This paper discusses the methodology for extracting and classifying a style and characteristic component from time-series data of a drivers’ body motion. The body motion while driving is measured using four wearable motion sensors for acquiring posture and movement of each body segment. To extract the style and characteristic component, we use the singular value decomposition (SVD) of the measured data and evaluate the contribution of each sensor module for describing the physical meaning of the extracted components. From these results, the characteristic component of drivers’ body motion can be extracted by using the right singular vectors obtained from SVD. In addition, using the 2nd and 3rd right singular vectors, it is possible to classify the characteristics of holding the posture of the steering wheel.