GB2574435A - Personalised nutritional information system - Google Patents
Personalised nutritional information system Download PDFInfo
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- GB2574435A GB2574435A GB1809264.3A GB201809264A GB2574435A GB 2574435 A GB2574435 A GB 2574435A GB 201809264 A GB201809264 A GB 201809264A GB 2574435 A GB2574435 A GB 2574435A
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- 235000016709 nutrition Nutrition 0.000 title claims abstract description 63
- 235000013305 food Nutrition 0.000 claims abstract description 60
- 238000004806 packaging method and process Methods 0.000 claims abstract description 6
- 230000003050 macronutrient Effects 0.000 claims abstract description 5
- 235000021073 macronutrients Nutrition 0.000 claims abstract description 5
- 239000004615 ingredient Substances 0.000 claims abstract description 3
- 239000011785 micronutrient Substances 0.000 claims abstract description 3
- 235000013369 micronutrients Nutrition 0.000 claims abstract description 3
- 235000018823 dietary intake Nutrition 0.000 claims description 11
- 238000010801 machine learning Methods 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 2
- 238000012549 training Methods 0.000 description 25
- 230000000694 effects Effects 0.000 description 13
- 239000000446 fuel Substances 0.000 description 9
- 238000012544 monitoring process Methods 0.000 description 9
- 229920002527 Glycogen Polymers 0.000 description 8
- 150000001720 carbohydrates Chemical class 0.000 description 8
- 229940096919 glycogen Drugs 0.000 description 8
- 230000035764 nutrition Effects 0.000 description 8
- 210000003205 muscle Anatomy 0.000 description 7
- 238000011084 recovery Methods 0.000 description 7
- 208000027418 Wounds and injury Diseases 0.000 description 5
- 230000006378 damage Effects 0.000 description 5
- 208000014674 injury Diseases 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 235000021074 carbohydrate intake Nutrition 0.000 description 4
- 230000001684 chronic effect Effects 0.000 description 4
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- 230000037081 physical activity Effects 0.000 description 3
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- 108090000623 proteins and genes Proteins 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000004580 weight loss Effects 0.000 description 3
- BXNJHAXVSOCGBA-UHFFFAOYSA-N Harmine Chemical compound N1=CC=C2C3=CC=C(OC)C=C3NC2=C1C BXNJHAXVSOCGBA-UHFFFAOYSA-N 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- 230000000386 athletic effect Effects 0.000 description 2
- 230000003190 augmentative effect Effects 0.000 description 2
- 235000015872 dietary supplement Nutrition 0.000 description 2
- 235000012631 food intake Nutrition 0.000 description 2
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- 230000002503 metabolic effect Effects 0.000 description 2
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- 239000000047 product Substances 0.000 description 2
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- 229930194542 Keto Natural products 0.000 description 1
- 102000008934 Muscle Proteins Human genes 0.000 description 1
- 108010074084 Muscle Proteins Proteins 0.000 description 1
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- 230000037396 body weight Effects 0.000 description 1
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- 235000021316 daily nutritional intake Nutrition 0.000 description 1
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- 230000037213 diet Effects 0.000 description 1
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- 238000005457 optimization Methods 0.000 description 1
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Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
Landscapes
- Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Engineering & Computer Science (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Nutrition Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- Physical Education & Sports Medicine (AREA)
- Medical Treatment And Welfare Office Work (AREA)
- Coloring Foods And Improving Nutritive Qualities (AREA)
Abstract
System comprising means 2 for transmitting nutritional information from a food item 1; means for transmitting the nutritional information to a server at a time t1 and for transmitting physiological information of a user following consumption of the food item to the server at a time t2; and means for providing updated physiological information to the user at a time t3 based on the nutritional information and the physiological information. May comprise means for providing updated physiological information to the user based on information provided by the user at a time t4. The means for transmitting nutritional information from a food item may comprise a NFC transmitter, which may be integrated into packaging of the food item. The nutritional information may comprise a food type, ingredients, calorie, macronutrient or micronutrient content of the food item. The means for transmitting the nutritional information to the server and for providing physiological information of the user may comprise a smart phone, smart watch, wearable smart device, smart clothing, smart shoes, or wearable body sensor. Also provided is a smart device configured to receive nutritional information from a food item without user input and transmit the information to a server.
