CN109785934B - Food recommendation method and related device - Google Patents
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- CN109785934B CN109785934B CN201910058742.2A CN201910058742A CN109785934B CN 109785934 B CN109785934 B CN 109785934B CN 201910058742 A CN201910058742 A CN 201910058742A CN 109785934 B CN109785934 B CN 109785934B
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Abstract
The embodiment of the application discloses a food recommendation method and a related device, which are applied to an electronic device comprising a substance detection sensor, wherein the method comprises the following steps: acquiring the first content of trace elements in the moving precursor through the substance detection sensor; acquiring the second content of trace elements in the body after movement through the substance detection sensor; determining the amount of trace element loss in the body based on the first content and the second content; food is recommended based on the amount of trace elements lost in the body. The embodiment of the application is beneficial to improving the rationality of diet.
Description
Technical Field
The application relates to the technical field of electronics, in particular to a food recommendation method and a related device.
Background
With the wide popularization of applications of mobile terminals (such as smartphones), applications that can be supported by mobile terminals are more and more, functions are more and more powerful, and smartphones are developed towards diversification and individuation, so that the mobile terminals become indispensable electronic products in the life of users. A large number of exercise APP can be installed in the current mobile terminal, an exercise program is set in the exercise APP, the exercise APP gives corresponding exercise recipes through analysis of background data, and an exercise fan usually carries out diet according to the exercise recipes recommended by the exercise APP.
Disclosure of Invention
The embodiment of the application provides a food recommendation method and a related device, which are used for matching food for a user according to the loss condition of trace elements before and after exercise, and improving the body-building effect.
In a first aspect, embodiments of the present application provide a food recommendation method applied to an electronic device, the electronic device including a substance detection sensor, the method including:
acquiring the first content of trace elements in the moving precursor through the substance detection sensor;
acquiring the second content of trace elements in the body after movement through the substance detection sensor;
determining the amount of trace element loss in the body based on the first content and the second content;
food is recommended based on the amount of trace elements lost in the body.
In a second aspect, embodiments of the present application provide an electronic device, including a processor, a substance detection sensor and a camera, the substance detection sensor being connected to the processor, wherein:
the processor obtains the first content of trace elements in the movement precursor through the substance detection sensor;
the processor acquires the second content of trace elements in the body after movement through the substance detection sensor;
the processor determines the loss amount of the trace elements in the body based on the first content and the second content;
The processor recommends food based on the amount of loss of the trace elements in the body.
In a third aspect, embodiments of the present application provide a food recommendation apparatus, applied to an electronic apparatus, the electronic apparatus including a substance detection sensor, the food recommendation apparatus including: the system comprises an acquisition module, a determination module and a recommendation module, wherein:
the acquisition module is used for acquiring the first content of trace elements in the movement precursor;
the acquisition module is also used for acquiring the second content of trace elements in the body after the exercise;
the determining module is used for determining the loss amount of the trace elements in the body based on the first content and the second content;
the recommending module is used for recommending food based on the loss amount of the microelements in the body.
In a fourth aspect, embodiments of the present application provide an electronic device comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of the first aspect of embodiments of the present application.
In a fifth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program, where the computer program is executed by a processor to implement some or all of the steps described in the method according to the first aspect of the embodiments of the present application.
In a sixth aspect, embodiments of the present application provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the method of the first aspect of embodiments of the present application. The computer program product may be a software installation package.
It can be seen that in the embodiment of the application, the content of the trace elements in the body before and after the exercise is obtained through the substance sensor, and the trace loss amount in the body before and after the exercise is determined, so that after the exercise, the relevant food is recommended according to the trace element loss amount in the body of the user, the targeted recommended body-building food is realized, and the body-building effect is improved.
These and other aspects of the present application will be more readily apparent from the following description of the embodiments.
Drawings
In order to more clearly describe the technical solutions in the embodiments or the background of the present application, the following description will describe the drawings that are required to be used in the embodiments or the background of the present application.
Fig. 1A is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 1B is a schematic diagram of a positional relationship between a substance detection sensor and a camera according to an embodiment of the present application;
FIG. 1C is a schematic diagram of a positional relationship between another substance detection sensor and a camera provided in an embodiment of the present application;
FIG. 2A is a schematic flow chart of a food recommendation method according to an embodiment of the present disclosure;
FIG. 2B is a schematic diagram of a display interface for food recommendation according to an embodiment of the present application;
FIG. 2C is a schematic diagram of a substance detection sensor according to an embodiment of the present application;
FIG. 2D is an infrared spectrogram provided in an embodiment of the present application;
FIG. 3 is a flow chart of another food recommendation method provided in an embodiment of the present application;
FIG. 4 is a functional block diagram of a food recommendation device according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of another electronic device according to an embodiment of the present application.
Detailed description of the preferred embodiments
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
The following will describe in detail.
The terms "first," "second," "third," and "fourth" and the like in the description and in the claims of this application and in the drawings, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or modules is not limited to only those steps or modules but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The electronic apparatus according to the embodiments of the present application may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices, or other processing devices connected to a wireless modem, and various forms of User Equipment (UE), mobile Station (MS), terminal devices (terminal devices), and so on. For convenience of description, the above-mentioned apparatuses are collectively referred to as an electronic device.
The embodiments of the present application are described in detail below.
