Systems and methods for non-invasive blood pressure measurement

• US 10,638,982 B2
• Filed: 07/17/2017
• Issued: 05/05/2020
• Est. Priority Date: 02/25/2015
• Status: Active Grant

• Current Assignee: Itamar Medical SPRY 2021 Limited Partnership
• Original Assignee: Spry Health, Inc. (Asahi Kasei Corporation)
• Inventors: Ferber, Elad, Narayanan, Ramkrishnan, Gol Gungor, Derya
• Primary Examiner(s): Turchen, Rochelle D
• Application Number:
  US15/652,076
• Publication Number:
  US 20170311902A1
• Time in Patent Office: 1,023 Days
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/02108 from analysis of pulse wave characteristics
• CPC Class Codes: A61B 5/02125 of pulse wave propagation time
• CPC Class Codes: A61B 5/6801 specially adapted to be attached to or worn on the body surface
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence

Abstract

Systems and methods for non-invasive blood pressure measurement are disclosed. In some embodiments, a system comprises a wearable member configured to generate first and second signals (e.g., PPG signals), and a blood pressure calculation system. The blood pressure calculation system includes a wave selection module configured to identify subsets of waves of the signals, a feature extraction module configured to generate sets of feature vectors form the subsets of waves, and a blood pressure processing module configured to calculate an arterial blood pressure value based on the sets of feature vectors and an empirical blood pressure calculation model, the empirical blood pressure calculation model configured to receive the sets of feature vectors as input values. The blood pressure calculation system further includes a communication module configured to provide a message including or being based on the arterial blood pressure value.

Claims

1. A system comprising:

a portable wearable member including;

an energy transmitter configured to project energy at a first wavelength and energy at a second wavelength into tissue of a user; and

an energy receiver configured to generate a first signal based on a first received portion of the energy at the first wavelength and a second signal based on a second received portion of the energy at the second wavelength, the first received portion of energy and the second received portion of energy each being received through the tissue of the user;

at least one hardware processor; and

memory containing executable instructions, the executable instructions being executable by the at least one hardware processor to control the at least one hardware processor to;

select a first subset of waves from a first set of waves of the first signal and a second subset of waves from a second set of waves of the second signal, the first subset of waves from the first set of waves being selected based on an average of the first set of waves over a first predetermined amount of time, the second subset of waves from the second set of waves being selected based on an average of the second set of waves over a second predetermined amount of time;

generate a first set of feature vectors from the first subset of waves, and a second set of feature vectors from the second subset of waves;

select an empirical blood pressure calculation model from one or more empirical blood pressure calculation models to calculate an arterial blood pressure value, the one or more empirical blood pressure calculation models including one or more pre-calibrated empirical blood pressure calculation models and one or more uncalibrated empirical blood pressure calculation models, each pre-calibrated empirical blood pressure calculation model being pre-calibrated based on a different group of individuals categorized by their biological information, the selection of the empirical blood pressure calculation model being based on whether biological information of the user is available and whether at least some of the biological information of the user matches at least one of the pre-calibrated empirical blood pressure calculation models, each of the empirical blood pressure calculation models being capable of at least assisting in calculation of the arterial blood pressure value using the first set of feature vectors from the first subset of waves and the second set of feature vectors from the second subset of waves;

calculate the arterial blood pressure value based on the first set of feature vectors, the second set of feature vectors, and the selected empirical blood pressure calculation model; and

present a signal to the user including or being based on the arterial blood pressure value.

2. The system of claim 1, wherein the executable instructions control the at least one hardware processor to select the first subset of waves from the first set of waves of the first sign, based on a mean and a standard deviation of the first signal, and select the second subset of waves from the second set of waves of the second signal, based on a mean and a standard deviation of the second signal.

3. The system of claim 2, wherein the executable instructions control the at least one hardware processor to select the first subset of waves from the first set of waves of the first signal, also based on a distance of a peak valley to a next peak valley of the first signal, and select the second subset of waves from the second set of waves of the second signal, also based on a distance of a peak valley to a next peak valley of the second signal.

4. The system of claim 1, wherein the executable instructions control the at least one hardware processor to select the first subset of waves from the first set of waves of the first signal, based on a distance of a peak valley to a next peak valley of the first signal and select the second subset of waves from the second set of waves of the second signal, based on a distance of a peak valley to a next peak valley of the second signal.