Description
Title
Personalised Nutritional Information System
Field of the Invention
The present invention is directed to tracking a user’s nutritional intake. In particular it is directed to generating and providing personalised nutritional information to a user based on their food intake around the time of exercise, anthropometric data and activity levels.
Background to the Invention
It has become popular in recent times for consumers to record and track their nutritional intake in some manner. For example, in the market today, there are several commercial products available that enable a person to monitor their daily calorific intake by several means; for example, inputting data manually into an “app”, scanning QR codes for input, taking pictures of bar codes on store bought products and taking pictures of food where the approximate calorific content is calculated. Solutions are offered that allow a user to balance their daily nutritional intake vs weight gain or loss. Such solutions may make suggestions on how to improve food intake vs exercise, however they do not analyse an overall physiological response of the body vs exercise to improve performance at exercise. Such approaches are analogous to Weight Watchers ® or Slimming World ® where diet is the main focus. Furthermore, such solutions do not consider how an individual may respond to a particular food type or macronutrient content and how improvement in the chosen exercise field can be achieved through personalised nutrition planning or prediction. In addition, it is a major disadvantage that such solutions require manual inputting or tracking of nutritional data into an application or other interface. This is cumbersome for the user and further leads to incorrect or incomplete inputting of data.
Removing the requirement for manual input of data and providing personalised feedback to a user as to their nutritional intake and predicting future needs would be a significant improvement over the state of the art.
Summary of the Invention
The present invention provides a system comprising means for providing nutritional information from a food item; means for transmitting the nutritional information of the food item to a server at a time t1 and for providing physiological information of a user following consumption of the food item to the server at a time t2; means for providing updated physiological information to the user at a time t3 based on the nutritional information provided at time t1 and the physiological information provided at time t2.
This is advantageous as it provides for the collection of nutritional information from a food item and furthermore for the collection of physiological information from a user. The food item may be a nutritional supplement. Upon collection of the information, the system provides for analysis and output of updated physiological information to a user. The updated physiological information takes into account the nutritional information associated with a food item and on the assumption that the user subsequently consumes the item. The updated information is provided to the user indicating the physiological response to the food item in the user’s body, reinforced by subjective user experience feedback.
Furthermore, if it is assumed that the user engages in physical exercise during the period between t2 and t3, examining the physiological response of the user to the nutritional intake of the food item at several time intervals during exercise provides for the possibility to, for example, (i) improve performance output of the user by recommending a sports nutrition package that should be eaten before, during and after training and (ii) develop an inline-real time energy or “fuel gauge” wherein the user will know when to eat the tailored nutrition to yield performance output. This system thus provides a tailored and individualised service using data analysis based on both nutritional and physiological information as calculated relative to the activity and anthropometric profile of the individual user.
The system may further comprise means for providing updated physiological information to the user further based on information provided by the user at a time t4. This information may comprise subjective user experience feedback. It may also further comprise basic data inputs describing the user such as for example, age, weight and height. The time t4 may be before time t1, i.e. the user may provide the system with initial information regarding their physical status and nutritional intake. Similarly the time t4, may be after the time t3, whereby the user reviews the information provided by the system at time t3 and provides individualised feedback.
The means for providing nutritional information from a food item may comprise a near field communication, NFC, transmitter. This is advantageous as it provides that nutritional information can be transmitted easily from a food item. It further obviates the requirement for a user to manually input data into an interface. The NFC transmitter may automatically transmit data, for example when in proximity to a smart device.
