System And Method For Determning Status Of Health Of Animals Arriving At A Feed Location

Abstract

A system and method are provided for screening and treating respiratory diseased animals such as livestock. Health measurements are taken of incoming animals to a location such as a feed yard. The measurements are used as inputs to an algorithm. Processing of the algorithm results in a prediction whether the animal is likely to become sick. A treatment decision is automatically generated by processing of the algorithm for display to a user. A “treat” decision may trigger a predetermined treatment protocol for the particular evaluated animal, while a “don't treat” decision allows the animal to be released.

Claims

1. A system for determining a health status of an animal upon arrival at a location, comprising: a computer processor for receiving and storing biometric data; at least one recording device for capturing and recording biometric data from the animal, said device communicating with said computer processor, said device including at least an audio recorder that records the biometric data obtained by auscultated heart and lung sounds of the animal; computer coded instructions executed by said computer processor including at least one algorithm for determining whether the animal should receive treatment; a user interface associated with the computer processor for displaying information obtained by execution of said computer processor; and wherein said algorithm includes a gradient boosted tree algorithm comprising input variables obtained from the recorded biometric data and corresponding to the recorded heart and lung sounds.

2. The system of claim 1, wherein: said input variables further include at least one of a body weight of the animal and a rectal temperature of the animal.

3. The system of claim 1, wherein: said algorithm incorporates the biometric data recorded as converted to numerical form for inputs to the algorithm, and in which raw signal dated recorded of the auscultated heart and lung sounds undergo bandpass filtering.

4. The system of claim 3, wherein: said input variables include a heart rate.

5. A system, as claimed in claim 3, wherein said input variables include a respiration rate.

6. The system of claim 3, wherein said algorithm includes additional inputs including arithmetic expressions of the recorded biometric data, said expressions including at least one of a cardiopulmonary ratio, a cardiac breath gap, a cardiac index, and a cardiac max.

7. The system of claim 1, further including: another user interface associated with the computer processor for displaying a health status of the animal, said health status including a likelihood the animal may develop BRD.

8. The system of claim 1, wherein: said displayed information includes a user treatment decision for the animal.

9. The system of claim 8, wherein: said at least one algorithm is a gradient boosted tree algorithm expressed by a function
F.sub.0(x)=arg min γ Σ.sub.i=1.sup.nL(y.sub.i, γ); wherein the function classifies the treatment decision to treat or not treat an animal; wherein γ represents a specific combination of inputs that arrive at the treatment decision; and wherein Σ L represents a misclassification error or number of falsely estimated instances i in a training set when compared to a true label y.sub.i.

10. The system of claim 9, wherein: said specific combination of inputs γ includes at least one of: (a) a cardio-pulmonary ratio (cpr), calculated as $\left(\frac{\mathrm{hr}\mathrm{percentile}}{\mathrm{rr}\mathrm{percentile}}\right),$ said cpr ratio representing a magnitude of stress experienced by the animal upon arrival at the location; (b) a cardiac breath gap (cbg), calculated as (heart rate−respiration rate); (c) a cardiac index (ci), calculated as $\left(\frac{\mathrm{hr}\mathrm{percentile}}{\mathrm{bw}\mathrm{percentile}}\right),$ said ci index representing a relationship between heart performance and size of the animal; and (d) a cardiac max (cm), calculated as $\left(\frac{hr}{75\mathrm{th}\mathrm{percentile}\mathrm{hr}\left(\mathrm{based}\mathrm{on}\mathrm{bw}\mathrm{and}\mathrm{rt}\right)}\right),$ said cm representing an estimation of how efficiently the animal is consuming oxygen upon arrival at the location.

11. The system of claim 9, wherein: execution of said at least one algorithm by said computer processor includes a plurality of decision stumps and a generated outcome resulting in a treatment decision.

12. The system of claim 11, wherein: said treatment decision is a treat decision.

13. The system of claim 11, wherein: said treatment decision is a don't treat decision.

14. The system of claim 9, wherein: execution of said at least one algorithm includes conducting iterative computations to arrive at the treatment decision.

