INTRODUCTION: In addition to personal feedback of coaches, Video analysis and sole pressure distribution (SPD) are used as objective methods for training control in Professional skiing. The value of SPD was investigated profoundly (Glitsch, 2001, Schöllhorn et al. 2001). There is, however, few information about objective training support in leisure sports. This study aims to introduce basic data to build a realtime training feedback algorithm (RTFA) for carving which can be applied to a simple mobile hardware System. METHOD: The study was conducted to clarify Statements concerning two main fields of interest in terms of a RTFA: 1) Is it possible to gain information about a)load distribution (left/right), b)balance (forward/backward), c)turn direction, d)characteristics of SPD as well as balance related to skiing skills, e)edging and f)speed only from 1 dimensional SPD (for pro's and amateurs)? 2) Can these Statements be made with the data from only 4 pressure sensors in a sole? A scientific sole pressure measurement system and video analysis were used to analyze SPD and motion patterns during carving. 6 pro skiers and 5 amateur skiers were tested. A cluster analysis, correlation analysis and center of mass calculation were performed to determine the number and placement of necessary pressure sensors regarding 2). Sole prototypes with a reduced sensor field were used for the in-field validation of the results from 1) and 2). Concerning a RTFA, 12 ski turns of pro's were split into 3 characteristic phases (introduction, steering phase, change) to retrieve characteristics (reference data) about the parameters showed in 1). RESULTS: The Statements in 1) were confirmed (pro's and amateurs) except for 1d). 1d) is no valid criteria to assess skiing skills. The validation showed that all Statements can be made with only 4 sensors. Their placement was determined, verified and matches the Position of anatomic landmarks of the foot. Fig. 1 shows one result (balance) regarding the quality of a turn (qbso/i= ratio forward/backward outer/inner ski, forward: ratio>1). DISCUSSION: The quality of the detection of the relevant parameters largely depends on snow conditions. Thus, ratio ranges and smart data filtering have to be defined. Individual variances in skiing style, which were existent for pro's as well, are here averaged to achieve reference data, A training algorithm probably also has to take into account these variances. CONCLUSION: As for the future, the prototype soles have to be tested together with the realtime feedback Software implemented on a cell-phone (audio feedback). It has to be verified in a separate study that, under controlled conditions, such a feedback system leads to "improved" skiing technique. This is planned to be conducted in skiing schools.
© Copyright 2007 4th International Congress on Science and Skiing. Veröffentlicht von University of Salzburg. Alle Rechte vorbehalten.