Non-Invasive Breathing Rate Estimation Using Wi-Fi CSI Perturbation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for breathing detection and rate estimation are invasive or require direct contact with measurement devices, making them inconvenient for widespread use in health monitoring.
Innovation Solution
A system that uses wireless communication signals to estimate breathing rate by computing a perturbation index from channel state information (CSI) and applying channel nulling techniques, allowing for non-invasive detection and rate estimation without the need for direct device contact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive or wired physiological sensors are used for breathing detection, then measurement precision is improved, but ease of operation deteriorates due to discomfort and hesitation to attach sensors to the body
Solution Approach 1:
The patent replaces mechanical physiological sensors with a wireless communication-based detection system. The system uses Wi-Fi channel state information (CSI) to detect breathing movements indirectly through changes in the electromagnetic channel caused by chest motion, eliminating the need for direct body contact and mechanical sensors.
Solution Approach 2:
The patent introduces an intermediary approach by using wireless signals as a mediator between the breathing motion and the detection system. The CSI data serves as an intermediary that captures breathing information without requiring direct sensor contact with the body, allowing indirect measurement through the electromagnetic field.
2Ease of operation
If wireless communication signals are used for breathing detection, then ease of operation is improved through non-invasive monitoring, but measurement precision may deteriorate due to signal interference and environmental factors
Solution Approach 1:
The patent implements feedback mechanisms through iterative reference CSI selection and perturbation index computation. The system continuously refines the reference CSI based on detected breathing patterns and adjusts the analysis accordingly, allowing the system to adapt to changing conditions and maintain measurement precision despite environmental variations.
Solution Approach 2:
The patent applies preliminary action through the selection and optimization of reference CSI data before performing breathing rate estimation. By pre-processing the CSI data to identify and select optimal reference points, the system prepares the data in advance to minimize the impact of environmental interference and maximize measurement accuracy.
3Measurement precision
If complex signal processing algorithms are applied to CSI data, then measurement precision is improved through better breathing detection, but device complexity increases
Solution Approach 1:
The patent segments the complex signal processing into distinct, manageable steps: reference CSI selection, perturbation index computation, breathing rate estimation, and validation. By dividing the complex algorithm into sequential modules, the system maintains precision while making the complexity more manageable and implementable.
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
Enables non-invasive, low-cost breathing detection and rate estimation using widely available Wi-Fi devices, providing a passive and almost installation-free solution for monitoring respiratory health.
Implementation Method 1
receiving a plurality of channel state information (CSI) from a wireless device
Data Source
AI summary
Various embodiments relate to a method for estimating a breathing rate, including: receiving a plurality of channel state information (CSI) from a wireless device; selecting an initial reference CSI from the plurality of CSI; computing a perturbation index using the initial reference CSI and a portion of the plurality of CSI; determining an optimal reference CSI based upon the perturbation index; re-computing the perturbation index using the optimal reference CSI on a portion of the plurality of CSI subsequent to the optimal reference CSI; and determining a breathing rate from the perturbation index using a frequency analysis of the perturbation index.