Haptic guidance improves the visuo-manual tracking of trajectories

Jérémy Bluteau, Sabine Coquillart, Yohan Payan, Edouard Gentaz, Jérémy Bluteau, Sabine Coquillart, Yohan Payan, Edouard Gentaz

Abstract

Background: Learning to perform new movements is usually achieved by following visual demonstrations. Haptic guidance by a force feedback device is a recent and original technology which provides additional proprioceptive cues during visuo-motor learning tasks. The effects of two types of haptic guidances-control in position (HGP) or in force (HGF)-on visuo-manual tracking ("following") of trajectories are still under debate. METHODOLOGY/PRINCIPALS FINDINGS: Three training techniques of haptic guidance (HGP, HGF or control condition, NHG, without haptic guidance) were evaluated in two experiments. Movements produced by adults were assessed in terms of shapes (dynamic time warping) and kinematics criteria (number of velocity peaks and mean velocity) before and after the training sessions. Trajectories consisted of two Arabic and two Japanese-inspired letters in Experiment 1 and ellipses in Experiment 2. We observed that the use of HGF globally improves the fluency of the visuo-manual tracking of trajectories while no significant improvement was found for HGP or NHG.

Conclusion/significance: These results show that the addition of haptic information, probably encoded in force coordinates, play a crucial role on the visuo-manual tracking of new trajectories.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1
Schematic view of haptic guidances: (a) Haptic guidance in position (HGP); the force felt by the user at time t is proportional to displacement between the current user position and the theoretical position on the model trajectory; (b) Haptic guidance in force (HGF); the force felt by the user at time t is the same as the force existing for the theoretical trajectory at the same time.
Figure 2
Figure 2
System overview: (a) The modified stylus pen; (b) The graphic User Interface displayed to the subject; (c) A subject undergoing training on the WYSIWYF interface.
Figure 3. Letters proposed in experiment 1:…
Figure 3. Letters proposed in experiment 1: Letters 1 and 2 are Arabic and letters 3 and 4 are “Japanese-like” letters.
Figure 4. All ellipses used in experiment…
Figure 4. All ellipses used in experiment 2: In red, the three references trajectories used before and after each training session; In green and blue, the trajectories used during the training sessions, equidistant in the choice of their diagonals (eccentricity).

References

    1. Schmidt RA. Motor control and learning: A behavioural emphasis, Second ed. Champaign, IL: Human Kinetics; 1987.
    1. Feygin D, Keehner M, Tendick R. Haptic guidance: experimental evaluation of a haptic training method for a perceptual motor skill. In proceedings of 10th Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2002:40–47.
    1. Liu J, Cramer S, Reinkensmeyer D. Learning to perform a new movement with robotic assistance: comparison of haptic guidance and visual demonstration. J Neuroengineering Rehabil, 2006;3(1743-0003 (Electronic)):20.
    1. Teo CL, Burdet E, Lim HP. A robotic teacher of chinese handwriting. In proceedings of 10th Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2002:335–341.
    1. Palluel-Germain R, Bara F, Hillairet de Boisferon A, Hennion B, Gouagout P, Gentaz E. A Visuo-haptic device - Telemaque - increases kindergarten children's handwriting acquisition. In proceedings of IEEE World Haptics 2007, 2007:72–77.
    1. Solis J, Avizzano CA, Bergamasco M. Teaching to write japanese characters using a haptic interface. In proceedings of 10th Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2002:255–262.
    1. Henmi K, Yoshikawa T. Virtual lesson and its application to virtual calligraphy system. In proceedings of Robotics and Automation, 1998;2:1275–1280.
    1. Gillespie PTCPB, O'Modhrain S, Zaretsky D. The virtual teacher. In ASME International Mechanical Engineering Conference and Exposition, 1998;64:171–174.
    1. Viviani P, Schneider R. A developmental study of the relationship between geometry and kinematics in drawing movements. Journal of Experimental Psychology: Human Perception and Performance, 1991;17(1):198–218.
    1. Viviani P, Terzuolo C. Trajectory determines movement kinematics. Neuroscience, 1982;7(2):431–437.
    1. Lacquaniti F, Terzuolo C, Viviani P. The law relating the kinematic and figural aspects of drawing movements. Acta Psychologica, 1983;54(1-3):115–130.
    1. Srimathveeravalli G, Thenkurussi K. Motor skill training assistance using haptic attributes. In proceedings of Haptic Interfaces for Virtual Environment and Teleoperator Systems,WHC, 2005:452–457.
    1. Morris D, Tan H, Barbagli F, Chang T, Salisbury K. Haptic feedback enhances force skill learning. In proceedings of EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2007:21–26.
    1. Yokokohji Y, Hollis RL, Kanade T. What you can see is what you can feel-development of a visual/haptic interface to virtual environment. In proceedings of Virtual Reality Annual International Symposium, 1996;265:46–53.
    1. Conti F. The CHAI Libraries. In Eurohaptics '03 2003
    1. Niels R. Radboud University Nijmegen, Faculty of Social Sciences, Department of Artificial Intelligence/Cognitive Science; 2004. Dynamic Time Warping: An intuitive way of handwriting recognition? Master's thesis.
    1. Krakauer JW, Ghilardi M, Ghez C. Independent learning of internal models for kinematic and kynematic control of reaching. Nature Neuroscience, 1999;2:1026–1031.
    1. Kawato M. Internal models for motor control and trajectory planning. Current Opinion in Neurobiology, 1999;9:718–727.
    1. Bartlett R, Wheat J, Robins M. Is movement variability important for sports biomechanists? Sports Biomecanics, 2007;6:224–243.

Source: PubMed

3
Prenumerera