EP3432790A1 - System and methods for authenticating vital sign measurements for biometrics detection using photoplethysmography via remote sensors - Google Patents
System and methods for authenticating vital sign measurements for biometrics detection using photoplethysmography via remote sensorsInfo
- Publication number
- EP3432790A1 EP3432790A1 EP17769567.3A EP17769567A EP3432790A1 EP 3432790 A1 EP3432790 A1 EP 3432790A1 EP 17769567 A EP17769567 A EP 17769567A EP 3432790 A1 EP3432790 A1 EP 3432790A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- heart rate
- rate value
- user
- fhrv
- shrv
- 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.)
- Withdrawn
Links
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Classifications
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- 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
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- A61B5/7278—Artificial waveform generation or derivation, e.g. synthesising signals from measured signals
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- A—HUMAN NECESSITIES
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- 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
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02405—Determining heart rate variability
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- 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
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02416—Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
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- A61B5/1171—Identification of persons based on the shapes or appearances of their bodies or parts thereof
- A61B5/1176—Recognition of faces
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- A—HUMAN NECESSITIES
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- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/70—Multimodal biometrics, e.g. combining information from different biometric modalities
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
- H04L63/0861—Network architectures or network communication protocols for network security for authentication of entities using biometrical features, e.g. fingerprint, retina-scan
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- H—ELECTRICITY
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- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/06—Authentication
- H04W12/065—Continuous authentication
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- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
- A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
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- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- 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
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
- A61B5/6898—Portable consumer electronic devices, e.g. music players, telephones, tablet computers
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/15—Biometric patterns based on physiological signals, e.g. heartbeat, blood flow
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- G—PHYSICS
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- 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
Definitions
- the present invention relates generally to the field of object class detection and authentication. More specifically, the present invention relates to a biometrics recognition and authentication system and methods based on remote photo-plethysmography measuring and analysis of skin color variations for observing human vital signs using non-invasive, remote, passive sensors of a mobile device, i.e. camera, including, but not limited, average heart rate, heart rate variation and respiratory rate.
- a biometrics recognition and authentication system and methods based on remote photo-plethysmography measuring and analysis of skin color variations for observing human vital signs using non-invasive, remote, passive sensors of a mobile device, i.e. camera, including, but not limited, average heart rate, heart rate variation and respiratory rate.
- Biometrics detection is a rapidly growing research area.
- Biometrics detection has several applications in many areas such as intelligent human-computer interfaces, crowd surveillance, security authentication, video coding, video conferencing, and content-based image retrieval.
- the human face is a dynamic object and has a great variability in its appearance, which makes biometrics detection become a difficult problem in computer vision and many other applications.
- some efficient methods have been developed. Traditionally, methods that focus on facial landmarks (such as eyes, nose, etc.), that detect face-like colors in circular regions, or that use standard feature templates, were used to detect faces. However, these attempts don't improve the accuracy of biometrics detection fundamentally.
- Biometrics detection is still a challenge because of several difficulties, such as variable face, orientations, different face sizes, partial occlusions of faces in an image, and changeable lighting conditions.
- various systems and methods for indicating skin color characteristics exist in the art.
- Robust biometrics detection using the hausdorff, by Jesorsky, O., Kirchberg, K.J., Frischholz, R.W. discloses a shape comparison approach to achieve fast, accurate biometrics detection that is robust to changes in illumination and background.
- the proposed method is edge-based and works on grayscale still images.
- the Hausdorff distance is used as a similarity measure between a general face model and possible instances of the object within the image.
- Feature-based biometrics detection against skin-color like backgrounds with varying illumination by Hu, W.C., Yang, C.Y., Huang, D.Y., Huang, C.H., discloses a three-stage scheme for real-time reliable biometrics detection is presented.
