DESC:
FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:
MULTI-MODE PHYSIOLOGICAL SIGNALS BASED
BIOMETRIC IDENTIFICATION

Applicant:
Tata Consultancy Services Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Nirmal Building, 9th floor,
Nariman point, Mumbai 400021,
Maharashtra, India

The following specification particularly describes the disclosure and the manner in which it is to be performed.
CROSS-REFERENCE TO RELATED APPLICATIONS AND PRIORITY
[001] The present application claims priority to a Patent Application Serial Number 4986/MUM/2015, filed before Indian Patent Office on Dec 31, 2015 and incorporates that application in its entirety.

TECHNICAL FIELD
[002] The present subject matter described herein, in general, relates to authentication of an individual’s identity and more particularly systems and methods to multi-mode authentication and certification of an individual’s identity by collecting and correlating heart signal waveforms taken from different parts of the human body.

BACKGROUND
[003] In recent years, individual’s identity recognition has become very important in various fields of industry. Identity recognition and authentication, criminal biological certification, safety and security at work and registration at work, plays an important role in a number of scenes of life.

[004] Some advanced techniques for approvals and matching biometric identity of an individual has been developed in the art. Few examples include a fingerprint recognition, retinal and iris recognition, facial recognition, and voice recognition. However, these techniques are too complex and have unfriendly acquisition aspects. Fingerprint recognition is an established and most mature technology, however it has several limitations. The fingerprint recognition system tends to be incorrect and cannot match the existence of a physical fingerprint owner if the person’s finger print forgery. Face recognition is also a known technique, however, it fails where an individual have gone through a plastic surgery to his face. Also, the face recognition system is not as unique as iris scan or DNA and does not allow for changes in appearance due to ageing.

[005] Another identity recognition techniques involves the use of retinal scanning technology. However, the retinal scanning technology requires a high precision optical sensor, it cannot be said even as easy to use. They require operation to the human eye. The Human eye is a very sensitive organ of the head and the people may try to avoid to undergo any kind of surgery. In addition to that the optical sensors are expensive and fragile.

[006] Various other techniques have been used in the past for the identification and authentication of human body, but none of them provides an effective method for the same. Therefore is a need of a system and method for multi-mode authentication and certification of an individual’s identity.

OBJECTIVE
[007] In accordance with the present disclosure, the primary objective is to provide a system and a method for multi-modal based authentication and certification of an individual’s biometric identity.

[008] Another objective of the disclosure is to provide a system and a method for enhancing security using simultaneous measurement and correlation of features of the heart signal waveforms.

[009] Other objectives and advantages of the present disclosure will be more apparent from the following description when read in conjunction with the accompanying figures, which are not intended to limit the scope of the present disclosure.

SUMMARY
[0010] The following presents a simplified summary of some embodiments of the disclosure in order to provide a basic understanding of the embodiments. This summary is not an extensive overview of the embodiments. It is not intended to identify key/critical elements of the embodiments or to delineate the scope of the embodiments. Its sole purpose is to present some embodiments in a simplified form as a prelude to the more detailed description that is presented below.

[0011] The present subject relates to a method and system for authentication and certification of an individual’s identity by collecting and correlating the features of the heart signal waveforms taken from different parts of the human body. Most importantly the heart signal based identification is based on involuntary functions of the human body i.e. the heart signal cannot be altered by the individual and therefore cannot be used in forgery unlike finger prints or face.

[0012] According to an embodiment, the system comprises two sources, a memory, a processor, a selection module, a tracking module, an analysis module and a correlation module. The plurality of sensors of the system capture two heart signal waveforms simultaneously from two different parts of the human body. The selection module of the system selects a portion of the videos recorded by the two sources. The tracking module of the system tracks features of the selected portion of the videos. The analysis module of the system analyze features of the heart signal waveforms of the selected portion of the videos recorded by the two sources. The correlation module takes the analyzed features of the heart signal waveform of the recorded videos by the first source of the system as a first input. Similarly, the correlation module also takes the analyzed features of the heart signal waveform of the recorded videos by the second source of the system as a second input. The correlation module of the system analyze the inputs and provides output as a result of approval or discard the authentication of individual’s identity.