15. A method for determining a health status of an animal upon arrival at a location, comprising: providing a computer processor for receiving and storing biometric data; providing at least one recording device; recording raw biometric data from the animal by use of at least an audio recorder that records heart and lung sounds; converting the raw biometric data recorded to manipulated heart and lung sound data; providing computer coded instructions executed by the computer processor including at least one algorithm for determining a health status of the animal; executing the algorithm with input variables corresponding to the manipulated heart and lung sound data; generating a user interface associated with the computer processor for displaying to a user a health status of the animal; and wherein said algorithm includes a gradient boosted tree algorithm comprising input variables corresponding to the manipulated heart and lung sound data of the animal.

16. The method of claim 15, wherein: said at least one algorithm further includes computer coded instructions for determining whether the animal should receive treatment; and said user interface further includes a treatment decision for the animal.

17. The method of claim 15, wherein: said input variables further include at least one of a body weight of the animal and a rectal temperature of the animal.

18. The method of claim 15, wherein: said manipulated heart and lung sound data includes the raw biometric data that undergoes bandpass filtering.

19. The method of claim 15, wherein: said manipulated heart and lung sound data includes a recorded heart rate.

20. The method of claim 15, wherein: said manipulated heart and lung sound data includes a respiration rate and selected recorded frequencies and amplitudes of recorded lung sounds.

21. The method of claim15, wherein said algorithm includes additional inputs including arithmetic expressions of recorded heart and lung sound data, said expressions including at least one of a cardiopulmonary ratio, a cardiac breath gap, a cardiac index, and a cardiac max.

22. The method of claim15, further including: generating a user interface associated with the computer processor wherein said health status including a likelihood the animal may develop BRD.

23. The method of claim 15, wherein: said health status includes a user treatment decision for the animal.

24. The method of claim 15, wherein: said at least one algorithm is a gradient boosted tree algorithm expressed by a function
F.sub.0(x)=arg min γ Σ.sub.i=1.sup.nL(y.sub.i, γ); wherein the function classifies the treatment decision to treat or not treat an animal; wherein γ represents a specific combination of inputs that arrive at the treatment decision; and wherein Σ L represents a misclassification error or number of falsely estimated instances i in a training set when compared to a true label y.sub.i.

25. The method of claim 24, wherein: said specific combination of inputs γ includes at least one of: (a) a cardio-pulmonary ratio (cpr), calculated as $\left(\frac{\mathrm{hr}\mathrm{percentile}}{\mathrm{rr}\mathrm{percentile}}\right),$ said cpr ratio representing a magnitude of stress experienced by the animal upon arrival at the location; (b) a cardiac breath gap (cbg), calculated as (heart rate−respiration rate); (c) a cardiac index (ci), calculated as $\left(\frac{\mathrm{hr}\mathrm{percentile}}{\mathrm{bw}\mathrm{percentile}}\right),$ said ci index representing a relationship between heart performance and size of the animal; and (d) a cardiac max (cm), calculated as $\left(\frac{hr}{75thpercentilehr\left(basedonbwandrt\right)}\right)$ said cm representing an estimation of how efficiently the animal is consuming oxygen upon arrival at the location.

26. The method of claim 24, wherein: execution of said at least one algorithm by said computer processor includes a plurality of decision stumps and a generated outcome resulting in a treatment decision.

27. The method of claim 26, wherein: said treatment decision is a treat decision.

28. The method of claim 26, wherein: said treatment decision is a don't treat decision.

29. The method of claim 24, wherein: execution of said at least one algorithm includes conducting iterative computations to arrive at the treatment decision.

30. A non-transitory computer-readable medium containing computer executable instructions, wherein, when executed by a computer processor, the instructions cause the computer processor to execute a method to determine a health status of an animal the computer-readable instructions comprising: instructions to receive and store data corresponding to recorded heart and lung sounds; instructions to convert the recorded heart and lung sounds to manipulated heart and lung sound data; instructions to execute an algorithm to determine the health status of the animal, wherein the algorithm comprises input variables corresponding to the manipulated heart and lung sound data; instructions to generate a user interface associated with the computer processor for displaying to a user the health status of the animal, wherein said health status includes technical recommendations for further evaluating whether the health status requires further analysis; and wherein said algorithm includes a gradient boosted tree algorithm comprising input variables corresponding to the manipulated heart and lung sound data of the animal.

31. The non-transitory computer-readable medium of claim 30 wherein: said instructions to execute the algorithm further include instructions to determine whether the animal should receive treatment; and said instructions to generate the user interface further include instructions to display to the user a treatment decision for the animal.

