Claims:We Claim:

1. A system for tracking a human being by the using real-time bio signals comprising of:

a tracking device comprising of: an Analog digital converter ADC and Digital to Analog converter configured to convert the readings obtained from a Galvanic skin conductor into analog signals, whereby the readings obtained from plurality of emotional parameters are done using a system on a chip (SoC), whereby the SoC is inclusive of: a secured ARM Cortex core configured to protect the device from both internal and external attacks;

a plurality of sensors configured to capture the emotions of the human being to whom the sensors are attached and convert the readings into analog signals through the tracking device, whereby the tracking device takes the readings obtained to the GPRS location using SMS and GSM technologies to the user using a mobile application ; and

a MySQL system for updating a database comprising of: an InnoDB storage engine configured to support SQL transactions; a InnoDB memcached engine configured to access InnoDB through the InnoDB APIs most of which are directly adopted from embedded InnoDB.

2. The system of claim 1, wherein the emotional parameters captured are from at least one of: galvanic skin conductance; blood volume pulse (BVP); and temperature, and emotions are at least one of: anger; fear; stress; sad and the like.

3. The system of claim 1, wherein the tracking device is wearable.

4. The system of claim 1, wherein the Advanced Microcontroller Bus Architecture (AMBA) is configured to establish interconnection amongst the specification for the connection and management of functional elements in SoC designs.

5. The system of claim 1, wherein the application is equipped to receive the SMS and map the coordinates to the existing maps.

6. The system of claim 1, wherein The handler API 508 is configured to run and process the messages from the human being wearing the device to the user receiving the messages.

7. A method for tracking a human being by the using real-time bio signals comprising of:

reading of the Galvanic skin conductance (GSR) sensor input values from the Analog to digital converter (ADC) followed by reading blood volume pulse (BVP) sensor input values and temperature sensor input values from ADC, whereby current location based on latitude and longitude of the human being is deciphered based on the values of BVP, GSR and temperature, whereby upon recording above normal values of the parameters then current location details to the preconfigured mobile numbers, real time data to the databases for history, analytics, and web services are sent to the user with mobile application.

8. The method of claim 7 wherein, the acceptable limits for the sensor input values are:GSR >0.29, if(BVP > 85) and if TEMP < 96.4 degree Fahrenheit.

9. The method of claim 7, wherein human emotion brings conduction in the body which is measured using Ohm’s law. , Description:TECHNICAL FIELD

[0001] The disclosed subject matter generally relates to the field of development of human tracking device using real time bio-signals. More particularly, the present disclosure relates to utilizing bio-signal data to detect an emergency.

BACKGROUND

[0002] Bio-signals are unique to living beings that can be continuously measured and monitored. Emotions are an unstoppable and uncontrollable aspect of human reaction to an action. It is a proved mechanism that encompasses variation in emotions due to different acts like expectations, focus to goals, appraisal and resulting reactions. When human body experiences different emotions like fear, anger, sad, happiness, then there is also change in different bio­ signals, which are flowing, in human body. The various bio-signals are: Galvanic skin conductance (GSR), blood volume pulse (BVP), brain waves (EEG), muscle tension, temperature, and respiration.
[0003] Tracking devices development was started as early as in 2000. Initially, it started only with GPS and transmitting the location using the GPS satellite. Attempts were made using mobile LBS and LCS based technologies in 2011 by Amit and Vineet Kushwaha. To assist with the exact information, at right place in real time with personalized setup and location sensitiveness. Many universities and research organization have started developing trackers using Wireless technologies such as Bluetooth, BLE and GSM. The attempt was made to implement tracking device using GSM and GPS.
[0004] Samuel King Opoku et. al. has developed indoor tracking tool using Bluetooth, GSM and GPS technologies. These mechanisms usually require line- of-sight operations, limited coverage and low-level programming language for accessing Bluetooth signal strength. Some attempts were also made using RFID for tracking the devices that are below 20 meters. Tanu Sharma, Bhanu Kapoor et.al have developed an algorithm using the sensors to capture the data on the human body emotions.
[0005] Capturing and accurate analysis of bio-signals is extremely helpful in analysing difficult situations especially situations where help is needed for the user. There is a need to develop human tracking device which can effectively communicate with end to end users and prevent them from succumbing to emergency situations.