The NFC transmitter may be integrated into the packaging of the food item or nutritional supplement. This is advantageous as it provides for integration of the transmitter into packaging typical to food items, i.e. no additional packaging is required to house the transmitter simplifying ease of use.
The nutritional information may comprise information indicating at least one of a food type, ingredients, calorie content, macronutrient and micronutrient content. This provides that accurate information may be output with respect to the effect on the user of the content of the food item.
The means for transmitting the nutritional information of the food item to a server and for providing physiological information of a user may comprise at least one of a smart phone, smart watch or a wearable smart device, smart clothing, augmented reality glasses, smart shoes, or other wearable body sensor. This is advantageous as typically a user will retain such a device on or close to their body, thus providing for transmission of physiological information. In addition, the physiological information from the user may be transmitted to the server via devices such as “Fitbit” ®, “Garmin”®, “Strava” ® or applications used to track athletic activity via satellite navigation and/or activity related accelerometer.
The means for providing updated physiological information to the user may comprise a machine learning means. This is advantageous as it provides that the machine learning means can learn about a user’s traits and activities and thus over a period of time provide more specific tailored feedback to a user about their nutritional intake and needs. To facilitate the machine learning, a large database of anonymised physiological output may be gathered based on historical training data, but also data generated in tandem with the response to the nutritional input. This allows for a bell curve to be created enabling a new user to be benchmarked against the bell curve with the ability for the system to tailor the nutritional offering to the user to improve/enhance his or her performance and nutrition personalisation goals.
The means for providing updated physiological information may further comprise information on projected nutritional intake for the user. This is advantageous as it provides a user with information indicating their nutritional requirements to optimise a given level of physical performance and recovery over a defined period of time.
The updated physiological information may be provided to the user in the form of a gauge indicating projected user energy levels. This is advantageous as it provides a user with visual indication of their current physical condition and a projection of how their physical condition will alter over time, for example, how their condition will alter throughout a training or exercise session. It may also provide a visual guide as to time spent in various metabolic states (e.g. fat burning, mixed metabolism, carbohydrate, anaerobic), stages of fuel up before training and stages of recovery including macronutrient requirements (e.g. protein, carbohydrate) after training.
A further aspect of the present invention comprises a smart device configured to receive nutritional information from a food item without user input; and transmit the nutritional information of the food item to a server. Such a device is advantageous as it obviates the requirement for a user to manually input data into an interface.
A further aspect of the present invention comprises a method of transmitting nutritional information of a food item to a server at a time t1; providing physiological information of a user following consumption of the food item to the server at a time t2; providing updated physiological information to the user at a time t3 based on the nutritional information provided at time t1 and the physiological information provided at time t2.
Brief Description of the Drawings
Figure 1 shows a system according to the invention.
Figure 2 shows an aspect of the system according to the invention indicating monitoring of activity through a smart device and transfer of information to a server.
Figure 3 shows an aspect of the system according to the invention indicating collection and analysis in a database and providing custom predictions on how and when to use food items to enhance performance and recovery.
Figure 4 shows an aspect of the system according to the invention indicating a live inline “fuel gauge” that can be used by the end user to increase performance by ensuring the correct nutritional intake during exercise
Detailed Description
The present invention provides a technology platform to monitor nutritional input vs a physiological body response and may include subjective user feedback. This provides that the system can provide information to tailor nutritional plans and packs that can enhance an end user’s performance. It is estimated, for example, that 10 kilometre running times could be improved by 2 to 5 minutes over a 3 to 6 month training period with the right balance of carbohydrate during training balanced with sufficient protein recovery, greater improvements can be achieved over longer distances. The present invention provides a means of gathering nutritional and physiological information such that tailored feedback can be provided to a user to help enhance their physical performance.
