GB2613761A - Food recommendation system linking data profiling and DNA analysis - Google Patents

Abstract

Delivering personalized food recommendation using Artificial Intelligence based on DNA analysis of individuals. This food or diet recommendation system is primarily based on the genetic data, historical references of the individual and also based on psychological and emotional response to food images that uses an Artificial Intelligence (AI) algorithm in conjunction with DNA test kits. It includes computer readable programs for receiving and processing a plurality of user specific genetic profile using Artificial intelligence and further displays food recommendation results for a plurality of user genetic profiles.

Description

FOOD RECOMMENDATION SYSTEM LINKING USER DATA PROFILING AND DNA

ANALYSIS

FIELD OF THE INVENTION

[00011The invention relates to methods, systems, and application, more particularly to graphical user interface (GUI) for delivering personalized food or diet recommendation using Artificial Intelligence based on DNA or gene analysis of individuals. The food or diet recommendation is based on the genetic data, historical references of the individual and also based on psychological and emotional response to food images that uses an Artificial Intelligence (Al) algorithm in conjunction with DNA test kits.

BACKGROUND OF THE INVENTION

[00021The World Health Organization estimates that non-communicable diseases such as cardiovascular diseases, cancer, chronic respiratory diseases and diabetes, are responsible for 63% of all deaths worldwide. Furthermore, it also points out that such disease are preventable through effective interventions that tackle shared risk factors such as the unhealthy diets. In this context, whereas a one-size-fits-all approach may fail, personalized nutrition can benefits consumers to adhere to a healthy, pleasurable, and nutritional diet when it is closely associated to individual parameters such as the physical and psychological characteristics including health status, phenotype and genotype, the consumer's needs and preferences, behavior, lifestyle, etc. Personalized nutrition or diet can be used for different target groups from healthy people to patients such as malnourished people, vulnerable groups, people with allergies or non-communicable diseases, including cancer.

[0003] Many personalized expert food or diet recommendation systemand related research studies have been introduced by different experts.However, with the advancement of technology such as application of Artificial Intelligence, Machine Learning, etc it becomes easier to process different individual parameters to suggest effective diet recommendation to user's.

RELATED ARTS

[0004]Due to the lifestyle change and other medical conditions, the need for personalized recommendation system is so important these days. Many organizations and individuals have undergone different research and studies for personalized food or diet or nutrition recommendation system by the use of DNA analysis or genetic composition or genetic history of an individual. Many patent applications also existfor recommendations of lifestyle change, physical-mental health and fitness, pharmaceutical guidelines based on the genetic analysis, genetic markers, and by the use of specific algorithms.

[0005]The World Health Organization identifies the overall increasing of non-communicable diseases as a major issue, such as premature heart diseases, diabetes, and cancer. Unhealthy diets have been identified as the important causing factor of such diseases. In this context, personalized nutrition emerges as a new research field for providing tailored food intake advices to individuals according to their physical, genotypic, physiological data, and further personal information. Specifically, in the last few years, several types of research studies have proposed computational models for personalized food recommendation using nutritional knowledge and user data.

[0006]There have been many studies and applications that recommend food/ dietary recommendations such as nutrition, meal plan and other supplements Examples of such food or diet recommendation system are taught in US patent application US20180114602A1, US20190290172A1, US20180240542A1 and US2018218434A1.The patent application, U5201801 14602A1 discloses an interactive GUI interface for implementing personalized health and wellness programs using user-specific medical, genetic, fitness, environmental and nutritional data. Patent application by Yaron et al., US20190290172A1, discloses methods and systems for providing personalized food and health management recommendations. It mainly discloses the method for determining an effect of a food on a glucose level of a user.

[0007]In the patent application, U520200320363A I,Neumann et. al discloses an artificial intelligence advisory systems and methods for vibrant constitutional guidance.In the patent application, Allen et. al discloses in the patent application US20180240542A1, discloses the system and method for implementing meal selection based on vitals, genotype and phenotype data. There are other patent applications that recommend food or dietary recommendation using DNA analysis (few of the others are US 20190252058, U520!00098809A I, JP2015064884A, U52018218434A I) but none uses Artificial intelligence for the food/ dietary suggestion in a food delivery application.

[0008]The patent application US20180057866A1 discloses a system that directly relates genetic information or DNA link to beverage preferences. These preferences given by an individual is a result of expression of genes specific for taste and olfactory receptors.

[0009] Dioszegietal, in their research studieshas found thesignificant association between genetic traits i.e. TAS2R38 variants (rs713598, rsl 726866, rs10246939) and bitter and sweet taste preference. The gene variant rs1761667 (CD36) has also been identified as for fat taste preference. The research have suggested that, the information could help to understand the development of individual taste and related food preferences and food choices that will aid the development of tailored public health strategy.

