Apparatus and method for wireless monitoring using ultra-wideband frequencies
A system for and a method of wirelessly monitoring one or more patients can include transmitting ultra-wideband pulses toward the one or more patients, receiving ultra-wideband signals, and sampling the ultra-wideband signals. Sampling the ultra-wideband pulses can be performed with a sample rate that is less than the Nyquist rate. Impulse response can be estimated and/or recovered by exploiting sparsity of the impulse response.
1. A monitoring system for assessing one or more patients, comprising:
a pulse generator configured to generate ultra-wideband pulses;
an ultra-wideband transceiver for transmitting the ultra-wideband pulses toward the one or more patients and receiving ultra-wideband signals from the one or more patients, wherein the ultra-wideband pulses have a Nyquist sampling rate;
a sampler for sampling the ultra-wideband signals at a sample rate less than the Nyquist sampling rate; and
a processor in communication with the sampler, wherein the processor is configured to monitor one or more biological functions in a non-isolated and time variant environment and to reconstruct a breathing waveform from the ultra-wideband signals based on an agnostic Bayesian matching pursuit algorithm.
2. The system of claim 1 , wherein the processor is configured to analyze a number of sampled pulses.
3. The system of claim 2 , wherein the number of sampled pulses is substantially equivalent to the ratio of the Nyquist sampling rate to the sample rate.
4. The system of claim 1 , wherein the ultra-wideband pulses are separated by a time interval of T p and wherein a subsampling ratio, N, conforms with T p f N =mN−1, where m is an integer and f N is the Nyquist sampling rate.
5. The system of claim 4 , wherein the processor is configured to execute a greedy algorithm to estimate an impulse response based on sparsity of the impulse response.
6. The system of claim 1 , wherein the processor is configured to monitor one or more biological functions in a non-isolated and time variant environment.
7. The system of claim 6 , wherein the one or more biological functions comprise respiration.
8. The system of claim 7 , wherein the one or more biological functions comprise heart rate.
9. The system of claim 7 , wherein the processor is configured to monitor movement.
10. A method of wirelessly monitoring one or more patients, comprising:
transmitting ultra-wideband pulses toward the one or more patients;
receiving ultra-wideband signals, wherein the ultra-wideband pulses have a Nyquist sampling rate;
sampling the ultra-wideband signals at a sample rate less than the Nyquist sampling rate;
calculating a differential signal and removing time-varying background clutter; and
reconstructing a breathing waveform from the ultra-wideband signals based on an agnostic Bayesian matching pursuit algorithm.
11. The method of claim 10 , further comprising analyzing a number of sampled pulses.
12. The method of claim 11 , wherein the number of sampled pulses is substantially equivalent to the ratio of the Nyquist sampling rate to the sample rate.
13. The method of claim 10 , wherein the ultra-wideband pulses are separated by a time interval of T p and wherein a subsampling ratio, N, conforms with T p f N =mN−1, where m is an integer and f N is the Nyquist sampling rate.
14. The method of claim 13 , further comprising executing a greedy algorithm to estimate an impulse response based on sparsity of the impulse response.
15. The method of claim 13 , further comprising calculating a differential signal and removing time-varying background clutter.
16. The method of claim 15 , further comprising estimating an impulse response.
17. The method of claim 16 , wherein the ultra-wideband signals are reflections of the ultra-wideband pulses, further comprising estimating a time of travel of the ultra-wideband pulses.
18. The method of claim 17 , further comprising calculating a position as a function of time to determine one or more biological functions.
19. The method of claim 15 , wherein the differential signal is a difference between a measurement at a current time instance and an earlier time instance.
20. The method of claim 10 , further comprising monitoring one or more biological functions.
21. The method of claim 20 , wherein the one or more biological functions comprise respiration.
22. The method of claim 21 , wherein the one or more biological functions comprise heart rate.
23. The method of claim 21 , further comprising monitoring movement.
24. The system of claim 1 , wherein the processor is configured to reconstruct a breathing waveform.
25. A computer having a non-transitory computer readable medium comprising a program for monitoring at least one patient and configured to execute:
transmitting to the at least one patient a sequence of N pulses having a period of T p and a Nyquist sampling rate;
receiving signals based on the sequence of N pulses;
subsampling the signals at a sample rate, wherein the sample rate is defined by the Nyquist sampling rate reduced by a factor of N and wherein N conforms to T p f N =mN−1, where m is an integer and f N is the Nyquist sampling rate; and
reconstructing a breathing waveform from the signals based on an agnostic Bayesian matching pursuit algorithm.
26. The computer of claim 25 , wherein the program further executes:
removing time-varying background clutter;
estimating an impulse response; and
tracking respiratory movement.
27. The computer of claim 26 , wherein the sequence of N pulses comprises ultra-wideband pulses.
28. The computer of claim 26 , wherein the sequence of N pulses comprises ultrasonic pulses.
29. The computer of claim 26 , wherein the program is further configures to track the respiratory movement while the at least one patient is in a non-isolated and time variant environment.