WO2015181622A1 - Systèmes et procédés pour estimer des paramètres hémodynamiques à partir d'une image de courbe physiologique - Google Patents

Systèmes et procédés pour estimer des paramètres hémodynamiques à partir d'une image de courbe physiologique Download PDF

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Publication number
WO2015181622A1
WO2015181622A1 PCT/IB2015/000821 IB2015000821W WO2015181622A1 WO 2015181622 A1 WO2015181622 A1 WO 2015181622A1 IB 2015000821 W IB2015000821 W IB 2015000821W WO 2015181622 A1 WO2015181622 A1 WO 2015181622A1
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WIPO (PCT)
Prior art keywords
curve
mobile device
image
physiological curve
physiological
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PCT/IB2015/000821
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English (en)
Inventor
Oscar Alvarez GUERRAS
Borja Barrachina LARRAZA
Pedro BERRAONDO
Original Assignee
Guerras Oscar Alvarez
Larraza Borja Barrachina
Berraondo Pedro
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Application filed by Guerras Oscar Alvarez, Larraza Borja Barrachina, Berraondo Pedro filed Critical Guerras Oscar Alvarez
Publication of WO2015181622A1 publication Critical patent/WO2015181622A1/fr

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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 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
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • 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
    • A61B5/026—Measuring blood flow
    • A61B5/0295—Measuring blood flow using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography

Definitions

  • the present disclosure relates generally to utilizing software methods in the assistance of perioperative goal-directed therapy.
  • methods of using software to calculate flow-based hemodynamic parameters useful in goal-directed therapy from images of physiological monitor traces are described.
  • GDT Perioperative goal-directed therapy
  • the present disclosure is directed to systems and methods for estimation of hemodynamic parameters from physiological curve images.
  • the systems and methods include an Internet-connected mobile device running a dedicated app, which in turn connects to an Internet-connected analysis server.
  • the mobile device is equipped with a camera for capturing pictures of a physiological monitor display, which can then be cropped in the app on the mobile device to extract the relevant physiological curve and upload it to the analysis server for processing and estimation of hemodynamic parameters.
  • the system can be implemented using any computer that is capable of taking an image, extracting a physiological curve, and uploading it to a network service for analysis, in still further examples, analysis can be performed by the mobile device instead of via a remote server.
  • FIG. 1 shows a schematic view of an example of a programmable computing device.
  • FIG. 2 shows a schematic view of an example of a mobile electronic device.
  • Fig. 3 is a diagram of the components of an example system for estimation of hemodynamic parameters from a physiological curve image.
  • Fig. 4 is a chart of the steps a user takes to utilize an example system for estimation of hemodynamic parameters from a physiological curve image.
  • Fig. 5 is a chart of the analysis steps performed by an example system for estimation of hemodynamic parameters from a physiological curve image.
  • Figs. 6A and 6B are close-ups of example physiological curves that are analyzed by an example system for estimation of hemodynamic parameters.
  • Various disclosed examples may be implemented using electronic circuitry configured to perform one or more functions.
  • the disclosed examples may be implemented using one or more application-specific integrated circuits (ASICs). More typically, however, components of various examples of the invention will be implemented using a programmable computing device executing firmware or software instructions, or by some combination of purpose-specific electronic circuitry and firmware or software instructions executing on a programmable computing device.
  • ASICs application-specific integrated circuits
  • FIG. 1 shows one illustrative example of a computer, computer 101 , that can be used to implement various embodiments of the invention.
  • Computer 101 may be incorporated within a variety of consumer electronic devices, such as personal media players, cellular phones, smart phones, personal data assistants, global positioning system devices, and the like.
  • computer 101 has a computing unit 103.
  • Computing unit 103 Computing unit
  • Processing unit 105 may be any type of processing device for executing software instructions, but will conventionally be a microprocessor device.
  • System memory 107 may include both a read-only memory (ROM) 109 and a random access memory (RAM) 1 1 1.
  • ROM read-only memory
  • RAM random access memory
  • Processing unit 105 and system memory 107 are connected, either directly or indirectly, through a bus 1 13 or alternate communication structure to one or more peripheral devices.
  • processing unit 105 or system memory 107 may be directly or indirectly connected to additional memory storage, such as a hard disk drive 1 17, a removable optical disk drive 1 19, a removable magnetic disk drive 125, and a flash memory card 127.
  • Processing unit 105 and system memory 107 also may be directly or indirectly connected to one or more input devices 121 and one or more output devices 123.
  • Input devices 121 may include, for example, a keyboard, touch screen, a remote control pad, a pointing device (such as a mouse, touchpad, stylus, trackball, or joystick), a scanner, a camera or a microphone.
  • Output devices 123 may include, for example, a monitor display, an integrated display, television, printer, stereo, or speakers.
  • computing unit 103 will be directly or indirectly connected to one or more network interfaces 1 15 for communicating with a network.
  • An interface 1 15 may employ any suitable connection agent for connecting to a network, including, for example, a wireless transceiver, a power line adapter, a modem, or an Ethernet connection.
  • the computing device may be connected to a variety of other peripheral devices, including some that may perform input, output and storage functions, or some combination thereof.
  • the computer 101 may be connected to a digital music player, such as an I POD® brand digital music player or iOS or Android based smartphone.
  • this type of digital music player can serve as both an output device for a computer (e.g., outputting music from a sound file or pictures from an image file) and a storage device.
  • computer 101 may be connected to or otherwise include one or more other peripheral devices, such as a telephone.
  • the telephone may be, for example, a wireless "smart phone," such as those featuring the Android or iOS operating systems.
  • a "smart phone” may also provide a user with one or more data management functions, such as sending, receiving and viewing electronic messages (e.g., electronic mail messages, SMS text messages, etc.), recording or playing back sound files, recording or playing back image files (e.g., still picture or moving video image files), viewing and editing files with text (e.g., Microsoft Word or Excel files, or Adobe Acrobat files), etc.
  • a user may connect the telephone with computer 101 so that their data maintained may be synchronized.
  • peripheral devices may be included with or otherwise connected to a computer 101 of the type illustrated in Fig. 1 , as is well known in the art.
  • a peripheral device may be permanently or semi-permanent!y connected to computing unit 103.
  • computing unit 103, hard disk drive 1 17, removable optica! disk drive 1 19 and a display are semi-permanent!y encased in a single housing.
  • Computer 101 may include, for example, one or more communication ports through which a peripheral device can be connected to computing unit 103 (either directly or indirectly through bus 1 13 ). These communication ports may thus include a parallel bus port or a serial bus port, such as a serial bus port using the Universal Serial Bus (USB) standard or the IEEE 1394 High Speed Serial Bus standard (e.g., a Firewire port). Alternately or additionally, computer 101 may include a wireless data "port," such as a Bluetooth ⁇ interface, a Wi-Fi interface, an infrared data port, or the like.
  • USB Universal Serial Bus
  • IEEE 1394 High Speed Serial Bus standard e.g., a Firewire port
  • computer 101 may include a wireless data "port," such as a Bluetooth ⁇ interface, a Wi-Fi interface, an infrared data port, or the like.
  • a computing device employed according various examples of the invention may include more components than computer 101 illustrated in Fig. 1 , fewer components than computer 101 , or a different combination of components than computer 101.
