APPARATUS FOR AND METHOD OF MEASURING BLOOD PRESSURE

• US 20160256116A1
• Filed: 12/07/2015
• Published: 09/08/2016
• Est. Priority Date: 03/06/2015
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: RIABKO, Maxim Vladimirovich, BAIK, Chanwook, KYOUNG, Jisoo, YOON, Youngzoon, LANTSOV, Alexey Dmitrievich, ROH, Younggeun, LEE, Jaesoong
• Granted Patent: US 10,405,806 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 2562/0233 Special features of optical sensors or probes classified in A61B5/00
• 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 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• 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

An apparatus for and a method of measuring blood pressure are provided. The apparatus includes a sensor configured to radiate light to a body part, and detect a light signal that is changed due to the body part. The apparatus further includes a signal processor configured to determine a bio signal based on the light signal; and a central processing unit configured to determine a blood pressure based on the bio signal and a blood pressure estimation algorithm.

Claims

1. An apparatus configured to measure blood pressure, the apparatus comprising:

a sensor configured to radiate light to a body part, and detect a light signal that is changed due to the body part;

a signal processor configured to determine a bio signal based on the light signal; and

a central processing unit configured to determine a blood pressure based on the bio signal and a blood pressure estimation algorithm.

2. The apparatus of claim 1, wherein the signal processor is further configured to:

extract a cycle of the light signal; and

sample data from the cycle of the light signal at equidistant time intervals or based on a user input.

3. The apparatus of claim 1, wherein the signal processor is further configured to:

compare power spectrums within a frequency range of bio signals that are determined based on channels; and

select a channel having a maximum power spectrum from the channels.

4. The apparatus of claim 3, wherein, the signal processor is further configured to, in response to the signal processor selecting the channel having the maximum power spectrum or using a single channel, select a part of a bio signal that corresponds to the selected channel or the single channel, in which a power spectrum value within the frequency range is greater than a value, as a valid part of the bio signal.

5. The apparatus of claim 1, further comprising a display configured to display the blood pressure.

6. The apparatus of claim 1, further comprising a memory configured to store the blood pressure estimation algorithm and information of the bio signal.

7. The apparatus of claim 1, wherein the sensor comprises a light emitter configured to radiate the light to the body part, and a light receiver configured to detect the light signal that is changed due to the body part,

the light receiver comprises a photodiode or an image sensor, and

the light emitter comprises a laser diode or a light emitting diode.

8. The apparatus of claim 1, wherein the sensor comprises a light emitter configured to radiate the light to the body part, and a light receiver configured to detect the light signal that is changed due to the body part,

the light emitter comprises a laser diode, and

the central processing unit is further configured to determine the blood pressure based on the bio signal in response to the sensor being spaced apart from a skin of an examinee.

9. The apparatus of claim 1, wherein the bio signal is periodically obtained at predetermined time intervals.

10. The apparatus of claim 1, wherein the central processing unit is further configured to determine the blood pressure based on the bio signal and one among a linear regression analysis algorithm, a multiple regression analysis algorithm, and a non-linear regression analysis algorithm.

11. The apparatus of claim 1, wherein the central processing unit is further configured to determine the blood pressure based on the bio signal and one among an artificial neural network algorithm, a k-nearest neighbor algorithm, a Bayesian network algorithm, a support vector machine algorithm, and a recurrent neural network algorithm.

12. The apparatus of claim 1, wherein the central processing unit is further configured to correct the blood pressure based on a blood pressure that is determined by another device.

13. The apparatus of claim 1, further comprising a body information interface configured to receive body information of at least one among an age, a gender, a weight, and a height of an examinee,

wherein the central processing unit is further configured to determine the blood pressure based on the bio signal and the body information.

14. The apparatus of claim 1, wherein the apparatus is portable, and is implemented in one among a wrist watch, a mobile smart phone, a tablet computer, an earphone, a headset, and glasses.

15. The apparatus of claim 1, wherein the apparatus is implemented in a wrist watch, and

the sensor is positioned on a back of a main body or a strap of the wrist watch.

16. A method of measuring blood pressure, the method comprising:

radiating light to a body part;

detecting a light signal that is changed due to the body part;

determining a bio signal based on the light signal;

correcting the bio signal;

extracting feature points from the corrected bio signal; and

combining a matrix of a blood pressure estimation algorithm with the feature points to determine a blood pressure.

17. The method of claim 16, wherein the extracting comprises:

determining a maximum point of the corrected bio signal and a minimum point adjacent to the maximum point; and

extracting the feature points from the corrected bio signal at equidistant time intervals or based on a user input.

18. The method of claim 16, wherein the matrix of the blood pressure estimation algorithm is determined by learning the blood pressure estimation algorithm such that the blood pressure that is determined by inputting the feature points in the blood pressure estimation algorithm is closer to an actual blood pressure.

19. The method of claim 16, wherein the blood pressure estimation algorithm is one among an artificial neural network algorithm, a k-nearest neighbor algorithm, a Bayesian network algorithm, a support vector machine algorithm, and a recurrent neural network algorithm.

20. The method of claim 16, wherein the correcting comprises:

correcting a baseline of a sequence of the bio signal; and

removing high frequency noise from the corrected sequence.