[0013] In another aspect, a method to authenticate biometric identity of an individual. the method comprising capturing a first video of a first body part and a second video of a second body part of the individual using a plurality of sensors, selecting a first region of the captured first video and a second region of the captured second video of the first and second body parts of the individual using selection module, tracking one or more features of the selected first region of the first video and one or more features of the selected second region of the second video using a tracking module, measuring one or more parameters of the tracked one or more features of the first video and one or more parameters of the tracked one or more features of the second video using an analysis module and correlating at least one parameter of the analyzed one or more parameters of the first video with at least one parameter of the analyzed one or more parameters of the second video using a correlating module, wherein the correlation authenticates biometric identity of the individual.

BRIEF DESCRIPTION OF THE FIGURES
[0014] The embodiments herein will be better understood from the following detailed description with reference to the drawings, in which:

[0015] Figure 1 is a block diagram showing a system multi-mode authentication and certification of an individual’s identity by correlating features of physiological signals of the human body.
[0016] Figure 2 is a schematic diagram showing a system for measuring features of the physiological signals of the different parts of the human body.

[0017] Figure 3 is a schematic diagram showing features of the heart signal waveforms.

[0018] Figure 4 is a schematic diagram showing a matrix of the correlation coefficients of the heart rates of face and finger of the human body.

[0019] Figure 5 illustrates a flow diagram showing a method for multi-mode authentication and certification of an individual’s identity by correlating features of physiological signals of the human body.

DETAILED DESCRIPTION
[0020] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words "comprising," "having," "containing," and "including," and other forms thereof, are intended to be equivalent in meaning and be open ended in that an item or commodities following any one of these words is not meant to be an exhaustive listing of such item or commodities, or meant to be limited to only the listed item or commodities.

[0021] It must also be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the preferred, systems and methods are now described. In the following description for the purpose of explanation and understanding reference has been made to numerous embodiments for which the intent is not to limit the scope of the disclosure.

[0022] One or more components of the disclosure are described as module for the understanding of the specification. For example, a module may include self-contained component in a hardware circuit comprising of logical gate, semiconductor device, integrated circuits or any other discrete component. The module may also be a part of any software program executed by any hardware entity for example processor. The implementation of module as a software program may include a set of logical instructions to be executed by a processor or any other hardware entity.

[0023] The disclosed embodiments are merely exemplary of the disclosure, which may be embodied in various forms.

[0024] The elements illustrated in the Figures interoperate as explained in more detail below. Before setting forth the detailed explanation, however, it is noted that all of the discussion below, regardless of the particular implementation being described, is exemplary in nature, rather than limiting. For example, although selected aspects, features, or components of the implementations are depicted as being stored in memories, all or part of the systems and methods consistent with the attrition warning system and method may be stored on, distributed across, or read from other machine-readable media.

[0025] Method steps of the disclosure may be performed by one or more computer processors executing a program tangibly embodied on a computer-readable medium to perform functions of the disclosure by operating on input and generating output. Suitable processors include, by way of example, both general and special purpose microprocessors. Generally, the processor receives (reads) instructions and data from a memory (such as a read-only memory and/or a random access memory) and writes (stores) instructions and data to the memory. Storage devices suitable for tangibly embodying computer program instructions and data include, for example, all forms of non-volatile memory, such as semiconductor memory devices, including EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROMs. Any of the foregoing may be supplemented by, or incorporated in, specially-designed ASICs (application-specific integrated circuits) or FPGAs (Field-Programmable Gate Arrays). A computer can generally also receive (read) programs and data from, and write (store) programs and data to, a non-transitory computer-readable storage medium such as an internal disk (not shown) or a removable disk.

[0026] In view of the foregoing, an embodiment herein provides a system and a method for authenticating biometric identity of an individual. It includes multi-mode authentication and certification of an individual’s identity by collecting and correlating features of heart signal waveforms from two different parts of the human body. The different body parts may be selected from chest, frontal face, finger, leg, calf, ear lobe etc. of the human body via different sensing devices. It should be appreciated that the heart signal based identification is based on involuntary functions of the human body i.e. the heart signal cannot be altered by the individual and therefore cannot be used in forgery unlike finger prints or face.

[0027] Referring figure 1, the system 100 includes a processor 102, a memory 104 communicatively coupled to the processor 102 and the memory 104 contains instructions that are readable by the processor 102, a plurality of sensors 106, a selection module 108, a tracking module 110, an analysis module 112 and a correlation module 114.

[0028] According to the preferred embodiment of the disclosure, the plurality of sensors 106 of the system 100 are configured to capture a first video and a second video of the individual, wherein a first video is of a first part of the individual’s body and a second video is of a second part of the individual’s body simultaneously. The plurality of sensors 106 include camera, mobile phone camera, and a wearable device having a camera and pulse oximeter. People cannot mimic the physiological signals unlike face masking/surgeries and finger print forgeries etc. for breaching security.

