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WO2022006634A1 - Système de mesure de tension artérielle - Google Patents

Système de mesure de tension artérielle Download PDF

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Publication number
WO2022006634A1
WO2022006634A1 PCT/AU2021/050730 AU2021050730W WO2022006634A1 WO 2022006634 A1 WO2022006634 A1 WO 2022006634A1 AU 2021050730 W AU2021050730 W AU 2021050730W WO 2022006634 A1 WO2022006634 A1 WO 2022006634A1
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WO
WIPO (PCT)
Prior art keywords
light
blood pressure
pulse
sensors
artery
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.)
Ceased
Application number
PCT/AU2021/050730
Other languages
English (en)
Inventor
Simon Charles Fleming
Alessio STEFANI
Suaning GREGG
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
University of Sydney
Original Assignee
University of Sydney
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Priority claimed from AU2020902358A external-priority patent/AU2020902358A0/en
Application filed by University of Sydney filed Critical University of Sydney
Publication of WO2022006634A1 publication Critical patent/WO2022006634A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • A61B5/02125—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics of pulse wave propagation time
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02—Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0233—Special features of optical sensors or probes classified in A61B5/00
    • A61B2562/0238—Optical sensor arrangements for performing transmission measurements on body tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/22—Arrangements of medical sensors with cables or leads; Connectors or couplings specifically adapted for medical sensors
    • A61B2562/221—Arrangements of sensors with cables or leads, e.g. cable harnesses
    • A61B2562/223—Optical cables therefor
    • 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A61B5/02141—Details of apparatus construction, e.g. pump units or housings therefor, cuff pressurising systems, arrangements of fluid conduits or circuits
    • 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 for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/026—Measuring blood flow
    • A61B5/0261—Measuring blood flow using optical means, e.g. infrared light
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/681—Wristwatch-type devices
    • 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
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • 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
    • A61B5/7235—Details of waveform analysis
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms

Definitions

  • the present invention relates generally to a system and method for measuring blood pressure and, in particular, to a system and method for non-invasively measuring blood pressure.
  • the present invention also relates to a method and apparatus for measuring blood pressure.
  • Cardiovascular disease is a significant cause of illness and death.
  • Blood pressure is an important indicator of cardiac function and health. Measurement of blood pressure can be used to identify if a patient is likely to have health issues or to develop future health issues.
  • sphygmomanometer a system known as a sphygmomanometer.
  • a patient’s upper arm is fastened into a bladder or cuff of the sphygmomanometer.
  • the bladder or cuff is inflated to cut off blood flow through an artery of the upper arm.
  • An air valve is used to slowly release air pressure exerted by the cuff and allow blood flow through the artery to recommence.
  • Pressure of the blood flow through the artery as the bladder is deflated creates a detectable vibration which is used to determine blood pressure.
  • the blood pressure is measured between systolic and diastolic pressures.
  • Continuous monitoring of blood pressure can reduce risk for patients at risk of cardiovascular disease.
  • Use of a traditional blood pressure cuff is a relatively disruptive and/or invasive procedure unsuitable for continuous measurement of blood pressure.
  • a patient is required to have the cuff applied and inflated in order to take a measurement.
  • Traditional cuff measurement systems are used to take an occasional “snapshot”, for example at every half hour, which can result in cardiovascular events occurring without being measured or even detected. The requirement to take regular snapshots can be intrusive to the patient, particularly overnight. Further, some patients find traditional cuff systems to be uncomfortable and stressful, resulting in increased blood pressure, being an inaccurate representation of cardiac performance and health.
  • Measurement of blood pressure continuously, or at least close to real-time, across a time period or as a patient performs exercise or other tasks would allow an accurate insight into cardiac operation and health of the patient to be determined. Measuring blood pressure regularly and based on activities would likely allow potential health issues to be more readily identified.
  • One aspect of the present invention provides a system configured for measuring blood pressure of a human subject, the system comprising: at least one light source; a pair of light guides, each configured to receive light from the at least one source and for placement over an artery of the subject, wherein a material from which the light guides are formed allows a path of light through the light guide to vary based on pulse flow through the artery; and a pair of light sensors, each of the light sensors configured to receive light from a corresponding one of the light guides and to generate a signal that varies correspondingly with the path of the light for determining pulse wave velocity between the light guides to measure blood pressure.
  • Another aspect of the present invention provides a method of measuring blood pressure of a subject, the method comprising: transmitting light from at least one light source into a pair of light guides, each of the light guides placed over an artery of the subject, wherein a material from which the light guides are formed allows a path of light through the light guide to vary based on pulse flow through the artery, receiving at each of a pair of light sensors, light received through a corresponding one of the pair of light guides, each of the light sensors configured to generate a signal that varies with alteration in the path of the light; determining, at a processing device, pulse wave velocity between the light guides using the generated signal for each of the light sensors; and determining blood pressure of the subject using the pulse wave velocity.
  • Another aspect of the present disclosure provides a non-transitory computer-readable medium having a computer program stored thereon to implement a method of measuring blood pressure of a subject, the method comprising: receiving measurements of each of a pair of electrical signals, each of the electrical signals generated by one of a pair of light sensors and varying according to light received through a corresponding one of a pair of optical fibres placed across an artery of the subject, the optical fibres formed of a material that allows a path of light through the light guide to vary based on pulse flow through the artery, each of the light sensors configured to generate a signal that varies with alteration in the path of the light as a pulse; determining a pulse wave velocity of the subject based on a transit time of a pulse between the pair of optical fibres; and determining a blood pressure of the subject using the determined pulse wave velocity.
  • FIG. 1 shows a testbench system for measuring blood pressure
  • FIG. 2 shows a system for measuring blood pressure as used on a human subject
  • FIG. 3A and 3B collectively form a schematic block diagram representation of an electronic device upon which described arrangements can be practised;
  • Fig. 4 shows a method for measuring systolic or diastolic blood pressure
  • Fig. 5 shows a method of generating a set of pulse signals as used in the method of Fig.
  • Fig. 6 shows a method of removing noise from a set of measured signals as used in the method of Fig. 5;
  • Figs. 7 A and 7B show measurements determined using the method of Fig. 4 and the system of Fig. 1
  • FIG. 8 shows a circuit for a system of measuring blood pressure
  • Fig. 9A shows a graph for blood pressure measurements determined using the system of Fig. 2 and the method of Fig. 4;
  • Fig. 9B shows an excerpt from the graph for blood pressure measurements of Fig. 9A;
  • Fig. 10 shows a method for measuring systolic and diastolic blood pressure
  • FIG. 11 shows another graph for blood pressure measurements determined using the system of Fig. 2 and the method of Fig. 4;
  • FIGs. 12A to 12D show an example implementation of a casing for a wearable system for measuring blood pressure
  • Appendix A shows example MatlabTM code used in relation to the system of Fig. 2.
  • the arrangements described herein relate to a blood pressure measuring system that can be implemented in a non-invasive manner, for example as a wearable device.
  • the arrangements described can be used to measure blood pressure in a manner near to real-time or relatively continuously compared to traditional sphygmomanometer based on inflation of a cuff or bladder.
  • the arrangements described relate to transmitting light through a pair of light guides placed on skin over an artery of a human subject. Pulses due to blood flow in the artery cause mechanical vibrations or perturbations which alter the path of the light through the light guides.
  • a sensor detects resultant changes or fluctuations in light intensity for each light guide. The fluctuations are used to calculate pulse wave velocity and accordingly blood pressure in the artery.
  • optical fibres have been made of materials such as glass, polymethyl methacrylate (PMMA) or other relatively hard materials.
  • the Young’s modulus of traditional optical fibres can be in the region of 1GPa to 72GPa.
  • Recent developments in optical fibre technology have allowed optical fibres to be manufactured of relatively soft materials such as polyurethane or other materials that can act as a suitable light guide with a Young’s modulus some orders of magnitude lower than glass or PMMA.
  • Some implementations of the relatively soft optical fibres have shown sensitivity to mechanical perturbations such as pressure, showing relatively large changes in transmitted optical power (or optical intensity) for relatively small changes in pressure.
