Recently, technologies to help the elderly or disabled people who have difficulty in walking are being developed. In order to develop these technologies, it is necessary to construct a system that gathers the gait data of people and analysis of these data is also important. In this research, we constructed the development of sensor system which consists of pressure sensor, three-axis accelerometer and two-axis gyro sensor. We used k-means clustering algorithm to classify the data for characterization, and then calculated the symmetry index with histogram which was produced from each cluster. We collected gait data from sensors attached on two subjects. The experiment was conducted for two kinds of gait status. One is walking with normal gait; the other is walking with abnormal gait (abnormal gait means that the subject walks by dragging the right leg intentionally). With the result from the analysis of acceleration component, we were able to confirm that the analysis technique of this data could be used to determine gait symmetry. In addition, by adding gyro components in the analysis, we could find that the symmetry index was appropriate to express symmetry better.