[0029] In the preferred embodiment of the disclosure, the selection module 108 of the system 100 is configured to select a first region of the captured first video and a second region of the captured second video of the individual. The one or more features of the first video and one or more features of the second video are characterized by physiological signal. The physiological signals obtained from the two different body parts of the individual are used for simultaneous measurement of waveforms and correlation between the features of the waveform.

[0030] In the preferred embodiment of the disclosure, the tracking module 110 of the system 100 configured to track one or more features of the selected first region of the first video and one or more features of the selected second video. The tracking module 110 is further configured to determine a maximum distance travelled by each point between two consecutive frames of the video. Generally, the selected regions of the first video and second video include a plurality of features such as pulse rate, HRV parameters, RR intervals, waveform matching etc.

[0031] In the preferred embodiment of the disclosure, the analysis module 112 of the system 100 configured to analyze one or more parameters of the tracked one or more features of the first video and one or more features of the second video of the individual, wherein the analyzed one or more parameters includes heart rate or pulse rate of the heart signal waveform. The analysis module 112 is further configured to detect peaks of the one or more features of the first video and the one or more features of the second video and to determine the heart rate or pulse rate of the heart signal waveform based on the detected peaks of the one or more features.

[0032] In the preferred embodiment of the disclosure, the correlation module 114 of the system 100 is configured to correlate at least one parameter of the analyzed one or more parameters of the first video with at least one parameter of the analyzed one or more parameters of the second video. Therefore, the output of the correlation module 114 authenticates biometric identity of the individual. It should be appreciated that the first input and the second input to the correlation module 114 should be of same nature. The output of the correlation module 114 of the system 100 will either approves or discard the authentication and certification of an individual’s identity.

[0033] In an example, as given in figure 2, to elaborate the preferred embodiment of the disclosure, a mobile phone having a front camera and a rear camera to capture videos. The mobile phone records simultaneously videos of two different body parts of the human body. The front camera of the mobile phone records a video of frontal face of the human body and simultaneously the rear camera of the mobile phone records a video of index finger. The pulse rate of the heart signal waveforms can be extracted from sequence of images of the recorded video of the frontal face, as one part of the human body and video of index finger as another part of the same human body. The extracted pulse signal by front camera takes as first input and the extracted pulse of the rear camera takes as a second input for correlation analysis. For the correlation analysis of the pulse signals, a standard correlation plot, such as Bland-Altmann plot, and the correlation coefficient threshold 0.92 may be used. The correlation analysis is performed on an average pulse signal values obtained from two cameras of the mobile phone. Since people cannot mimic the physiological signals, therefore the correlation analysis result of the pulse signal of the heart signal waveforms will either approve or discard the authentication and certification. It should be appreciated that in the disclosure, heart signal waveforms are taken as physiological signals of the human body. In this example the sequence of two instant heart rates extracted from the two heart signal waveforms of different parts of the human body as given in Figure 3. Pearson correlation coefficient is used as correlation coefficient of the correlation analysis, where 1 (One) is total positive correlation and 0 (Zero) is no correlation and -1 (Minus One) is total negative correlation. In the figure 4, a matrix of correlation coefficients, obtained from two heart signal waveforms of two different parts of human body, which can be seen across the diagonal elements of the matrix.

[0034] In the preferred embodiment of the disclosure, the extraction of pulse rate from captured the first video and the second video of the individual is either by measuring head motion caused by Newtonian reaction to the influx of heart at each pulse or color intensity due to heart flow in the human body.

[0035] Referring figure 5 illustrates a method 200 to authenticate biometric identity of an individual. It includes multi-mode authentication and certification of an individual’s identity by collecting and correlating features of the heart signal waveforms from different parts of the human body.

[0036] In the preferred embodiment of the disclosure, at step 202, where the method captures a first video of a first body part and a second video of a second body part of the individual using a plurality of sensors 106. At least one of the captured first video and second video includes head motion of the individual. The plurality of sensors 106 include camera, mobile phone camera, and a wearable device having a camera and pulse oximeter. People cannot mimic the physiological signals unlike face masking/surgeries and finger print forgeries etc. for breaching security.

