Introducing coordination in hand position analysis during a steering wheel-based tracking task using fuzzy sets

Abstract This paper describes a new approach to analyse the way both hands are placed in relation to the steering wheel. The study is based on a 2D-tracking task, in which the stimulus is a steering wheel angle signal recorded while driving on 7 road geometries in real situations at 30 km/h. Hand movements are measured using a 3D-motion capture system. Data analysis is based on the segmentation of the hand angular position using 8 fuzzy angle windows (labelled as approximately 0°, approximately 45°, etc.), when the hand rests on the steering wheel, one window, else. To obtain information about the coordination aspect, 9 × 9 bivariate windows are considered for each time sample (recorded at 25 Hz); then, the average membership values are computed for each individual driving situation. The individual membership value sets related to the road geometries are studied via Correspondence Analysis, allowing to displaying both the inter- and intra-individual differences and the most discriminating bivariate windows. The methodology with 9 × 9 windows is more complex but implies less information loss than alternative ones e.g. when the two hands are separately analysed, which constitutes 9 + 9 windows and contains no information about the coordination aspect.