SUMMARY

[0006] Exemplary embodiments of the present disclosure are directed towards a system and method for tracking human beings using real-time bio signals.
[0007] An exemplary object of the present disclosure is directed towards protecting women and children in dangerous situations.
[0008] Another exemplary object of the present disclosure is directed towards estimating emotions accurately.
[0009] Yet another exemplary object of the present disclosure is directed towards constant checking of the battery life of device, and sensor data capturing in various climatic conditions.
[00010] An exemplary aspect of the present subject matter is directed towards an analog digital converter ADC and Digital to Analog converter configured to convert the readings obtained from a Galvanic skin conductor into analog signals, and the readings obtained from emotional parameters are done using a system on a chip (SoC) which has a secured ARM Cortex core to protect the device from both internal and external attacks; a plurality of sensors to capture the emotions of the human being to whom the sensors are attached and convert the readings into analog signals through the tracking device which takes the readings obtained to the GPRS location using SMS and GSM technologies to the user using a mobile application ; and a MySQL system for updating a database with an InnoDB storage engine to support SQL transactions; a InnoDB memcached engine to access InnoDB through the InnoDB APIs most of which are directly adopted from embedded InnoDB.

BRIEF DESCRIPTION OF DRAWINGS

[00011] In the following, numerous specific details are set forth to provide a thorough description of various embodiments. Certain embodiments may be practiced without these specific details or with some variations in detail. In some instances, certain features are described in less detail so as not to obscure other aspects. The level of detail associated with each of the elements or features should not be construed to qualify the novelty or importance of one feature over the others.

[00012] FIG. 1 is an architecture depicting emotion estimation with bio-signals monitoring device, according to an exemplary embodiment of the present disclosure.

[00013] FIG. 2 depicts a general case of relationships between different emotional states, according to an exemplary embodiment of the present disclosure.

[00014] FIG. 3 is a diagram depicting an environment of a parent set up of the tracking device, according to an exemplary embodiment of the present disclosure.

[00015] FIG. 4 is a block diagram depicting a system for tracking human beings using real-time bio signals, according to an exemplary embodiment of the present disclosure.

[00016] FIG. 5 is a block diagram depicting Memcached API Implementation for InnoDB storage implementation, according to an exemplary embodiment of the present disclosure.

[00017] FIG. 6 is a block diagram depicting a solution architecture, according to an exemplary embodiment of the present disclosure.

[00018] FIG. 7 is a flow chart depicting a method of tracking a human being by the using real-time bio signals, according to an exemplary embodiment of the present disclosure.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

[00019] It is to be understood that the present disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The present disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting.

[00020] The use of “including”, “comprising” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. The terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced item. Further, the use of terms “first”, “second”, and “third”, and the like, herein do not denote any order, quantity, or importance, but rather are used to distinguish one element from another.

[00021] Referring to FIG. 1 is an architecture 100, depicting emotion estimation with bio-signals monitoring device, according to an exemplary embodiment of the present disclosure. The device (to be discussed in detail in subsequent figures) is a wearable device. When emotions not limiting to, anger, fear, happiness and the like are inducted 102 through the device, then the measurement of different ANS values 104 is done. A subjective validation is done at priority. Finally the estimation of the emotional state 108 of a person, which is the variation of the objective evaluation (experimental value) and ideal or expected values (subjective evaluation) 106 is done. As emotion varies it bring change in sympathetic nerve of the ANS in excited condition, the sweat is secreted form the sweat gland and it decreases the galvanic skin response (GSR) and heart rate is also under continuous control of autonomic nervous system which increase heart rate.

[00022] Referring to FIG. 2, it depicts a general case 200, of relationships between different emotional states, according to an exemplary embodiment of the present disclosure. The emotions considered in this figure are, not limited to, Blood Volume Pulse (BVP), GSR, temperature and the like.

[00023] The expected value of GSR, BVP and Temperature for various emotions is as mentioned in the table given below:

Sensors RELAX NORMAL FEAR
GSR 0.15-0.25 0.15 0.29
BVP 72 73 85
TEMP
(oF) 98.2 98.4 96.4

[00024] The figure 200 represents the general case with more relationships between different emotional states depicting normal state 202, when fear sets on 204 leads to stress 206. Usually fear and stress are interrelated. Finally, upon relaxation 208, the stress 206 disappears; the body relaxes and returns to a normal state 202. Figure 200 shows the general case with more relationships between the four different states depicting the inner process of emotions.