Figure 1 shows a system according to the invention. A system is provided comprising means for providing nutritional information from a food item 1. The means comprises an NFC transmitter 2 integrated into food packaging, for example, a food wrapper. The food item itself may be a specifically designed food stuff, such as an energy bar, for enhancing athletic performance. The NFC transmitter is uniquely coded with nutritional information specific to the food item.
The system further comprises a smart phone 3 or other smart enabled device for detecting information from the NFC transmitter. The smart device is utilised for transmitting the nutritional information of the food item to a server at a time t1 and for providing physiological information of a user following consumption of the food item to the server at a time t2. The server comprises a database 4 of information relating to food items, physiological data and dates and times of physical activity. The database information is analysed in order to provide updated physiological information to the user at a time t3 based on the nutritional information provided at time t1 and the physiological information provided at time t2. A user may provide additional information to the server to further personalise the updated physiological information being provided. For example, a user may provide basic data inputs to the server including but not limited to: a user’s age, bodyweight, height, gender, chosen sport or activity, number of weekly training sessions, session duration and intensity. Furthermore, a user may input a performance goal to further refine the information provided to them, such goals may include weight loss, muscle gain, to be lean and toned, to be performance or race ready or to provide enjoyment and health.
Figure 2 shows an aspect of the system according to the invention indicating monitoring of activity through a smart device and transfer of information to a server. For example, a user’s activity may be monitored by a “Fitbit”®, “Garmin”®, “Strava”® or applications 5 used to track athletic activity (including but not limited to heart rate, pace, power output, calories burned) via satellite navigation and/or accelerometer during the period between t1, when nutritional information of a food item, for example an energy bar, is transmitted to the server and t2, a time after consumption of the food item. Monitoring during this period allows for the system to analyse the effect of the food item on a user’s body. Monitoring of information may include monitoring the time of exercise, the duration of exercise, a user’s heart rate, GPS data for distance, pace/speed, elevation and incline. Information may be gathered from an accelerometer. Information may be gathered from a thermometer to measure and athlete’s temperature and ambient temperature. Sweat rate may also be monitored such as with a galvanic skin response. Monitoring can also occur during periods of rest and during periods when the user has not necessarily consumed a food item. Such monitoring can provide information which is used to form a “baseline” for a given user. This allows the system to more accurately provide information specific to a user’s energy requirements.
Unaided, most people do not fuel their sport appropriately for optimal performance, largely because of the time between nutritional intake and performance change (the effects of appropriate carbohydrate intake are most visible during the third hour of exercise). It has been noted by Kimber et al (2002) and Harger Domitrovich et al (2007) that optimal fuelling is linked to faster race finish times, increased time to exhaustion, reduced RPE (rate of perceived exertion), improved motor skills for longer in skill sports, suppressed hepatic glucose output, and sparing of muscle glycogen use - this means a faster recovery for the next session.
Monitoring of nutritional input and activity levels in a user allows for information to be provided to the users with respect to carbohydrate use and requirements and muscle glycogen levels (exercise fuel store). The user can then alter the training and nutritional intake with a view to improving their overall performance. Furthermore, gastrointestinal disturbance during exercise is often linked to inappropriate nutrition strategies and such strategies are highly variable between individuals. While this can be avoided through gastrointestinal training with incremental carbohydrate quantities, there is currently no method to monitor and refine this gut training. Training load (intensity and volume) can be used to predict injury rates, this accuracy increases if energy balance (chronic nutritional status) is also monitored. The combined data can be used to calculate and predict injury and illness risk from under or over loading.
Furthermore, as per Figure 3, such monitoring can provide information which is used to form a prediction 6 for a user as to when they should consume a food item 1 to maximise their performance during a given exercise session or maximise efforts toward a particular nutrition strategy (e.g. faster training, glycogen depletion training, low carb high fat training, keto training, paleo, weight loss, fat burning). It may also be used to provide a schedule to a user of when specific food items should be consumed, as well as the number and quantity, in order to improve performance.
