Estimating Human Physical States from Chronological Gait Features Acquired with RFID Technology

¹ Ritsumeikan University, 1-1-1 Noji-higashi Kusatsu Shiga, 5258577, Japan
² National ICT Australia (NICTA), 13 Garden Street Eveleigh NSW, 2015, Australia
¹ Tel.: +81-77-561-5037

¹ E-mail: y_uemura@de.is.ritsumei.ac.jp

Received: 31 August 2015 /Accepted: 15 October 2015 /Published: 30 November 2015

Abstract: This paper proposes a method to estimate the state of the user to provide proactive hospitality from features of their gait pattern acquired with a Radio Frequency Identifier (RFID) system. This method uses RFID readers on each shoe, as well as RFID tags installed on the floor. The ID of each tag is organized as a map, to show the precise position of the user. The reader and tags communicate while the user is walking. We extract feature components which represents gait patterns. Two-way ANOVA test and correlation analysis are conducted to find significant features. We classify the state of the user from these components with the Naȉve Bayes, the Support Vector Machine, and the Random Forest. Compared with each combination of the analysis and the machine learning method, the most efficient way is found to identify the state of the user. The experimental results show that different state of users can be classified appropriately. Finally, variable importance and the feasibility of proposed method are discussed to show potential implications of the proposed approach.

Keywords: Shopping, Customer, Hospitality, Gait, RFID, The states of the user.

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