  • Some implementations of the invention may employ one or more computing devices that are intended to have a very specific functionality, such as a digital music player or server computer. These computing devices may thus omit unnecessary peripherals, such as the network interface 1 15, removable optical disk drive 1 19, printers, scanners, external hard drives, etc.
  • Some implementations of the invention may alternately or additionally employ computing devices that are intended to be capable of a wide variety of functions, such as a desktop or laptop personal computer. These computing devices may have any combination of peripheral devices or additional components as desired.
  • computers may define mobile electronic devices, such as smartphones, tablet computers, or portable music players, including wearable devices such as Google® Glass or other mobile computing platforms that are easily attached to or carried on one's person, often operating the IOS, Symbian, Windows-based (including Windows Mobile and Windows 8), or Android operating systems.
  • wearable devices such as Google® Glass or other mobile computing platforms that are easily attached to or carried on one's person, often operating the IOS, Symbian, Windows-based (including Windows Mobile and Windows 8), or Android operating systems.
  • an exemplary mobile device, mobile device 200 may include a processor unit 203 (e.g., CPU) configured to execute instructions and to carry out operations associated with the mobile device.
  • the controller may control the reception and manipulation of input and output data between components of the mobile device.
  • the controller can be implemented on a single chip, multiple chips or multiple electrical components.
  • various architectures can be used for the controller, including dedicated or embedded processor, single purpose processor, controller, ASIC, etc.
  • the controller may include microprocessors, DSP, A/D converters, D/A converters, compression, decompression, etc.
  • the controller together with an operating system operates to execute computer code and produce and use data.
  • the operating system may correspond to well known operating systems such iOS, Symbian, Windows-based (including Windows Mobile and Windows 8), or Android operating systems, or alternatively to special purpose operating system, such as those used for limited purpose appliance-type devices.
  • the operating system, other computer code and data may reside within a system memory 207 that is operatively coupled to the controller.
  • System memory 207 generally provides a place to store computer code and data that are used by the mobile device.
  • system memory 207 may include read-only memory (ROM) 209, random-access memory (RAM) 21 1 .
  • system memory 207 may retrieve data from storage units 294, which may include a hard disk drive, flash memory, etc.
  • storage units 294 may include a removable storage device such as an optical disc player that receives and plays DVDs, or card slots for receiving mediums such as memory cards (or memory sticks).
  • Mobile device 200 also includes input devices 221 that are operatively coupled to processor unit 203.
  • Input devices 221 are configured to transfer data from the outside world into mobile device 200.
  • input devices 221 may correspond to both data entry mechanisms and data capture mechanisms, in particular, input devices 221 may include touch sensing devices 232 such as touch screens, touch pads and touch sensing surfaces, mechanical actuators 234 such as button or wheels or hold switches, motion sensing devices 238 such as accelerometers, location detecting devices 238 such as global positioning satellite receivers, WiFi based location detection functionality, or cellular radio based location detection functionality, force sensing devices such as force sensitive displays and housings, image sensors, and microphones. Input devices 221 may also include a clickable display actuator.
  • Mobile device 200 also includes various output devices 223 that are operatively coupled to processor unit 203.
  • Output devices 233 are configured to transfer data from mobile device 200 to the outside world.
  • Output devices 233 may include a display unit 292 such as an LCD, speakers or jacks, audio/tactile feedback devices, light indicators, and the like.
  • Mobile device 200 also includes various communication devices 246 that are operativeiy coupled to the controller.
  • Communication devices 248 may, for example, include both an I/O connection 247 that may be wired or wireiessly connected to selected devices such as through IR, USB, or Firewire protocols, a global positioning satellite receiver 248, and a radio receiver 250 which may be configured to communicate over wireless phone and data connections.
  • Communication devices 246 may also include a network interface 252 configured to communicate with a computer network through various means which may include wireless connectivity to a local wireless network, a wireless data connection to a cellular data network, a wired connection to a local or wide area computer network, or other suitable means for transmitting data over a computer network.
  • a network interface 252 configured to communicate with a computer network through various means which may include wireless connectivity to a local wireless network, a wireless data connection to a cellular data network, a wired connection to a local or wide area computer network, or other suitable means for transmitting data over a computer network.
  • Mobile device 200 also includes a battery 254 and possibly a charging system.
  • Battery 254 may be charged through a transformer and power cord or through a host device or through a docking station. In the cases of the docking station, the charging may be transmitted through electrical ports or possibly through an inductance charging means that does not require a physical electrical connection to be made.
  • the various aspects, features, embodiments or implementations of the invention described above can be used alone or in various combinations.
  • the methods of this invention can be implemented by software, hardware or a combination of hardware and software.
  • the invention can also be embodied as computer readable code on a computer readable medium.
  • the computer readable medium is any data storage device that can store data which can thereafter be read by a computer system, including both transfer and non-transfer devices as defined above. Examples of the computer readable medium include read-only memory, random access memory, CD-ROMs, flash memory cards, DVDs, magnetic tape, optical data storage devices, and carrier waves.
  • the computer readable medium can also be distributed over network-coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.
  • System 300 includes a physiologic monitor 310 that includes a display 320, a mobile device 330 that includes a camera, and an analysis server 380 in data communication via network connections 350 and 370 through the Internet 360 with the mobile device 330.
  • System 300 functions to implement the method 400 outlined in Fig. 4, as described in steps 401 through 407.
