Tutorial D: Understanding Coordination and Movement Variability: Application of Vector Coding in Dynamical Systems
Chair: Nachiappan Chockalingam, PhD (Staffordshire University) firstname.lastname@example.org
Name: Affiliation/Institution: Email:
Robert A. Needham, PhD Staffordshire University email@example.com
Nachiappan Chockalingam, PhD Staffordshire University firstname.lastname@example.org
Roozbeh Naemi, PhD Staffordshire University email@example.com
Joseph Hamill, PhD University of Massachusetts firstname.lastname@example.org
The application of dynamical systems theory to describe the complex behavior of human movement is becoming increasingly popular in biomechanics and motor control research. A dynamical systems framework offers non-linear data analysis techniques that can quantify movement coordination and coordination variability over time. An angle-angle diagram illustrates the continuous interaction between two segments and provides a qualitative view on coordination. Vector coding is a data analysis technique that calculates the vector orientation between data points on an angle-angle diagram. The vector orientation, which can range between 0-360°, is a quantifiable measure that is referred to as the coupling angle. Each coupling angle across a normalized movement cycle can be assigned to a coordination pattern classification. This tutorial will provide a comprehensive review on methodological considerations, and on theory and practice of vector coding. This includes recent developments on a new coordination classification that expands on current ideologies, the introduction of a novel approach to quantify segmental dominancy during a movement cycle, comment on the appropriate use of circular statistics, and provide new data reporting techniques that have the capability to visually display multiple trials and segmental couplings. In addition, this tutorial will provide an insight on how vector coding offers a new perspective on the functional workings of the foot that traditional linear data analysis and reporting techniques cannot detail. Finally, current theories on coordination variability and overuse injuries will be presented.
Nachiappan Chockalingam (Staffordshire University/ University of Malta): Whilst outlining the need for changes to clinical data reporting, Nachi will introduce dynamical systems and provide an overview of the theoretical background to coordination and movement variability. He will also highlight the differences between linear and non-linear analysis. Whilst emphasizing the usefulness of single subject research designs which forms the basis of dynamical systems approach, he will introduce novel concepts for clinical data reporting such as coordination profiling.
Robert A. Needham (Staffordshire University): Rob will introduce and define vector coding. He will provide an overview of our previous work and the development of a new coordination pattern classification. His lecture will also introduce concepts relating to quantification of segmental dominancy using lower limb data. In addition, Rob will touch on statistical approaches with a focus on circular statistics. He will conclude by presenting novel approaches on reporting several outcome measures using vector coding.
Joseph Hamill (University of Massachusetts/ Staffordshire University): Joe will outline his pioneering work in this area of dynamical systems and provide an overview of the developments and its applications. He will outline the use of such approaches in various clinical scenarios with a focus on foot and ankle. Whilst discussing coordination patterns during various foot fall patterns during running, Joe will also touch on coordination variability and its link to incidence of injury and its continuum.
Roozbeh Naemi (Staffordshire University): Roozbeh will introduce advanced mathematical calculations behind dynamical systems and vector coding. He will provide a critical analysis of previous papers and provide an overview of how our current approaches provide clarity to the background calculations in vector coding. Where appropriate, Roozbeh will use examples from foot and ankle data to provide an understanding of the concepts.