32. The non-transitory computer-readable medium of claim 30, wherein: said health status includes a user treatment decision for the animal.

33. The non-transitory computer-readable medium of claim 31, wherein: said at least one algorithm is a gradient boosted tree algorithm expressed by a function
F.sub.0(x)=arg min γ Σ.sub.i=1.sup.nL(Y.sub.i, γ); wherein the function classifies the treatment decision to treat or not treat an animal; wherein γ represents a specific combination of inputs that arrive at the treatment decision; and wherein Σ L represents a misclassification error or number of falsely estimated instances i in a training set when compared to a true label y.sub.i).

34. The non-transitory computer-readable medium of claim 33, wherein: said specific combination of inputs γ includes at least one of: (a) a cardio-pulmonary ratio (cpr), calculated as $\left(\frac{\mathrm{hr}\mathrm{percentile}}{\mathrm{rr}\mathrm{percentile}}\right),$ said cpr ratio representing a magnitude of stress experienced by the animal upon arrival at the location; (b) a cardiac breath gap (cbg), calculated as (heart rate−respiration rate); (c) a cardiac index (ci), calculated as $\left(\frac{\mathrm{hr}\mathrm{percentile}}{\mathrm{bw}\mathrm{percentile}}\right),$ said ci index representing a relationship between heart performance and size of the animal; and (d) a cardiac max (cm), calculated as $\left(\frac{hr}{75thpercentilehr\left(basedonbwandrt\right)}\right)$ said cm representing an estimation of how efficiently the animal is consuming oxygen upon arrival at the location.

35. The non-transitory computer-readable medium of claim 33, wherein: execution of said at least one algorithm by said computer processor includes a plurality of decision stumps and a generated outcome resulting in a treatment decision.

36. The non-transitory computer-readable medium of claim 35, wherein: said treatment decision is a treat decision.

37. The non-transitory computer-readable medium of claim 35, wherein: said treatment decision is a don't treat decision.

38. The non-transitory computer-readable medium of claim 33, wherein: execution of said at least one algorithm includes conducting iterative computations to arrive at the treatment decision.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0115] FIG. 1 is an example user interface showing information for entering data regarding an animal to be added to the data processing system in order that a health status can be obtained and optionally, to obtain a treatment decision that can be made once data is recorded; this figure also shows selected information about animals who have already been processed, sorted by lots within a feed yard;

[0116] FIG. 2 is another example user interface that displays a health record including a treat/no treat decision for an animal that has been processed. The user interface also shows additional selected information about the animal, information about the feed yard, and notes that may be added by the caregiver;

[0117] FIG. 3 is a perspective view of an example wireless audio digital recording unit that can be used to obtain and record auscultations for data entry;

[0118] FIG. 4 is a bottom plan view of a recording paddle of the audio digital recording unit showing a plurality of audio sensors; and

[0119] FIG. 5 is a block diagram showing a system of the invention including a number of data processing devices and field devices enabling recorded animal data to be processed and subsequently communicated within a communications network for treating selected animals.

DETAILED DESCRIPTION

[0120] FIG. 1 is an example user interface 10 associated with entering, recording and processing data of an animal on arrival to a location such as a feed yard. More specifically, this figure provides a schematic depiction or representation of an animal for which a new data record 12 is to be created for the animal as it is received to the location. The animal may be specifically identified, for example, by use of an RFID tag that is associated with the animal. The tag may contain detailed information about the animal to include its prior health history and other data. Entering the tag data is one example of how an animal may be initially set up and recorded in a data processing system of the invention enabling subsequent tracking and treatment.

[0121] Once the user completes entry of new information about the animal record to be created, or if information about the animal is has been automatically uploaded (such as by RFID tag data), this figure also shows a function for the user to begin reading biometric data for the animal, shown at block 14. A digital recording unit such as an electronic stethoscope can be used to record auscultation data. Accordingly, as detailed further below, the digital recording unit communicating with a data processor of the associated computer processing system of the invention enables the upload of the auscultation data.

[0122] FIG. 1 also shows information about the number and location of animals within the feed yard, shown as Lot numbers 16 with the corresponding number of animals 18 found in each lot at that time, along with a count of whether the animals have been treated or not treated. The treated animals are shown with a syringe symbol 20 while those animals not treated are shown with the syringe symbol crossed out 22.