  • the example system 300 implementing method 400 addresses many of the shortcomings existing with conventional systems and methods. For example, by utilizing an image captured from a physiologic monitor 310, analysis and computation of hemodynamic parameters is accomplished without the need for additional specialized sensors or catheters. The data is acquired by second hand use (via image capture) of existing sensors employed by a commonly deployed physiologic monitor 310. Furthermore, the use of an app downloaded onto the mobile device 330, typically a smartphone or tablet that is common in the workplace, can significantly reduce the costs associated with specialized equipment, and make deployment much more widespread than otherwise possible with purpose-dedicated equipment.
  • the mobile device 330 is ideally a device such as an iPhone, iPod or IPad from
  • the mobile device 330 is preferably equipped with a built-in camera to allow for easy capture of an image of the display 320 of physiologic monitor 310.
  • the mobile device 330 runs an application that facilitates capture of the physiologic monitor display 320, allows either manual cropping of a physiologic curve including a pulse pressure curve 340 or a plethysmographic curve 345, as shown in Fig.
  • the mobile device 330 communicates with the analysis server 380 over a network connection. As depicted in Fig. 3, this network connection 350 may communicate via the Internet 360, where the analysis server 380 is remotely located ("cioud' -based), and is also capable of two-way communication via a network connection 370 to the Internet.
  • the mobile device 330 could alternatively be implemented using any computing platform that is capable of receiving a captured image of a physiological monitor display 320, cropping the image of the display 320 to extract a physiologic curve, and communicating with the analysis server 380 to send the curve and receive results.
  • step 401 a user with a mobile device equipped with a camera, e.g. smartphone, IPod, iPad, tablet, or similar such device, opens the app that has previously been loaded on the device.
  • step 402 the user uses the mobile device's camera to take a picture of the screen of a physiologic monitoring system that includes either a pulse pressure curve 340 or a plethysmographic curve 345.
  • the app can automatically select the curve if it is in red.
  • step 403 may directly crop the curve from the image. This is depicted in Fig. 3, where the mobile device 330's touch display is used by the user with cropping brackets to select the relevant physiological curve 340.
  • automatic selection can be performed by the analysis server 380. in such an implementation, the mobile device 330 would skip step 404 and, after capture in step 402 and entry of parameters in step 404 (described below), upload the uncropped image of display 320 to the analysis server 380, which would perform step 403 in automatic fashion as described above before engaging in analysis.
  • step 404 the user optionally supplies the heart rate, maximum blood pressure, and minimum blood pressure, which are used by the system to estimate cardiac output. If these parameters are not supplied, only the pulse pressure variation will be computed.
  • the app uploads the image to an analysis server 380 in step 405.
  • the analysis server 380 analyzes the image, step 408, which will be described in greater detail with reference to Fig. 5, and finally in step 407, the analysis server 380 returns the analysis results to the app for viewing and utilization by the user.
  • the user can check the analysis quality by viewing the computed hemodynamic parameters and graphs based on the parameters generated by the app or, optionally, the analysis server 380. Users can also plot the time series of the different parameters, and calculate derivative parameters such as the cardiac index.
  • Fig. 3 depicts the analysis server 380 as being located on the Internet 380.
  • the analysis server 380 can also be implemented using an internet-based cloud service, a remotely placed server, or a server placed locally on a network owned by the care facility utilizing the disclosed invention. Having a cloud-based implementation perform the analysis provides benefits such as simplification of the software requirements on the mobile device 330, generally increased analysis speed, and ease of keeping the analysis software up-to-date.
  • Such analysis server 380 if not implemented in a cloud-based manner, can be implemented using dedicated, discrete computer hardware of suitable specifications, or in a virtuaiized server environment. Alternatively, for locations where a continuous network connection is not feasible, and given a mobile device 330 of suitable processing power, the app itself could perform the analysis locally on the mobile device 330, obviating the need for an analysis server 380.
  • analysis method 500 the processing steps taken by the analysis server 380 in analyzing a suitable physiologic curve, will now be described.
  • a two-dimensional signal must be extracted, with the x-axis being the time of the pulse pressure curve, and the y-axis being the pressure level.
  • the two- dimensional image is analyzed with respect to columns of pixels.
  • step 501 the image is converted from color to grayscale to simplify analysis.
  • a single channel of color e.g. the red channel, could be utilized if conversion to grayscale is not feasible.
  • step 502 simplifies each pixel in the image to a single numeric value representing its intensity, with lower values representing darker pixels, and higher values corresponding to brighter, higher intensity pixels.
  • the physiological curve signal is obtained by determining the pixel of maximum intensity value in each column of the image (also and interchangeably referred to herein as a "point" along the pulse pressure curve signal). This is accomplished by analyzing the first column of the image and determining which row contains the pixel with the highest value.
  • step 502 false high points are avoided by taking the number of rows in the image and multiplying that number by a suitable constant, thereby creating a subset window above and below the row location of the maximum intensity value in which to choose the maximum intensity value for the next pixel column.
  • step 504 any points at the highest value of the number of rows are eliminated.
  • An example of this method being applied will better demonstrate its operation: if the image to be analyzed has 600 rows, a subset window of 120 (600 * .2) would be utilized, if the pixel of maximum intensity value in column one is located in row 252, only the pixels in rows 132 through 372 of the second column (252 +/- 120) will be evaluated, and the pixel of maximum intensity will be selected from that range. For the third column, the pixels in the rows +/- 120 from the row of the pixel of maximum intensity selected in the second column will be evaluated, and so forth until all columns have been evaluated, resulting in an x-y signal representative of the physiological curve.
