Monostatic full-duplex Wi-Fi Gesture sensing Dataset

Dataset Overview URL: https://huggingface.co/datasets/JessicaSanson/wird_gest_wifi_gesture_monostatic_intel Scope notice: This is the full dataset released to accompany the paper and enable reproducibility of the reported results. It contains an extensive set of recordings (191,442 raw frames, 722 complete gesture instances, 5 subjects) across multiple environments (lab and public café). For algorithm validation, cross-location generalization testing, or replication of the paper's Range-Doppler processing method, the data is sufficient as-is. WIRD-GEST: Gesture Recognition via Wi-Fi Range-Doppler — Full Dataset Paper: WIRD-GEST: Gesture Recognition in the Real World Using Active Range-Doppler Wi-Fi Sensing on COTS Hardware Authors: Jessica Sanson, Rahul C. Shah, Yazhou Zhu, Rafael Rosales, Valerio Frascolla Year: 2026 Venue: ICC 2026, URL: https://arxiv.org/pdf/2603.22131v1 This dataset contains Channel State Information (CSI) recordings and pre-processed Range-Doppler maps for Gesture Recognition — capturing 5 distinct hand movements (clockwise, forward/back, pulse, side-to-side, and up/down). The data is collected using monostatic full-duplex Wi-Fi sensing on commercial off-the-shelf (COTS) laptops (Lenovo ThinkPad Wi-Fi 6E) — no external sensors, no dedicated transmitter, no hardware modification of any kind. Unlike bistatic datasets that require a separate transmitter (e.g., a router) and receiver, here a single unmodified laptop simultaneously transmits and receives by sharing the Local Oscillator and baseband processing, using the device's own self-interference as the sensing signal. CSI is read directly from the built-in NIC. License MIT License — Copyright (c) 2026 Intel Corporation Permission is hereby granted, free of charge, to any person obtaining a copy of this dataset and associated documentation, to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies, subject to the above copyright notice and this permission notice appearing in all copies. Ethics and Privacy Informed consent obtained from all participants Full GDPR compliance Anonymized participant IDs No PII, video, or audio recordings