Author keywords: Accelerometer Wearable Sensors Skill Assessment Pattern Recognition
Variability is an inherent feature of human movement, but little research has been done in order to measure such a characteristic using inertial sensors attached to person’s body (wearable sensors). Therefore the aim of this preliminary study is to investigate the assessment of human movement variability for dance activities. We asked thirteen participants to repeatedly dance two salsa steps (simple and complex) for 20 seconds. We then used a technique from nonlinear dynamics (time-delay embedding) to obtain the reconstructed state space for visual assessment of the variability of dancers. Such reconstructed state space is graphically linked with their level of skillfulness of the participants.
Miguel P. Xochicale
map479@bham.ac.uk
The University of Birmingham, UK
Chris Baber
c.baber@bham.ac.uk
The University of Birmingham, UK
Mourad Oussalah
moussala@ee.oulu.fi
University of Oulu, Finland
Acronym of the event: WeRob2016
Name of the event: The International Symposium on Wearable Robotics
Web page: http://www.werob2016.org/
Contact emails: jegv07@gmail.com
Submission page: https://easychair.org/conferences/?conf=werob2016