- the proposed three-stage scheme is a feature-based method that is mainly based on skin color and facial features. Skin regions are obtained using a YCbCr skin-color model in the first stage. In the second stage, a face template measure is used to obtain face candidates and then a suitable face box is used to effectively remove non-face regions from the face candidates. Finally, facial features are measured to detect faces from face candidates in the third stage.
- Biometrics detection technology based on skin color segmentation and template matching by Chen, A. P., Pan, L., Tong, Y.B., Ning, N., discloses a methodology for biometrics detection from video recordings of the human face and demonstrates an implementation using a digital camera with ambient daylight providing illumination by obtaining the accurate binary image.
- Photoplethysmography imaging as a new research field is used to extract physiological information in recent years.
- volume of the blood in the blood vessels is constantly changing during the cardiac circulation system and human face is a part of a living body, there is a constant blood flow in the subject's face region.
- Photoplethysmography corresponds to the variations in reflected light due to cardiovascular blood volume pulse.
- HR heart rate
- Non-contact, automated cardiac pulse measurements using video imaging and blind source separation by Ming-Zher Poh, Daniel J. McDuff, and Rosalind W. Picard, discloses color video recordings of the human face and is based on automatic face tracking along with blind source separation of the color channels into independent components.
- the cardiac pulse rate extracted from videos recorded by a basic webcam is compared to an FDA-approved finger blood volume pulse (BVP) sensor and achieved high accuracy and correlation even in the presence of movement artifacts.
- BVP finger blood volume pulse
- the pulsatile signal extracted from face as a unique feature may be used to improve the robustness of non-contact biometrics detection by comparing and correlating it to the pulsatile signal extracted from additional regions of the user's body (such as a fingertip) using a real-time simultaneous PPGi technology via remote sensors of the same mobile device.
- One or more members of a group can be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is herein deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims.
- Fig. 1 presents a high level data flow diagram of the method disclosed by the present invention
- FIG. 2 presents, an example of a generalized presentation of the present invention first heart rate value (FHRV) and said second heart rate value (SHRV) comparison; and
- FIG. 3 presents an embodiment of the system disclosed by the present invention.
- the technology described herein relates to generating, storing and using semantic networks and databases to correlate physiological and psychological states of users and/or groups of users using their voice intonation data analysis.
- the term "user” used interchangeably in the present invention refers hereinafter to any party that employs a biometrics recognition and authentication system based on remote photo- plethysmography measuring and analysis of skin color variations for observing human vital signs using non-invasive, remote, passive sensors of a mobile device, i.e. camera, including, but not limited, average heart rate, heart rate variation and respiratory rate.
- mobile device interchangeably refers, but not limited to such as a mobile phone, laptop, tablet, wearable computing device, cellular communicating device, digital camera (still and/or video), PDA, computer server, video camera, television, electronic visual dictionary, communication device, personal computer, and etc.
- the present invention means and methods are performed in a standalone electronic device comprising at least one screen. Additionally or alternatively, at least a portion of such as processing, memory accessible, databases, includes a cloud-based platform, and/or web-based platform.
- the software components and/or image databases provided are stored in a local memory module and/or stored in a remote server.
- PPG photoplethysmography
- PPGi photoplethysmography imaging
- the implemented authenticating vital sign measurements for biometrics detection of a user using photoplethysmography (PPG) and photoplethysmography imaging (PPGi) analyses via remote sensors of a mobile device method can be executed using a computerized process according to the example method 100 illustrated in FIG. 1.
- the method 100 commences by simultaneously activating at least one front camera sensor, at least one back camera sensor of the mobile device at step 102. Video of a first body region of the user via at least one first front camera sensor and a second body region of said user via said at least one back camera sensor obtained at steps 104 and 106, respectively.
- Extraction of a first pulsatile signal of the user using photoplethysmography imaging (PPGi) analysis of the first body region of said user in said video is carried out at step 108.
- extraction of a second pulsatile signal corresponding to the second body region of the user (step 110).
- a first heart rate value (FHRV) based on photoplethysmography imaging analysis of video of the first body area is calculated at step 112.
