Methods, apparatus, servers, and systems for vital signs detection and monitoring

Patent metadata

Field	Value
Publication number	US-11012285-B2
Application number	US-201816127151-A
Country	US
Kind code	B2
Filing date	Sep 10, 2018
Priority date	Dec 5, 2012
Publication date	May 18, 2021
Grant date	May 18, 2021

Abstract

The present teaching relates to vital sign detection and monitoring based on channel state information (CSI). In one example, an apparatus for vital sign detection is disclosed. The apparatus comprises a receiver, a processor and a memory communicatively coupled with the processor. The receiver is configured for receiving at least one wireless signal from a multipath channel that can be impacted by a vital sign of at least one living being. The processor is configured for: extracting a time series of channel state information (CSI) for the multipath channel from the at least one wireless signal, obtaining one or more periodic fluctuations based on a spectral analysis of the time series of CSI, and determining whether the vital sign is present based on the one or more periodic fluctuations.

First claim

What is claimed is:

1. An apparatus for vital sign detection, comprising:
a receiver configured for receiving at least one wireless signal from a multipath channel that can be impacted by one or more vital signs of one or more living beings;
a processor; and
a memory communicatively coupled with the processor,
wherein the processor is configured for:
extracting at least one time series of channel information (TSCI) of the multipath channel from the at least one wireless signal,
computing a similarity matrix based on the at least one TSCI, each matrix element being a measure of similarity between two channel information (CI) of the at least one TSCI,
obtaining one or more periodic fluctuations based on a spectral analysis of the at least one TSCI based on the similarity matrix,
performing a decomposition of the similarity matrix,
generating a spectrum based on the decomposition of the similarity matrix,
detecting one or more extrema of the spectrum,
determining rates of the one or more periodic fluctuations based on the one or more detected extrema, and
determining whether the one or more vital signs are present based on at least one of: the one or more periodic fluctuations, the rates, or the detected extrema.

2. The apparatus of claim 1 , wherein at least one of:
a vital sign comprises at least one of: breathing, heartbeat, and another vital sign having a periodic pattern;
the processor is further configured for determining one or more vital sign analytics of the one or more living beings, upon determining the one or more vital signs are present;
the spectral analysis is performed based on at least one of: a MUSIC based algorithm, a Root-MUSIC based algorithm, a parametric scheme, a non-parametric scheme, machine learning, and another spectral analysis algorithm.

3. The apparatus of claim 1 , wherein:
the processor is further configured for:
cleaning the at least one TSCI by subtracting background information from the CI,
normalizing the at least one TSCI, and
calculating at least one measure of similarity each based on a pair of CI among the at least one TSCI, wherein the spectral analysis is performed based on the at least one measure of similarity; and

a measure of similarity of a pair of CI is calculated based on at least one of: a time-reversal resonance strength (TRRS), a cross-correlation, an inner product of two vectors, a similarity score, a distance score, a phase correction, a timing correction, a timing compensation, and a phase offset compensation, of the pair of CI.

4. The apparatus of claim 1 , wherein at least one of:
the processor is further configured for:
smoothing the similarity matrix in time domain to generate a smoothed similarity matrix, wherein the spectral analysis is performed based on the smoothed similarity matrix;

the processor is further configured for:
computing a TRRS matrix based on the at least one TSCI,
performing an eigenvalue decomposition on the TRRS matrix,
obtaining a noise subspace based on the eigenvalue decomposition,
generating a pseudo-spectrum based on the noise subspace,
performing spectrum folding on the pseudo-spectrum to generated an updated pseudo-spectrum,
trimming the updated pseudo-spectrum into a range related to vital sign rate, and
detecting one or more peaks of the updated pseudo-spectrum within the range,
wherein one or more vital sign rates of the one or more vital signs of the one or more living beings are determined based on the one or more peaks; and

the processor is further configured to:
computing a TRRS matrix based on the at least one TSCI,
performing an eigenvalue decomposition on the TRIS matrix,
obtaining a noise subspace based on the eigenvalue decomposition,
obtaining a matrix based on the noise subspace,
generating a polynomial equation based on the obtained matrix, and
selecting one or more complex roots of the polynomial equation,
wherein the one or more vital sign rates of the one or more vital signs of the one or more living beings are determined based on an information related to at least one of: angle and phase, of the one or more complex roots.