Referring to fig. 1A, fig. 1A is a schematic structural diagram of an electronic device 100 according to an embodiment of the invention, where the electronic device 100 includes: the electronic device comprises a shell 110, a display 120 arranged on the shell 110, and a main board 130 arranged in the shell 110, wherein a processor 140 and a memory 150 are arranged on the main board 130, as shown in fig. 1B, a substance detection sensor 160, a camera 170 and the like are further arranged on the electronic device, the substance detection sensor 160 and the camera 170 are connected with the processor 140, the processor 140 is connected with the display 120, the electronic device 100 further comprises a radio frequency system 180 as shown in fig. 1A, and the radio frequency system 180 comprises a transmitter 181, a receiver 182 and a signal processor 183, wherein;
The processor 140 is configured to obtain, by using the substance detection sensor, a first content of trace elements in the moving precursor; and the substance detection sensor is used for acquiring the second content of trace elements in the body after movement; and determining an amount of trace elements lost in the body based on the first and second levels; and for recommending food based on the amount of trace elements lost in the body.
The display 120 includes a display driving circuit, a display screen, and a touch screen, where the display driving circuit is configured to control the display screen to display content according to display data and display parameters (for example, brightness, color, saturation, etc.) of a picture, and the touch screen is configured to detect a touch operation, and the display screen is an organic light emitting diode display screen OLED.
The camera 170 may be a front camera of the electronic device 100, or may be a rear camera of the electronic device 100, but no matter whether the camera 170 is a front camera or a rear camera, the substance detection sensor 160 is disposed close to the camera 170, for example, as shown in fig. 1B, when the camera 170 is a rear dual camera, the substance detection sensor 160 is disposed in the middle of two cameras, or, as shown in fig. 1C, when the camera 170 is a rear single camera, the substance detection sensor 160 is disposed above the camera 170, and the like, which is not limited herein.
The substance detecting sensor 160 may detect various substances, such as heat, moisture, sugar, blood oxygen, fat, trace elements, etc., and since different substances have different absorption capacities on near infrared spectrums, a plurality of channels are integrated in the substance detecting sensor 160, when detecting substances, infrared light is emitted by the infrared LED lamp in the substance detecting sensor 160, and then the lighting device in the substance detecting sensor 160 collects infrared light of different wavelengths reflected back in each channel due to irradiation of different substances, so as to obtain an infrared spectrum, and performs big data analysis on the infrared spectrum, thereby determining the substance components.
The shape and size of the motherboard 130 may be any size and shape that can be accommodated by the electronic device 100, which is not limited herein.
The processor 140 includes an application processor and a baseband processor, and the processor 140 is a control center of the electronic device 100, and connects various parts of the entire electronic device using various interfaces and lines, and executes various functions and processes data of the electronic device 100 by running or executing software programs and/or modules stored in the memory 150 and calling the data stored in the memory 150, thereby performing overall monitoring of the electronic device 100. The application processor mainly processes an operating system, a user interface, an application program and the like, and the baseband processor mainly processes wireless communication. It will be appreciated that the baseband processor described above may not be integrated into the processor.
The memory 150 may be used to store software programs and modules, and the processor 140 executes various functional applications and data processing of the electronic device 100 by executing the software programs and modules stored in the memory 150. The memory 150 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, application programs required for at least one function, and the like; the storage data area may store data created according to the use of the electronic device, etc. In addition, memory 150 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.
It can be seen that, in the embodiment of the present application, the first content of the trace elements in the exercise precursor and the second content of the trace elements in the exercise post are obtained through the material sensor 160, and the trace loss amount in the exercise precursor and the exercise post is determined based on the first content and the second content, so that after the exercise, the relevant food is recommended for the user according to the trace loss amount in the body, so as to supplement the trace elements lost in the exercise process, realize the targeted recommended exercise food, avoid blind diet after the exercise, and improve the exercise effect.
In one possible example, the processor 140 is specifically configured to, in terms of obtaining the first content of trace elements in the moving precursor by the substance-detecting sensor: scanning any part of the body of a user through the substance sensor to obtain a first group of data corresponding to the part; and determining a moisture content of the site based on the first set of data; and determining the moisture content in the user's body based on the correspondence of the moisture content of the site to the moisture content in the body and the moisture content of the site; and determining a first content of trace elements in the exercise precursor based on the correspondence between the moisture content in the user's body and the content of trace elements and the moisture content in the user's body.
In one possible example, the processor 140 is specifically configured to, in terms of obtaining the first content of trace elements in the moving precursor by the substance-detecting sensor: acquiring a motion type and determining at least one key part corresponding to the motion type; and scanning the at least one key part of the body of the user through the substance sensor to obtain a second set of data corresponding to each key part; and determining a moisture content for each of the key locations based on the second set of data; and determining the content of trace elements in each key part based on the moisture content of each key part, and determining the first content of trace elements in the exercise precursor based on the content of trace elements in each key part.
In one possible example, when determining the content of trace elements in each of the key locations based on the moisture content of each of the key locations, and determining the first content of trace elements in the exercise precursor based on the content of trace elements in each of the key locations, the processor 140 is specifically configured to: determining the content of the trace elements of each key part based on the corresponding relation between the preset moisture content of each key part and the content of the trace elements and the moisture content of each key part; and the volume of the user and the volume of each key part are acquired; and determining a ratio of the volume of each key location to the volume of the user; and the method is used for obtaining the content of the trace elements in at least one sport precursor based on the ratio of each key part and the content of the trace elements in each key part, and taking the average content of the trace elements in the at least one sport precursor as the first content of the trace elements in the sport precursor.
In one possible example, the processor 140 is specifically configured to, when acquiring the volume of the user and the volume of each of the key locations: acquiring a whole body image of a user through the camera, and determining the volume of the user based on the whole body image of the user; and the global image of each key part is acquired through the camera, and the volume of each key part is obtained based on the global image of each key part. The electronic device acquires the whole body image of the user through the camera, so that the contour features of the user can be obtained, and the volume of the user can be calculated according to the contour features.
