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Dual-Node UWB Radar for Arm Motion Recognition

- Citation Author(s):
- Submitted by:
- GuipIng Lin
- Last updated:
- Tue, 04/08/2025 - 02:32
- DOI:
- 10.21227/h3v5-m717
- License:
- Categories:
- Keywords:
Abstract
Ultra Wideband (UWB) signals offer high spatio-temporal resolution, penetrability, and low cost, which facilitates accurate characterization of limb features through micro-Doppler (mD) analysis, even with micro random body movements, during the wireless contactless sensing. Due to challenges introduced by arm motions, which may be perpendicular to the radar, we introduce a dual radar arm motion recognition system with light-weighted feature extraction and appropriate data fusion. This architecture will enhance the motion characterization by integrating complementary perspectives from orthogonal radar nodes. Through proper morphological filtering and motion feature extraction, we adopt the spatio-temporal feature fusion and Doppler signatures to enhance the diverse arm motion recognition via attention-guided weighting.
Description: The dataset contains all the raw data for the front and left side nodes in the “XFront” and “XLeft” folders, respectively. Each folder contains 1002 .mat data, and each .mat data includes 5 times of the same action. Each .mat file is named as: "front/side _ initials of the experimenter _ distance from X4 _ motion name (corresponding to the motion graph with the corresponding name in the paper) _ serial number".
Size: The total size of all objects is 357M.
Platform: Matlab, Python.
Environment: Windows10, python3.7.
Contact information: lgp_sz23@163.com.
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