Patrick Marmaroli

Body part-centered and full body-centered peripersonal space representations.

Dedicated neural systems represent the space surrounding the body, termed Peripersonal space (PPS), by integrating visual or auditory stimuli occurring near the body with somatosensory information. As a behavioral proxy to PPS, we measured participants’ reaction time to tactile stimulation while task-irrelevant auditory or visual stimuli were presented at different distances from their body. In 7 experiments we delineated the critical distance at which auditory or visual stimuli boosted tactile processing on the hand, face, and trunk as a proxy of the PPS extension. Three main findings were obtained. First, the size of PPS varied according to the stimulated body part, being progressively bigger for the hand, then face, and largest for the trunk. Second, while approaching stimuli always modulated tactile processing in a space-dependent manner, receding stimuli did so only for the hand. Finally, the extension of PPS around the hand and the face varied according to their relative positioning and stimuli congruency, whereas the trunk PPS was constant. These results suggest that at least three body-part specific PPS representations exist, differing in extension and directional tuning. These distinct PPS representations, however, are not fully independent from each other, but referenced to the common reference frame of the trunk.

Observation of Vehicle Axles Through Pass-by Noise: A Strategy of Microphone Array Design

This paper focuses on road traffic monitoring using sounds and proposes, more specifically, a microphone array design methodology for observing vehicle trajectory from acoustic-based correlation functions. In a former work, authors have shown that combining generalized cross correlation (GCC) functions and a particle filter onto the audio signals simultaneously acquired by two sensors placed near the road allows the joint estimation of the speed and the wheelbase length of road vehicles as they pass by. This is mainly due to the broadband nature of the tire/road noise, which makes their spatial dissociation possible by means of an appropriate GCC processor. At the time, nothing has been said about the best distance to chose between the sensors. A methodology is proposed here to find this optimum, which is expected to improve the observation quality and, thus, the tracking performance. Theoretical developments of this paper are partially assessed with preliminary experiments.

Pass-by noise acoustic sensing for estimating speed and wheelbase length of two-axle vehicles.

This paper focuses on acoustic road traffic monitoring and looks, more specifically, into the problem of speed and wheelbase length estimation of two-axle vehicles as they pass by. It is known that both front and rear axle trajectories may be dissociated using cross-correlation based methods in conjunction with a well designed two-element microphone array placed on the roadside. This is mainly due to the broadband nature of the tyre/road noise which makes two peaks appear, one per axle, in the correlation measurement when the vehicle is in the broadside direction. This paper aims at analyzing such a “bimodal’’ observation in order to automatically extract the position, speed, and wheelbase length of passing-by vehicles. We propose to conduct this tracking problem using a particle filter that model the position-variant bimodal sound source nature of the vehicles. The theoretical developments presented in this paper are experimentally assessed through real in-situ measurements.