In one possible example, the processor 140 is further configured to, after recommending the food based on the loss amount of the trace element in the body: acquiring the weight of food to be eaten through the camera, wherein the recommended food comprises the food to be eaten; and a substance component obtaining unit for obtaining the substance component of the food to be eaten by the substance detection sensor; and determining energy of the food to be consumed based on the weight of the food to be consumed and the material composition; and for obtaining energy that has been ingested prior to eating the food to be eaten; and means for obtaining an allowable intake energy set in a preset diet plan, determining a remaining ingestible energy based on the allowable intake energy and the ingested energy, and determining an edible amount of the food to be eaten based on the remaining ingestible energy and the energy of the food to be eaten; and recommending the edible amount of the food to be eaten to a user.
In one possible example, the processor 140 is specifically configured to, when acquiring the energy that has been ingested prior to eating the food to be eaten: acquiring the total amount of each eaten food before eating the food to be eaten through the camera; and for obtaining, by the camera, a remaining amount after eating the each of the eaten foods; and determining an eating amount of each of the eaten foods based on the total amount and the remaining amount; and obtaining a substance component of each of the eaten foods by the substance sensor, determining the ingested energy of each of the eaten foods based on the substance component and the eating amount of each of the eaten foods, and obtaining the ingested energy before eating the foods to be eaten.
Referring to fig. 2A, fig. 2A is a schematic flow chart of a food recommendation method provided in an embodiment of the present application, which is applied to an electronic device shown in fig. 1A-1C, wherein the electronic device includes a substance detection sensor and a camera, and the substance detection sensor is disposed close to the camera, and the food recommendation method includes:
step 201: the electronic device obtains the first content of trace elements in the moving precursor through the substance detection sensor.
The electronic device may be provided with an application program of a fitness guidance type, an interface diagram of the application program of the fitness guidance type is shown in fig. 2B, a user may start a scanning function by clicking a scanning icon or a scanning function key in the application program, that is, a substance detection sensor in the electronic device is started to scan a user body, so as to obtain a set of data of multiple substances at a scanning position.
The scanning position may be any part of the user's body, or may be a key part corresponding to the current exercise type, and the key part corresponding to the exercise type may be one part, or may be a plurality of parts, for example, the key part corresponding to the abdomen rolling exercise is set as the abdomen, and the key part corresponding to the running is set as the leg, the arm and the waist.
The specific implementation process of scanning the body of the user through the substance detection sensor and acquiring a set of data of a plurality of substances at the scanning position may include the process shown in fig. 2C-2D, firstly, as shown in fig. 2C, scanning the body of the user through the substance detection sensor, emitting infrared light to irradiate the scanning position, collecting reflected infrared light, then drawing an infrared spectrogram shown in fig. 2D according to the infrared light reflected by the substance acquired by the substance detection sensor, and finally, analyzing a set of data at the scanning position according to the infrared spectrogram.
The specific implementation manner of analyzing a group of data of the scanning position according to the infrared spectrogram can be as follows: as shown in fig. 2D, A, B, C respectively represent infrared spectrum absorption curves obtained when the electronic device scans different body parts, for example, a is an infrared spectrum absorption curve obtained by scanning the abdomen of the user, B is an infrared spectrum absorption curve obtained by scanning the legs of the user, C is an infrared spectrum absorption curve obtained by scanning the arms of the user, wherein the substance detection sensor integrates N different channels between 750nm and 1100nm in wavelength, emits near infrared light of different wavelengths in each channel, then, the infrared spectrum as shown in fig. 2D can be drawn according to the reflected infrared light collected by each channel, then, the band in which the absorption peak appears is determined, the absorption peak appears in different bands represents different substances, a first set of mapping relations between the types of substances and the bands, such as the absorption peak of the a curve, the B curve, the C curve appear in a first band and a second band, determining that the absorption peak of the first wave band shows that the abdomen, the leg and the arm all contain the first substance by inquiring the first mapping relation set in the database, determining that the absorption peak of the second wave band shows that the abdomen, the leg and the arm all contain the second substance, determining that the contents of the first substance in the abdomen, the leg and the arm are different if the peak values of the absorption peak of the first substance in the first wave band and the absorption peak of the second wave band are different, storing the second mapping relation set of the peak values of the absorption peak of the different substances and the contents of the substances in the database, inquiring a plurality of mapping relations corresponding to the first substance in the second mapping relation set according to the peak values of the absorption peak of the first substance in the A curve, the B curve and the C curve, and determining the contents of the first substance in the A curve, the B curve and the C curve respectively, and similarly, inquiring a plurality of mapping relations corresponding to the second substance in the second mapping relation set according to the peak values of the absorption peaks of the second substance in the A curve, the B curve and the C curve, and respectively determining the content of the second substance in the A curve, the B curve and the C curve, namely determining a group of data of the scanning position.
In one possible example, when scanning any part of the body of the user through the substance sensor, the specific implementation process of obtaining the first content of the trace elements in the movement precursor may be: scanning any part of the body of a user through the substance sensor to obtain a first group of data corresponding to the part; determining a moisture content of the site based on the first set of data; and determining the moisture content in the user body based on the corresponding relation between the moisture content of the part and the moisture content in the body and the moisture content of the part.
In the foregoing possible examples, the first set of data includes a substance component of the location and a content of each substance component, and the process of obtaining the moisture content of the location may be: acquiring an infrared spectrogram corresponding to the part through a substance sensor, inquiring a wave band of water in the infrared spectrogram in a first mapping relation set, acquiring an absorption peak value corresponding to the wave band, and inquiring a substance content corresponding to the absorption peak value in a second mapping relation set, wherein the substance content is the moisture content.