  • Sensitivity of optical fibres manufactured from polyurethane to pressure has been described in M. R. Kaysir, A. Stefani, R. Lwin and S. Fleming, "Measurement of weak low frequency pressure signal using stretchable polyurethane fiber sensor for application in wearables," 20173rd International Conference on Electrical Information and Communication Technology (EICT), Khulna, 2017, pp. 1-5, doi: 10.1109/EICT.2017.8275189.
  • the arrangements described herein relate to using the relatively soft optical fibres to measure blood pressure by measuring changes in pressure due to pulse as blood flows through an artery.
  • Optical fibres that can act as light guides and having a Young’s modulus of a similar magnitude to skin and human tissues (for example toward a range of 420KPa and 850KPa) have become available.
  • the examples below relate to using optical fibres with a Young’s modulus in the region of 15MPa, for example, between 1 MPa and 50 MPa.
  • a suitable light guide can allow light to travel through the undistorted guide by reflectance, yet be sensitive to perturbations or changes in pressure due to pulse.
  • the softness of the waveguide used in the arrangements described can vary depending on the material from which the light guide is formed and sensitivity of the material to mechanical vibrations or perturbations, and the structure of the light guide.
  • the light guide is an optical fibre manufactured from polyurethane and having a Young’s modulus of approximately 15 MPa.
  • the light guide can relate to any conduit through which light can be transmitted and which is sensitive to mechanical perturbations of the order of a pulse through human skin in an area such as an inner wrist, for example a hollow-core optical fibre.
  • Fig. 1 shows an example of a system 100 for measuring blood pressure.
  • the system 100 comprises a light source 110, a pair of optical fibres 120a and 120b and a pair of light sensors 150a and 150b.
  • the light source 110 comprises a pair of light sources 110a and 110b.
  • the light source 110 can comprise a single light source, light from which is split into two channels.
  • the example system 100 also includes a processing device 160 in communication with the light sensors 150a and 150b.
  • the light sensors 150a and 150b may be integral components of the processing device 160 or the processing device may be a component of one or both of the light sensors 150a and 150b.
  • the light sources 110a and 110b can each be any light source suitable for transmitting light through an optical fibre such as a laser diode.
  • the light source 110 can be a similar device to 110a and 110b.
  • the light source 110 is optically coupled to the light guides 120a and 120b so that light shines through each of the light guides.
  • the light guides 120a and 120b are suitable for transmitting light while being suitably soft to be sensitive to changes in pressure due to pulse.
  • the light guides 120a and 120b are optical fibres, and hereafter referred to as optical fibres.
  • the fibres 120a and 120b are relatively soft and flexible, typically manufactured of polyurethane and having a Young’s modulus in the region of 15MPa.
  • the light guides 120a and 120b are capillary fibres or hollow-core fibres.
  • the optical fibres 120a and 120b have a diameter of 1.5mm and a wall thickness in a range of 0.2mm to 0.25mm.
  • the light sensors 150a and 150b are configured to sense light travelling through a corresponding one of the optical fibres 120a and 120b from one of the light sources 110a and 110b.
  • the sensors 150a and 150b sense variations in intensity of the light received through the corresponding fibre.
  • the sensors 150a and 150b can include photodiodes or other types of devices capable of generating an output that varies with light received. The variations in light can be stored and/or processed by the processing device 160.
  • the system 100 relates to a testbench implementation for modelling measurement of blood pressure.
  • the system 100 is used in manner so that the optical fibres 120a and 120b are placed over an artery 130 in which a liquid representing blood travels in a pulsating manner in a direction 140.
  • the optical fibres 120a and 120b are a known distance D1 apart.
  • Fig. 2 shows a system 200 for measuring blood pressure of a human subject.
  • the system 200 is similar in structure to the system 100.
  • the system 200 comprises at least a pair of light sources shown as 210a and 210b, a pair of light guides 220a and 220b and a pair of light sensors 250a and 250b.
  • Each of the light sensors 250a and 250b is illuminated by light travelling through a corresponding one of the waveguides 220a and 220b.
  • the example system 200 also includes a processing device 260 in communication with the light sensors 250a and 250b.
  • the light sensors 250a and 250b may be integral components of the processing device 260 or the processing device may be a component of one or both of the light sensors 250a and 250b.
  • the system 200 operates in a similar manner to the system 100.
  • the light sources 210a and 210b are similar to the light sources 110a and 110b.
  • the light guides 220a and 220b are typically optical fibres similar to 120a and 120b and are hereafter referred to as optical fibres.
  • the light sensors 250a and 250b are similar to the light sensors 150a and 150b.
  • the system 200 is configured for measurement of blood pressure of a human subject.
  • the optical fibres 220a and 220b are for placement against an area of skin over an artery 230 in order to measure blood pressure.
  • the optical fibres 220a and 220b are a distance D2 apart in a direction of blood flow through the artery.
  • the area of skin can relate for example to skin in a region of the subject’s inner wrist covering a radial artery so that the optical fibres 220a and 220b cross an artery 230 sequentially along a direction of blood flow 240.
  • Other areas of the body where skin is suitably close to an artery can also be used, for example areas of an ankle, upper arm, or neck.
  • the optical fibres 220a and 220b can be placed in any two locations where a distance travelled by the blood flowing in the artery between the optical fibres is known.
  • Figs. 3A and 3B collectively form a schematic block diagram of a general purpose electronic device 301 including embedded components, upon which the blood pressure measuring methods to be described are desirably practiced.
  • the electronic device 301 may be, for example, a wearable device in which processing resources are limited.
  • the system 200 can be fully integrated to the electronic device 301 or may be implemented in part on a wearable device and in part on an electronic device such as a smartphone, a tablet or the like.
  • a wearable device may be a single device worn on one part of the body or comprise two or more modules, each module including a light guide and a light sensor (for example 220a and 250a) for receiving light via a source and for placement on a certain part of the body.
  • the methods to be described may also be performed in part on a wearable device and in part on higher-level devices such as desktop computers, server computers, and other such devices with significantly larger processing resources.
  • the system 100 can be implemented in a similar manner to the system 200 in relation to the module 301.
  • the electronic device 301 comprises an embedded controller 302. Accordingly, the electronic device 301 may be referred to as an “embedded device.”
  • the controller 302 has a processing unit (or processor) 305 which is bi directionally coupled to an internal storage module 309.
  • the storage module 309 may be formed from non-volatile semiconductor read only memory (ROM) 360 and semiconductor random access memory (RAM) 370, as seen in Fig. 3B.
  • the RAM 370 may be volatile, non volatile or a combination of volatile and non-volatile memory.
  • the electronic device 301 includes a display controller 307, which is connected to a video display 314, such as a liquid crystal display (LCD) panel or the like.
  • the display controller 307 is configured for displaying graphical images on the video display 314 in accordance with instructions received from the embedded controller 302, to which the display controller 307 is connected.
  • the electronic device 301 also includes user input devices 313 which are typically formed by keys, a keypad or like controls.
  • the user input devices 313 may include a touch sensitive panel physically associated with the display 314 to collectively form a touch-screen.
  • Such a touch-screen may thus operate as one form of graphical user interface (GUI) as opposed to a prompt or menu driven GUI typically used with keypad-display combinations.
  • GUI graphical user interface
  • Other forms of user input devices may also be used, depending on whether the module 300 is integrated into a wearable device or not such as a microphone (not illustrated) for voice commands or a joystick/thumb wheel (not illustrated) for ease of navigation about menus.
  • the electronic device 301 also comprises a portable memory interface 306, which is coupled to the processor 305 via a connection 319.
  • the portable memory interface 306 allows a complementary portable memory device 325 to be coupled to the electronic device 301 to act as a source or destination of data or to supplement the internal storage module 309. Examples of such interfaces permit coupling with portable memory devices such as Universal Serial Bus (USB) memory devices, Secure Digital (SD) cards, Personal Computer Memory Card International Association (PCM I A) cards, optical disks and magnetic disks and the like, depending on implementations.
