Predicting audio step feedback for real walking in virtual environments

When navigating in virtual environments by using real walking, the correct auditory step feedback is usually ignored, although this could give more information to the user about the ground he is walking on. One reason for this are time constraints that hinder a replay of a walking sound synchronous to the haptic step feedback when walking. In order to add a matching step feedback to virtual environments, this paper introduces a calibration-free system which can predict the occurrence time of a step-down event based on an analysis of the user’s gait. For detecting reliable characteristics of the gait, accelerometers and gyroscopes are used that are mounted on the user’s foot. Since the proposed system is capable of detecting the characteristic events in the foot’s swing phase, it allows a prediction that gives enough time to replay sound synchronous to the haptic sensation of walking. In order to find the best prediction regarding prediction time and accuracy, data gathered in an experiment is analyzed regarding reliably occurring characteristics in the human gait. Based on this, a suitable prediction algorithm is proposed.

Predicting audio step feedback for real walking in virtual environments

When navigating in virtual environments by using real walking, the correct auditory step feedback is usually ignored, although this could give more information to the user about the ground he is walking on. One reason for this are time constraints that hinder a replay of a walking sound synchronous to the haptic step feedback when walking. In order to add a matching step feedback to virtual environments, this paper introduces a calibration-free system which can predict the occurrence time of a step-down event based on an analysis of the user’s gait. For detecting reliable characteristics of the gait, accelerometers and gyroscopes are used that are mounted on the user’s foot. Since the proposed system is capable of detecting the characteristic events in the foot’s swing phase, it allows a prediction that gives enough time to replay sound synchronous to the haptic sensation of walking. In order to find the best prediction regarding prediction time and accuracy, data gathered in an experiment is analyzed regarding reliably occurring characteristics in the human gait. Based on this, a suitable prediction algorithm is proposed.