Further, after the moisture content of the part is obtained, the moisture content in the user is obtained based on a preset proportionality coefficient of the moisture content of the part and the moisture content in the body, and then the content of the trace elements in the body of the user is obtained based on the corresponding relation between the moisture content in the body and the content of the trace elements in the body.
For example, if the part is an arm, and the preset ratio of the moisture content of the arm to the moisture content in the body is detected to be 1.2, the moisture content in the body is 67.2%, for example, when the moisture content in the body is 60% -70%, the corresponding content of the trace elements in the body is 0.01%, and the first content of the trace elements in the body is determined to be 0.01%.
In one possible example, when the substance sensor scans a critical portion corresponding to the movement type, the process of obtaining the first content of the trace element in the movement precursor may be: acquiring a motion type and determining at least one key part corresponding to the motion type; scanning at least one key part of the body of the user through the substance sensor, and acquiring a second group of data corresponding to each key part; determining a moisture content of the each key location based on the second set of data; determining the content of trace elements of each key part based on the moisture content of each key part, and determining the first content of trace elements in the exercise precursor based on the content of trace elements of each key part.
The process of determining the moisture content of each key portion based on the second set of data is the same as the process of determining the moisture content of any portion, and will not be described.
Optionally, in the above possible examples, the determining the content of the trace element in each key location based on the correspondence between the preset moisture content of each key location and the content of the trace element and the moisture content of each key location may be implemented as follows: acquiring the volume of a user and the volume of each key part; determining the ratio of the volume of each key part to the volume of the user; and obtaining the content of the trace elements in the at least one exercise precursor based on the duty ratio of each key part and the content of the trace elements in each key part, and taking the average content of the trace elements in the at least one exercise precursor as the first content of the trace elements in the exercise precursor.
Wherein, the content of trace elements in each key part is determined based on the correspondence relationship between the moisture content of part of key parts and the content of trace elements in the body shown in the following table 1.
TABLE 1
The specific implementation process for obtaining the volume of the user may be: the whole body image of the user is acquired by the camera, the weight (mass) of the user is determined based on the whole body image of the user, and the density of the human body is set to be 1kg/m because the density of the human body is approximate to the density of water 3 The volume of the user is obtained by dividing the mass by the density, wherein, based onThe implementation process of determining the weight of the user by the whole body image of the user can be as follows: gray processing is carried out on the whole body image to obtain a pixel value of each pixel point in the whole body image, whether each pixel point belongs to a human body pixel point is judged based on the pixel value, if so, all human body pixel points are obtained after preservation for standby, all human body pixel points are traversed, and the highest human body pixel point, the lowest human body pixel point, the leftmost human body pixel point and the rightmost human body pixel point in the whole body image are obtained; taking the difference value between the highest pixel point of the human body and the lowest pixel point of the human body as the human body pixel height, and taking the difference value between the leftmost pixel point and the rightmost pixel point of the human body as the human body pixel width; identifying bone points in the whole-body image based on the pixel values, and taking the distance between the bone points farthest from the whole-body image as a human body depth value; acquiring the pixel width of the cross section of the effective visual angle field of the human body in the whole-body image, wherein the determining process is consistent with the obtained human body pixel width, and the actual height of the human body is obtained based on the depth value, the human body pixel width, the pixel width of the cross section and the human body pixel height; and obtaining the weight of the user based on the actual height of the human body and preset parameters.
According to the depth value, the human body pixel width, the pixel width of the cross section and the human body pixel height, the obtained actual height of the human body can be obtained by the following calculation formula:
H＝2d×tan(28)×w 1 /(w 2 2 ×h)
wherein d is the depth value, w 1 For the human body pixel width, w 2 The pixel width of the cross section is H, the pixel height of the human body is H, and the actual height of the human body is H;
based on the actual height of the human body and preset parameters, the weight of the user can be obtained through the following calculation formula:
W＝a×H b ×(2d×tan(28)×w 1 /w 2 ) c
wherein W is the weight of the user, a, b and c are preset parameters obtained through training a plurality of human body samples in advance, and the values of the parameters are 27, 2 and 0.6 respectively.
Alternatively, the volume of each key site may be acquired by reference to the process of acquiring the volume of the user, which will not be described in detail herein.
Further, based on the volume of each key part and the volume of the user, the ratio of the volume of each key part to the volume of the user is obtained, based on the ratio and the content of trace elements of each key part, the content of trace elements in the body corresponding to the key part is obtained, the content of trace elements in the body corresponding to each key part is averaged, the average content of trace elements in the body corresponding to at least one key part is obtained, the average content is used as the first content of trace elements in the movement precursor, and the obtained first content of trace elements in the movement precursor is higher in accuracy and errors are reduced in a mode of averaging the content of trace elements in the body corresponding to a plurality of key parts.
Step 202: the electronic device obtains the second content of trace elements in the body after movement through the substance detection sensor.
Optionally, the process of obtaining the second content of trace elements in the body after exercise is identical to the process of obtaining the first content of trace elements in the body before exercise in step 201, which will not be described here.
Step 203: the electronic device determines the loss amount of the trace elements in the body based on the first content and the second content.
Optionally, based on the first content and the second content, obtaining the variation of the content of the microelements in the body before and after exercise, and multiplying the obtained weight of the user by the variation to obtain the loss of the microelements in the body.
Step 204: the electronic device recommends food based on the loss amount of the in-vivo microelements.