  • USB Universal Serial Bus
  • SD Secure Digital
  • PCM I A Personal Computer Memory Card International Association
  • the electronic device 301 also has a communications interface 308 to permit coupling of the device 301 to a computer or communications network 320 via a connection 321.
  • the connection 321 may be wired or wireless.
  • the connection 321 may be radio frequency or optical.
  • An example of a wired connection includes Ethernet.
  • an example of wireless connection includes BluetoothTM type local interconnection, Wi-Fi (including protocols based on the standards of the IEEE 802.11 family), Infrared Data Association (IrDa) and the like.
  • the electronic device 301 is configured to perform some special function.
  • the embedded controller 302 possibly in conjunction with further special function components 310, is provided to perform that special function.
  • the components 310 may include at least the light sources 210a and 210b, the optical fibres 220a and 220b and the light sensors 250a and 250b.
  • the other components of the device 301 relate to the processing device 260.
  • the special function components 310 is connected to the embedded controller 302.
  • some functions for measuring blood pressure can be implemented in a wearable device and some on another device, such as a smartphone or a server computer.
  • the smartphone or server computer can perform at least some of the functions of the device 260.
  • the device 301 may represent those components required for short range communications with a device such as a cellular telephone or a tablet device or for long range telecommunications such as in a cellular environment.
  • the special function components 310 may also include a number of encoders and decoders of a type including Joint Photographic Experts Group (JPEG), (Moving Picture Experts Group) MPEG, MPEG-1 Audio Layer 3 (MP3), and the like.
  • JPEG Joint Photographic Experts Group
  • MP3 MPEG-1 Audio Layer 3
  • the module 301 may communicate with the sensor arrangements 250a and 250b in a wired or wireless manner.
  • the methods described hereinafter may be implemented using the embedded controller 302, where at least portions of processes of Figs. 4, 5 and 6 may be implemented as one or more software application programs 333 executable within the embedded controller 302.
  • the electronic device 301 of Fig. 3A implements the described methods.
  • the steps of the described methods are effected by instructions in the software 333 that are carried out within the controller 302.
  • the software instructions may be formed as one or more code modules, each for performing one or more particular tasks.
  • the software may also be divided into two separate parts, in which a first part and the corresponding code modules performs the described methods and a second part and the corresponding code modules manage a user interface between the first part and the user.
  • the software 333 of the embedded controller 302 is typically stored in the non-volatile ROM 360 of the internal storage module 309.
  • the software 333 stored in the ROM 360 can be updated when required from a computer readable medium.
  • the software 333 can be loaded into and executed by the processor 305.
  • the processor 305 may execute software instructions that are located in RAM 370.
  • Software instructions may be loaded into the RAM 370 by the processor 305 initiating a copy of one or more code modules from ROM 360 into RAM 370.
  • the software instructions of one or more code modules may be pre installed in a non-volatile region of RAM 370 by a manufacturer. After one or more code modules have been located in RAM 370, the processor 305 may execute software instructions of the one or more code modules.
  • the application program 333 is typically pre-installed and stored in the ROM 360 by a manufacturer, prior to distribution of the electronic device 301.
  • the application programs 333 may be supplied to the user encoded on one or more CD-ROM (not shown) or memory cards and read via the portable memory interface 306 of Fig. 3A prior to storage in the internal storage module 309 or in the portable memory 325.
  • the software application program 333 may be read by the processor 305 from the network 320, or loaded into the controller 302 or the portable storage medium 325 from other computer readable media.
  • Computer readable storage media refers to any non-transitory tangible storage medium that participates in providing instructions and/or data to the controller 302 for execution and/or processing.
  • Examples of such storage media include USB memory, a magneto-optical disk, flash memory, or a computer readable card such as a PCMCIA card and the like, whether or not such devices are internal or external of the device 301.
  • Examples of transitory or non-tangible computer readable transmission media that may also participate in the provision of software, application programs, instructions and/or data to the device 301 include radio or infra-red transmission channels as well as a network connection to another computer or networked device, and the Internet or Intranets including e-mail transmissions and information recorded on Websites and the like.
  • a computer readable medium having such software or computer program recorded on it is a computer program product.
  • the second part of the application programs 333 and the corresponding code modules mentioned above may be executed to implement one or more graphical user interfaces (GUIs) to be rendered or otherwise represented upon the display 314 of Fig. 3A.
  • GUIs graphical user interfaces
  • a user of the device 301 and the application programs 333 may manipulate the interface in a functionally adaptable manner to provide controlling commands and/or input to the applications associated with the GUI(s).
  • Other forms of functionally adaptable user interfaces may also be implemented, such as an audio interface utilizing speech prompts output via loudspeakers (not illustrated) and user voice commands input via the microphone (not illustrated).
  • Fig. 3B illustrates in detail the embedded controller 302 having the processor 305 for executing the application programs 333 and the internal storage 309.
  • the internal storage 309 comprises read only memory (ROM) 360 and random access memory (RAM) 370.
  • the processor 305 is able to execute the application programs 333 stored in one or both of the connected memories 360 and 370.
  • ROM read only memory
  • RAM random access memory
  • the processor 305 is able to execute the application programs 333 stored in one or both of the connected memories 360 and 370.
  • the application program 333 permanently stored in the ROM 360 is sometimes referred to as “firmware”.
  • Execution of the firmware by the processor 305 may fulfil various functions, including processor management, memory management, device management, storage management and user interface.
  • the processor 305 typically includes a number of functional modules including a control unit (CU) 351, an arithmetic logic unit (ALU) 352, a digital signal processor (DSP) 353 and a local or internal memory comprising a set of registers 354 which typically contain atomic data elements 356, 357, along with internal buffer or cache memory 355.
  • CU control unit
  • ALU arithmetic logic unit
  • DSP digital signal processor
  • the processor 305 typically also has one or more interfaces 358 for communicating with external devices via system bus 381 , using a connection 361.
  • the application program 333 includes a sequence of instructions 362 through 363 that may include conditional branch and loop instructions.
  • the program 333 may also include data, which is used in execution of the program 333. This data may be stored as part of the instruction or in a separate location 364 within the ROM 360 or RAM 370.
  • the processor 305 is given a set of instructions, which are executed therein. This set of instructions may be organised into blocks, which perform specific tasks or handle specific events that occur in the electronic device 301. Typically, the application program 333 waits for events and subsequently executes the block of code associated with that event.
  • Events may be triggered in response to input from a user, via the user input devices 313 of Fig. 3A, as detected by the processor 305. Events may also be triggered in response to other sensors and interfaces in the electronic device 301.
  • the execution of a set of the instructions may require numeric variables to be read and modified. Such numeric variables are stored in the RAM 370.
  • the disclosed method uses input variables 371 that are stored in known locations 372, 373 in the memory 370.
  • the input variables 371 are processed to produce output variables 377 that are stored in known locations 378, 379 in the memory 370.
  • Intermediate variables 374 may be stored in additional memory locations in locations 375, 376 of the memory 370. Alternatively, some intermediate variables may only exist in the registers 354 of the processor 305.
  • the execution of a sequence of instructions is achieved in the processor 305 by repeated application of a fetch-execute cycle.
  • the control unit 351 of the processor 305 maintains a register called the program counter, which contains the address in ROM 360 or RAM 370 of the next instruction to be executed.
  • the contents of the memory address indexed by the program counter is loaded into the control unit 351.
  • the instruction thus loaded controls the subsequent operation of the processor 305, causing for example, data to be loaded from ROM memory 360 into processor registers 354, the contents of a register to be arithmetically combined with the contents of another register, the contents of a register to be written to the location stored in another register and so on.
  • the program counter is updated to point to the next instruction in the system program code. Depending on the instruction just executed this may involve incrementing the address contained in the program counter or loading the program counter with a new address in order to achieve a branch operation.
  • Each step or sub-process in the processes of the methods described below is associated with one or more segments of the application program 333, and is performed by repeated execution of a fetch-execute cycle in the processor 305 or similar programmatic operation of other independent processor blocks in the electronic device 301.
