimanual movements , 2008, Vision Research.

[14]  H. Deubel,et al.  Independent Allocation of Attention to Eye and Hand Targets in Coordinated Eye-Hand Movements , 2011, Psychological science.

[15]  B. Hommel.  Event files: feature binding in and across perception and action , 2004, Trends in Cognitive Sciences.

[16]  Michael I. Jordan,et al.  Generalization to Local Remappings of the Visuomotor Coordinate Transformation , 1996, The Journal of Neuroscience.

[17]  H. Müller,et al.  Visually guided pointing movements are driven by the salience map. , 2011, Journal of vision.