Identification of posture-related syncope using head-mounted sensors

• US 10,667,697 B2
• Filed: 06/26/2019
• Issued: 06/02/2020
• Est. Priority Date: 06/14/2015
• Status: Active Grant

• Current Assignee: Facense Ltd.
• Original Assignee: Facense Ltd.
• Inventors: Tzvieli, Ori, Frank, Ari M, Tzvieli, Arie, Thieberger, Gil
• Primary Examiner(s): Porta, David P
• Assistant Examiner(s): Boosalis, Fani
• Application Number:
  US16/453,993
• Publication Number:
  US 20190313915A1
• Time in Patent Office: 342 Days
• CPC Class Codes: A61B 2562/0271 Thermal or temperature sensors
• CPC Class Codes: A61B 2562/0276 comprising a thermosensitive compound
• CPC Class Codes: A61B 2576/00 Medical imaging apparatus involving image processing or analysis A61B1/00009, A61B6/52 and A61B8/52 take precedence; image processing per se G06T; details of algorithms for analysing medical images G06T7/0012
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 5/0077 Devices for viewing the surface of the body, e.g. camera, magnifying lens
• CPC Class Codes: A61B 5/015 By temperature mapping of body part
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/6814 Head
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/748 Selection of a region of interest, e.g. using a graphics tablet
• CPC Class Codes: G01J 2005/0077 Imaging
• CPC Class Codes: G01J 5/0025 Living bodies ear thermometers G01J5/0011; detecting, measuring or recording for diagnostic purposes A61B5/00
• CPC Class Codes: G01J 5/0205 Mechanical elements; Supports for optical elements
• CPC Class Codes: G01J 5/0265 Handheld, portable ear thermometers G01J5/049
• CPC Class Codes: G01J 5/041 Mountings in enclosures or in a particular environment
• CPC Class Codes: G01J 5/07 Arrangements for adjusting the solid angle of collected radiation, e.g. adjusting or orienting field of view, tracking position or encoding angular position optical collimating elements G01J5/0806
• CPC Class Codes: G01J 5/12 using thermoelectric elements, e.g. thermocouples
• CPC Class Codes: G01J 5/485 Temperature profile
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing

Abstract

Described herein are embodiments of systems and a method to identify orthostatic hypotension and postural-orthostatic tachycardia syndrome. One system includes a head-mounted device configured to measure photoplethysmographic signal (PPG signal) at a region on a user'"'"'s head, and a head-mounted camera configured to capture images indicative of the user'"'"'s posture. Additionally, the system includes a computer that calculates systolic and diastolic blood pressure values based on the PPG signal, and identifies orthostatic hypotension based on a drop of systolic blood pressure below a first threshold, and/or a drop of diastolic blood pressure below a second threshold, within a predetermined duration from a transition in the posture from supine to sitting posture, or from sitting to standing posture.

Claims

1. A system configured to identify orthostatic hypotension, comprising:

a head-mounted device configured to measure photoplethysmographic signal (PPG signal) at a region on a user'"'"'s head;

a head-mounted camera configured to capture images indicative of the user'"'"'s posture; and

a computer configured to;

calculate systolic and diastolic blood pressure values based on the PPG signal; and

identify orthostatic hypotension based on a drop of systolic blood pressure below a first threshold, and/or a drop of diastolic blood pressure below a second threshold, within a predetermined duration from a transition in the posture from supine to sitting posture, or from sitting to standing posture.

2. The system of claim 1, wherein the computer adjusts calculations of the blood pressure values based on the user'"'"'s posture, such that for the same PPG signal the computer outputs different values for the blood pressure values for the following different postures:

standing, sitting, and lying down.

3. The system of claim 2, wherein the computer is further configured to utilize a model to calculate the blood pressure values;

wherein the model was generated based on samples comprising;

feature values generated from PPG signals of multiple users and images of the multiple users, and labels generated based on corresponding values of blood pressure values of the multiple users; and

wherein a first non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were sitting, and a second non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were standing.

4. The system of claim 2, wherein the computer is further configured to utilize a model to calculate the blood pressure values;

wherein the model was generated based on samples comprising;

feature values generated from PPG signals of multiple users and images of the multiple users, and labels generated based on corresponding values of blood pressure values of the multiple users; and

wherein a first non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were sitting, and a second non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were lying down.

5. The system of claim 2, wherein the head-mounted device is a contact photoplethysmographic device.

6. The system of claim 2, wherein the head-mounted device is a second camera located more than 10 mm away from the region on the user'"'"'s head, and the PPG signal is recognizable from color changes in a region in images taken by the second camera.

7. The system of claim 2, wherein the computer is further configured to generate feature values based on data comprising the PPG signal and the images, and to utilize a model to calculate the blood pressure values based on the feature values;

wherein one or more of the feature values are indicative of the user'"'"'s posture, and the PPG signal is indicative of cardiac pulse wave arrival times at the region on the user'"'"'s head;

wherein the computer is further configured to;

(i) receive a second photoplethysmographic signal (second PPG signal) indicative of pulse wave arrival times at a second region on the user'"'"'s body, which is at least 25 mm away from the region on the user'"'"'s head, and (ii) generate at least one of the feature values based on the second PPG signal; and

wherein the at least one of the feature values are indicative of a difference in cardiac pulse wave arrival times at the region and the second region.

8. The system of claim 7, wherein the second region is located on a wrist of the user, and further comprising a wrist-mounted device configured to measure the second PPG signal.