  • testbench implementation for example the system 100
  • optical fibres for example hollow-core optical fibres
  • the testbench implementation uses a Moens-Korteweg approach for determining pulse wave velocity.
  • Pulse wave velocity can be described as the velocity at which a blood pressure pulse propagates through the human circulatory system.
  • the arrangements described relate to measuring pulse wave velocity for an artery in a wrist, such as a radial artery. Blood pressure can be determined from pulse wave velocity using multiple relationships.
  • the Moens-Korteweg model finds pulse wave velocity as a function of the parameters of the arterial system based on Equation (1) below.
  • Equation (1) t is the thickness of the arterial wall, E is the elastic modulus of the arterial wall, ris the inner radius of the artery and p is the density of blood.
  • the elastic modulus is typically dependent on the blood pressure, BP, in accordance with Equation (2) below.
  • Equation (2) Eo is the zero-pressure elastic modulus and a is a constant that depends on the artery and the person.
  • the elastic modulus increases exponentially as a function of blood pressure.
  • pulse wave velocity is expressed as shown in Equation (3) below.
  • Equation (3) can be used to express blood pressure in terms of PWV as per Equation (4) below.
  • Equation (4) includes two constants, k ⁇ and kz, typically specific to an artery of a specific individual person.
  • the constants /ci and kz can be determined by two-point calibration, that is by measuring the blood pressure and simultaneous pulse wave velocity for two blood pressures.
  • the two-point calibration can be performed using a sphygmomanometer or another calibrated blood pressure measurement method to make two blood pressure and pulse wave velocity measurements.
  • An average radial artery has been shown to have a diameter of 2.5mm with a thickness of 0.25mm. See M. Failla, C. Giannattasio, A. Piperno, A. Vergani, A. Grappiolo, G. Gentile, E. Meles, and G. Mancia; Radial artery wall alterations in genetic hemochromatosis before and after iron depletion therapy; Hepatology, 32 (3):569-573, 2000.
  • the testbench implementation uses an artificial artery manufactured from polyurethane with a diameter of 4mm and an approximate thickness of 0.4 mm, similar to a typical healthy human artery.
  • Polyurethane has a Young’s modulus in the order of 15 MPa. Based on use of the square root in Equations (1) and (3) for thickness, zero-pressure elastic modulus and common diameter to thickness ratio, use of the artificial artery 130 is considered to affect pulse wave velocity by a factor of ten.
  • Water and blood have average densities of 997 kg/m 3 and 1060 Kg/m 3 respectively.
  • Water is used as a model for blood in the testbench implementation on this basis.
  • the model artery 130 is connected to a tap on one end so that water flows in the direction 140 to simulate directionality of a blood flow carrying a pulse through an artery.
  • a detectable pulse wave is carried along the length of the model artery 130.
  • the pressure used to apply the fibres to the artificial artery was typically sufficient to detect perturbations from the pulses without deforming the fibres.
  • the pressure required can vary depending on factors such as the material of the light guides, structure of the wave light guides and sensitivity of the light sensors.
  • the optical fibres 120a and 120b of the testbench implementation have a diameter of 1.5mm and the fibre wall has a thickness of 0.2mm.
  • the optical fibres 120a and 120b are each 15cm in length.
  • the diameter and thickness of the wall of the fibres 120a and 120b affect sensitivity of the measuring system.
  • the optical fibres 120a and 120b are separated by a distance D1, being 6cm.
  • the distance D1 between the fibres 120a and 120b determines the transit time of the pulses to be measured from 120a to 120b respectively.
  • the larger the distance D1 the greater the delay between measurement of a pulse at a first fibre (such as 120a) and the measurement by the second fibre (such as 120b).
  • the distance D1 between the fibres is relevant to determining the pulse wave velocity.
  • one of the light sources is a laser diode with 980nm wavelength, 13mm diameter and 30mW power and the other light source (110b) is a laser diode with a 650nm wavelength and 6mm diameter and 5mW power.
  • Diodes manufactured by LaserlandTM or CoherentTM can be used for example.
  • a plastic lens (not shown) with copper casing of each of the laser diodes 110a and 110b is used to optically couple a light source to the corresponding one of the fibres 120a and 120b.
  • Each of the light sensors 150a and 150b of the testbench includes a photodiode to detect the light transmitted through the corresponding fibre 120a and 120b.
  • a HamamatsuTM S5972 IR + Visible Light Si PIN Photodiode, Through Hole TO-18 is used for each of the light sensors 150a and 150b in one example implementation.
  • the end of each fibre and the sensitive area of the photodiode are optically coupled. The optical coupling can be implemented using a mechanical means that allows the light to travel through each optical fibre to contact the corresponding light sensor.
  • Coupling the fibres 120a and 120b to the sensors 150a and 150b respectively is controlled using a 3D mechanical precision stage in the testbench implementation. Coupling is implemented to avoid coupling light into the cladding of the fibre to avoid an increase in changes in light intensity that are not due to transit of a pulse under the light guide, which may affect accuracy of the corresponding sensor 150a or 150b.
  • each optical fibre 120a and 120b is manufactured from a material that prevents light being guided into the cladding, such as black polyurethane.
  • Light incident on the sensors 150a and 150b causes electrical properties of the sensors to change and accordingly generates a change in an associated generated electrical signal. For example, as intensity of light shining on the photodiodes of the testbench implementation varies, the current generated by a circuit formed using the photodiodes varies correspondingly. As a pulse of blood passes through the artery 130 under a fibre (such as 120a) the path of the light through the fibre (such as 120a) is varied by mechanical perturbations and the intensity of the light received at the corresponding photodiode (such as 150a) is varied. The electrical signal, for example the current generated by the photodiode of the sensor 150a, varies correspondingly. The pulse passes under the optical fibre 120b after the fibre 120a.
  • the effect of the pulse travelling under the fibre 120b has a similar effect on electrical signals generated by the photodiode of the sensor 150b. If the fibre 120b is further in direction of travel of the pulse, the electrical signals generated at 150b may vary compared to those generated at 150a but be of similar order.
  • Any change in electrical signal generated as a result of light intensity varying across the photodiodes is measured using any suitable measuring device, for example an oscilloscope, voltmeter or current sensor. Finger pressure on the artificial artery 130, while water flows in the direction 140, creates the pulse waves. The pressure and the water flow level can be optimized based on experimentation to maximize the change of signal from the fibres. Voltage change due variations in intensity of light travelling through both fibres 120a and 120b has been observed and experimental runs of about 25 pulses with about 1 Hz frequency have been recorded for a test set of 2x10 9 samples for a 25 second time window for example.
  • Fig. 4 shows a method 400 for measuring blood pressure using the testbench implementation.
  • the method 400 is implemented by the system 100.
  • portions of the method 400 are implemented by operation of the components 110a-110b, 120a-120b and 150a- 150b.
  • Other portions of the method 400 are implemented by the processing device 160, for example by modules of the software 333 stored in the memory 309 and controlled under execution of the processor 305.
  • the method 400 can be used to measure systolic or diastolic blood pressure. Examples discussed in relation to testbench and human implementations hereafter relate to measurement of systolic blood pressure.
  • the method 400 is implemented when the system 100 is applied to the model artery 130. That is, the optical fibres 120a and 120b are placed in contact with the model artery 130. Sufficient pressure is applied to the optical fibres 120a and 120b against the model artery 130 to allow changes in pressure in liquid travelling through the model artery 130 to disrupt passage of light through the optical fibres 120a and 120b.
  • the method 400 starts at a transmission step 410.
  • the light sources 110a and 110b emit light for transmission through the optical fibres 120a and 120b.
  • the laser diodes of the sources 110a and 110b are switched on continuously.
  • the transmitted light enters and travels along a corresponding one of the optical fibres 120a and 120b.
  • Each of the light sensors 150a and 150b receives light from the corresponding optical fibre.
  • Operation of the step 410 may be in part controlled by operation of the application 333, for example by enabling a software controlled switch using a power control algorithm.
  • the method 400 continues from step 410 to a measuring step 420.
  • step 420 operates to measure variations in electrical signals generated by each of the light sensors 150a and 150b over time as pulses pass through the model artery 130.
