Social data shoes for gait monitoring of elderly people in smart home

Gait monitoring technology has recently become of increasing interest in the biometric as well as biomedical fields for observation of the human movement, especially walking that can refer to physical status of individuals. For this objective, data shoes own many advantages such as cheaper cost and rich of direct information from the walking. In this paper, we have developed a data shoe system for gait monitoring in home area. To observe gait behaviors, the sensor suite includes five force sensitive resistors (FSRs) which were installed on the insole of the shoe. Zigbee wireless communication technology was used as low-cost data transfer between the sensor suite and the receiver system which is USB-connected to a computer. The summary of the gait data can be submitted and displayed on social media such as Facebook in order that relatives or care-takers can monitor the wearer closely. Principal component analysis (PCA) pattern recognition of the experimental data has shown that this system can classify normal and abnormal walking patterns in a group of elderly volunteers. The integration of sensors, wireless technology and social ability with computer software could make the social data shoe system monitor the gait behaviors during the wearing time.