Bluetooth Sensor Data for Gait-Based Person Identification

The human gait is unique and so is the impact of a walking human on the propagation of wireless signals within a wireless network. Using appropriate pattern recognition techniques, a person can thus be identified just from a time series of Received Signal Strength (RSS) measurements. This dataset holds bidirectional RSS measurements recorded within a mesh network of four Bluetooth sensor devices. During the measurements, a total of 14 subjects walked individually through the setup. A total of more than 10,000 recordings are provided.

人类步态独具特色，且行走人类对无线网络中无线信号的传播产生独特影响。通过采用适当的模式识别技术，个体可仅从接收信号强度（RSS）测量的时间序列中得以识别。本数据集包含在四个蓝牙传感器设备构成的网状网络内记录的双向RSS测量数据。在测量过程中，共有14名受试者依次通过该设置进行行走。总计提供了超过10,000次记录。