[0123] FIG. 1 is an example user interface with certain functional attributes that enable a user to create a new record for an animal arriving at the location and to begin entering a biometric data, it being understood that the particular user interface can be alternatively arranged in a manner that is most convenient for visualization by the user. In addition to auscultation data, a user may also enter information regarding the body weight and rectal temperature of the animal. Each of these additional data elements can be automatically uploaded by field devices that communicate with the data processor responsible for handling algorithm calculations. For example, a weigh scale and digital rectal thermometer can be co-located within a chute which holds the animal while recording of auscultations are conducted.

[0124] FIG. 2 provides another example of a user interface 30 showing information recorded about the animal. More specifically, this figure shows a schematic representation of the animal 32 and which side of the animal was used for recording heart and lung sounds. In this example, the right side of the animal was contacted by a1 recording unit. The body weight 34 and temperature 36 are also displayed, along with the feed yard owner/operator 38, location 40, and lot number 42 where the animal is located.

[0125] FIG. 2 also displays the treatment decision that is generated once the algorithm is processed with the recorded data of the animal. As shown, the treatment decision 44 is depicted with a syringe symbol along with a date and time in which the treatment decision was created. The treatment decision is generated within a very short time period after the recorded data is entered so that the animal can be treated while being held in the chute or other confined location in which the recorded data is obtained from the animal.

[0126] Further information shown in the sample user interface of FIG. 2 includes an RFID identification number or code 46 and an optional tag identifier 48 that may be used for identification purposes only within the feed yard. Another optional feature of this sample user interface is a notes section 50 that may be populated with special instructions for the care of the animal or any other notes a caregiver may wish to add. FIG. 2 also illustrates standard navigation features shown as a cancel function 52 and a save/next function 54 enabling the user to navigate between user interfaces as desired.

[0127] Although FIG. 2 specifically illustrates an example of a treatment decision, it shall be understood that the invention does not require a decision to be generated only regarding a diagnosis and/or treatment. The invention has broader applicability and can be used to generate other decisions such as whether to transport an animal to another location, to provide a different feeding protocol for the animal, or to provide a different environment for the animal such as removal of the animal from a feed yard where the animal may experience a higher level of stress. Specifically, for example, a decision can be made whether to transport an animal to another location if the animal exhibits recorded data indicative that the animal is unduly stressed or potentially sick. This decision to transport or not transport is not made as a result of any particular diagnosis or treatment decision, but rather, based on other criteria that indicates the health status of the animal is such that the animal should be further evaluated and/or isolated as a precaution.

[0128] FIG. 3 illustrates one example of an audio digital recording unit 60 that can be used to gather auscultation data including heart and lung sounds. The recording unit is capable of recording and transmitting the data wirelessly to a remote computing device. Alternatively, the unit itself may have its own microprocessor, memory, software/firmware and database(s) for manipulation of data to record and generate a tangible output for the user to receive and further manipulate on a another computing device. The unit 60 is depicted as having an arm or extension 62, a handle 64, and a paddle 64 that houses audio sensors for recording sounds.

[0129] Referring also to FIG. 4, the panel may incorporate a plurality of audio sensors 66. The use of redundant audio sensors as opposed to a single sensor may provide more reliable data for use in the algorithm. A single audio output from the group of sensors may be achieved by computing mean averages of the recorded data and then generating a single audio signal reflective of the computed averages.

[0130] FIG. 5 provides an example computer processing and communication network that may be used in connection with the system and method of the invention disclosed herein. More specifically, FIG. 5 illustrates a block diagram of a system 100 that includes one or more user computers shown as feed yard computer 102, a chute side computer 104, and customer network 106, in which each of the computers 102, 104 and network 106 may alternatively comprise more than one computer. Specifically, the feed yard computer 102 represents one or more computers used in a feed yard or feedlot environment used to automatically control the accounting, feeding, and treatment of animals prior to harvesting. The chute side computer 104 represents one or more computers used in a feed lot environment that may be used to initially receive and record data regarding animals being received into the feedlot. The customer network 106 represents one or more computers of third parties who may seek to exchange data with the feed lot, such as financial institutions, cattle growers, and other third parties who are involved with a livestock industry. These user computers 102, 104, and network 106 may comprise general purpose personal computers (including, merely by way of example, personal computers and/or laptop computers running various versions of Microsoft's Windows® and/or Apple® operating systems) and/or workstation computers running any of a variety of commercially-available LINUX®, UNIX® or LINUX®-like operating systems. These user computers 102, 104, and network 106 may also have any of a variety of applications, including for example, database client and/or server applications, and web browser applications. Alternatively, the user computers 102, 104, and computers within network 106 may be any other electronic device, such as a thin-client computer, Internet-enabled mobile telephone, and/or personal digital assistant, capable of communicating via a network and/or displaying and navigating web pages or other types of electronic documents.

