FootprintID Dataset: Footstep-Induced Structural Vibration Data for Indoor Person Identification with Different Walking Speeds

The dataset consists of structural vibration data (vertical velocity of floor structure) induced by 10 people’s footsteps as they walk around with 8 different walking speeds, sensed by 5 geophone sensors.

The footstep-induced structural vibration data is stored as footstep traces, each consisting of a series of consecutive footsteps (see the sample plot). The dataset is stored in a MAT-file named People.mat. The dataset includes three layers of labels: 1) person identity i (i = 1, 2, ..., 10), 2) sensor number j (j = 1, 2, ..., 5), and 3) walking speed k (k = 1, 2, ..., 8). The speed k represents the walking speeds of \(\mu,\ \ \mu+\sigma,\ \ \mu+2\sigma,\ \ \mu+3\sigma,\ \ \mu-\sigma,\ \ \mu-2\sigma,\ \ \mu-3\sigma\), and self-selected speed by each person respectively. \(\mu\) and \(\sigma\) refer to the mean and standard deviation of the step frequencies. To access the footstep traces from the person i, sensor j with walking speed k, please use the MATLAB syntax People{i}.Sen{j}.S{k}. This gives a \(m\times n\) cell structure. \(m\) denotes the individual trace number, of which the number of traces varies from 10 to 12; \(n\) represents the level of amplification, including 2000X, 4000X, and 6000X, corresponding to n = 1, n = 2, and n = 3 respectively. To read and plot a sample trace of footstep-induced floor vibration, use the script read_data.m. For more details, please refer to the original FootprintID paper in the following link: https://dl-acm-org.stanford.idm.oclc.org/doi/10.1145/3130954

The human walking experiment involves 10 participants aged between 20 to 29 years old, of which 8 are male and 2 are female. Their walking area is 30ft X 6ft along a hallway with concrete floor. Each of the participants wears flat bottom shoes.

The sensing unit consists of 5 components: 1) the geophone (SM-24), 2) the amplification module, 3) the processor board, 4) the communication module (XBee radio), and 5) the batteries. The sensing unit converts the structural vibration velocity into voltages records. The sampling frequency is 1000Hz.

The hardware unit, experiment setup, and a sample data plot can be found in Experiment Introduction.pdf. Further implementation details can be found in the original FootPrintID paper in the link above.

Please cite this dataset as:

Yiwen Dong, Shijia Pan, Tong Yu, Mostafa Mirshekari, Jonathon Fagert, Amelie Bonde, Ole J. Mengshoel, Pei Zhang, and Hae Young Noh. 2021. The FootprintID Dataset: Footstep-Induced Structural Vibration Data for Person Identification with 8 Different Walking Speeds. Zenodo, DOI: https://doi.org/10.5281/zenodo.4691144

Shijia Pan, Tong Yu, Mostafa Mirshekari, Jonathon Fagert, Amelie Bonde, Ole J. Mengshoel, Hae Young Noh, and Pei Zhang. 2017. FootprintID: Indoor Pedestrian Identification through Ambient Structural Vibration Sensing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 3, Article 89 (September 2017), 31 pages. DOI: https://doi.org/10.1145/3130954

本数据集包含由10名受试者以8种不同步行速度行走时产生的楼面结构竖向振动速度数据，由5个检波器（geophone）采集得到。

脚步引发的结构振动数据以脚步轨迹（footstep traces）形式存储，每条轨迹包含一系列连续行走的脚步信号（详见示例绘图）。数据集存储于名为People.mat的MATLAB数据文件（MAT-file）中。本数据集包含三层标签：1）受试者身份编号\(i\)（\(i = 1, 2, dots, 10\)）；2）传感器编号\(j\)（\(j = 1, 2, dots, 5\)）；3）步行速度等级\(k\)（\(k = 1, 2, dots, 8\)）。其中速度等级\(k\)分别对应步频均值\(mu\)、\(mu+sigma\)、\(mu+2sigma\)、\(mu+3sigma\)、\(mu-sigma\)、\(mu-2sigma\)、\(mu-3sigma\)以及受试者自选步行速度，此处\(mu\)与\(sigma\)分别指代步频的均值与标准差。若需调取受试者\(i\)、传感器\(j\)、速度等级\(k\)对应的脚步轨迹数据，可使用MATLAB语法`People{i}.Sen{j}.S{k}`。该语法将返回一个\(m imes n\)元胞数组（cell structure），其中\(m\)为单条数据集的轨迹数量，轨迹数量介于10至12之间；\(n\)代表放大倍数档位，分别对应2000倍、4000倍与6000倍放大，对应\(n=1\)、\(n=2\)与\(n=3\)。若需读取并绘制单条脚步引发的楼面振动轨迹样本，可使用脚本`read_data.m`。更多细节可参阅下述链接中的原始FootprintID论文：https://dl-acm-org.stanford.idm.oclc.org/doi/10.1145/3130954

本次人类步行实验共招募10名年龄介于20至29岁之间的受试者，其中男性8名，女性2名。受试者的步行区域为沿混凝土走廊的30英尺×6英尺（30ft×6ft）通道。所有受试者均穿着平底鞋。

传感单元由5个部分组成：1）检波器（geophone，型号SM-24）；2）放大模块（amplification module）；3）处理器板（processor board）；4）通信模块（communication module，即XBee无线电（XBee radio））；5）电池组。传感单元将结构振动速度转换为电压记录数据。采样频率为1000Hz。

实验装置、硬件单元以及样本数据绘图均可参阅`Experiment Introduction.pdf`文件。更多实现细节可参阅前述链接中的原始FootprintID论文。

本数据集的引用格式如下：

董一文, 潘世佳, 于桐, Mostafa Mirshekari, Jonathon Fagert, Amelie Bonde, Ole J. Mengshoel, 张培, 以及Noh Hae Young. 2021. 《FootprintID数据集：用于8种步行速度下人员识别的脚步引发结构振动数据》. Zenodo, DOI: https://doi.org/10.5281/zenodo.4691144

潘世佳, 于桐, Mostafa Mirshekari, Jonathon Fagert, Amelie Bonde, Ole J. Mengshoel, Noh Hae Young, 以及张培. 2017. 《FootprintID：基于环境结构振动传感的室内行人识别》. ACM交互、移动、可穿戴与普适技术汇刊（Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.）1, 3, 第89篇文章（2017年9月）, 共31页. DOI: https://doi.org/10.1145/3130954