Optionally, the recommending food by the electronic device based on the loss amount of the trace elements in the body specifically includes: the electronic device obtains target trace elements corresponding to a movement type and a loss ratio list of each target trace element, wherein trace elements which are lost in a body of a user of the target trace elements in the movement type are obtained, the loss amount of each target trace element is obtained based on the loss ratio and the loss amount of trace elements in the body, at least one target food is screened out from a pre-stored food library, each target food at least comprises one of the lost trace elements, the at least one target food is combined to obtain a plurality of combination results, the sum of the content of each lost trace element in each combination is calculated, a combination mode that the sum of the content of each lost trace element is greater than or equal to the loss amount of trace elements in the body is taken as a target combination, the food collocation mode in the target combination is pushed, and the daily recommended area shown in fig. 2B shows the food collocation mode in each target combination.
For example, if the target trace elements corresponding to the long-distance running motion are calcium, iron, and zinc, and the loss ratios are 50%, 30%, and 20%, respectively, if the loss of trace elements in the body is m, it is determined that the loss of calcium, iron, and zinc is 0.5m, 0.3m, and 0.2m, respectively, and if there are N target foods containing at least one trace element of calcium, iron, and zinc, the N target foods are combined, and the obtained combination result is thatThe method comprises the steps of respectively calculating the content of calcium, iron and zinc in each combination result, taking the combination result with the content of calcium, iron and zinc being larger than the loss amount (namely 0.5m, 0.3m and 0.2 m) of the calcium, iron and zinc as a target combination, and pushing the food collocation mode in each target combination to a user as a collocation scheme, so that the user can select the collocation scheme according to the requirement, and the lost microelements are supplemented.
It can be seen that in the embodiment of the application, the loss amount of the microelements in the body before and after the exercise of the user is obtained, and the corresponding food is matched for the user according to the loss amount of the microelements in the body, so that the lost microelements are supplemented, the damage to the physical health of the user due to the loss of the microelements is avoided, the exercise effect is improved, the blind diet of the user is avoided, the diet behavior of the user after the exercise is standardized, the diet matching scheme after the exercise can be obtained without the guidance of professional staff, and the user experience is improved.
In a possible example, the specific implementation process of determining the ratio of the volume of each key location to the volume of the user may further be: the feature map of each key part is obtained through a camera, feature analysis is carried out on the feature map of each key part to determine the body part, for example, if the feature map comprises navel, abdomen is recognized, or the circumference of each key part is obtained according to the feature map, the body part corresponding to each key part is determined according to the circumference, for example, arms are used when the circumference is 15-25cm, thighs are used when the circumference is 35-50cm, and the like, and the method is not limited herein; after determining the body part corresponding to each key part, according to the pre-stored ratio of the volume of the body part to the volume of the body, the ratio of the volume of each key part to the volume of the user is obtained, for example, the ratio of each limb part to the volume of the body is obtained based on medical big data analysis specifically as follows: the ratio of the abdomen is 12%, the ratio of the arms is 10%, the ratio of the legs is 30%, the ratio of the chest is 35%, the ratio of the head is 8%, and the ratio of the neck is 5%, so that the limb parts corresponding to each key part are identified, and the ratio of the volume of each key part to the volume of the user is obtained.
It can be seen that, in this example, the ratio of the critical part to the body can be obtained quickly according to the preset ratio of the volume of the body part to the body volume, and the content of trace elements in the body and the loss amount can be obtained quickly based on the ratio, so that the speed of recommending food is improved, and the user experience is improved.
In one possible example, when the user performs the diet plan, the method further comprises: acquiring the weight of food to be eaten through the camera, wherein the recommended food comprises the food to be eaten; acquiring the substance components of the food to be eaten through the substance detection sensor; determining energy of the food to be consumed based on the weight of the food to be consumed and the material composition; acquiring energy which has been ingested prior to eating the food to be eaten; acquiring allowable energy set in a preset diet plan, determining remaining ingestible energy based on the allowable energy and the ingested energy, and determining the edible amount of the food to be eaten based on the remaining ingestible energy and the energy of the food to be eaten; recommending the edible amount of the food to be eaten to a user.
And acquiring a first ratio of the residual ingestible energy relative to the energy of the food to be eaten, and pushing the edible amount of the food to be eaten to a user based on taking the first ratio as the ratio of the edible amount of the food to be eaten relative to the weight of the food to be eaten, thereby obtaining the edible amount of the food to be eaten.
The allowable energy set in the preset diet plan comprises energy which is suitable for the user to ingest once, such as allowable energy A before exercise, allowable energy B after exercise and the like. The ingested energy includes the ingested energy within a period corresponding to the current allowable energy ingestion, such as within half an hour or 15 minutes after exercise, etc.
In the above possible examples, the implementation of the obtaining of the energy that has been ingested before eating the food to be eaten may be: acquiring the total amount of each eaten food before eating the food to be eaten through the camera; acquiring the residual quantity after eating each eaten food through the camera; determining a serving size of each of the consumed foods based on the total amount and the remaining amount; and acquiring the substance component of each eaten food through the substance sensor, determining the ingested energy of each eaten food based on the substance component and the eating amount of each eaten food, and obtaining the ingested energy before eating the food to be eaten.
After determining the ingested energy of each edible food, the ingested energy is stored into an application as shown in fig. 2B, and when each edible food is eaten, a relevant button of the application is clicked, and the total amount ingested before the edible food is eaten is inquired, so that the edible amount of the edible food is controlled.
It can be seen that in this example, the energy of the food consumed each time and the energy already ingested can be recorded by the camera and the substance sensor when the diet plan is executed, the diet is reasonably controlled according to the energy already ingested and the energy allowed to be ingested, the rationality of diet management is improved, and blind diet or blind diet is avoided when the diet plan is executed.