9. The system of claim 2, wherein the computer is further configured to generate feature values based on data comprising the PPG signal and the images, and to utilize a model to calculate the blood pressure values based on the feature values;

wherein one or more of the feature values are indicative of the user'"'"'s posture, and the PPG signal is indicative of cardiac pulse wave arrival times at the region on the user'"'"'s head;

wherein the computer is further configured to;

(i) receive a signal indicative of the user'"'"'s heart'"'"'s electrical activity (EA signal), and (ii) generate at least one of the feature values based on the signal indicative of the user'"'"'s heart'"'"'s electrical activity;

wherein the EA signal is indicative of times at which one or more of the following cardiac activity phases occur;

atrial systole, ventricular systole, and ventricular repolarization; and

wherein the at least one of the feature values are indicative of a difference in time between when a certain cardiac activity phase of the user and when a corresponding pulse wave arrives at the region on the user'"'"'s head.

10. The system of claim 1, wherein the computer is further configured to generate feature values based on data comprising the PPG signal and the images, and to utilize a model to calculate the blood pressure values based on the feature values;

and wherein a feature value, from among the feature values, which is based on the images, is indicative of the vertical distance between the head-mounted device and the user'"'"'s heart.

11. The system of claim 1, wherein the computer is further configured to generate feature values based on data comprising the PPG signal and the images, and to utilize a model to calculate the blood pressure values based on the feature values;

and wherein a feature value, from among the feature values, which is based on the images, is indicative of the vertical distance between the head-mounted device and the brachial artery of the user.

12. The system of claim 1, wherein the computer is further configured to generate feature values based on data comprising the PPG signal and the images, and to utilize a model to calculate the blood pressure values based on the feature values;

and wherein a feature value, from among of the feature values, is generated based on the images and is indicative of whether the user'"'"'s legs are crossed.

13. A system configured to identify Postural-Orthostatic Tachycardia Syndrome, comprising:

a head-mounted device configured to measure photoplethysmographic signal (PPG signal) at a region on a user'"'"'s head;

a head-mounted camera configured to capture images indicative of the user'"'"'s posture; and

a computer configured to detect tachycardia based on the PPG signal, and to identify Postural-Orthostatic Tachycardia Syndrome based on detecting occurrence of the tachycardia within a predetermined duration from a transition in the posture from supine or sitting posture to standing posture.

14. The system of claim 13, wherein the head-mounted device is a contact photoplethysmographic device.

15. A method for identifying orthostatic hypotension, comprising:

measuring, by a head-mounted device, a photoplethysmographic signal (PPG signal) at a region on a user'"'"'s head;

capturing, by a head-mounted camera, images indicative of the user'"'"'s posture;

calculating systolic and diastolic blood pressure values based on the PPG signal; and

identifying orthostatic hypotension based on a drop of systolic blood pressure below a first threshold, and/or a drop of diastolic blood pressure below a second threshold, within a predetermined duration from a transition in the posture from supine to sitting posture, or from sitting to standing posture.

16. The method of claim 15, further comprising generating feature values based on data comprising the PPG signal and the images, and utilizing a model to calculate the blood pressure values based on the feature values;

wherein the model was generated based on samples comprising;

feature values generated from PPG signals of multiple users and images of the multiple users, and labels generated based on corresponding values of blood pressure values of the multiple users; and

wherein a first non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were sitting, and a second non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were lying down.

17. The method of claim 15, further comprising a 4-non-transitory computer-readable medium having instructions stored thereon that, in response to execution by a system including a processor and memory, causes the system to perform operations described in the method of claim 15.

18. The method of claim 15, further comprising generating feature values based on data comprising the PPG signal and the images, and utilizing a model to calculate the blood pressure values based on the feature values;

wherein the model was generated based on samples comprising;

feature values generated from PPG signals of multiple users and images of the multiple users, and labels generated based on corresponding values of blood pressure values of the multiple users; and

wherein a first non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were sitting, and a second non-empty subset of the samples were generated based on PPG signals and images taken while at least some of the multiple users were standing.

19. The method of claim 15, further comprising generate feature values based on data comprising the PPG signal and the images, and utilizing a model to calculate the blood pressure values based on the feature values;

wherein one or more of the feature values are indicative of the user'"'"'s posture, and the PPG signal is indicative of cardiac pulse wave arrival times at the region on the user'"'"'s head; and

further comprising;

(i) receiving a second photoplethysmographic signal (second PPG signal) indicative of pulse wave arrival times at a second region on the user'"'"'s body, which is at least 25 mm away from the region on the user'"'"'s head, and (ii) generating at least one of the feature values based on the second PPG signal; and

wherein the at least one of the feature values are indicative of a difference in cardiac pulse wave arrival times at the region and the second region.

20. The method of claim 15, further comprising generating feature values based on data comprising the PPG signal and the images, and utilizing a model to calculate the blood pressure values based on the feature values;

wherein one or more of the feature values are indicative of the user'"'"'s posture, and the PPG signal is indicative of cardiac pulse wave arrival times at the region on the user'"'"'s head; and

further comprising;

(i) receiving a signal indicative of the user'"'"'s heart'"'"'s electrical activity (EA signal), and (ii) generating at least one of the feature values based on the signal indicative of the user'"'"'s heart'"'"'s electrical activity;

wherein the EA signal is indicative of times at which one or more of the following cardiac activity phases occur;

atrial systole, ventricular systole, and ventricular repolarization; and

wherein the at least one of the feature values are indicative of a difference in time between when a certain cardiac activity phase of the user and when a corresponding pulse wave arrives at the region on the user'"'"'s head.