- the similar procedure concerning the second body area in order to obtain a second heart rate value (SHRV) is carried out at step 114.
- the purpose of the present procedure is to obtain a comparative output value (COV) between the first heart rate value (FHRV) and the second heart rate value (SHRV). Vitality is authenticated if the first heart rate value (FHRV) and second heart rate value (SHRV) coincide. Otherwise, the procedure is repeated.
- COV comparative output value
- a generalized presentation of the present invention first heart rate value (FHRV) and said second heart rate value (SHRV) comparison according to the example system 200 illustrated in FIG. 2.
- the system if configured to present to the user a comparison output value (COV) between said first heart rate value (FHRV) and said second heart rate value (SHRV).
- the comparison output value (COV) between said first heart rate value (FHRV) and said second heart rate value (SHRV) is used to detect and authenticate the body regions of the user and/or used to detect and authenticate the identity of the user.
- FIG. 3 graphically illustrates, according to another preferred embodiment of the present invention, an example of computerized system for implementing the invention 300.
- the systems and methods described herein can be implemented in software or hardware or any combination thereof.
- the systems and methods described herein can be implemented using one or more computing devices which may or may not be physically or logically separate from each other. Additionally, various aspects of the methods described herein may be combined or merged into other functions.
- the illustrated system elements could be combined into a single hardware device or separated into multiple hardware devices. If multiple hardware devices are used, the hardware devices could be physically located proximate to or remotely from each other.
- the methods can be implemented in a computer program product accessible from a computer-usable or computer-readable storage medium that provides program code for use by or in connection with a computer or any instruction execution system.
- a computer-usable or computer-readable storage medium can be any apparatus that can contain or store the program for use by or in connection with the computer or instruction execution system, apparatus, or device.
- a data processing system suitable for storing and/or executing the corresponding program code can include at least one processor coupled directly or indirectly to computerized data storage devices such as memory elements.
- Input/output (I/O) devices can be coupled to the system.
- Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks.
- the features can be implemented on a computer with a display device, such as an LCD (liquid crystal display), virtual display, or another type of monitor for displaying information to the user, and a keyboard and an input device, such as a mouse or trackball by which the user can provide input to the computer.
- a display device such as an LCD (liquid crystal display), virtual display, or another type of monitor for displaying information to the user
- a keyboard and an input device such as a mouse or trackball by which the user can provide input to the computer.
- a computer program can be a set of instructions that can be used, directly or indirectly, in a computer.
- the systems and methods described herein can be implemented using programming languages such as FlashTM, JAVATM, C++, C, C#, Visual BasicTM, JavaScriptTM, PHP, XML, HTML, etc., or a combination of programming languages, including compiled or interpreted languages, and can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
- the software can include, but is not limited to, firmware, resident software, microcode, etc. Protocols such as SOAP/HTTP may be used in implementing interfaces between programming modules.
- the components and functionality described herein may be implemented on any desktop operating system executing in a virtualized or non-virtualized environment, using any programming language suitable for software development, including, but not limited to, different versions of Microsoft WindowsTM, AppleTM MacTM, iOSTM, AndroidTM, UnixTM/X-WindowsTM, LinuxTM, etc.
- the system could be implemented using a web application framework, such as Ruby on Rails.
- the processing system can be in communication with a computerized data storage system.
- the data storage system can include a non-relational or relational data store, such as a MySQLTM or other relational database. Other physical and logical database types could be used.
- the data store may be a database server, such as Microsoft SQL ServerTM, OracleTM, IBM DB2TM, SQLITETM, or any other database software, relational or otherwise.
- the data store may store the information identifying syntactical tags and any information required to operate on syntactical tags.
- the processing system may use object- oriented programming and may store data in objects.
- the processing system may use an object-relational mapper (ORM) to store the data objects in a relational database.
- ORM object-relational mapper
- an RDBMS can be used.
- tables in the RDBMS can include columns that represent coordinates.