5. The system of claim 1, wherein the first set of feature vectors include first measurement values and first metric values, the first measurement values corresponding to amplitude or location points of a particular wave, the first metric values being generated from metric functions that use at least one of the first measurement values, and the second set of feature vectors include second measurement values and second metric values, the second measurement values corresponding to amplitude or location points of a particular wave, the second metric values being generated from metric functions that use at least one of the second measurement values.

6. The system of claim 5, wherein each of the first measurement values and the second measurement values include any of wave peak locations or amplitudes, or wave valley locations or amplitudes.

7. The system of claim 5, wherein each of the first metric functions and second metric functions include one or more particular metric functions that calculate a distance between two measurements values.

8. The system of claim 1, wherein the first wavelength is the same as the second wavelength.

9. The system of claim 1, wherein the first wavelength is different from the second wavelength.

10. The system of claim 1, wherein the first signal and the second signal each comprise photoplethysmogram (PPG) signal.

11. A method comprising:

projecting, from an energy transmitter, energy at a first wavelength and energy at a second wavelength into tissue of a user;

generating, at an energy receiving, a first signal based on a first received portion of the energy at the first wavelength and a second signal based on a second received portion of the energy at the second wavelength, the first received portion of energy and the second received portion of energy each being received through the tissue of the user;

selecting, by at least one hardware processor, a first subset of waves from a first set of waves of the first signal and a second subset of waves from a second set of waves of the second signal;

generating, by the at least one hardware processor, a first set of feature vectors from the first subset of waves, and a second set of feature vectors from the second subset of waves;

selecting, by the at least one hardware processor, an empirical blood pressure calculation model from one or more empirical blood pressure calculating models to calculate an arterial blood pressure value, the one or more empirical blood pressure calculating models including one or more pre-calibrated empirical blood pressure calculation models and one or more uncalibrated empirical blood pressure calculation models, each pre-calibrated empirical blood pressure calculating model being pre-calibrated based on a different group of individuals categorized by their biological information, the selection of the empirical blood pressure calculation model being based on whether biological information of the user is available and whether at least some of the biological information of the user matches at least one of the pre-calibrated empirical blood pressure calculation models, each of the empirical blood pressure calculation models being capable of at least assisting in calculation of the arterial blood pressure value using the first subset of waves and the second set of feature vectors form the second subset of waves;

calculating, by the at least one hardware processor, the arterial blood pressure value based on the first set of feature vectors, the second set of feature vectors, and the selected empirical blood pressure calculation model; and

presenting a signal to the user including or being based on the arterial blood pressure value.

12. The method of claim 11, wherein the first subset of waves is selected from the first set of waves of the first signal, based on a mean and a standard deviation of the first signal over a first predetermined amount of time, and the second subset of waves is selected from the second set of waves of the second signal, based on a mean and a standard deviation of the second signal over a second predetermined amount of time.

13. The method of claim 12, wherein the first subset of waves is selected from the first set of waves of the first signal, also based on a distance of a peak valley to a next peak valley of the first signal, and the second subset of waves is selected from the second set of waves of the second signal, also based on a distance of a peak valley to a next peak valley of the second signal.

14. The method of claim 11, wherein the first subset of waves is selected from the first set of waves of the first signal, based on a distance of a peak valley to a next peak valley of the first signal, and the second subset of waves is selected from the second set of waves of the second signal, based on a distance of a peak valley to a next peak valley of the second signal.

15. The method of claim 11, wherein the first set of feature vectors include first measurement values and first metric values, the first measurement values corresponding to amplitude or location points of a particular wave, the first metric values being generated from metric functions that use at least one of the first measurement values, and the second set of feature vectors include second measurement values and second metric values, the second measurement values corresponding to amplitude or location points of a particular wave, the second metric values being generated from metric functions that use at least one of the second measurement values.

16. The method of claim 15, wherein each of the first measurement values and the second measurement values include any of wave peak locations or amplitudes, or wave valley locations or amplitudes.

17. The method of claim 15, wherein each of the first metric functions and second metric functions include one or more particular metric functions that calculate a distance between two measurement values.

18. The method of claim 11, wherein the first wavelength is the same as the second wavelength.

19. The method of claim 11, wherein the first wavelength is different from the second wavelength.

20. The method of claim 11, wherein the first signal and the second signal each comprise photoplethysmogram (PPG) signal.