Alessandro Maria Selvitella
Authors:
Prof. Kathleen Lois Foster, Department of Biology, Ball State University
Prof. Alessandro Maria Selvitella, Department of Mathematical Sciences, Purdue University Fort Wayne
Extraordinary advancements in computing power have facilitated the development and application of sophisticated statistical analyses to biological fields such as genomics, ecology, and evolution. However, even now, when powerful hardware and software tools have never been more accessible and despite significant advancements in statistical theory, physiological branches of biology, like biomechanics, seem to be stuck in the past, with the ubiquitous and almost exclusive use of classical univariate statistics. In this poster, we will discuss how more modern machine learning methods impact and revolutionize the extraction and analysis of biomechanical data. This will be discussed in the context of lizard locomotion and contrasted with the results of classical univariate analyses.
