Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 32 | Sensing your heartbeat (and others) |
Qiyang Wu Xin Chen Xuanqi Wang Yukai Han |
design_document1.pdf final_paper1.pdf final_paper2.pdf proposal1.pdf |
Howard Yang | |
| # Problem Traditional human activity monitoring systems often rely on cameras, wearable sensors, or specialized hardware, which can be intrusive, expensive, or inconvenient. However, WiFi signals, which are already ubiquitous in indoor environments, can be repurposed for non-contact human sensing. The challenge lies in accurately extracting and interpreting fine-grained Channel State Information (CSI) to detect subtle human activities, such as breathing, gestures, and potentially even heartbeats, while mitigating environmental interference. Solution Overview Our solution for utilizing WiFi as a radar is to leverage Channel State Information (CSI) to sense human activities. We achieve this by extracting fine-grained CSI signals from WiFi devices and applying signal processing techniques to interpret movement patterns. The system consists of a WiFi transmitter and receiver and these devices can continuously capture CSI variations caused by human motion. Advanced algorithms are then used to distinguish different actions like heartbeats and body gestures by analyzing phase shifts and amplitude changes in the wireless signals. This approach enables non-contact human activity sensing, making it suitable for applications in health monitoring and human-computer interaction. Solution Components Subsystem1: WIFI signal transmission system The WiFi signal transmission system consists of Intel AX200 or AX210 network cards and external antennas to ensure stable and high-quality signal transmission. These components work together to provide a robust wireless communication setup necessary for collecting Channel State Information (CSI). Subsystem2: CSI Extraction Tool/Software The CSI signal processing system extracts WiFi CSI data using Ubuntu 22.04 LTS and PicoScenes software, which enables real-time signal analysis for detecting fine-grained variations in the wireless channel. Subsystem3: Human Action Recognition System The human action recognition system leverages CSI data to detect human movements by analyzing signal variations. Using MATLAB, Python and specialized CSI analysis toolboxes, it processes amplitude and phase changes to detect different human activities accurately. Criterion for Success Accurate Respiration Detection: The system must reliably detect human breathing patterns using CSI data by analyzing amplitude and phase variations in WiFi signals. Robust Interference Mitigation: The system should effectively filter out environmental noise and external disturbances, such as movement from non-human objects or signal fluctuations caused by multipath effects. Detection of Heartbeat and Other Physiological Signals (If possible): The system should capture and differentiate finer physiological signals, such as heartbeats, using advanced signal processing techniques. Distribution of Works Xin Chen [ECE] – Signal Processing Develops signal processing algorithms to analyze CSI data, extracting key features such as amplitude and phase variations for human activity recognition. Implements filtering and denoising techniques to improve signal quality and enhance detection accuracy. Works closely with system integration to ensure seamless data flow and efficient processing of CSI signals. Qiyang Wu [EE] – System Integration and Data Transmission Manages real-time data transmission between WiFi hardware and processing units, ensuring minimal latency and packet loss. Develops communication protocols to synchronize CSI data collection with processing algorithms. Optimizes data handling and storage to support continuous CSI analysis and facilitate system scalability. Xuanqi Wang [EE] – Hardware Setup and Optimization Configures WiFi devices, antennas, and receivers to ensure stable and high-quality CSI signal collection. Optimizes antenna placement to maximize sensitivity to movement and reduce interference. Works on power management and circuit adjustments to ensure system reliability and efficiency in different environments. Yukai Han [ME] – Mechanical Design Designs mounting structures and enclosures to securely position WiFi devices for optimal signal reception. Ensures stability and repeatability of the setup to maintain consistency in experiments. Assists in planning and executing test scenarios, considering environmental factors that may impact CSI signal variations. |
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