Walking in Sync: Two is Company, Three’s a Crowd

Submitted by richard on Tue, 04/07/2015 - 19:27
Kleomenis Katevas, Hamed Haddadi, Laurissa Tokarchuk, Richard G. Clegg
2nd Workshop on Physical Analytics (WPA), Florence, Italy
Year
2015
Abstract
Eventual gait synchronization between two individuals while
walking and talking with each other has been shown to be an
indicator of agreeableness and companionship. The inferred
physical signal from this subconscious phenomenon can potentially
be an indicator of cooperation or relation between
two individuals. In this paper we investigate this effect,
and whether having a third person actively engaging in the
same act or conversation can reduce this synchronization
level. Using high frequency accelerometer data from a dedicated
smartphone app, we perform a number of controlled
experiments on a number of individuals in different group
configuration. Our results bring an interesting insight: it is
the non-verbal social signals such as the gaze, head orientation
and gestures that is the key factor in synchronization,
not necessarily the number or configuration of the walkers.
These early results can lead us on detecting relationships
between individuals or detecting the group formation and
numbers for crowd-sensing applications when only partial
data is available.
Description

This paper describes preliminary results on analysing the movements of people walking next to each other. The data is collected from mobile phone movement sensors carried by experimental subjects. The accelerometers on mobile phones show synchronisation when compared. Correlations between time series are used to infer the presence of a third party with when people are walking. This is preliminary work on a small data set with only three participants.

bibtex
@inproceedings{sync_wpa_2015,
title={Walking in Sync: Two is Company, Three’s a Crowd},
author= {Kleomenis Katevas and Hamed Haddadi and Laurissa Tokarchuk and Richard G. Clegg},
year=2015,
booktitle={Proc. of Workshop on Physical Analytics }
}
Paper type
Subject area