- data representing user events, virtual elements, etc. can be stored in tables in the RDBMS.
- the tables can have pre-defined relationships between them.
- the tables can also have adjuncts associated with the coordinates.
- Suitable processors for the execution of a program of instructions include, but are not limited to, general and special purpose microprocessors, and the sole processor or one of multiple processors or cores, of any kind of computer.
- a processor may receive and store instructions and data from a computerized data storage device such as a read-only memory, a random access memory, both, or any combination of the data storage devices described herein.
- a processor may include any processing circuitry or control circuitry operative to control the operations and performance of an electronic device.
- the processor may also include, or be operatively coupled to communicate with, one or more data storage devices for storing data.
- data storage devices can include, as non-limiting examples, magnetic disks (including internal hard disks and removable disks), magneto- optical disks, optical disks, read-only memory, random access memory, and/or flash storage.
- Storage devices suitable for tangibly embodying computer program instructions and data can also include all forms of non-volatile memory, including, for example, semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.
- the processor and the memory can be supplemented by, or incorporated in, ASICs (application- specific integrated circuits).
- the systems, modules, and methods described herein can be implemented using any combination of software or hardware elements.
- the systems, modules, and methods described herein can be implemented using one or more virtual machines operating alone or in combination with each other. Any applicable virtualization solution can be used for encapsulating a physical computing machine platform into a virtual machine that is executed under the control of virtualization software running on a hardware computing platform or host.
- the virtual machine can have both virtual system hardware and guest operating system software.
- the systems and methods described herein can be implemented in a computer system that includes a back-end component, such as a data server, or that includes a middleware component, such as an application server or an Internet server, or that includes a front-end component, such as a client computer having a graphical user interface or an Internet browser, or any combination of them.
- the components of the system can be connected by any form or medium of digital data communication such as a communication network. Examples of communication networks include, e.g., a LAN, a WAN, and the computers and networks that form the Internet.
- One or more embodiments of the invention may be practiced with other computer system configurations, including hand-held devices, microprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, etc.
- the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a network.
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Abstract
Description
Claims
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US201662311414P | 2016-03-22 | 2016-03-22 | |
PCT/IL2017/050361 WO2017163248A1 (en) | 2016-03-22 | 2017-03-22 | System and methods for authenticating vital sign measurements for biometrics detection using photoplethysmography via remote sensors |
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Publication Number | Publication Date |
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EP3432790A1 true EP3432790A1 (en) | 2019-01-30 |
EP3432790A4 EP3432790A4 (en) | 2019-10-02 |
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EP17769567.3A Withdrawn EP3432790A4 (en) | 2016-03-22 | 2017-03-22 | System and methods for authenticating vital sign measurements for biometrics detection using photoplethysmography via remote sensors |
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EP (1) | EP3432790A4 (en) |
WO (1) | WO2017163248A1 (en) |
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EP4033972A4 (en) * | 2019-12-02 | 2024-01-10 | Binah.Ai Ltd | System and method for physiological measurements from optical data |
JP2023545426A (en) * | 2020-10-09 | 2023-10-30 | ビナー.エーアイ リミテッド | System and method for blood alcohol determination by optical data |
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US20140276104A1 (en) * | 2013-03-14 | 2014-09-18 | Nongjian Tao | System and method for non-contact monitoring of physiological parameters |
US10856747B2 (en) * | 2014-01-07 | 2020-12-08 | Samsung Electronics Co., Ltd. | Method and system for measuring heart rate in electronic device using photoplethysmography |
US20150302158A1 (en) * | 2014-04-21 | 2015-10-22 | Microsoft Corporation | Video-based pulse measurement |
US10028668B2 (en) * | 2014-05-06 | 2018-07-24 | Alivecor, Inc. | Blood pressure monitor |
US9465930B2 (en) * | 2014-08-29 | 2016-10-11 | Dropbox, Inc. | Fingerprint gestures |
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2017
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