[0131] System 100 further includes a communications network 110. The network 110 may be any type of network familiar to those skilled in the art that can support data communications using any of a variety of commercially-available protocols, including without limitation TCP/IP, SNA, IPX, AppleTalk®, and the like. Merely by way of example, the communications network 110 maybe a local area network (“LAN”), such as an Ethernet network, a Token-Ring network and/or the like; a wide-area network; a virtual network, including without limitation a virtual private network (“VPN”); the Internet; an intranet; an extranet; a public switched telephone network (“PSTN”); an infra-red network; a wireless network (e.g., a network operating under any of the IEEE 802.11 suite of protocols, the Bluetooth™ protocol known in the art, and/or any other wireless protocol); and/or any combination of these and/or other networks.

[0132] The system may also include one or more server computers 120. One type of server may include a web server used to process requests for web pages or other electronic documents from user computers 102, 104, and network 106. The web server can be running an operating system including any of those discussed above, as well as any commercially-available server operating systems. The web server can also run a variety of server applications, including HTTP servers, FTP servers, CGI servers, database servers, Java servers, and the like. In some instances, the web server may publish operations available as one or more web services.

[0133] The system 100 may also include one or more file and/or application servers, which can, in addition to an operating system, include one or more applications accessible by a client running on one or more of the user computers 102, 104, and network 106. The file/application server(s) may be one or more general purpose computers capable of executing programs or scripts in response to the user computers 102, 104, and network 106. As one example, the server may execute one or more web applications. The web application may be implemented as one or more scripts or programs written in any programming language, such as Java®, C, C#™ or C++, and/or any scripting language, such as Perl, Python, or TCL, as well as combinations of any programming/scripting languages. The application server(s) may also include database servers, including without limitation those commercially available from Oracle®, Microsoft, Sybase®, IBM® and the like, which can process requests from database clients running on a user computer.

[0134] In one functional aspect, an application server may create web pages dynamically for displaying the functionality associated with the system to include the user interface of FIGS. 1 and 2. The web pages created by the web application server may be forwarded to a user computer via a web server. Similarly, the web server may be able to receive web page requests, web services invocations, and/or input data from a user computer and can forward the web page requests and/or input data to the web application server. In another functional aspect, the server 120 may also function as a file server.

[0135] The system 100 may also include a database 130. The database 130 may reside in a variety of locations. By way of example, database 130 may reside on a storage medium local to (and/or resident in) one or more of the computers 102, 104, and network 106. Alternatively, it may be remote from any or all of the computers 102, 104, and network 106, and in communication (e.g., via the network 110) with one or more of these. In a particular set of embodiments, the database 130 may reside in a storage-area network (“SAN”). Similarly, any necessary files for performing the functions attributed to the computers 102, 104, and network 106 may be stored locally on the respective computer and/or remotely, as appropriate. The database 130 may be a relational database, such as Oracle® database, that is adapted to store, update, and retrieve data in response to SQL-formatted commands.

[0136] The system may further include one or more mobile devices 140 such as “smart phones”. These mobile devices 140 communicate with the network 110 as by a web interface. The network 110 may also represent a cloud provider who facilitates communication with communication endpoints or computers of the customer network 106. The mobile devices 140 may communicate with any other of the computers in the system through the network 110, such as the feed yard computer system 102 as also shown in FIG. 5. The mobile devices have their own internal computer processing capabilities with integral computer processors and other supporting hardware and software. The mobile devices may be specially configured to run a mobile software application(s) in order to view user interfaces and to view and update system data. All of the functionality associated with the system as applied to the computers 102, 104, and 106 may be incorporated in the mobile devices 140 as modified by mobile software applications especially adapted for the mobile device hardware and operating systems. In connection with operating systems, it should therefore be understood that the mobile devices are not limited to any particular operating system, Apple iOS and Android-based systems being two examples.