[00025] The normalization of GSR is obtained by using the following equation:

Normalized_GSR = ( original_GSR – relax_GSR)
relax_GSR

[00026] Original state is a normal state of GSR value, which usually prolongs for a longer period without any acute stress the average value will be 0.15 resistance. The relax GSR values is the one that comes after the stress starts disappearing and body starts relaxing (values will decrement from 0.30 to 0.15 over a period of time).

[00027] As mentioned before GSR mainly depends upon sweat gland activity, so when a human feels any emotion then our body reacts according to it and starts excreting sweat out of body. This brings more conduction in body and variation of resistance in the body of the human being by using ohm law can be measured.

[00028] After all the features were extracted and provided as input to learning systems, which were trained to differentiate the emotions of a person. In particular, popular learning algorithms were employed: Naive Bayes Classifier.

[00029] The Bayesian Classification represents a supervised learning method as well as a statistical method. It assumes probabilistic model and it allows us to capture uncertainty about the model in a principled way by determining probabilities of the outcomes. Bayesian reasoning is applied to decision making and inferential statistics which deals with probabilities. It mainly uses the knowledge of prior events to predict future events.

Bayes Theorem:

P (h|D) = P(h) p(h|D)
P(D)

[00030] Bayes Theorem computes the conditional probabilities of the different classes given the values of attributes of an unknown sample and then the classifier will predict that the sample belongs to the class having the highest posterior probability in that case. Instance is represented by an n-dimensional feature vector, (xl, x2, ... ,xn), sample is classified to a class c from a set of possible classes C according to the maximum a posterior:

?(p(xt|C) =c)

Classifv(x1,x2…xn)=argmaxp(C=c)it=1;

D: Set of tuples Each Tuple is an 'n' dimensional attribute vector
X: (xl,x2,x3, .... xn) Let there be 'm'
Classes: C 1, C2, C3 ... Cm Classifier predicts X belongs to Class Ci if P(CilX) > P(CjIX)for J<=j<=m,j<> i
Maximum Posteriori Hypothesis P(CilX) = P(x/Ci) P(Ci) I P(X)
Maximize P(X/Ci) P(Ci) as P(X) is constant with many attributes, computing of this is expensive to evaluate P(X/Ci).
Naive Assumption of "class conditional independence n
P(x|Ci)? [p(x)k]|Ci
K=1
P(x/Ci) = P(xJICi) * P(x2ICi) * ... * P(xnl Ci)

[00031] The conditional probability in the given above formula is obtained from the estimates of the probability mass function using training data of that scenario. Moreover, the independence assumption may not be a realistic model of the probabilities involved; it may still permit relatively accurate classification performance.

[00032] Referring to FIG. 3 is a diagram 300, depicting an environment of a parent set up of the tracking device, according to an exemplary embodiment of the present disclosure. The environment 300 comprises of a tracking device 306 which is a wearable device, not limiting to an ARM device. Physical measurements of different parameter (GSR/BVP/Temp) values are done using the Qualcomm snapdragon 400 system on a chip (SoC), which is portable and requires low power consumption. The SoC has a secured ARM Cortex core, Analog to digital converter (ADC) and Digital to Analog converter, Global Positioning System, Global System for mobile communication, Bluetooth and many other inbuilt peripherals.

[00033] Hardware designing along with the sensors 308 is done with either ADC or I2C protocol. Software design and implementation is done in operating system like Android and Linux housed in mobile phones which operate the applications 302. The tracking procedure is configured to send the SMS to the preconfigured number on the periodic basis with SOS button ON automatically, using the sensor- based algorithm. Building an application 302 in iPhone and Android based smart phone which can receive the SMS and map the coordinates to the existing maps in the phone is developed. For configurations, history, and analytics a database is required. The removal of the device 306 is easily detectable by the user. The user here is the one wearing the device and whose emotions are being kept a track of for action of the second user using the mobile application 302 on his/her device. The device 306 is configured to interface with input/output peripherals and memory. The Advanced Microcontroller Bus Architecture (AMBA) is configured to establish interconnection amongst the specification for the connection and management of functional elements in SoC designs. This device 306 estimates the emotions based on the bio signals captured from sensors 308 from the body of the user and capture fear, anger, happiness and the like emotions of the user. The said device sends GPRS locations using SMS and GSM technologies to the second user accessing the mobile application 302. A debug interface is configured to allow and remove errors arising from the system’s hardware and/or software. This interface blocks the unwanted messages. A secured ARM core is configured to protect the device from both internal and external attacks.