Referring to fig. 3, fig. 3 is a schematic flow chart of a food recommendation method according to an embodiment of the present application, which is consistent with the embodiment shown in fig. 2A, and is applied to the electronic device shown in fig. 1A-1C, where the electronic device includes a substance detection sensor and a camera, and the substance detection sensor is disposed close to the camera, and the food recommendation method includes:
step 301: the electronic device acquires a motion type and determines at least one key part corresponding to the motion type.
Step 302: the electronic device scans the at least one key part of the body of the user through the substance sensor to obtain a group of data corresponding to each key part.
Step 303: the electronic device determines the moisture content of each key location based on the set of data.
Step 304: the electronic device determines the content of the trace elements in each key part based on the corresponding relation between the preset moisture content of each key part and the content of the trace elements and the moisture content of each key part.
Step 305: the electronic device acquires a whole body image of the user through the camera, and determines the volume of the user based on the whole body image of the user.
Step 306: the electronic device obtains the global image of each key part through the camera, and obtains the volume of each key part based on the global image of each key part.
Step 307: the electronics determine a ratio of the volume of each of the keypoints relative to the volume of the user based on the volume of the user and the volume of each of the keypoints.
Step 308: the electronic device obtains the content of the trace elements in at least one movement precursor based on the ratio of each key part and the content of the trace elements in each key part, and takes the average content of the trace elements in the at least one movement precursor as the first content of the trace elements in the movement precursor.
Step 309: the electronic device obtains the second content of trace elements in the body after movement through the substance detection sensor.
Step 310: the electronic device determines the loss amount of the trace elements in the body based on the first content and the second content.
Step 311: the electronic device recommends food based on the loss amount of the in-vivo microelements.
It should be noted that, the specific implementation of each step of the method shown in fig. 3 may refer to the specific implementation of the foregoing method, which is not described herein.
The foregoing embodiments mainly describe the solutions of the embodiments of the present application from the point of view of the method-side execution procedure. It will be appreciated that the electronic device, in order to achieve the above-described functions, comprises corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
According to the embodiment of the application, the electronic device may be divided into the functional modules according to the method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment of the present application, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.
Referring to fig. 4, fig. 4 is a functional block diagram of a food recommendation device provided in an embodiment of the present application, where the food recommendation device 400 is applied to an electronic device, the electronic device includes a substance detection sensor and a camera, the substance detection sensor is disposed close to the camera, and the food recommendation device 400 includes an acquisition module 401, a determination module 402, and a recommendation module 403, where:
an acquisition module 401 for acquiring a first content of trace elements in the exercise precursor;
the obtaining module 401 is further configured to obtain a second content of trace elements in the body after exercise;
a determining module 402 for determining an amount of trace elements lost in the body based on the first content and the second content;
A recommending module 403, configured to recommend food based on the loss amount of the trace elements in the body.
In one possible example, in acquiring the first content of trace elements in the exercise precursor, the acquisition module 401 is specifically configured to: scanning any part of the body of a user through the substance sensor to obtain a first group of data corresponding to the part; and determining a moisture content of the site based on the first set of data; and determining the moisture content in the user's body based on the correspondence of the moisture content of the site to the moisture content in the body and the moisture content of the site; and determining a first content of trace elements in the exercise precursor based on the correspondence between the moisture content in the user's body and the content of trace elements and the moisture content in the user's body.
In one possible example, when obtaining the first content of trace elements in the exercise precursor, the obtaining module 401 is specifically configured to: acquiring a motion type and determining at least one key part corresponding to the motion type; and scanning the at least one key part of the body of the user through the substance sensor to obtain a second set of data corresponding to each key part; and determining a moisture content for each of the key locations based on the second set of data; and determining the content of trace elements in each key part based on the moisture content of each key part, and determining the first content of trace elements in the exercise precursor based on the content of trace elements in each key part.
In one possible example, when determining the content of the trace elements of each key site based on the moisture content of each key site, the obtaining module 401 is specifically configured to: determining the content of the trace elements of each key part based on the corresponding relation between the preset moisture content of each key part and the content of the trace elements and the moisture content of each key part; and the volume of the user and the volume of each key part are acquired; and determining a ratio of the volume of each key location to the volume of the user; and the method is used for obtaining the content of the trace elements in at least one sport precursor based on the ratio of each key part and the content of the trace elements in each key part, and taking the average content of the trace elements in the at least one sport precursor as the first content of the trace elements in the sport precursor.
In one possible example, when acquiring the volume of the user and the volume of each key location, the acquiring module 401 is specifically configured to: acquiring a whole body image of a user, and determining the volume of the user based on the whole body image of the user; and acquiring a global image of each key part, and obtaining the volume of each key part based on the global image of each key part.
In one possible example, when the user performs a diet plan, the acquisition module 401 is further to: acquiring the weight of food to be eaten; the substance component for obtaining the food to be eaten; and determining energy of the food to be consumed based on the weight of the food to be consumed and the material composition; and for obtaining energy that has been ingested prior to eating the food to be eaten; and means for obtaining an allowable intake energy set in a preset diet plan, determining a remaining ingestible energy based on the allowable intake energy and the ingested energy, and determining an edible amount of the food to be eaten based on the remaining ingestible energy and the energy of the food to be eaten; an edible amount for recommending the food to be eaten to a user
In one possible example, the obtaining module 401, when obtaining the energy that has been ingested before eating the food to be eaten, is specifically configured to: obtaining a total amount of each of the consumed foods before eating the food to be eaten; and for obtaining a residual amount after eating said each of the consumed foods; and determining an eating amount of each of the eaten foods based on the total amount and the remaining amount; and means for obtaining a material composition of each of the consumed foods, determining an ingested energy of each of the consumed foods based on the material composition and the consumption of each of the consumed foods, resulting in an ingested energy prior to eating the food to be consumed.
