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In our previous study on gait recognition, we developed the application on iOS for smart phone to record not only the acceleration but also more data such as the rotation of the phone around the 3 axes. And then we performed preliminary experiments using the application to collect the user-generated acceleration data on walking when the phone was held calling and touching as well as in the pocket. However, the acceleration data were recorded for only 4 subjects on one day. In this study, we carry out additional experiments increasing the number of subjects and adding the data recorded on other day. The results show that although the correctly classified rate when the phone is in the pocket is not yet affected by the number of subjects, the performance in the cases of calling and touching is influenced by the small number of subjects. Interestingly, we observe that the additional data on other day have a different effect on identification performance according to phone holding states. We also examine the influence of various walking states for one subject. Furthermore, we discuss the application of an immunity-based diagnosis model to gait recognition to integrate the identification results from multiple smart phone sensors

Toward Application of Immunity-based Model to Gait Recognition Using Smart Phone Sensors: A Study of Various Walking States