A user may transmit data to the server over a long period of time, for example over a period of months. In this manner, as user data collection points increase in frequency and data sets stored in the database become larger, it becomes possible to build an in-line “fuel gauge” and other metabolic gauges as per Figure 4 that may be visible to a user before, during and after training. The gauge 7 may be visible for example on an “app” on the smart device or augmented reality device. The app can for example (i) send a “nudge” to a user eat a nutrition bar or other food item (ii) warn the user when approaching “empty” so user can decide if he/she will consume nutrition. The gauge may be based on the individuals’ physiological response to nutrition as analysed and determined by the system of the invention. This graphical representation of the relevant user data may be adjusted to present a number of scenarios such as fuel levels before, during and after training.
The system will now be described in use using a brief illustrative example. A user is about to engage in physical activity, for example a 5 km run. The user retrieves a food item 1, for example an energy bar, before commencing their run. The user has a smart enabled device 3 on her wrist in the form of a GPS watch. Nutritional information is transmitted from the food item via an NFC transmitter 2 to the watch. The nutritional information is transmitted to a database 4 at a server at a time t1. The user consumes the energy bar and physiological information about the user is transmitted to the server at a time t2 following consumption of the bar. The user then sets off to complete their run. Upon completion of the run at a time t3, the server sends updated physiological information to the user. Based on the updated physiological information, the user is also presented with feedback as to the effect of the food item 1 on their performance and suggestions, such as, how consuming of an additional item may improve performance, how altering the time of consumption may improve performance.
The system may also provide for machine learning based on a user’s data accumulated over a period of time. Such learning further serves to increase the specificity of information available to a user about their past performance and their potential further performances.
The present system provides for offering real time analysis and updates of nutritional information and physical activity information. This provides for optimizing of athletes’ carbohydrate intake and immediate protein recovery. This yields improved exercise performance and muscle protein synthesis.
The optimization may be performed by tracking carbohydrate intake, performance, user feedback and RPE (rate of perceived exertion) or another objective surrogate marker. The data may be collated and provided as tailored feedback to an individual. Furthermore, that data is used to train a machine learning model to improve feedback and provide predictions for each individual user.
Specific instances of the types of information to be provided to a user and the benefits of that information include:
a. Recovery sessions: users may be monitored to ensure that they are optimally fuelled up before, during and after exercise so that they finish nutritionally recovered to maximize achievable muscle glycogen levels. This allows for higher intensity training at the next session.
b. Low carbohydrate, or fasted state, or glycogen depleted training: a user exploring a specific nutritional training strategy may be provided with specific feedback on how various muscle glycogen levels and exogenous carbohydrate intake levels influence their performance data. As there is currently no accurate nutritional tracking system, there is no system that relates nutritional status to training status.
c. Response tracking to carbohydrate loading: a user can test time to fatigue in various carbohydrate loading strategies to prepare an optimal approach for races.
d. Chronic nutritional/energy deficit status: for athletes who train twice daily or on consecutive days who may not have sufficient time to replenish muscle glycogen between sessions, the system may provide a predicted real time muscle glycogen ‘fuel gauge’ to predict when it is time to fuel up or reduce training volume.
e. Predict injury risk from ACWR (acute to chronic workload ratio): employing exponential weighted rolling averages of training and nutritional load to predict injury risk and dictate recommended training volume.
Through sufficient data learning the system may predict:
a. Nutritional fatigue from wearable/smart device monitored biomarkers before it is felt by the user and before it impairs performance
b. Early prediction of injury risk from chronic nutritional strategies
The words “comprises/comprising” and the words “having/including” when used herein with reference to the present invention are used to specify the presence of stated features, integers, steps or components but do not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof.
It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination.
Claims (11)
1. A system comprising:
means for transmitting nutritional information from a food item;
means for transmitting the nutritional information of the food item to a server at a time t1 and for transmitting physiological information of a user following consumption of the food item to the server at a time t2;
means for providing updated physiological information to the user at a time t3 based on the nutritional information provided at time t1 and the physiological information provided at time t2.