Nevertheless,noneofthepr orartsexplainedabovediscloses food recommendation system that uses Al algorithm in conjunction with DNA test kits along with psychological and emotional response to food images that enhance the decision to choose the best food recommendations.

SUMMARY OF INVENTION

[0010]The embodiments described herein relate to a graphical user interface for food or dietary recommendation based on a tripartite system, that is, combining DNA test kit, a psychological food image profiling (identifying foods that they like or dislike) and also based on their past order history for different target groups from healthy people to patients, using Al (Artificial Intelligence) algorithm. [0011] According to one embodiment of the present invention, it discloses a food delivery application for food or diet recommendation system that uses a tripartite system combining genetic or DNA tests,psychological response to food image profiling and past order history to generate comprehensive suggestions to a user profile.

[0012] In one embodiment of the present invention discloses a food delivery applicationthat employs data or results from DNA test kitsor gene analysis, or DNA ancestry test for food or dietary recommendation using Al algorithm.

[0013]in another aspect of the present invention,the system uses artificial intelligence, specifically, it is focused on employing either machine or deep learning algorithms to implementthe food recommendation system.

[0014] According to yet another embodiment of the present invention, it employs psychological and emotional response to food images that enhance the decision for food recommendation using Al algorithm.

[0015] According to yet another embodiment of the present invention, it uses data from the previously ordered history of the individual profile for food or dietary recommendation using Al algorithm [0016]In yet another embodiment of the present invention, the food recommendation systemuses the preferred biological samples as either saliva or cheek tissue. The samples are collected from individual user, which in turn, are send to the laboratory for DNA testing and analysis; this data further are used in the system for optimal food recommendation system.

[0017]In yet another embodiment of the present invention, It discloses a food recommendation system that uses the method of genealogy along with AI-based algorithm, that specifically relies upon person's unique identity that is his DNA code. The person has specific traits based upon his genetic makeup that decides his preferences for food, beverages, tastes and different cuisines etc. These specific traits could be revealed by DNA or gene profiling studies with Al based tool that gives psychological food image profiling. These attributes help to understand which food the person likes and/or dislikes.

[0018]In another embodiment of the present invention, the system uses artificial intelligence, specifically, it is focused on implementing either machine and deep learning algorithms, that may be within the scope of the application such as logistic regression, naive bayes, Recurrent Neural Network (RNN), Multilayer Perceptron (MLP), Gated Recurrent Units (GRU), and Long Short-Term Memory (LSTM). The Artificial Intelligence based automatic system alerts the user's by recommending healthy diet and may use predictive data mining algorithm.

BRIEF DESCRIPTION OF DRAWINGS

[0019]Figure 1 illustrates an embodiment of the computer/network system upon which the food/diet recommendation system of disclosed is implemented.

[0020] Figure 2 illustrates an exemplary diagram of the food/diet recommendation system with the relevant databases and its interaction.

[0021] Figure 3 is a flowchart that discloses the system and method of collecting and analyzing user-specific data to develop comprehensive, personalized dietary recommendation using Artificial intelligence, according to one embodiment of the invention.

[0022] Figure 4 illustratesan embodiment of the invention of the food/diet recommendation system for Genome dataset preparation that is linked to an Al (Artificial Intelligence) tool.

[0023] Figure 5 is a block diagram that illustrates the connection of the tripartite database system for the food/diet recommendation system.

[0024] Figure 6 illustrates the method of recommending food/diet preferences in the food recommendation system for improving user health, wellness and user preferences.

[0025]Figure 7 illustrates all the databases used in the implementation of the food recommendation system using Al specific tool.Other aspects of the present invention shall be more readily understood when considered in conjunction with the accompanying drawings, and the following detailed description, neither of which should be considered limiting. Each of the objects stated above will be described in further detail in the next sections.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026]Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art of this disclosure. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and should not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Well known functions or constructions may not be described in detail for brevity or clar [0027]The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0028]With reference to the use of the words "comprise" or comp ses or 'comprising' in the foregoing description and/or in the following claims, unless the context requires otherwise, those words are used on the basis and clear understanding that they are to be interpreted inclusively, rather than exclusively, and that each of those words is to be so interpreted in construing the foregoing description and the following claims.

[0029] Various embodimentsof the invention described herein include systems, methods and/or devices used to enable personalized dietary or food recommendations to a user based on the user's genotype like genetic markers, such as SNPs; the user's psychological or emotional response to food image profiling and also based on the past history of user selection.