  • voltages generated by the photodiodes of each of the sensors 150a and 150b are measured.
  • the measured voltages can be stored in a memory such as the memory 309.
  • the memory may be a component of a wearable embodiment of the system 100 for example.
  • the measurements can be transmitted to a memory of a separate processing unit, for example by wireless communication.
  • the measured signals can be stored at predetermined intervals, for example at a frequency of 100Hz.
  • the method 400 continues from step 420 to a pulse signal generating step 430.
  • the application 333 operates to use the measurements taken at step 420 to determine or generate a representation of the pulse signal generated through pulsation of water through the artery 130.
  • a signal is generated for each of the measurements taken for the sensors 150a and 150b.
  • An example method 500, as implemented at step 430 is described hereafter with respect to Fig. 5.
  • the generated signal provides a representation of pressure changes due to a pulse being exerted on each of the fibres 120a and 120b, for example a discrete or continuous envelope of the pulse signal.
  • the step 430 outputs a representation of the pulse signal for signals generated by each of the sensors 150a and 150b.
  • the method 400 continues from step 430 to an identify pulse step 440.
  • the step 440 executes on the processor 305 to identify occurrence of a pulse at each of the sensors 150a and 150b, for example a time at which a pulse is identified. Each occurrence is identified based on the signals generated step 430.
  • occurrence of the pulse as measured at the sensor 150a is identified based on a peak of a continuous envelope signal generated for the sensor 150a, corresponding to pulse flow under the fibre 120a.
  • Relative occurrence of the pulse being measured at the sensor 150b is identified based on a peak of a continuous envelope signal generated for the sensor 150b, corresponding to pulse flow under the fibre 120b.
  • Relative occurrence of a pulse can be determined using different techniques that can be used for pattern identification such as identification of peak, identification of peak ranges, curve fitting, a trained classifier and the like.
  • the method 400 continues from step 440 to a determine pulse wave velocity step 450.
  • the application 333 executes to determine pulse wave velocity by firstly determining pulse transit times (PTT) based on the pulse occurrence identified at step 440.
  • PTT pulse transit times
  • the PTT relates to the time a pulse crossed the first of the fibres (such as 120a) based on the corresponding sensor (150a) and the same pulse crossed the second of the fibres (such as 120b) based on the corresponding sensor (150b). Effectively, the PTT provides a transit time of the pulse between the optical fibres.
  • the pulse wave velocity is determined from a distance D between the fibres (D1 of Fig. 1) divided by the transit time, as per Equation (5) below.
  • PWV between 10 and 20 m/s can correspond to blood pressure between 50 and 150 mmHg, respectively (see for example Chen et al.; Annals of Biomedical Engineering, Vol. 40, No. 4, April 2012).
  • a PWV of between 5 and 30 m/s can correspond to blood pressure between 100 mmHg and 220 mmHg in the 20- to 80-year old age group (see for example Kim, E., Park, C., Park, J. et al.; Relationship between blood pressure parameters and pulse wave velocity in normotensive and hypertensive subjects: invasive study; J Hum Hypertens 21, 141-148 (2007)).
  • the distance D relates to the distance D1 of Fig. 1 or the distance D2 of Fig. 2 and represents a distance travelled by blood flow carrying the pulse between the first and second optical fibres.
  • execution of step 440 gave pulse wave velocity between 2 and 6 m/s with an average value of 2.4 m/s.
  • Equation (6) Another model was used based on properties of the artificial artery manufactured from polyurethane, as shown by Equation (6):
  • Equation (6) t is the thickness of the pipe wall, E is the elastic modulus of the pipe material, ris the radius of the pipe, p the density of the liquid, K the compressibility of the liquid and Y is a value related to how the pipe is supported.
  • Equation (6) a pulse wave velocity of 38.8 m/s was also obtained.
  • the method 400 continues under execution of the processor 305 from step 450 to a determine blood pressure step 460.
  • the step 460 executes to determine blood pressure using the pulse wave velocity determined as step 450 based on Equation (4) using constants /ci and /C2 determined in calibration.
  • the method 400 ends on execution of step 460.
  • Fig. 5 shows the method 500 of generating or determining pulse signals as implemented at step 430 of Fig. 4.
  • the method 500 can implemented by the processing device 160, for example by modules of the software 333 stored in the memory 309 and controlled under execution of the processor 305.
  • the method 500 starts a noise removal step 510.
  • the step 510 operates to remove or filter noise from each of the signals measured at step 420.
  • An example implementation that can be used at step 510 is described in relation to Fig. 6.
  • the step 510 can also apply techniques to adjust resolution of the measured electrical signals, for example using techniques such as interpolation for signals in the time domain or zero padding for signals converted to the frequency domain.
  • Step 510 can return noise-processed measurements in the frequency domain or the time domain.
  • Fig. 6 shows an example method of removing noise, as implemented at step 510 of the method 500.
  • the method 600 provides an example implementation of methods than can be used to at least partially remove noise from the electrical signals generated by each of the sensors 150a and 150b. In other implementations of the method 600 other techniques may be used.
  • the method 600 can be implemented by the processing device 160, for example by modules of the software 333 stored in the memory 309 and controlled under execution of the processor 305.
  • the method 600 starts at an FFT step 610.
  • the step 610 operates to apply a forward fast Fourier transform (FFT) to the voltage data measured at step 420 to transform the data measured from each of the sensors 150a and 150b from the temporal domain to the frequency domain.
  • FFT forward fast Fourier transform
  • the method 600 continues under control of the processor 305 from step 610 to a filtering step 620.
  • the example filtering step 620 applies a bandpass filter to the transformed data generated in step 610.
  • An example of a band used is between 0.5Hz and 14.8Hz.
  • Parameters of the step 620 are selected based on noise present in the collected components, for example from a mains supply powering the laser diodes and any other spurious signals depending on the implementation.
  • the method 600 ends after execution of step 620.
  • the method 500 continues from step 510 to a generate signal step 520.
  • the step 520 operates to generate a pulse signal representing each set of filtered measurements generated at step 510. If the noise processed signals of the step 510 are generated in the frequency domain, the step 520 also executes to convert the generated signal to the time domain, for example using an inverse fast Fourier transform corresponding to the forward transform used at step 610.
  • the signals may be generated by applying methods such as interpolation algorithms, curve fitting algorithms and the like to each set of measurements. In an example implementation, a MatlabTM “interp” function, which interpolates to minimize the mean-square error between interpolated points and ideal values can be used.
  • each generated pulse signal can be additionally normalised to within a range at step 520.
  • each signal is normalised to between 0 and 1.
  • step 520 The effect of operation of step 520 is to generate a representation of pulse using measurements reflecting the changes in electrical signals generated by each of 150a and 150b due to changes in pressure applied to the corresponding optical fibres 120a and 120b.
  • the generated signal can be used to identify occurrence of a pulse at each optical fibre.
  • the method 500 ends after execution of step 520.
  • Fig. 7 A shows a graph 700 being a typical result of operation of the system 100 using the testbench in which the artery 130 is an artificial artery manufactured from polyurethane.
  • the graph 700 shows variation in amplitude of the normalised voltage signals generated at step 520 in relation to time.
  • Both fibres 120a and 120b result in similar signals from the pulse, as indicated by traces 705 and 710.
  • the pulses relate to water waves and have maxima and minima. The nature of the wave does not allow the pulse wave velocity to be obtained by simply looking at the transit time of the maxima of each trace.
  • the pulse arrives earlier at the fibre (for example 120a) closer to the source (for example to a tap in the testbench implementation or to a subject’s heart in a measurement taking using a human) and later at the fibre (such as 120b) further from the pulse source.
  • an envelope of the pulses was determined at step 430 using measurements taken at each of 150a and 150b, at step 420.
  • Fig 7B shows a graph 750 in which envelopes 760 and 765 correspond to the traces 705 and 710 respectively.
  • the envelopes 760 and 765 measure the pulse wave moving across the fibres 120a and 120b. Pulse transit times of 10 to 30 ms are measured based on comparing the maxima of the envelopes 760 and 765.