[0137] FIG. 5 also schematically illustrates a plurality of measuring digital audio recording units 150 in which each may have supporting sensor circuitry (not shown) for recording and transmitting audio signals to the chute side computer or other computers within the network. For example, the digital audio recording units 150 could be the audio digital recording unit 60 shown in FIG. 2, as depicted.

[0138] In accordance with any of the computers 102, 104, and 106, these may be generally described as general-purpose computers with elements that cooperate to achieve multiple functions normally associated with general purpose computers. For example, the hardware elements 102, 104, and 106 may further include one or more input devices (e.g., a mouse, a keyboard, etc.); and one or more output devices (e.g., a display device, a printer, etc.). The computers may also include one or more storage devices. By way of example, storage device(s) may be disk drives, optical storage devices, solid-state storage device such as a random access memory (“RAM”) and/or a read-only memory (“ROM”), which can be programmable, flash-updateable and/or the like.

[0139] Each of the computers and server described herein may include a computer-readable storage media reader; a communications peripheral (e.g., a modem, a network card (wireless or wired), an infra-red communication device, etc.); working memory, which may include RAM and ROM devices as described above. The server may also include a processing acceleration unit, which can include a DSP, a special-purpose processor and/or the like.

[0140] The computer-readable storage media reader can further be connected to a computer-readable storage medium, together (and, optionally, in combination with storage device(s)) comprehensively representing remote, local, fixed, and/or removable storage devices plus storage media for temporarily and/or more permanently containing computer-readable information. The computers and serve permit data to be exchanged with the network 110 and/or any other computer, server, or mobile device.

[0141] The computers and server also comprise various software elements and an operating system and/or other programmable code such as program code implementing a web service connector or components of a web service connector. It should be appreciated that alternate embodiments of a computer may have numerous variations from that described above. For example, customized hardware might also be used and/or particular elements might be implemented in hardware, software (including portable software, such as applets), or both. Further, connection to other computing devices such as network input/output devices may be employed.

[0142] It should also be appreciated that the method described herein may be performed by hardware components or may be embodied in sequences of machine-executable instructions, which may be used to cause a machine, such as a general-purpose or special-purpose processor or logic circuits programmed with the instructions to perform the methods. These machine-executable instructions may be stored on one or more machine readable mediums, such as CD-ROMs or other type of optical disks, ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards, flash memory, or other types of machine-readable mediums suitable for storing electronic instructions. Alternatively, the methods may be performed by a combination of hardware and software.

[0143] The term “software” as used herein shall be broadly interpreted to include all information processed by a computer processor, a microcontroller, or processed by related computer executed programs communicating with the software. Software therefore includes computer programs, libraries, and related non-executable data, such as online documentation or digital media. Executable code makes up definable parts of the software and is embodied in machine language instructions readable by a corresponding data processor such as a central processing unit of the computer. The software may be written in any known programming language in which a selected programming language is translated to machine language by a compile, interpreter or assembler element of the associated computer.

[0144] Considering the foregoing exemplary computer and communications network and elements described therein, In connection with one embodiment of the invention, it may be considered a software program or software platform with computer coded instructions that enable execution of the functionality associated with the user interface of FIGS. 1 and 2. More specifically, the invention may be considered a software program or software platform that executes the algorithm based on data inputs to the algorithm as described including, without limitation, heart and lung sound data, body weight, and rectal temperature.

[0145] In connection with another embodiment of the invention, it may be considered a combined software and hardware system including (a) a software program or software platform with computer coded instructions that enable execution of the functionality associated with the user interfaces of FIGS. 1 and 2 along with the execution of the algorithm to generate the treat/don't treat decision, and (b) hardware elements including the plurality of audio sensors that record auscultated sounds, a weigh scale for recording animal weight, and a rectal thermometer for recording animal temperature.

[0146] In connection with yet another embodiment of the invention, it may be considered a sub-combination including one or more user interfaces generated by the software and the field devices that provide inputs to a data processor of a computer that runs the software for purposes of generating the treatment decision by use of the algorithm.

[0147] While the invention is described herein with respect to multiple preferred embodiments, it should be understood that the invention is not strictly limited to these embodiments and therefore, the invention in totality should be considered commensurate with the scope of the claims appended hereto.