[00034] Referring to FIG. 4 is a block diagram 400, an environment for tracking human beings using real-time bio signals, according to an exemplary embodiment of the present disclosure. Hardware designing along with the sensors 308 is done with either ADC or I2C protocol. Software design and implementation is done in operating system like android and linux housed in mobile phones which operate the applications 302. A tracking system is developed which can send the SMS to the preconfigured number on the periodic basis with SOS button ON automatically, using the sensor-based algorithm. Building an application 302 in iPhone and Android based smart phone which can receive the SMS and map the coordinates to the existing maps in the phone is developed. For configurations, history, and analytics a database is required which is set up and fixed at one place. Updating of the database is done using MySQL. Databases are used for inserting, deleting, modifying, updating and history tracking of an individual tracking device. The server is equipped to coordinate between the application based smart phone or mobile device with the application 302 to the tracking device 306. Also, server will maintain the Geo fencing Zone, Periodic updated information, Location History, On demand tracking, Real time tracking, Community help, Contacts, Groups etc. In the server all the maps are incorporated, such that we can use the server to keep the location details of all the registered devices. Databases are used for inserting, deleting, modifying, updating and history tracking of an individual tracking device 306. The device 306 is powered with wireless charging system, Peltier cell, piezoelectric cells and solar cells.

[00035] Referring to FIG. 5 is a block diagram 500, depicting Memcached API Implementation for InnoDB storage implementation, according to an exemplary embodiment of the present disclosure. Updating of the database (as shown in FIG. 4) is done using MySQL process 501. Databases are used for inserting, deleting, modifying, updating and history tracking of an individual tracking device. InnoDB is a storage engine 502 for the database management system MySQL. It supports SQL transactions. The My SQL server 508 is configured to store and retrieve the data which has been obtained from the device as and when requested by the mobile application and/or any other application running parallely. The InnoDB memcached engine 504 accesses InnoDB through the InnoDB APIs 506 most of which are directly adopted from embedded InnoDB. The InnoDB API 506 functions are passed to the InnoDB memcached engine 504 as a callback function. The InnoDB API 506 access the InnoDB tables directly, and are mostly DML operations with the exception of memcached commands are implemented through the InnoDB memcached API 506. The handler API 510 is configured to run and process the messages received.

[00036] Referring to FIG. 6 is a block diagram 600, depicting a solution architecture, according to an exemplary embodiment of the present disclosure. A tracking system is configured to send the SMS to the preconfigured number on a periodic basis with the SOS button which is ON automatically, using the sensor based algorithm. Building an application in iPhone and Android based smart phone enabled to receive the SMS and map the coordinates to the existing maps in the phone is developed and explained through the figure 600.

[00037] Referring to FIG. 7 is a flow chart 700, depicting a method for tracking a human being by the using real-time bio signals, according to an exemplary embodiment of the present disclosure. Once the user wears the tracking device then, based on the emotions generated, the reading of the Galvanic skin conductance (GSR) sensor input values from the Analog to digital converter (ADC) is taken at step 702 which is followed by reading blood volume pulse (BVP) sensor input values from ADC at step 704. Reading temperature sensor input values from ADC is done at step 706. It is enquired at step 708 whether GSR >0.29, if(BVP > 85) and if TEMP < 96.4 degree F. If the enquiry to step 708 is yes, then reading the current location based on latitude and longitude is done at step 710. If the enquiry to step 708 is no, then the step reverts to step 702. The action in step 710 is divided into step 712a by sending the current location details to the preconfigured mobile numbers and step 712b by sending the current location, real time data and other information to the databases for history, analytics, web services and the like. Based on the location shared and emotion signals the necessary action is taken at step 714 by the second user who receives the information through his/her mobile application in their respective devices.

Expected values of different aged groups are given in the below table:
AGE GSR BVP TEMPERATURE
1-10 16-35 70-90 97-98.3
11-30 14-29 60-70 97.1-98.3
30-45 23-25 71-72 97.9-98.3
>45 22-23 72-75 98.2- 98.7

[00038] Although the present disclosure has been described in terms of certain preferred embodiments and illustrations thereof, other embodiments and modifications to preferred embodiments may be possible that are within the principles and spirit of the invention. The above descriptions and figures are therefore to be regarded as illustrative and not restrictive.

[00039] Thus the scope of the present disclosure is defined by the appended claims and includes both combinations and sub-combinations of the various features described hereinabove as well as variations and modifications thereof, which would occur to persons skilled in the art upon reading the foregoing description.