  • the pulse wave velocity is determined using Equation (5). A resulting pulse wave velocity of 2 to 6 m/s was determined.
  • the testbench implementation shows that the system 100 is suitable for determining blood pressure in the typical pulse range of a human subject.
  • the arrangements and techniques used for the system 100 can be equally adapted for use on a human and readily extrapolated for measuring blood pressure of a human.
  • the system 200 is used to measure blood pressure of a human subject.
  • the light sources 210a and 210b are the same as one another, each being a laser diode configured to emit light at 650nm wavelength, around 1mm width and 5mW power laser.
  • the light guides 220a and 220b in the example of the system 200 are hollow-core or capillary guidance optical fibres manufactured of polyurethane having a wall thickness of 0.25mm and a diameter of 1.5mm. Each of the fibres 220a and 220b has a length of 5cm.
  • the sensors 250a and 250b of the example implementation of the system 200 each include a photo diode, being a HamamatsuTM S5972 IR + Visible Light Si PIN Photodiode, Through Hole TO-18.
  • the laser diodes of the light sources 210a and 210b are optically coupled to the fibres 220a and 220b in a manner to allow the laser light to enter the fibres 220a and 220b in a relatively straight line.
  • the area 290 relates to skin covering the artery of the inner right wrist of the subject. Pressure is applied to the fibres 220a and 220b to a sufficient degree to hold the fibres 220a and 220b closely against skin over the artery to sense mechanical vibrations or perturbations caused by blood flow.
  • a strap or band may be used to secure the fibres along an inner wrist in manner sufficiently close or tight enough to be sensitive to changes in pressure from pulse but without applying uncomfortable pressure or damage to typical human skin.
  • the area 290 may relate to a single area, or to two or more external areas of the human body suitable for measuring pulse through an artery if the system 200 is a wearable comprising two or more modules. Suitable areas can include the wrist, neck, thigh and ankle for example.
  • Fig. 8 shows an example circuit 800 for measuring blood pressure of a human.
  • a circuit configured for measuring blood pressure can be integral to the light sensors 250a and 250b or can have some components separate to the sensors 250a and 250b.
  • the example circuit 800 includes photodiodes 850a and 850b, such as the HamamatsuTM S5972 IR examples, corresponding to components of the sensors 250a and 250b.
  • the circuit 800 includes two channels, one for each of the photodiodes. Each channel has an output node,
  • the output nodes 890a and 890b are each connected to a corresponding measuring device.
  • each output may be connected to a pin of an chickenTM analog to digital converter device for measuring voltage.
  • Each channel includes a resistance arrangement (820a, 820b), buffering (830a and 830b) and gain stages (840a and 840b). The difference between the input at each resistor network 820a and 820b and an input voltage from a supply 870 is amplified.
  • the example implementation for the human subject uses an input voltage of 3.93 V at 870 and a gain of approximately 60 across each of the channels 810a and 810b. Recordings of the voltage across the photodiodes 850a and 850b are taken at the outputs 890a and 890b at a frequency of 6.25 kHz.
  • Blood pressure of the human subject is determined using the system 200 of Fig. 2 and the method 400 of Fig. 4.
  • the method 400 is implemented when the optical fibres 220a and 220b are held against the wrist of a subject with sufficient pressure to detect pulse.
  • the light sources 210a and 210b are activated such that light travels through the optical fibres 220a and 220b.
  • the light travelling through each optical fibre is received at a corresponding one of the sensors 250a and 250b (such as 850a and 850b).
  • the material from which the light guides are formed allows transmission of light through the light guide to vary based on pulse flow through the artery.
  • the variation in the path of the light varies the intensity of the light application to the sensors 250a and 250b.
  • Each of the sensors 250a and 250b receives the light from the corresponding light guide and generates an electrical signal that varies with the light intensity, that is varies correspondingly to the transmission path of the light through the optically-coupled light guide.
  • step 420 electrical signals resultant from light being received are measured and stored for each of the sensors 250a and 250b (for example the diodes 850a and 850b).
  • the measurements can be stored on the processing device 260 for example.
  • the method 400 continues to step 430 to determine a pulse signal for each set of measurements.
  • the step 430 executes the method 500 for each the measurements stored for each of the sensors 250a and 250b.
  • Step 430 can be implemented using the method 500 for example.
  • the step 510 can be implemented using the method 600.
  • each signal can be converted to the frequency domain using a forward fast Fourier transform.
  • Each frequency domain signal is then filtered at step 620, for example using a second order Butterworth bandpass filter.
  • the bandpass filter can have a band of between 0.2Hz and 45Hz.
  • a band of 1 Hz to 5Hz was used.
  • the range of the bandpass filter can vary depending on a rate at which measurements are taken at step 420, components used in the circuit 800, or sensitivity of the fibres 220a and 220b.
  • a human pulse has a frequency typically in a range of 1Hz
  • the range of the filter can have a minimum of approximately 0.5Hz in some implementations.
  • Appendix A shows example MatlabTM code for implementing a filter and identifying a pulse. In other implementations other techniques may be used to process the voltages measured from devices 750a and 750b.
  • the filtered measurements are inverse fast Fourier transformed at the step 520 to generate two sets of data in the time domain, each corresponding to one of the measurements taken for 750a and 750b.
  • the step 520 executes to generate a normalised signal for each set of filtered measurements, each corresponding to a measurement taken by one of 250a and 250b.
  • a pulse occurrence is identified for each of the two measurement signals.
  • pulse wave velocity is determined using the identified pulse times.
  • the pulse wave velocity is determined at step 450 for the human implementation using Equation (7): r g _ distance (m) time (s) ' '
  • the distance in Equation (7) for the human implementation relates to the distance D2 of Fig. 2.
  • the time in Equation (7) for the human implementation is the difference between the pulse times identified for each signal at step 440.
  • the method 400 determines blood pressure at step 460 using the pulse wave velocity determined at step 450, Equation (4) and constants /ci and kz determined for the test subject by two-point calibration.
  • the blood pressure can be determined at step 460 using different techniques.
  • a machine learning approach such as a trained classifier can be used to determine the blood pressure from the pulse wave velocity.
  • an artificial intelligence (Al) program can be trained using suitable examples of pulse wave velocity and corresponding blood pressure can be used to determine the subject’s blood pressure at step 460.
  • Fig. 9A shows a graph 900.
  • the graph 900 shows signal generated at step 520 using signals measured for each of the sensors 850a and 850b.
  • Fig. 9B shows a graph 920.
  • the graph 920 shows a portion of the graph 900.
  • the portion shown in the graph 920 shows a sample pulse envelope 930 generated using a measurement taken using optical fibres 220a and 220b for the human implementation.
  • the signal 930 shows a profile corresponding to a typical pulse profile for a human.
  • the electrical signals generated by the light sensors 250a and 250b are used for determining pulse wave velocity between the light guides to measure blood pressure.
  • the implementation performed using a human subject shows that relatively soft optical fibres are suitable for use in measuring human blood pressure.
  • the size and softness of the fibres and the resultant sensitivity to mechanical perturbations caused by blood pulsing through an artery allow a less invasive or intrusive measurement than a cuff to be used. Rather, a wearable device suitable for holding the fibres 220a and 220b sequentially along an artery is possible.
  • the wearable device would allow blood pressure to be measured in a near real-time continuous manner without distress to the subject or disturbing the subject.
  • a wearable device could also allow blood pressure measurements to be taken when the subject is undergoing activity such as running.
  • the sources 210a-210b and sensors 250a-250b used in the human implementation are suitable for integration into a wearable device.
  • Blood pressure is measured in terms of systolic pressure and diastolic pressure.
  • the method of Fig. 4 is used to determine systolic blood pressure in the examples described above.
  • Systolic blood pressure is measured as described in relation to Fig. 4 by determining pulse wave velocity at step 450 based on occurrence of a maximum value of the signal determined at step 430 using measurements for each of the light sensors.
  • Systolic pressure is typically a more important indicator of many health conditions than diastolic pressure.