  • multiplier 0.2 was used in this example; this value was empirically determined to optimize performance of the analysis. However, it will be appreciated that there are a range of values that will work, and depending on the cleanliness and quality of the image to be analyzed, different values may yield more accurate results.
  • the multiplier may either be preset into the system or made user-adjustable if greater user control over the performance of the image analysis is desired. These parameters may also be preset with several value sets that are tuned to achieve optimal results depending on whether a pulse pressure curve or a p!ethysmographic curve is utilized.
  • step 505 two smoothed signals are generated from the original signal, the first using a 50- point average, and the second using a three-point average.
  • the averaging values of 50 and three points were determined empirically to be optimal; however, a range of values are usable, and these values may be made user-adjustable if the ability for the user to fine-tune the performance of the analysis is desired.
  • Peak detection in step 506 is carried out by first analyzing the 50-point smoothed signal. If a given point value is higher than the points of the five preceding columns and the five succeeding columns it is considered a peak.
  • the value of five for preceding and succeeding columns is empirically determined, and may be varied to tune the efficiency of peak detection.
  • the size of each physiological cycle is calculated in step 507 by taking the mean of the differences between two peaks.
  • step 508 the 3-point smoothed signal is searched for the maximum value that is located between each peak detected in step 508 +/- the size of the cycle between the peaks determined in step 507, divided by 2.
  • the signal is searched for a minimum value between each peak minus the size of the physiological cycle divided by 2, and minus the physiological cycle divided by 3 and the peak plus the size of the physiological cycle divided by 2.
  • the angle of a line drawn through the peaks is calculated, and used in step 509 to horizontaiize the three-point smoothed signal.
  • the exact peak locations are determined from the horizontalized three-point smoothed signal in step 510.
  • step 512 the location of the dicrotic wave is detected by rotating the descending segment of each cycle, and applying a rotation that allows detection of a minimum point that is at least a specified minimum distance from the end of the descending cycle segment.
  • the signal is iteratively rotated and analyzed until an angle is employed that results in the dicrotic wave appearing as a minimum point located at least the specified minimum distance from the end of the descending cycle segment.
  • rotations may optionally be limited to 30 degrees, 45 degrees, and 50 degrees, which have been empirically determined to yield useful results.
  • the specified minimum distance is preferably half the length of the descending segment, but may optionally be set by the user should user control over algorithm fine tuning be desired.
  • step 513 the maximum slope of the descending segment of each cycle Is computed by determining the angle between two points that are ideally 20 pixel columns apart. This number has been determined to yield good results when employed on signals of varying quality that may result for varying quality source images. However, it can be made user-adjustable if greater user control over the analysis performance is desired.
  • step 514 the cardiac output is estimated by determining the area under each cycle up to the dicrotic wave and dividing the result by 500.
  • Prior art implementations use several points extracted from pulse pressure signals to determine this area. However, it has been determined empirically that simply using a constant achieves an accurate estimate while cutting down on analysis complexity. The constant of 500 has been determined to yield good results, but this value could be made user adjustable should greater control over analysis performance be desired.
  • the server returns the result to the user via the app, as detailed above in the description of Fig. 4.
  • Figs. 6A and 6B two examples of physiological curves 600 and 601 such as would be useful in analysis method 500 are depicted. Both curves include a peak 610 and minimums 620.
  • the dicrotic wave, used in method 500 to estimate cardiac output, is shown as range 630 in each example curve.
  • physiological curve 600 the dicrotic wave range 630 is seen as the portion following the peak where the curve transitions to a shallow decay from the initial steep drop coming from peak 610, and lasts until the second minimum 620, which marks the start of a new wave cycle.
  • physiological curve 601 a dicrotic notch 640 is clearly visible, which can be detected to help connote the start of the dicrotic wave range 630.
  • the foregoing methods can be adapted to analyze a video clip of a physiologic monitors pulse pressure curve, as opposed to a single picture, by first extracting a frame from the video for analysis, in such an implementation, the extracted frame serves as the still image to be analyzed, with the frame either selected automatically by software, or by the user.
  • the above-mentioned analysis parameters and constants can be adjusted as necessary to optimize analysis of a plethysmography waveform as needed.
  • inventions described in this application may be made by a variety of industrial processes, including by various mechanical, electrical and software development techniques. Further, the inventions described herein may be used in industrial contexts, including improving health and patient care delivery endeavors.
  • the system may include a physiologic monitor attached to a patient, an Internet-connected mobile device equipped with a camera capable of capturing an image of the physiologic monitor display, and a corresponding Internet-connected analysis server capable of communicating with the mobile device for analyzing the display image and returning analysis results to the mobile device.
  • the mobile device allows the user to crop out the relevant portion of the display image, specifically a physiological curve, and then supplies the extracted curve to the analysis server.
  • the server analyzes the extracted curve to determine relevant hemodynamic parameters, which are then supplied back to the mobile device.
  • the mobile device may be programmed to automatically extract the relevant curve, or the analysis server may perform automatic curve extraction.
  • the mobile device itself may perform all extraction and analysis, without reliance on a separate network-connected server.
  • Applicant(s) reserves the right to submit claims directed to combinations and subcombinations of the disclosed inventions that are believed to be novel and non-obvious. Inventions embodied in other combinations and subcombinations of features, functions, elements and/or properties may be claimed through amendment of those claims or presentation of new claims in the present application or in a related application. Such amended or new claims, whether they are directed to the same invention or a different invention and whether they are different, broader, narrower or equal in scope to the original claims, are to considered within the subject matter of the inventions described herein.

