AU2021107074B4 - Remote detection for blood pressure with radar sensor - Google Patents
Remote detection for blood pressure with radar sensor Download PDFInfo
- Publication number
- AU2021107074B4 AU2021107074B4 AU2021107074A AU2021107074A AU2021107074B4 AU 2021107074 B4 AU2021107074 B4 AU 2021107074B4 AU 2021107074 A AU2021107074 A AU 2021107074A AU 2021107074 A AU2021107074 A AU 2021107074A AU 2021107074 B4 AU2021107074 B4 AU 2021107074B4
- Authority
- AU
- Australia
- Prior art keywords
- blood pressure
- radar sensor
- lstm
- person
- remote detection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S13/583—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of continuous unmodulated waves, amplitude-, frequency-, or phase-modulated waves and based upon the Doppler effect resulting from movement of targets
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/35—Details of non-pulse systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/415—Identification of targets based on measurements of movement associated with the target
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Pathology (AREA)
- Cardiology (AREA)
- General Physics & Mathematics (AREA)
- Veterinary Medicine (AREA)
- Computer Networks & Wireless Communication (AREA)
- Biophysics (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Electromagnetism (AREA)
- Radiology & Medical Imaging (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Vascular Medicine (AREA)
- Physiology (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
A remote detection device for blood pressure with SIL-radar sensor. The radar sensor collects
continuous signals for a person who stably faces the sensor within a one-meter distance. The
collected signal is decomposed into non-overlapping patches for long short-term memory
(LSTM) processing. A deep neural network is designed, incorporated with LSTM, to detect the
range of blood pressure.
Description
Remote detection for blood pressure with radar sensor
Field of the Invention
[0001] This invention relates to non-contact detection of blood pressure, in operable communication with radar sensors.
Background of the Invention
[0002] Blood pressure could reflect many health conditions, thus the ability to measure blood pressure is quite important for daily health monitoring, particularly in aged caring communities. A common approach for blood pressure is to pose a constriction for a limb, which is a precise approach to measure blood pressure in a hospital or home. However, this approach cannot be used for continuous monitoring, which impedes its development on daily health monitoring. Therefore, a new approach that remotely and continuously detects blood pressure is now desirable.
[0003] In the current market, there exist some methods that use radar sensors to achieve the continuous detection of blood pressure. However, these methods require that the radar sensor is attached to the skin of the person so that the micro-change of skin can be captured that is caused by the person's respiration and heartbeat. A major limitation of these methods is that some people, especially senior people, do not welcome the wearable device because of uncomfortable feelings and mental stress.
[0004] To address this issue, this invention will take advantage of self-injection-locked radar (SIL-radar) that has the ability to remotely capture the micro-change of skin, for the detection of blood pressure.
Summary of the Disclosure
[0005] The blood pressure detection system comprises a radar sensor and a detector.
[0006] The radar sensor collects continuous signals for the person who stably faces the radar sensor within a 1-meter distance.
[0007] The collected continuous signal is decomposed into non-overlapping patches for LSTM processing.
[0008] A deep neural network-based detector, incorporated with LSTM, is designed to detect the range ofbloodpressure.
Brief Description of the Drawings
[0009] Figure 1 shows an exemplary radar-based blood pressure detection system in accordance with an embodiment.
[0010] Figure 2 shows exemplary data processing in the system of Figure 1 in accordance with an embodiment.
Description of Embodiments
[0011] Figure 1 shows device 101 for a home environment, living room or the like.
[0012] Device 101 comprises a radar sensor 104 and detector 105. The data 103 is operable in system memory 102 for interpretation and execution of the computational functionality.
[0013] In the embodiment shown, person 106 is facing device 101.
[0014] The detector can be configured to detect the blood pressure range of person 106.
[0015] To measure a person's blood pressure during a time period T (such as 30 seconds), the radar sensor firstly collects continuous radar signal 107 for the time period T, denoted as RS(T). Then, RS(T) is decomposed into N non-overlapping patches 108 according to the time series, denoted as RS(T) = [rs(ti), rs(t 2 ), ... , rs(tn)] T .
[0016] A deep neural network-based detector 105 is invented to detect the corresponding blood pressure range 109 from RS(T). The detector is composed of several convolutional layers and an LSTM layer. The detailed structure of the detector is shown in the table below.
LayerIndex Filter Size Filter Stride Pad Filter Channel 1 3x3 1 1 128 2 (batch normalization) - -
3 (ReLU) - -
4 3x3 1 1 128 5 (batch normalization) - -
6 (ReLU) - - -
7 3x3 2 1 256 8 (batch normalization) - - -
9 (ReLU) - -
10 3x3 1 1 256 11 (batch normalization) - -
12(ReLU) - -
13 3x3 1 1 512 14 (batch normalization) - -
15 (ReLU) - - -
16 3x3 2 1 512 17 (batch normalization) - - -
18 (ReLU) - - -
19 (LSTM) - - - 1024
20 (fully connected) - - - 1024
21 (fully connected) - - - 2
[0017] The output of the deep neural network-based detector 105 is denoted as Q E R2 ,
where Q(1) is the floor of the blood pressure, and Q(2) is the ceiling of the blood pressure.
[0018] The loss function defined in the equation below is adopted to train the detector:
[0019] [Equation 1] L = (IQ (1) - G(1)| + IQ(2) - G (2)|)/2
[0020] where G(1) and G(2) are the floor and ceiling of real blood pressure, respectively.