Referring to fig. 5, in accordance with the embodiment shown in fig. 2A and 3, fig. 5 is a schematic structural diagram of an electronic device 500 according to an embodiment of the present application, where the electronic device 500 includes a substance detection sensor and a camera, and the substance detection sensor is disposed near the camera, and the electronic device 500 further includes a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the following steps:
acquiring the first content of trace elements in the moving precursor through the substance detection sensor;
acquiring the second content of trace elements in the body after movement through the substance detection sensor;
determining the amount of trace element loss in the body based on the first content and the second content;
food is recommended based on the amount of trace elements lost in the body.
In one possible example, the above-mentioned program comprises instructions, in particular for performing the following steps, when the first content of trace elements in the movement precursor is obtained by means of the substance detection sensor:
scanning any part of the body of a user through the substance sensor to obtain a first group of data corresponding to the part; determining a moisture content of the site based on the first set of data; determining the moisture content in the user body based on the corresponding relation between the moisture content of the part and the moisture content in the body and the moisture content of the part; the first content of trace elements in the precursor of the movement is determined based on the correspondence of the moisture content in the user's body to the content of trace elements and the moisture content in the user's body.
In one possible example, the above-mentioned program comprises instructions, in particular for performing the following steps, when the first content of trace elements in the movement precursor is obtained by means of the substance detection sensor: acquiring a motion type and determining at least one key part corresponding to the motion type; scanning the at least one key part of the body of the user through the substance sensor to obtain a second group of data corresponding to each key part; determining a moisture content of the each key location based on the second set of data; determining the content of trace elements of each key part based on the moisture content of each key part, and determining the first content of trace elements in the exercise precursor based on the content of trace elements of each key part.
In one possible example, when determining the content of trace elements of each of the key sites based on the moisture content of each of the key sites, determining the first content of trace elements in the exercise precursor based on the content of trace elements of each of the key sites, the program comprises instructions specifically for performing the steps of: determining the content of the trace elements of each key part based on the corresponding relation between the preset moisture content of each key part and the content of the trace elements and the moisture content of each key part; acquiring the volume of a user and the volume of each key part; determining the ratio of the volume of each key part to the volume of the user; and obtaining the content of the trace elements in the at least one exercise precursor based on the duty ratio of each key part and the content of the trace elements in each key part, and taking the average content of the trace elements in the at least one exercise precursor as the first content of the trace elements in the exercise precursor.
In one possible example, the electronic device further includes a camera, and the program includes instructions for performing the following steps when acquiring the volume of the user and the volume of each key location: acquiring a whole body image of a user through the camera, and determining the volume of the user based on the whole body image of the user; and acquiring global images of each key part through the camera, and obtaining the volume of each key part based on the global images of each key part.
In one possible example, when the user performs a diet plan, the program further comprises instructions for performing the steps of: acquiring the weight of food to be eaten through the camera, wherein the recommended food comprises the food to be eaten; acquiring the substance components of the food to be eaten through the substance detection sensor; determining energy of the food to be consumed based on the weight of the food to be consumed and the material composition; acquiring energy which has been ingested prior to eating the food to be eaten; acquiring allowable energy set in a preset diet plan, determining remaining ingestible energy based on the allowable energy and the ingested energy, and determining the edible amount of the food to be eaten based on the remaining ingestible energy and the energy of the food to be eaten; recommending the edible amount of the food to be eaten to a user.
In one possible example, the program comprises instructions for, when acquiring energy that has been ingested before eating the food to be eaten, performing the steps of: acquiring the total amount of each eaten food before eating the food to be eaten through the camera; acquiring the residual quantity after eating each eaten food through the camera; determining a serving size of each of the consumed foods based on the total amount and the remaining amount; and acquiring the substance component of each eaten food through the substance sensor, determining the ingested energy of each eaten food based on the substance component and the eating amount of each eaten food, and obtaining the ingested energy before eating the food to be eaten.
The embodiment of the present application further provides a computer storage medium, where the computer storage medium is configured to store a computer program, where the computer program is executed by a processor to implement part or all of the steps of any one of the methods described in the embodiments of the method, where the computer includes an electronic device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any one of the methods described in the method embodiments above. The computer program product may be a software installation package, said computer comprising electronic means.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as the division of the modules described above, are merely a logical function division, and may be implemented in other manners, such as multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical or other forms.
The modules described above as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in software functional modules.
The integrated modules described above, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the above-mentioned method of the various embodiments of the present application. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be implemented by a program that instructs associated hardware, and the program may be stored in a computer readable memory, which may include: flash disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.
The foregoing has outlined rather broadly the more detailed description of embodiments of the present application, wherein specific examples are provided herein to illustrate the principles and embodiments of the present application, the above examples being provided solely to assist in the understanding of the methods of the present application and the core ideas thereof; meanwhile, as those skilled in the art will have varying points in specific implementation and application scope in light of the ideas of the present application, the above description should not be construed as limiting the present application.
Claims (9)
1. A food recommendation method, applied to an electronic device including a substance detection sensor, comprising:
acquiring a motion type of a user, and determining at least one key part corresponding to the motion type;
Scanning at least one key part of the body of the user through the substance detection sensor to obtain data corresponding to each key part, and determining the moisture content of each key part based on the data;
determining the content of trace elements of each key part based on the moisture content of each key part, and determining the first content of trace elements in the exercise precursor based on the content of trace elements of each key part; acquiring the second content of trace elements in the body after movement through the substance detection sensor;
determining the amount of trace element loss in the body based on the first content and the second content;
acquiring at least one target trace element corresponding to the exercise type and the loss proportion of each target trace element, wherein the at least one target trace element is a trace element which is lost in the body of a user in the process of executing the exercise type;
determining the loss amount of each target trace element according to the loss proportion of each target trace element and the loss amount of the trace element in the body;
screening at least one target food from a preset food warehouse, wherein each target food at least comprises one of the target microelements;
Combining the at least one target food to obtain a plurality of combinations;
calculating the sum of the contents of each target trace element contained in target foods in each combination, and taking a combination mode that the sum of the contents of each target trace element is larger than or equal to the sum of the loss amounts of the target trace elements as a target combination;
pushing the food collocation mode in the target combination.
