Shichen Zhang (Michigan State University), Qijun Wang (Michigan State University), Maolin Gan (Michigan State University), Zhichao Cao (Michigan State University), Huacheng Zeng (Michigan State University)

This paper aims to design and implement a radio device capable of detecting a person's handwriting through a wall. Although there is extensive research on radio frequency (RF) based human activity recognition, this task is particularly challenging due to the textit{through-wall} requirement and the textit{tiny-scale} handwriting movements. To address these challenges, we present RadSee---a 6 GHz frequency modulated continuous wave (FMCW) radar system designed for detecting handwriting content behind a wall. RadSee is realized through a joint hardware and software design. On the hardware side, RadSee features a 6 GHz FMCW radar device equipped with two custom-designed, high-gain patch antennas. These two antennas provide a sufficient link power budget, allowing RadSee to "see'' through most walls with a small transmission power. On the software side, RadSee extracts effective phase features corresponding to the writer's hand movements and employs a bidirectional LSTM (BiLSTM) model with an attention mechanism to classify handwriting letters. As a result, RadSee can detect millimeter-level handwriting movements and recognize most letters based on their unique phase patterns. Additionally, it is resilient to interference from other moving objects and in-band radio devices. We have built a prototype of RadSee and evaluated its performance in various scenarios. Extensive experimental results demonstrate that RadSee achieves 75% letter recognition accuracy when victims write 62 random letters, and 87% word recognition accuracy when they write articles.

View More Papers

Truman: Constructing Device Behavior Models from OS Drivers to...

Zheyu Ma (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; EPFL; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Qiang Liu (EPFL), Zheming Li (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Tingting Yin (Zhongguancun…

Read More

Blackbox Fuzzing of Distributed Systems with Multi-Dimensional Inputs and...

Yonghao Zou (Beihang University and Peking University), Jia-Ju Bai (Beihang University), Zu-Ming Jiang (ETH Zurich), Ming Zhao (Arizona State University), Diyu Zhou (Peking University)

Read More

Towards LLM-Assisted Vulnerability Detection and Repair for Open-Source 5G...

Rupam Patir (University at Buffalo), Qiqing Huang (University at Buffalo), Keyan Guo (University at Buffalo), Wanda Guo (Texas A&M University), Guofei Gu (Texas A&M University), Haipeng Cai (University at Buffalo), Hongxin Hu (University at Buffalo)

Read More

EAGLEYE: Exposing Hidden Web Interfaces in IoT Devices via...

Hangtian Liu (Information Engineering University), Lei Zheng (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Shuitao Gan (Laboratory for Advanced Computing and Intelligence Engineering), Chao Zhang (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Zicong Gao (Information Engineering University), Hongqi Zhang (Henan Key Laboratory of Information Security), Yishun Zeng (Institute for Network Sciences…

Read More