[0021] The parameters, including N and T, is empirically set according to a different lively environment.
[0022] The foregoing description, for purposes of explanation, used specific nomenclature to provide a thorough understanding of the invention. However, it will be apparent to one skilled in the art that specific details are not required in order to practice the invention. Thus, the foregoing descriptions of specific embodiments of the invention are presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed as obviously many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the invention and its practical applications, thereby enabling others skilled in the art to best utilize the invention and various embodiments with various modifications as are suited to the particular use contemplated. It is intended that the following claims and their equivalents define the scope of the invention.
[0023] The term "approximately" or similar as used herein should be construed as being within 10% of the value stated unless otherwise indicated.
Claims (1)
1. A non-contact blood pressure detection system comprising a SIL-radar sensor configured to collect continuous signals for a person who faces the radar sensor within a 1-meter distance, and a deep neural network-based detector incorporated with LSTM and configured to process the collected continuous signals and to detect the blood pressure range of the person.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2021107074A AU2021107074B4 (en) | 2021-08-25 | 2021-08-25 | Remote detection for blood pressure with radar sensor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2021107074A AU2021107074B4 (en) | 2021-08-25 | 2021-08-25 | Remote detection for blood pressure with radar sensor |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| AU2021107074A4 AU2021107074A4 (en) | 2021-12-02 |
| AU2021107074B4 true AU2021107074B4 (en) | 2022-06-16 |
Family
ID=78716654
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| AU2021107074A Active AU2021107074B4 (en) | 2021-08-25 | 2021-08-25 | Remote detection for blood pressure with radar sensor |
Country Status (1)
| Country | Link |
|---|---|
| AU (1) | AU2021107074B4 (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014022584A1 (en) * | 2012-08-01 | 2014-02-06 | Niema Pahlevan | Cardiac microwave signal determination of cardiovascular diseases |
| US20160100766A1 (en) * | 2014-10-09 | 2016-04-14 | Panasonic Intellectual Property Management Co., Ltd. | Non-contact blood-pressure measuring device and non-contact blood-pressure measuring method |
| CN111887824A (en) * | 2020-07-30 | 2020-11-06 | 杭州电子科技大学 | Arteriosclerosis detection device based on millimeter waves and neural network |
| US20210045640A1 (en) * | 2019-08-16 | 2021-02-18 | Poltorak Technologies, LLC | Device and method for medical diagnostics |
-
2021
- 2021-08-25 AU AU2021107074A patent/AU2021107074B4/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014022584A1 (en) * | 2012-08-01 | 2014-02-06 | Niema Pahlevan | Cardiac microwave signal determination of cardiovascular diseases |
| US20160100766A1 (en) * | 2014-10-09 | 2016-04-14 | Panasonic Intellectual Property Management Co., Ltd. | Non-contact blood-pressure measuring device and non-contact blood-pressure measuring method |
| US20210045640A1 (en) * | 2019-08-16 | 2021-02-18 | Poltorak Technologies, LLC | Device and method for medical diagnostics |
| CN111887824A (en) * | 2020-07-30 | 2020-11-06 | 杭州电子科技大学 | Arteriosclerosis detection device based on millimeter waves and neural network |
Also Published As
| Publication number | Publication date |
|---|---|
| AU2021107074A4 (en) | 2021-12-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108606798B (en) | Non-contact atrial fibrillation intelligent detection system based on deep convolution residual error network | |
| Rosales et al. | Heart rate monitoring using hydraulic bed sensor ballistocardiogram 1 | |
| EP3329845A1 (en) | Biological condition determination device and biological condition determination method | |
| JP2011513037A (en) | Health monitoring and management system | |
| Tamura | Home geriatric physiological measurements | |
| CN110115574A (en) | The method and apparatus of rhythm of the heart | |
| US10813593B2 (en) | Using visual context to timely trigger measuring physiological parameters | |
| WO2016168979A1 (en) | Vital sign analysis method and system | |
| US20230105909A1 (en) | Method and System For Generating An ECG Signal | |
| WO2016190348A1 (en) | Monitoring device | |
| Jones et al. | Reliable respiratory rate estimation from a bed pressure array | |
| KR20120036638A (en) | Healthcare system integrated muti kinds sensor | |
| Phillips et al. | Radar walk detection in the apartments of elderly | |
| Pino et al. | Non-invasive BCG monitoring for non-traditional settings | |
| KR20060084916A (en) | Telehealthcare system and service using an intelligent mobile robot | |
| Liu et al. | Patient walk detection in hospital room using Microsoft Kinect V2 | |
| KR20150114057A (en) | System and method for monitoring sleeping condition | |
| AU2021107074B4 (en) | Remote detection for blood pressure with radar sensor | |
| CN104814732B (en) | A kind of ECG monitor | |
| Liu et al. | A novel body posture recognition system on bed | |
| KR20190103626A (en) | A portable ECG electrode and an ECG measurement system for small animals | |
| Li et al. | Health activities monitoring and warning system for geriatric daily living in extra care homes | |
| Mathivanan et al. | IoT based continuous monitoring of cardiac patients using Raspberry Pi | |
| T'Jonck et al. | Accelerometer based activity tracking to support elderly care in nursing homes | |
| CN109106371A (en) | A kind of device and method monitoring physiological parameter |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| FGI | Letters patent sealed or granted (innovation patent) | ||
| FF | Certified innovation patent |