  • occurrence of the pulse is identified based upon occurrence of a peak in the pulse signal determined at step 430, for example a peak 940 shown in Fig. 9B (for the light sensor 250a), and a time between the peak 940 and a peak of a signal determined for the other light sensor (250b).
  • each pulse is identified at step 440 based on occurrence of a minimum of the signal generated for each light guide, for example a minimum of a signal generated for the sensor 250a and a minimum of a signal generated for the sensor 250b.
  • a minimum or foot 950 of the signal 930 is shown in Fig. 9B.
  • Diastolic blood pressure is measured using the method 400 by determining pulse wave velocity at step 450 based on identification of the occurrence of pulse based on a minimum value (at step 440) of the signal generated at step 430 using measurements for each of the light sensors.
  • pulse wave velocity relating to diastolic pressure is determined using the identified pulse times for the foot or minimum of each generated signal using Equation (7) and the corresponding distance (for example D2 for the system 200).
  • Diastolic blood pressure is determined at step 460 using the pulse wave velocity determined at step 450, Equation (4) and constants /ci and kz determined for the test subject by two-point calibration.
  • the signal 930 shows a profile similar to that of a typical human pulse.
  • the foot or minimum 950 can be used to determine diastolic blood pressure and the peak or maximum 940 can be used to determine systolic blood pressure.
  • each signal generated at step 430 can provide an indication of relative variation in magnitude of a pulse signal over time. That is, each signal determined at 430 can provide a relative indication of pressure due to pulse between minimum (such as 950) and maximum (such as 940).
  • Fig. 10 shows a method 1000 for obtaining a blood pressure measurement using the testbench implementation.
  • the method 1000 can be implemented using the system 100 or the system 200, in a similar manner to the method 400.
  • the method 1000 starts at a transmitting step 1010.
  • the step 1010 operates in a similar manner to the step 410.
  • the light sources 210a and 210b are activated such that light travels through the optical fibres 220a and 220b.
  • the light travelling through each optical fibre is received at a corresponding one of the sensors 250a and 250b.
  • the material from which the light guides are formed allows transmission of light through the light guide to vary based on pulse flow through the artery.
  • the variation in the path of the light varies the intensity of the light application to the sensors 250a and 250b.
  • Each of the sensors 250a and 250b receives the light from the corresponding light guide and generates an electrical signal that varies with the light intensity, that is varies correspondingly to the transmission path of the light through the optically-coupled light guide.
  • the method 1000 continues from step 1010 to a measuring step 1020.
  • the step 1020 operates in a similar manner to step 420. Electrical signals resultant from light being received are measured and stored for each of the sensors 250a and 250b. The measurements can be stored on the processing device 260 for example.
  • the method 1000 continues from step 1020 to a generating step 1030.
  • the step 1030 operates in a similar manner to the step 430 to generate or determine a pulse signal for each set of measurements taken at step 1020.
  • the step 1030 can execute the method 500 for each the measurements stored for each of the sensors 250a and 250b.
  • the method 1000 continues from step 1030 to an identify pulse range step 1040.
  • the step 1040 identifies occurrence of a range of a pulse for each of the two measurement signals generated at step 1030.
  • the step 1040 identifies occurrence of a pulse based on a maximum of the generated signal (for systolic pressure) or a minimum of each generated signal (for determining diastolic pressure).
  • the step 1040 operates to identify the range of the pulse based on both the minimum (such as 950) and maximum (such as 930) of each generated signal.
  • the maximum and minimum occurrences can be determined using similar techniques to those described in relation to step 440.
  • the method 1000 continues from step 1040 to a determine pulse wave velocity step 1050.
  • two values of pulse wave velocity are determined using the ranges identified at step 1040.
  • pulse wave velocity is determined using Equation (7) for (i) occurrence of the minimum of each pulse signal for each of the sensor, and (ii) occurrence of the maximum of each pulse signal for each of the sensor.
  • the distance D2 and the minimum for each signal generated using measurements from 250a and 250b are used to generate a first pulse wave velocity for determining diastolic pressure.
  • the distance D2 and the maximum for each signal generated using measurements from 250a and 250b are used to generate a second pulse wave velocity for generating systolic pressure.
  • the method 1000 continues from step 1050 to a determine blood pressure step 1060.
  • the step 1060 operates to determine both diastolic and systolic blood pressure.
  • Diastolic blood pressure is determined using the pulse wave velocity determined at step 1050 using the minimum reading from each signal, Equation (4) and constants /ci and kz determined for the test subject by two-point calibration.
  • Systolic blood pressure is determined using the pulse wave velocity determined at step 1050 using the maximum reading from each signal, Equation (4) and constants /ci and kz determined for the test subject by two-point calibration.
  • the diastolic and systolic pressures can be determined at step 1060 using different techniques.
  • Fig. 11 shows a graph 1100.
  • the graph 1100 shows signal generated at step 520 using signals measured for each of the sensors 850a and 850b.
  • the light guides 220a and 220b are positioned on the inside wrist of a 40-year old male in an arrangement where the distance D2 is 2 cm.
  • a signal 1105 corresponds to measurements at a first light guide (such as 220a) and a signal 1110 corresponds to measurements at a second light guide (such as 220b).
  • the signals 1105 and 1110 represent pulse-shape patterns.
  • Figs. 12A to 12D show an example device casing 1200 for a wearable implementation.
  • Fig.12A shows a top perspective view 1200a of the device casing 1200.
  • the device casing 1200 can be made from any material suitable for containing components for a wearable device.
  • the casing 1200 has wrist strap attachment points, for example 1220, which can be used for attaching the casing 1200 to a human subject’s body.
  • the attachment points 1220 can be eyelets or clamps or the like for attaching a strap (not shown) for tying the casing 1200 to the subject’s inside wrist.
  • the strap would be adjustable, for example made of Velcro or having a slidable buckle arrangement to adjust fit and how tightly the casing 1200 is held against the subject’s skin.
  • the casing 1200 has compartments 1205a and 1205b, one on each side for holding the light sensors (such as 250a and 250b) and compartments 1210a and 1210b, one on each side, for holding the light sources (such as 210a and 210b).
  • the casing also has a compartment 1215 for any other electronics (such as the processing device 260 or components such as 830a and 830b shown in Fig. 8).
  • Fig. 12B shows a bottom perspective view 1200b of the casing 1200.
  • the attachment points 1220 hold the lower face 1260 of the device 1200 against the user’s skin.
  • One of the light guides 220a and 210b receives light from the corresponding light source in the compartment 1210a or 1210b.
  • the light guide is connected to the corresponding light sensor in the associated compartment 1205a or 1205b.
  • Each light guide runs along a path from the conduit 1225-1 to 1225-2.
  • a pressure adjustment pad 1230a or 1230b is provided along a path of each light guide.
  • Each of the pressure adjustment pads 1230a and 1230b can be used to adjust the pressure with which the associated light guide is held against a subject’s skin.
  • a pulse traveling through the artery will affect the path of the light travelling through each light guide at different times.
  • the changes in light intensity are sensed at the sensors in 1210a and 1210b and used as described in relation to Fig. 4 or Fig. 10 to determine the subject’s blood pressure.
  • Fig. 12C shows an exploded top perspective view 1200c of the casing device 1200.
  • Fig. 12D shows an exploded bottom perspective view 1200d of the casing device 1200.
  • Figs. 12C and 12D show that a pressure adjustment mechanism 1235 is provided for each of the pressure pads 1230a and 1230b.
  • each adjustment mechanism is a screw.
  • Each screw 1235 can be tightened or loosened to adjust the pressure by which the corresponding one of the pads 1230a and 1230b holds a light guide against the user’s skin.
  • other pressure adjustment systems may be used to vary the pressure with which light guides are held against a user’s skin such as a ratchet system or the like.
  • Fig. 1 and Fig. 2 indicate that a pair of relatively soft light guides (such as optical fibres) can be used to measure blood pressure in a continuous, non-intrusive manner using at least one light source and a light sensor corresponding to each light guide. Variations of the structure and form of Figs. 1 and 2 are possible while still allowing blood pressure to be measured in a near-real time manner.
