Radar Sleep Monitoring Active Motion Suppression
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Solution Overview
Problem
Existing non-contact sleep monitoring methods using radar sensors face challenges in accurately estimating heart rate due to the breathing motion magnification effect caused by mattress surface displacement during sleep, which overwhelms the heartbeat signal and leads to inaccurate vital sign estimation.
Innovation Solution
The implementation of an active motion suppression technique that selects specific range bins with optimal phase differences to enhance the signal-to-noise ratio, allowing for the separation and recovery of the heartbeat signal from the respiration interference, using a radar sensor system that processes RF response signals to monitor vital signs and classify sleep states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If non-contact radar sensing is used for sleep monitoring, then patient comfort and ease of operation are improved, but measurement precision deteriorates due to breathing motion magnification artifacts
Solution Approach 1:
The patent segments the radar signal processing into multiple range bins to separate the breathing motion artifacts from the heartbeat signal. By dividing the signal into different spatial zones and selectively processing specific range bins, the system can isolate and suppress unwanted breathing artifacts while preserving the heartbeat information, thus resolving the contradiction between non-contact comfort and measurement accuracy.
Solution Approach 2:
The patent extracts and removes the breathing motion magnification artifacts from the radar signal through selective range bin processing. By identifying and extracting only the relevant signal components containing heartbeat information while discarding or suppressing the breathing artifacts, the system maintains patient comfort without sacrificing measurement precision.
2Device complexity
If existing radar signal processing approaches are used, then device complexity is reduced, but measurement precision deteriorates due to inability to suppress breathing artifacts
Solution Approach 1:
The patent applies preliminary signal processing steps to prepare the radar data before vital sign extraction. By pre-organizing the signal into range bins and identifying breathing artifact patterns in advance, the system establishes a foundation for accurate heartbeat detection without requiring overly complex processing algorithms, thus balancing device complexity with measurement precision.
Solution Approach 2:
The patent transitions from traditional time-domain signal analysis to a multi-dimensional approach by incorporating range bin spatial information. This dimensional expansion allows the system to separate breathing artifacts from heartbeat signals based on their different spatial characteristics, improving measurement precision while maintaining manageable device complexity through structured signal organization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively suppresses breathing motion artifacts, enabling accurate remote sleep monitoring and improved heart rate estimation, allowing for more reliable diagnosis of sleep conditions without the need for contact sensors.
Implementation Method 1
transmitting a radar signal toward a subject and receiving a radio frequency (RF) response signal corresponding to the radar signal
Implementation Method 2
processing the RF response signal to produce one or more vital sign signals
Data Source
AI summary
Methods and systems for remote sleep monitoring are provided. Such methods and systems provide non-contact sleep monitoring via remote sensing or radar sensors. In this regard, when processing backscattered radar signals from a sleeping subject on a normal mattress, a breathing motion magnification effect is observed from mattress surface displacement due to human respiratory activity. This undesirable motion artifact causes existing approaches for accurate heart-rate estimation to fail. Embodiments of the present disclosure use a novel active motion suppression technique to deal with this problem by intelligently selecting a slow-time series from multiple ranges and examining a corresponding phase difference. This approach facilitates improved sleep monitoring, where one or more subjects can be remotely monitored during an evaluation period (which corresponds to an expected sleep cycle).