5. The apparatus of claim 1 , wherein at least one of:
one or more vital sign rates of the one or more vital signs of the one or more living beings are determined by:
determining vital sign rate estimations based on the spectral analysis of the at least one TSCI,
partitioning the vital sign rate estimations into a plurality of clusters each with an associated likelihood which indicates a possibility for that cluster to represent a vital sign rate,
merging two clusters in the plurality of clusters into one cluster when a centroid distance between the two clusters is less than a threshold,
recalculating the vital sign rate estimation and its associated likelihood for each merged cluster, and
determining the one or more vital sign rates based on one or more clusters having the highest associated likelihoods among the clusters after merging;

the processor is further configured for estimating a quantity of the one or more living beings based on a number of clusters of vital sign rate estimations; and
the processor is further configured for monitoring the one or more vital sign rates of the one or more vital signs of the one or more living beings continuously as they perform at least one of doing exercises, working, sleeping, eating, drinking, standing, sitting, walking, running, and any other activities.

6. The apparatus of claim 1 , wherein:
the at least one wireless signal is received through a network that is at least one of:
Internet, an Internet-protocol network, and another multiple access network;

the receiver is associated with a physical layer of at least one of: a wireless PAN, IEEE 802.15.1 (Bluetooth), a wireless LAN, IEEE 802.11 (Wi-Fi), a wireless MAN, IEEE 802.16 (WiMax), WiBro, HiperMAN, mobile WAN, GSM, GPRS, EDGE, HSCSD, iDEN, D-AMPS, IS-95, PDC, CSD, PHS, WiDEN, CDMA2000, UMTS, 3GSM, CDMA, TDMA, FDMA, W- CDMA, HSDPA, W-CDMA, FOMA, 1×EV-DO, IS-856, TD-SCDMA, GAN, UMA, HSUPA, LTE, 2.5G, 3G, 3.5G, 3.9G, 4G, 5G, 6G, 7G, another wireless system and another mobile system.

7. A method, implemented on a machine including at least a receiver, a processor and a memory communicatively coupled with the processor for vital sign detection, comprising:
receiving at least one wireless signal from a multipath channel that can be impacted by at least one vital sign each associated with a respective living being of one or more living beings;
extracting at least one time series of channel information (TSCI) of the multipath channel from the at least one wireless signal;
calculating a similarity matrix based on the at least one TSCI, each entry of the similarity matrix being a similarity score between two channel information CI of the at least one TSCI;
obtaining one or more periodic fluctuations based on a spectral analysis of the at least one TSCI based on the similarity matrix;
performing a decomposition on the similarity matrix;
generating a spectrum based on the decomposition of the similarity matrix;
performing spectrum folding on the spectrum;
detecting one or more peaks of the spectrum;
determining frequency of the one or more periodic fluctuations based on the one or more peaks; and
determining whether the at least one vital sign is present based on at least one of: the one or more periodic fluctuations, the frequency, or the one or more peaks.

8. The method of claim 7 , wherein a vital sign comprises at least one of:
breathing, heartbeat or another vital sign having a periodic pattern, and the method further comprises determining one or more analytics of the at least one vital sign of the one or more living beings, upon determining

Assignees

• Chen Chen
• Wang Beibei
• Han Yi
• Zhang Feng
• Lai Hung Quoc Duc
• Chen Yan
• Liu K J Ray
• Au Oscar Chi Lim
• Origin Wireless Inc

Inventors

• Chen Chen
• Wang Beibei
• Han Yi
• Zhang Feng
• Lai Hung-Quoc Duc
• Chen Yan
• Liu K J Ray
• Au Oscar Chi-Lim

Classifications

• H04W72/21

  in the uplink direction of a wireless link, i.e. towards the network · CPC title

• H04L5/0048

  Allocation of pilot signals, i.e. of signals known to the receiver (allocation of control signalling H04L5/0053; use of control signalling H04L5/0091) · CPC title

• H04L27/362 Primary

  Modulation using more than one carrier, e.g. with quadrature carriers, separately amplitude modulated (H04L27/366 takes precedence) · CPC title

• H04B1/38

  Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving · CPC title

• H04W72/0413

  Electricity · mapped topic