[0030]Figure 1 illustrates the fundamental network diagram upon which the food/diet recommendation system is implemented. The users (10,20,30) access the communication network (40), whom access the food delivery application. Upon accessing the application it searches the relevant food recommendation server (50) for the specific task.The servers (50) access the relevant databases (51,52,53,54,55,56) in order to perform the processes to generate best optimal food recommendation to the registered users.The genetic data analyzed from the laboratory (55) is stored in the database (51).The registered user profile is stored in the database,user profile database (53) and the geographic related data is stored in database (54). Further, the system stores user's past order history in the database, users past order history (52) and the psychological response to food image is recorded in the database named, psychological/emotional food image profiling (56).The figure 100, thus, shows the overall basic network diagram of the system.The psychological response to food image is recorded when the users are hungry. lnfact the user is asked to select foods they like as well as foods they dislike or are intolerant towards them. This data is then further correlated with genetic database 51 to ascertain and suggest food items liked or disliked by theusers with similar genetic make up.

[0031]Basic flowchart of the food recommendation system is described in Figure. 2.The system discloses a system and method that uses user-specific data for food or dietary recommendation using Al algorithm. Fig. 2 illustrates an embodiment of the invention, in which the system (200) collects and analyzesindividual-specific data(220)such as genotypic data of an individual; psychological responses to food image profiling; and based on user's past order history from mobile application on a portable electronic device such as mobile devices. The extracted data performs specific Artificial Intelligence based algorithm (230), andrecommends (240) and display (250) specific food or dietary plan as per the individual profile. The user has the option to select (260) and place orders from the recommended food menu.

[0032]1n order to automate the process of recommendation, the system uses artificial intelligence, specifically, itfocuses on employ ngeither machine and deep learning algorithms. The Artificial Intelligence based automatic system alerts the user's by recommending healthy diet and may use predictive data mining algorithm.

[0033] The automated food/diet recommendation system could provide great benefits when compared to human nutritionists; it also faces a number of limitations ranging from usability, efficiency, efficacy to satisfaction. There is a need to integrate contextual and social information as well as to enhance the accuracy of the received input data. The system developed will achieve desired effect in the long term as a mobile platform application for daily use.

[0034] Further,figure 3 illustrates a block diagram (300) of the food/diet recommendation system withthe flow of process and its interaction with the relevant databases for food or cuisines suggestions to individuals. It discloses that individual users ( I 0,20,and 30) access the interface (302) of food delivery application. The individual user's register in the app with relevant information for general profile; the system also asks for suitable questionnaire to fill in.The individual registered user's data will be accessed by the system for best optimal food recommendation and the system access it for proper processing from the user profile database (304). The system also accessesother data from databasesfor optimal food recommendation. The system suggests food or cuisines based on the country of origin from the database, Geographic database (305).1t recommends food based on the users past ordered history from the database user past order (307); from genotypic data using the database genetical/ ancestral data database (306); and also using psychological response to food images which is being extracted from the registered users from the database named, psychological/emotionalfood image profiling database (308). It stores the likes and dislikes of individual food preferences. Thus, the system uses a tripartite system of datasets, specifically,the genotypicdata, the emotional and/or psychological response to food image profiling and based on theusers past order history. The flow of the processes and the databases is depicted in the figure 300.

[0035]The food recommendation system employs the method of DNA analysis which is implemented in the food recommendation system for optimal suggestions to individuals.Figure 4 illustrates an embodiment of the invention of the food/diet recommendation system for the genome dataset preparation that is linked to an Al tool.Figure 4 depicts the flowchart (400) which describes the general procedure for collecting and processing of genetic material from client, based on which the food preferences are given. DNA kit is provided to the client wherein the cheek epithelial tissue rubbed with cotton swab or saliva sample of a client is collected (410). The biological sample collected from client is sent to genetic laboratory with utmost precaution without any chances of contamination.

[0036] DNA is extracted from the tissue sample using extraction method (420). The extracted and purified DNA then amplified before actual genetic analysis to get more number of DNA copies. PCR is most suitable and fastest technique for in vitro amplification of DNA (430).The critical step of gene analysis is to identify specific sequences on DNA/ genetic material for which sequence specific probes are used. The gene probes attach to the complimentary sequences and give illumination reaction. The identified sequences are the genetic markers also called SNPs (Single Nucleotide Polymorphism) of choice. In this disclosure the sequences are genetic alleles also termed as gene traits for food preferences of an individual client. The gene marker identification technique (440) is one of the latest techniques such as, RT-PCR, Microarray, RFLP, DNA Finger printing and soon.The results of genetic trait identification are stored in a system (Computer database) to form genetic dataset (450). This dataset input is processed by smart Al tool (460) to give client specific food recommendation solution.

