An Investigation of Pain Related Disability with Movement Quantity and Quality in Pre-Professional Dancers

Abstract

This thesis explored the relationship between dancers' movement quantity and quality with pain outcomes. Machine learning models applied to wearable sensor data that were capable of field-based, objective quantification of dancers' movement quantity and quality were developed. This system was used in a longitudinal, field-based study to explore the relationship of pre-professional, female dancers movement quantity and quality with pain and pain related disability.