2. The method of claim 1, wherein determining the trace element content of each key site based on the moisture content of each key site, determining the first trace element content in the exercise precursor based on the trace element content of each key site, comprises:
determining the content of the trace elements of each key part based on the corresponding relation between the preset moisture content of each key part and the content of the trace elements and the moisture content of each key part;
acquiring the volume of a user and the volume of each key part;
determining the ratio of the volume of each key part to the volume of the user;
and obtaining the content of the trace elements in the at least one exercise precursor based on the duty ratio of each key part and the content of the trace elements in each key part, and taking the average content of the trace elements in the at least one exercise precursor as the first content of the trace elements in the exercise precursor.
3. The method of claim 2, wherein the electronic device further comprises a camera, the substance detection sensor is disposed proximate to the camera, the acquiring the volume of the user and the volume of each critical location comprises:
acquiring a whole body image of a user through the camera, and determining the volume of the user based on the whole body image of the user;
and acquiring global images of each key part through the camera, and obtaining the volume of each key part based on the global images of each key part.
4. The method of claim 3, wherein after pushing the food collocation in the target combination, the method further comprises:
acquiring the weight of food to be eaten through the camera, wherein the recommended food comprises the food to be eaten;
acquiring the substance components of the food to be eaten through the substance detection sensor;
determining energy of the food to be consumed based on the weight of the food to be consumed and the material composition;
acquiring energy which has been ingested prior to eating the food to be eaten;
acquiring allowable energy set in a preset diet plan, determining remaining ingestible energy based on the allowable energy and the ingested energy, and determining the edible amount of the food to be eaten based on the remaining ingestible energy and the energy of the food to be eaten;
Recommending the edible amount of the food to be eaten to a user.
5. The method of claim 4, wherein the capturing of energy that has been ingested prior to eating the food to be consumed comprises:
acquiring the total amount of each eaten food before eating the food to be eaten through the camera;
acquiring the residual quantity after eating each eaten food through the camera;
determining a serving size of each of the consumed foods based on the total amount and the remaining amount;
and acquiring the substance component of each eaten food through the substance sensor, determining the ingested energy of each eaten food based on the substance component and the eating amount of each eaten food, and obtaining the ingested energy before eating the food to be eaten.
6. The utility model provides an electronic device, its characterized in that includes treater, material detection sensor and camera, material detection sensor with the camera is connected respectively the treater, wherein:
the processor is used for acquiring the motion type of the user and determining at least one key part corresponding to the motion type; scanning at least one key part of the body of the user through the substance detection sensor to obtain data corresponding to each key part, and determining the moisture content of each key part based on the data; determining the content of trace elements of each key part based on the moisture content of each key part, and determining the first content of trace elements in the exercise precursor based on the content of trace elements of each key part; and the substance detection sensor is used for acquiring the second content of trace elements in the body after movement; and determining an amount of trace elements lost in the body based on the first and second levels; the method comprises the steps of obtaining at least one target trace element corresponding to the exercise type and loss proportion of each target trace element, wherein the at least one target trace element is a trace element which is lost in a user in the process of executing the exercise type; determining the loss amount of each target trace element according to the loss proportion of each target trace element and the loss amount of the trace element in the body; screening at least one target food from a preset food warehouse, wherein each target food at least comprises one of the target microelements; combining the at least one target food to obtain a plurality of combinations; calculating the sum of the contents of each target trace element contained in target foods in each combination, and taking a combination mode that the sum of the contents of each target trace element is larger than or equal to the sum of the loss amounts of the target trace elements as a target combination; pushing the food collocation mode in the target combination.
7. The utility model provides a food recommendation device, its characterized in that is applied to electron device, electron device includes material detection sensor and camera, material detection sensor is close to the camera sets up, food recommendation includes acquisition module, determination module and recommendation module, wherein:
the acquisition module is used for acquiring the motion type of a user and determining at least one key part corresponding to the motion type; scanning at least one key part of the body of the user through the substance detection sensor to obtain data corresponding to each key part, and determining the moisture content of each key part based on the data; determining the content of trace elements of each key part based on the moisture content of each key part, and determining the first content of trace elements in the exercise precursor based on the content of trace elements of each key part;
the acquisition module is also used for acquiring the second content of trace elements in the body after the exercise;
the determining module is used for determining the loss amount of the trace elements in the body based on the first content and the second content;
the recommendation module is used for acquiring at least one target trace element corresponding to the exercise type and the loss proportion of each target trace element, wherein the at least one target trace element is a trace element which is lost in the body of a user in the process of executing the exercise type; determining the loss amount of each target trace element according to the loss proportion of each target trace element and the loss amount of the trace element in the body; screening at least one target food from a preset food warehouse, wherein each target food at least comprises one of the target microelements; combining the at least one target food to obtain a plurality of combinations; calculating the sum of the contents of each target trace element contained in target foods in each combination, and taking a combination mode that the sum of the contents of each target trace element is larger than or equal to the sum of the loss amounts of the target trace elements as a target combination; pushing the food collocation mode in the target combination.
8. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-5.
9. A computer readable storage medium for storing a computer program for execution by a processor to implement the method of any one of claims 1-5.
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