[0037] Onemethod employed in the food recommendation system uses the method of genealogy along with AI-based algorithm, which specifically relies upon person's unique identity that is his DNA code. The person has specific traits based upon his genetic makeup that decides his preferences for food, beverages, tastes and different cuisines etc. These specific traits could be revealed by DNA or gene profiling studies with Artificial Intelligence based tool that gives psychological food image profiling. These attributes help to understand which food the person likes and/or dislikes.

[0038]The DNA/Genetic analysis report of every individual is linked to Al based tool that works on AT related algorithm, which is broader in scope, and is not limited to machine and deep learning algorithms like, logistic regression, naive bayes, Recurrent Neural Network (RNN), Multilayer Perceptron (MLP), Gated Recurrent Units (GRU), and Long Short-Term Memory (LSTM) , that uses information generated from databases and gives solution. Solution is nothing but Food recommendation that is food preferences, diet plan and /or food recipes which will best suit the person's genetic trait.Person's genetic trait also reveals the diseases/disorders that the person inherits. This information could be the best source of data to be taken into account to avoid future mishaps caused by unhealthy eating and lifestyle habits. Thus, if such data is found during DNA analysis, it will give us an opportunity to change and promote healthy diet and lifestyle.

[0039]Thepresentinvention, employs psychological and emotional response to food images that enhance the decision for food recommendation using Al algorithm Further in case of psychological response to the food images, the recommendations not only depend upon genetic trait but is based upon other factors such as age, gender, ethnicity, etc. The present invention determines if psychological event is the reason for food choices/ preferences of an individual.

[0040] The term used within the disclosure is DNA Code that refers to his genetic attribute or his genetic makeup, more elaborately person's DNA, genome, genotype, haplotype, chromatin, chromosome, alleles, gene, gene cluster, gene locus, genetic polymorphism, genetic mutation, nucleotide, nucleotide base pair, single nucleotide polymorphism (SNP), restriction fragment length polymorphism (RFLP), variable tandem repeat (VTR), microsatellite sequence, genetic marker, sequence marker, sequence tagged site (STS), plasmid, genetic expression (i.e., transcription) state, including the nucleotide sequence and encoded amino acid sequence associated with any of the above.

[0041] The present invention employs the DNA/Gene profiling by any of the following method to understand person's unique gene traits. The method is any of the latest technique but not limited to SNP identification by Gene sequencing, RFLP, Microan-ay, RT-PCR, etc.The system further identifies specific gene traits which are coded by gene sequences also called SNPs (Single nucleotide polymorphism) that are unique to individual and varies from person to person. These SNPs are identified by incorporating gene markers during one of the above method to understand the person's food preferences.

[0042] The DNA code or gene analysis used in the present invention is carried out by providing gene test kit to an individual. The kit includes the material to collect biological sample of an individual and a small manual to guide that person about how to collect and send that sample.

[0043] In yet another embodiment of the present invention, the system or method further discloses biological sample could be any tissue or body fluid containing Person's DNA and is tissue sample. More specifically tissue sample could be epithelial tissue from buccal cavity or hair root or skin, fingernail etc. The body fluid is any of the following fluid like blood, tears, saliva, urine, nasal secretion, spinal fluid etc. [0044] The food recommendation system uses the preferred biological samples as either saliva or cheek tissue. The biological sample is received from the client/ individual who is interested in more specifically genetic based selection of diet. DNA kit is provided to client is equipped with a sterile and sealed test ampoule filled with suitable buffer, cotton swab to take out the tissue from cheek, and a small manual for guidance.

[0045] The sample delivered to laboratory is processed with utmost care to avoid any damage or contamination to DNA/ Genetic material. It is first extracted from tissue using appropriate procedure, purified and then placed for amplification. Amplified DNA is further reacted with specific probes using suitable method for identification of genetic makers related to taste and olfactory receptors collectively called food preferences traits on individual's DNA1Genetic material.

[0046] Resulting information from the above test about presence/absence of genetic markers is stored in digital gene database. This stored information is sent for processing by a processor which gives an indication or information for food preferences of an individual. As described above in Figure 4, itdescribes how Genome dataset preparation is done, that is linked to an Al tool.