Abstract

L'invention concerne des systèmes et des procédés qui permettent d'estimer des paramètres hémodynamiques à partir d'images de courbe physiologique. Un dispositif mobile capture des images d'un dispositif d'affichage de dispositif de surveillance physiologique, lesdites images étant utilisées pour extraire la courbe physiologique pertinente et la téléverser sur un serveur d'analyse pour le traitement et l'estimation de paramètres hémodynamiques, dans certains exemples, le dispositif mobile, qui est connecté à Internet, exécute une application dédiée, et, à son tour, se connecte à un serveur d'analyse connecté à Internet, dans certains autres exemples, le système peut être mis en œuvre à l'aide d'un ordinateur quelconque qui est capable de prendre une image, d'extraire une courbe physiologique et de la téléverser sur un service de réseau pour une analyse. Dans encore d'autres exemples, une analyse peut être effectuée par le dispositif mobile au lieu de par l'intermédiaire d'un serveur à distance.
PCT/IB2015/000821 2014-05-29 2015-05-12 Systèmes et procédés pour estimer des paramètres hémodynamiques à partir d'une image de courbe physiologique WO2015181622A1 (fr)

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Cited By (2)

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Publication number Priority date Publication date Assignee Title
CN109480812A (zh) * 2018-10-09 2019-03-19 江西师范大学 一种基于物联网通讯的脉搏健康数据管理系统
WO2019122406A1 (fr) 2017-12-22 2019-06-27 Assistance Publique - Hopitaux De Paris Méthode de mesure de la pression artérielle moyenne

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
ANONYMOUS: "Capstesia App Anestesia", 8 April 2014 (2014-04-08), XP002743657, Retrieved from the Internet <URL:http://www.androidpit.es/aplicacion/com.simu.capstesia> [retrieved on 20150826] *
CAPSTESIA APP ANESTESIA: "IntroducciOn Capstesia castellano", 8 January 2014 (2014-01-08), pages 20150827, XP054976033, Retrieved from the Internet <URL:https://www.youtube.com/watch?v=ZQwG7XpuOis> [retrieved on 20150827] *
CECCONI ET AL., CRITICAL CARE, vol. 17, 2013, pages 209

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019122406A1 (fr) 2017-12-22 2019-06-27 Assistance Publique - Hopitaux De Paris Méthode de mesure de la pression artérielle moyenne
US11638529B2 (en) 2017-12-22 2023-05-02 Assistance Publique—Hopitaux de Paris System for measuring the mean arterial pressure
CN109480812A (zh) * 2018-10-09 2019-03-19 江西师范大学 一种基于物联网通讯的脉搏健康数据管理系统

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