Towards the Analysis of Movement Variability in Human-Humanoid Imitation Activities
Channel: Miguel Xochicale
Date: 2017-10-12

Towards the Analysis of Movement Variability in Human-Humanoid Imitation Activities

Miguel P. Xochicale and Chris Baber

PAPER CONFERENCE: https://www.researchgate.net/publication/320357111_Towards_the_Analysis_of_Movement_Variability_in_Human-Humanoid_Imitation_Activities

GITHUB REPO: https://github.com/mxochicale/hai2017

ABSTRACT:
In this paper, we present preliminary results for the analysis of movement
variability in human-humanoid imitation activities.
We applied the state space reconstruction's theorem which help us to have
better understanding of the movement variability than other techniques
in time or frequency domains.
In our experiments, we tested our hypothesis where participants,
even performing the same arm movement, presented slight differences in
the way they moved. With this in mind, we asked eighteen participants to
copy NAO's arm movements while we collected data from inertial sensors
attached to the participants' wrists and estimated the head pose using
the OpenFace framework.
With the proposed metric, we found that sixteen out of eighteen participants
imitate the robot well by moving their arms symmetrically and by keeping
their heads static; two participants however moved their head in a synchronous way
even when the robot's head was completely static and two different participants
moved their arms asymetrically to the robot.
Although the work is in its early stage, we believe that such preliminary
results are promising for applications in rehabilitation, sport science,
entertainment or education.