Systems and methods for breathing detection and rate estimation using wireless communication signals

1. A method for estimating a breathing rate, comprising:

receiving at a first wireless communication device a wireless signal from a second wireless communication device;

measuring, by the first wireless communication device, a plurality of channel state information (CSI) data points from the wireless signal, wherein breathing-related motion over time changes the CSI data points between the first and second communication devices;

selecting, by the first wireless communication device, an initial reference CSI data point from the plurality of CSI data points;

computing, by the first wireless communication device, a first perturbation index curve for the wireless signal using the initial reference CSI data point and a portion of the plurality of CSI data points;

finding, by the first wireless communication device, an optimal reference CSI data point from within the plurality of CSI data points associated with a maximum perturbance index value from within the first perturbation index curve;

computing, by the first wireless communication device, a second perturbation index curve for the wireless signal using the optimal reference CSI data point and a portion of the plurality of CSI data points subsequent to the optimal reference CSI; and

determining, by the first wireless communication device, the breathing rate from the second perturbation index curve using a frequency analysis.

2. The method of claim 1 , wherein computing either the first or second perturbation index curves includes using channel nulling.

3. The method of claim 2 , wherein channel nulling includes:

calculating a nulling matrix; and

applying the nulling matrix to the plurality of CSI data points.

4. The method of claim 1 , wherein computing either the first or second perturbation index curves Γ n includes computing:

Γ n =10 log 10 |Σ k,k+1∈Ψ Δh k n H Δh k+1 n |−10 log 10 Σ k,k+1∈Ψ ∥h k n ∥ 2 ,

where Δh k n is channel change information for CSI n , h k n is the CSI for sample n, Ψ is the set of all the available tones, and k is tone index.

5. The method of claim 1 , wherein the frequency analysis of the second perturbation index curve includes applying a fast Fourier transform (FFT).

6. The method of claim 1 , wherein determining the breathing rate includes:

calculating a standard deviation of the second perturbation index curve over a window set of CSI data points; and

indicating a breathing detection failure when the standard deviation is below a predetermined threshold value.

7. The method of claim 1 , wherein the frequency analysis includes:

performing a frequency transformation of the second perturbation index curve over a window set of CSI data points; and

determining the breathing rate as a frequency with a highest value.

8. The method of claim 7 , further comprising:

calculating a peak-to-total power ratio using the frequency with the highest value; and

indicating a breathing detection failure when the peak-to-total power ratio is below a predetermined threshold value.

9. The method of claim 7 , further comprising sliding the window set of CSI data points and re-calculating the breathing rate.

10. The method of claim 7 , further comprising:

determining a breathing rate detection failure;

computing an average of the second perturbation index curve values corresponding to the window set of CSI data points;

indicating motion when the average of the second perturbation index curve values corresponding to the window set of CSI data points is above a predetermined threshold; and

indicating no motion when the average of the second perturbation index curve values corresponding to the window set of CSI data points is below a predetermined threshold.

11. A breathing rate estimation device, comprising:

a first wireless communication device configured to:

receive a wireless signal from a second wireless communication device;

measure a plurality of channel state information (CSI) data points from the wireless signal, wherein breathing-related motion over time changes the CSI data points between the first and second communication devices;

select an initial reference CSI data point from the plurality of CSI data points;

compute a first perturbation index curve for the wireless signal using the initial reference CSI data point and a portion of the plurality of CSI data points;

find an optimal reference CSI data point from within the plurality of CSI data points associated with a maximum perturbance index value from within the first perturbation index curve;

compute a second perturbation index curve for the wireless signal using the optimal reference CSI data point and a portion of the plurality of CSI data points subsequent to the optimal reference CSI; and

determine the breathing rate from the second perturbation index curve using a frequency analysis.

12. The system of claim 11 , wherein computing either the first or second perturbation index curves includes using channel nulling.

13. The system of claim 12 , wherein channel nulling includes:

calculating a nulling matrix; and

applying the nulling matrix to the plurality of CSI data points.

14. The system of claim 11 , wherein computing either the first or second perturbation index curves Γ n includes computing:

Γ n =10 log 10 |Σ k,k+1∈Ψ Δh k n H Δh k+1 n |−10 log 10 Σ k,k+1∈Ψ ∥h k n ∥ 2 ,

where Δh k n is channel change information for CSI n , h k n is the CSI for sample n, Ψ is the set of all the available tones, and k is tone index.

15. The system of claim 11 , wherein the frequency analysis of the second perturbation index curve includes applying a fast Fourier transform (FFT).

16. The system of claim 11 , wherein determining the breathing rate includes:

calculating a standard deviation of the second perturbation index curve over a window set of CSI data points; and

indicating a breathing detection failure when the standard deviation is below a predetermined threshold value.

17. The system of claim 11 , wherein the frequency analysis includes:

performing a frequency transformation of the second perturbation index curve over a window set of CSI data points; and

determining the breathing rate as a frequency with a highest value.

18. The system of claim 17 , wherein the first wireless communication device is further configured to:

calculate a peak-to-total power ratio using the frequency with the highest value; and

indicate a breathing detection failure when the peak-to-total power ratio is below a predetermined threshold value.

19. The system of claim 16 , wherein the first wireless communication device is further configured to slide the window set of CSI data points and re-calculate the breathing rate.

20. The system of claim 16 , wherein the first wireless communication device is further configured to:

determine a breathing rate detection failure;

compute an average of the second perturbation index curve values corresponding to the window set of CSI data points;

indicate motion when the average of the second perturbation index curve values corresponding to the window set of CSI data points is above a predetermined threshold; and

indicate no motion when the average of the second perturbation index curve values corresponding to the window set of CSI data points is below a predetermined threshold.