1100471-Figure 5 depicts all the relevant databases used to implement the food/diet recommendation. The system (500) recommends optimal food/dietary recommendation for individual user's based on AT smart tool and by linking DNA analysis. The system of the present invention uses data's stored in the databases, namely, Geographic database (560),Genetid Ancestry database (550) ,User's Past Order History database (540), Registered User Profile database (530), and Psychological/ Emotional Food Image Profiling database (520) . In one embodiment of the invention, the user register's with the food delivery application via the interface. The registered user data is stored in a database registered user profile (530) which stores information such as personal user information, users vital information etc. The database genetic/ancestry database (550) stores data received from the laboratory testing and processing database (550a), wherein it stores the results of each individual's DNA analysis information such as biological samples, DNA /gene code etc. The system also stores data related to user's past order history in the database user's past order history (560), and also from the database (520) to retrieve the response to psychological food image profiling.Not to exclude, it also recommends data from the user's place of origin (560). Thus, the system provides an enhanced optimal food recommendation by using primarily the tripartite databases (520,530,550).

[0048] Figure 6 illustrates the overall flowchart of the process in which the optimal food /diet is recommended to the individual. The system gathers user data (610) and creates an individual user specific profile (620). The registered user profile is requested to fill in questionnaire related to general information, food preferences, likes or dislikes or taste preferences of individual (630) ; collects data related to DNA test kit (640); user's country of origin (650) to know whether food preferences is related to ancestral data and its typical food type; psychological or emotional response to food image profiling (660) and based on the user's past order history (670). Then, the system has an AT specific algorithm based system (680) that recommends precise food recommendations to individual. It further uses the tripartite system to suggest best optimal food recommendations to the users to enhance the health, wellness and preferences of the users.

[0049]An overview of the relationship between the tripartite system (710,720 and 740) and its processes is illustrated in figure 7, to provide an optimized food or dietary recommendation system 700. The system access the genetic data or DNA analysis send by individual registered user processed, tested and analyzed from the laboratory system (720); it extracts the past order historical data and user's vital data (710) and also the psychological and emotional response to food image profiles (740).

The AT based algorithm runs on the basis of this tripartite system and recommends optimized food recommendation system.

[0050] Reference throughout this specification to "one embodiment,-an embodiment, or similar language means that a particular feature, structure. or characteristic described in connection with the embodiment is included in atleast one embodiment of the present invention. Thus, appearances of the phrases in one embodiment,' n an embodiment,"and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.

[0051] Furthermore, the described features, structures, or characteristics of the invention may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are included to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention can be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the invention. The terms "DB" and "Database" have been interchangeably used in the current specification. Similarly, the terms "Al and Artificial Intelligence have been used interchangeably in the specification."

Claims (8)

1. Claims: I. A method of food recommendation system comprising: a. the steps for receiving a plurality of user specificgenetic profile details; b. the steps for processing a plurality of genetic profiles details of the usersusing Artificial Intelligence algorithm; c. the steps for processing results of a plurality of user genetic profiles for gene analysis; d. the steps for displaying food recommendation results for a plurality of user genetic profiles.
2. 2. A system for recommending and ordering food online comprising: a. a computer usable medium having a computer implemented program for recommending food items to a plurality of users based on their genetic profiles; b. a computer program configured to obtain the order history from the transitory storage medium of the user device; c. a computer program configured to recommend food items based on the genetic profile of plurality of users.d. a distributed computing environment comprising a plurality of client or user computers and at least one server connected to the client computers, the server capable of connecting by one or more communication links to a plurality of users.
3. 3. A system according to claim 2 comprising: a. a web server; b. computerized databases interacting with the said web server; said databases include user profile database; geographic database; genetic results database; user past order history database; psychological food image profiling database; c. collecting and processing results from aplurality of usersgenetic profiles in order to recommend said users; a specific diet.
4. 4. A system according to claim 2, wherein: a. user profile database includes a plurality of users credentials; b. geographic database includes geographic profiles of a plurality of food items; c. past order history database includes a plurality of past orders history data; d. psychological food image profile database includes a plurality of food images for visual representations of food items; e. genetic results database includes a plurality of genetic or DNA profile data of the users.
5. 5. A method of food recommendation system further comprising: a. a tripartite system comprising genetic data of the user; user's psychological response to food image profiling and user's past order history.b. a tripartite system wherein the Artificial Intelligence algorithm intuitively recommends food items based on the user's genetic profile, psychological response of the user to various food images and past order history of the user.
6. 6. The method of claim 5, wherein the Artificial Intelligence algorithm is automated with the food recommendation system to suggest optimal diet recommendation to the said users.
7. 7. The method of claim 5, wherein the Artificial Intelligence algorithm uses machine or deep learning algorithms to execute food recommendations.
8. 8. The method of claim 5, wherein the psychological response to food image profiling is the actual response of the user towards visual stimulation when they see various food images in the said food recommendation system.