INTRODUCTION: It is an efficient mean to film swimmer`s swimming motion of their whole body in order to grasp swimmer`s technique. However, it is difficult to understand differences in detailed motion such as twisting arms or paths of arm strokes from the actual motion images. In order to understand the detailed motion of the forearm in swimming, Ohgi [1] used 3D accelerations and 3D angular velocities obtained by a data logger. Synchronizing the actual motion images with the acquired logger data makes the detailed swimming motion more understandable. Furthermore, the top view over the swimmers was observed by a camera for wave resistance against the swimmers. The wavelet transform, which is chronological frequency analysis, was also performed on these logger data and the dominant frequency was grasped chronologically in different swimming styles. METHODS: Underwater and overwater cameras were attached with a cart on pipe rail trucks at a poolside. Two motion images were combined into an unified image by a video mixer. The data logger with 3D accelerometer, 3D gyro sensor and depth sensor built in was used for acquisition of stroke motions. This device was attached on the forearm. The assessment experiment of swimming stroke operations was conducted. Swimming motions were recorded visually and digitally simultaneously. The logged data were analyzed by wavelet transformation in order to distinguish the minute differences graphically. RESULTS:Motion images of swimming were obtained like watching through plexiglas wall by the observation device. The swimming motions and 3D acceleration and 3D angular velocity signal waves were synchronized into a motion picture. Analysis of swimming motion signals becomes easier because of references of the synchronized motion pictures. In graphical patterns of swimming stroke motion, a deep stripe patterns appear in a main stroke period (2.0sec). Each of a quarter (0.5sec) and a half (1.0 sec) periods of fundamental stroke were also obtained as a stripe pattern in S-shaped free-style stroke. It is possible to discuss the different patterns with each player in the same swimming style. DISCUSSION: The author developed whole body observation apparatus in swimming. The motion pictures were synchronized with 3D acceleration and 3D angular velocity data which recorded the forearm actions. Furthermore, wavelet transform of swimming stroke was carried out and the swimming motion was visualized.
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