[0037] In the preferred embodiment of the disclosure, at step 204, where the method selects a first region of the captured first video and a second region of the captured second video of the first and second body parts of the individual using selection module 108. The one or more features of the first video and the one or more features of the second video are characterized by a plurality of physiological signals. The physiological signals obtained from the two different body parts of the individual are used for simultaneous measurement of waveforms and correlation between the features of the waveform.

[0038] In the preferred embodiment of the disclosure, at step 206, where the method tracks one or more features of the selected first region of the first video and one or more features of the selected second region of the second video using a tracking module 110. Generally, the selected regions of the first video and second video include a plurality of features such as pulse rate, HRV parameters, RR intervals, waveform matching etc.

[0039] In the preferred embodiment of the disclosure, at step 208, where the method analyzes one or more parameters of the tracked one or more features of the first video and one or more parameters of the tracked one or more features of the second video using an analysis module 112. Further, the analysis module 112 is to detect peaks of the one or more features of the first video and the one or more features of the second video and to determine the heart rate or pulse rate of the heart signal waveform based on the detected peaks of the one or more features.

[0040] In the preferred embodiment of the disclosure, at step 210, where the method is correlating at least one parameter of the analyzed one or more parameters of the first video with at least one parameter of the analyzed one or more parameters of the second video using a correlating module 114. Finally, the correlation authenticates biometric identity of the individual. It should be appreciated that the first input and the second input to the correlation module 114 must be of same nature. The correlation output will either approves or discard the authentication and certification of an individual’s identity.

[0041] The preceding description has been presented with reference to various embodiments. Persons having ordinary skill in the art and technology to which this application pertains will appreciate that alterations and changes in the described structures and methods of operation can be practiced without meaningfully departing from the principle, spirit and scope.

,CLAIMS:
1. A computer implemented method to authenticate biometric identity of an individual, the method comprising:
capturing a first video of a first body part and a second video of a second body part of the individual using a plurality of sensors;
selecting a first region of the captured first video and a second region of the captured second video of the first and second body parts of the individual using selection module;
tracking one or more features of the selected first region of the first video and one or more features of the selected second region of the second video using a tracking module;
analyzing one or more parameters of the tracked one or more features of the first video and one or more parameters of the tracked one or more features of the second video using an analysis module; and
correlating at least one parameter of the analyzed one or more parameters of the first video with at least one parameter of the analyzed one or more parameters of the second video using a correlating module, wherein the correlation authenticates biometric identity of the individual.

2. The method claimed in claim 1, wherein at least one of the captured first video and second video includes head motion of the individual.

3. The method claimed in claim 1, wherein the one or more features of the first video and the one or more features of the second video are characterized by a plurality of physiological signals.

4. The method claimed in claim 1, wherein the analyzing of one or more parameters of the tracked one or more features include heart rate or pulse rate of the heart signal waveform.

5. The method claimed in claim 1, wherein the tracking of the one or more features include determining a maximum distance travelled by each point between consecutive frames of the video.
6. The method claimed in claim 1, wherein the analyzing of the one or more features further includes:
detecting peaks of the heart signal waveforms; and
determining the pulse rate or heart rate of the heart signal waveforms.

7. A system for authenticating biometric identity of an individual, the system comprising:
a plurality of sensors to capture a first video and a second video of the individual, wherein a first video is of a first part of the individual’s body and a second is of a second part of the individual’s body;
a selection module configured to select a first region of the captured first video and a second region of the captured second video of the individual;
a tracking module configured to track one or more features of the selected first region of the first video and second region of the second video;
an analysis module configured to analyze one or more parameters of the tracked one or more features of the first video and the second video of the individual, wherein the analyzed one or more parameters includes heart rate or pulse rate of the heart signal waveform; and
a correlation module configured to correlate at least one parameter of the analyzed one or more parameters of the first video with at least one parameter of the analyzed one or more parameters of the second video, wherein output of the correlation module authenticate biometric identity of the individual.

8. The system claimed in claim 7, wherein the plurality of sensors include camera, mobile phone camera, a wearable device having a camera and pulse oximeter.

9. The system claimed in claim 7, wherein the one or more features of the first video and one or more features of the second video are characterized by physiological signal.

10. The system claimed in claim 7, wherein the tracking module is further configured to determine a maximum distance travelled by each point between two consecutive frames of the video.
11. The system claimed in claim 7, wherein the analysis module is further configured to detect peaks of the one or more features of the first video and the one or more features of the second video; and
determine the heart rate or pulse rate of the heart signal waveform based on the detected peaks of the one or more features.