  • relatively soft light guides such as optical fibres
  • the light guides 220a and 220b may have a form that differs from traditional optical fibres.
  • the waveguide may relate to conduits formed in a substrate, for example a polymer tube partially embedded in a substrate or channels formed in a substrate. A portion of the tube that is not embedded in the substrate is placed against the skin and is subject to the perturbations or changes in pressure caused by pulse through an artery.
  • the light guides can be formed of a material that selectively controls light absorption, such as black polyurethane
  • a single light source and a device to split light emitted by the single source can replace the light sources 210a and 210b in some implementations.
  • laser diodes are used as a light source.
  • Other light sources may also be used.
  • a suitable light source is relatively compact and power efficient, for example to a degree practical for use in a wearable device.
  • a suitable light source also typically has light beam directionality appropriate for coupling the beam into a light guide or optical fibre.
  • the diameter of the core inside the light guides through which light travels (for example the inner diameter of the fibres 220a and 220b) can also be adjusted based upon factors such as implementation (for example if a wearable device), noise tolerance, expected noise and material from which the light guides are manufactured.
  • the light guides should have a diameter large enough for guiding and in-coupling (receiving) light from the corresponding light source but small enough to be robust for wear applied to a human while sensitive to perturbations of a pulse through skin.
  • the sensors 150a and 150b sense variations in intensity of the light travelling through the corresponding waveguides. Intensity of the light varies or fluctuates due to perturbations in the corresponding waveguide (such as 250a for example) as a pulse passes through the artery underneath skin against which the waveguide is placed.
  • the sensors can be any sensor suitable for sensing variations in intensity of light caused by the pulse and generating an electrical signal that varies with the intensity, such as photodiodes, photoresistors or other types of photodetectors. Selection of a particular type of sensor can depend on factors such as implementation (for example wearable), material and structure of the light guides, the location of the optical fibres on the human body and the like.
  • Each of the fibres 120a/120b or 220a/220b is cut to a particular length.
  • the length can be varied depending on the nature of the light source and light sensor used in conjunction with the waveguide.
  • the length of a light guide should preferably be sufficient to cross the artery without picking up additional noise signals.
  • the systems 100 and 200 have different distances D1 and D2 between optical fibres (light guides), resulting in different pulse transit times being measured.
  • the distance between the light guides can be varied based on factors such as implementation (such as wearable or otherwise), a location on the body where the light guides are likely to be placed, ease of measurement and potential for error in measurement. For example, placement on a part of the body can effect local changes in pressure (such as an arm lifting) and fibres that are overly far apart may require some synchronisation to avoid error.
  • the distance should be sufficient to allow identification of the different effect of the pulse on light travelling through each light guide, in terms of timing or pulse shape used to determine blood pressure.
  • each light source is continuously turned on.
  • each light source may be switched periodically by a controller.
  • a typical pulse has a frequency of approximately 1 Hz.
  • Switching of the light sources can be controlled based on the frequency of a typical pulse and on data determined through experimentation for a particular implementation, for example, depending on the material of the optical fibres, reactivity of the light sensors and the like.
  • each light source may switch in a synchronised manner at a frequency of 10 kHz, with a 50% duty cycle, on for 500 ms of the pulse and being off for 500 ms. Switching each light source periodically can reduce power consumption, which can be advantageous in wearable implementations for example.
  • Fig. 6 provides an example of noise removal only.
  • Other techniques such as different forms of noise removal such as other forms of filtering, adaptive techniques and noise removal algorithms can be used.
  • Removal of noise at step 510 can be implemented with or without conversion to the frequency domain.
  • step 520 can generate signals using techniques such as interpolation algorithms, curve fitting algorithms and the like.
  • the arrangements described are applicable to the health and medical industries, particularly for the cardiovascular health industries, as well as the health monitoring and fitness tracking industries.
  • Ability to measure blood pressure continuously near real-time in a manner that does not cause disturbance or intrusion to a patient can allow early identification of potential conditions. Health events and conditions are more likely to be detected through blood pressure measurements.
  • This function returns the time (in samples) at which a PPG peak occurs based on a threshold value MPH.
  • % @param Fs is the sample rate in Hz
  • % @param hpOrder is the order of the high pass Butterworth filter
  • % @param IpOrder is the order of the low pass Butterworth filter
  • % @param MPH is a twiddle parameter to set the min peak heights (findpeaks)

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Cardiology (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Animal Behavior & Ethology (AREA)
  • Pathology (AREA)
  • Veterinary Medicine (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Surgery (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Physiology (AREA)
  • Vascular Medicine (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Psychiatry (AREA)
  • Signal Processing (AREA)
  • Hematology (AREA)
  • Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)

Abstract

L'invention concerne un système et un procédé de mesure de la tension artérielle. Le système comprend au moins une source de lumière, une paire de guides de lumière et une paire de capteurs de lumière. Chacun des guides de lumière est conçu pour recevoir de la lumière provenant de ladite au moins une source et pour être placé sur une artère du sujet. Un matériau dont les guides de lumière sont formés permet la variation d'un trajet de lumière à travers le guide de lumière sur la base d'un écoulement pulsé à travers l'artère. Chacun des capteurs de lumière est conçu pour recevoir de la lumière provenant d'un des guides de lumière et pour générer un signal qui varie de manière correspondante avec le trajet de la lumière pour déterminer une vitesse d'onde pulsée entre les guides de lumière pour mesurer la tension artérielle.
PCT/AU2021/050730 2020-07-08 2021-07-08 Système de mesure de tension artérielle Ceased WO2022006634A1 (fr)

Applications Claiming Priority (2)

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AU2020902358 2020-07-08
AU2020902358A AU2020902358A0 (en) 2020-07-08 Blood pressure monitoring system

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2000010453A1 (fr) * 1998-08-24 2000-03-02 Baruch Martin C Appareil et procede permettant de mesurer le temps de transit d'impulsion
US20080181556A1 (en) * 2007-01-31 2008-07-31 Tarilian Laser Technologies, Limited Waveguide and Optical Motion Sensor Using Optical Power Modulation
US20160338601A1 (en) * 2014-12-31 2016-11-24 Huijia Health Life Technology Co., Ltd. Optical fiber continuous detecting blood sensor and wearing apparatus thereof
WO2018184979A1 (fr) * 2017-04-07 2018-10-11 Koninklijke Philips N.V. Console, système et procédé de mesure de vitesse d'onde d'impulsion dans un vaisseau sanguin

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2000010453A1 (fr) * 1998-08-24 2000-03-02 Baruch Martin C Appareil et procede permettant de mesurer le temps de transit d'impulsion
US20080181556A1 (en) * 2007-01-31 2008-07-31 Tarilian Laser Technologies, Limited Waveguide and Optical Motion Sensor Using Optical Power Modulation
US20160338601A1 (en) * 2014-12-31 2016-11-24 Huijia Health Life Technology Co., Ltd. Optical fiber continuous detecting blood sensor and wearing apparatus thereof
EP3263020A1 (fr) * 2014-12-31 2018-01-03 Huijia Health Life Technology Co., Ltd. Capteur de détection continue de pression artérielle de type à fibres optiques et dispositif portable associé
US20190290138A1 (en) * 2014-12-31 2019-09-26 Huijia Health Life Technology Co., Ltd. Optical fiber blood pressure continuous detection wristband and wearing apparatus
WO2018184979A1 (fr) * 2017-04-07 2018-10-11 Koninklijke Philips N.V. Console, système et procédé de mesure de vitesse d'onde d'impulsion dans un vaisseau sanguin

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Title
PEREIRA T. ET AL.: "Novel Methods for Pulse Wave Velocity Measurement", JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING, vol. 34, 2015, pages 555 - 565, XP055409829 *
SEGERS P. ET AL.: "How to Measure Arterial Stiffness in Humans", ARTERIOSCLEROSIS, THROMBOSIS AND VASCULAR BIOLOG Y, vol. 40, 2020, pages 1034 - 1043, XP055893936 *

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