IMPROVING SPRINGBOARD DIVING THROUGH BIOMECHANICAL ANALYSES AND KNOWLEDGE BASED EXPERT SYSTEM APPLICATION

Abstract

Springboard diving, like most sports, optimizes certain aspects of human performance through skill development. To assist with achieving proficiency in the execution of a skill, a systematic method of evaluating a· skill to detect errors and to deduce. corrections is required. The purpose of this thesis was to study such skill assessment for forward, nontwisting dives, from both a quantitative and qualitative perspective. Research focussing on the quantitative aspect of the diver-springboard system was based on applied mechanics. A mathematical model was developed to simulate the vertical component of springboard-diver motion. The model was designed to incorporate learned movement skills and permitted an evaluation of the effects of varying a given parameter on the overall performance. Specifically, by altering the timing of execution of these sub-skills, the height achieved by the diver during the flight phase can be maximized. The qualitative analysis focused on emulating coaching strategies relating to skill assessment. Both the determination of the attributing cause of a major performance error and suggestions for correcting this error were accomplished by applying knowledge based expert system technology. The resulting system was a springboard diving skill analysis program. It produced appropriate and valuable advice in a user acceptable format. These results suggest that application of knowledge based expert system technology to the skill assessment aspect of coaching is a viable method for disseminating coaching expertise.