Measurement of instantaneous perceived self-motion using continuous pointing

Joshua H. Siegle, Jennifer L. Campos, Betty J. Mohler, Jack M. Loomis, Heinrich H. Bülthoff

    Research output: Contribution to journalArticlepeer-review

    35 Citations (Scopus)

    Abstract

    In order to optimally characterize full-body self-motion perception during passive translations, changes in perceived location, velocity, and acceleration must be quantified in real time and with high spatial resolution. Past methods have failed to effectively measure these critical variables. Here, we introduce continuous pointing as a novel method with several advantages over previous methods. Participants point continuously to the mentally updated location of a previously viewed target during passive, full-body movement. High-precision motion-capture data of arm angle provide a measure of a participant's perceived location and, in turn, perceived velocity at every moment during a motion trajectory. In two experiments, linear movements were presented in the absence of vision by passively translating participants with a robotic wheelchair or an anthropomorphic robotic arm (MPI Motion Simulator). The movement profiles included constant-velocity trajectories, two successive movement intervals separated by a brief pause, and reversed-motion trajectories. Results indicate a steady decay in perceived velocity during constant-velocity travel and an attenuated response to mid-trial accelerations.

    Original languageEnglish
    Pages (from-to)429-444
    Number of pages16
    JournalExperimental Brain Research
    Volume195
    Issue number3
    DOIs
    Publication statusPublished - 2009 May

    Keywords

    • Continuous pointing
    • Inertial cues
    • Passive transport
    • Self-motion perception
    • Spatial updating

    ASJC Scopus subject areas

    • General Neuroscience

    Fingerprint

    Dive into the research topics of 'Measurement of instantaneous perceived self-motion using continuous pointing'. Together they form a unique fingerprint.

    Cite this