2. The system of claim 1 further comprising means for providing updated physiological information to the user further based on information provided by the user at a time t4.
3. The system of claim 1 wherein the means for transmitting nutritional information from a food item comprises a near field communication, NFC, transmitter.
4. The system of claim 3 wherein the NFC transmitter is integrated into packaging of the food item.
5. The system of any preceding claim wherein the nutritional information comprises information indicating at least one of a food type, ingredients, calorie content, macronutrient and micronutrient content of the food item.
6. The system of claim 1 wherein the means for transmitting the nutritional information of the food item to a server and for providing physiological information of a user comprises at least one of a smart phone, smart watch, wearable smart device, smart clothing, smart shoes, wearable body sensor.
7. The system of claim 1 wherein the means for providing updated physiological information to the user comprises a machine learning means.
8. The system of any preceding claim wherein the updated physiological information further comprises information on projected nutritional intake for the user.
9. The system of claim 8 wherein the updated physiological information is provided to the user in the form of a gauge indicating projected user energy levels
10. A smart device configured to:
receive nutritional information from a food item without user input; and transmit the nutritional information of the food item to a server.
11. A method comprising:
transmitting nutritional information of a food item to a server at a time t1;
providing physiological information of a user following consumption of the food item to the server at a time t2;
providing updated physiological information to the user at a time t3 based on the nutritional information provided at time t1 and the physiological information provided at time t2.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB1809264.3A GB2574435A (en) | 2018-06-06 | 2018-06-06 | Personalised nutritional information system |
| PCT/EP2019/064076 WO2019233875A1 (en) | 2018-06-06 | 2019-05-29 | Personalised nutritional information system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB1809264.3A GB2574435A (en) | 2018-06-06 | 2018-06-06 | Personalised nutritional information system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| GB201809264D0 GB201809264D0 (en) | 2018-07-25 |
| GB2574435A true GB2574435A (en) | 2019-12-11 |
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|---|---|---|---|
| GB1809264.3A Withdrawn GB2574435A (en) | 2018-06-06 | 2018-06-06 | Personalised nutritional information system |
Country Status (2)
| Country | Link |
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| GB (1) | GB2574435A (en) |
| WO (1) | WO2019233875A1 (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111524576B (en) * | 2020-05-08 | 2023-07-07 | 四川大学 | A food weight estimation learning system for weight control |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090132016A (en) * | 2008-06-19 | 2009-12-30 | 주식회사 케이티 | Health care device based on ubiquitous sensor network and method thereof, health care service system and method using same |
| WO2018036944A1 (en) * | 2016-08-23 | 2018-03-01 | Koninklijke Philips N.V. | Method and system for food and beverage tracking and consumption recommendations |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EA029289B1 (en) * | 2011-07-08 | 2018-03-30 | Лайфкью Глоубл Лимитед | PERSONAL ASSISTANT POWER SUPPLY AND GOOD WELLNESS |
| US20160262693A1 (en) * | 2013-10-14 | 2016-09-15 | Case Western Reserve University | Metabolic analyzer for optimizing health and weight management |
-
2018
- 2018-06-06 GB GB1809264.3A patent/GB2574435A/en not_active Withdrawn
-
2019
- 2019-05-29 WO PCT/EP2019/064076 patent/WO2019233875A1/en not_active Ceased
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090132016A (en) * | 2008-06-19 | 2009-12-30 | 주식회사 케이티 | Health care device based on ubiquitous sensor network and method thereof, health care service system and method using same |
| WO2018036944A1 (en) * | 2016-08-23 | 2018-03-01 | Koninklijke Philips N.V. | Method and system for food and beverage tracking and consumption recommendations |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2019233875A1 (en) | 2019-12-12 |
| GB201809264D0 (en) | 2018-07-25 |
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