SpecRF-Posture Dataset

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Dataset information

Country of origin
Updated
2024.06.11 00:00
Created
2024.04.03
Available languages
English
Keywords
Quality scoring

Dataset description

In recent years, the utilization of Radio Frequency (RF) signals for Human Posture Recognition (HPR) has emerged as a promising approach in wireless sensing technology. Recent studies within RF systems have demonstrated the effectiveness of S21 parameters for human body-related classification tasks. Inspired by these advancements and the enhanced network performance offered by WiFi-6E, our system leverages S21 parameters within this frequency range for posture recognition. By analyzing the S21 parameters, we introduce SpecRF-Posture, a novel system designed for the accurate classification of human posture. Unlike previous approaches, we explore the use of low-cost hardware, based only on passive specular reflections that occur in the path between a steerable horn transmitter, a reflective surface, the Space-of-Interest (SoI), and an omnidirectional receiver. To characterize the region where the individual is positioned using specular reflections, our system achieves beam scanning by mechanically rotating the transmitter at regular intervals. Our work evaluates the viability of utilizing passive scatters within the propagation medium for HPR or similar tasks, at a low hardware cost. For each posture (Standing, T-shape, Side, Sitting, Lying down), we collected 120 samples (referred to as sweeps) from one volunteer, resulting in a dataset of 600 samples (1 subject × 5 postures × 120 sweeps). Each sample is characterized by dimensions (n_resolution, n_angles), where n_resolution=151 represents the number of frequencies between 5.925 GHz and 6.5 GHz, defining the resolution of the frequency range, and n_angles = 25 denotes the number of angles through which the antenna rotates. This spectrum of postures included minor movements of the hands or head to introduce variability into the data and make the model robust to different ways of assuming these postures. Each sweep corresponds to a .csv file where each row corresponds to a frequency and each pair of columns corresponds to the real and imaginary parts of the S21 parameter measured at each angle of rotation of the transmitter antenna. 
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32
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2019
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