Automatic seat support member adjustment method and system based on human body sitting state

Abstract

An automatic seat support member adjustment method and system based on a human body seating state. The method comprises: in response to the activation of a support automatic adjustment mode, receiving vital sign data of a human body, and determining a pressure threshold on the basis of the vital sign data; driving a support member to move back and forth until the support member fits against the human body and a fitting pressure value between the support member and the human body satisfies the pressure threshold; and receiving the fitting pressure value in real time, and on the basis of the comparison between the fitting pressure value and the pressure threshold, driving the support member to move in real time. A pressure threshold that meets a user requirement is determined by collecting the vital sign information, and on the basis of the comparison between the fitting pressure value collected by a pressure sensor on the support member and the pressure threshold, the support strength of the support member is automatically adjusted, rapid adaptation to a posture change of a user can be achieved, the fit between the support member and a corresponding part of the human body is maintained, and the comfort of the user is improved.

Description

Automatic adjustment method and system of seat support based on human seating state TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of seats, in particular to an automatic adjustment method and system of seat support based on human seating state. BACKGROUND

[0002] When using a seat for a long time, especially an office chair or a vehicle seat, the adaptability of human support is crucial to the comfort and health of the user. TECHNICAL PROBLEM

[0003] Taking a lumbar support as an example, there are mainly two ways for the lumbar support adjustment of the existing seat to adapt to the human body. One is to use a mechanical spring to follow the waist, which relies on a spring and a knob puller to manually adjust the lumbar support forward and backward. It lacks intelligent adjustment capability and cannot automatically adjust the strength and position of the waist support according to the user's body shape and sitting posture, resulting in discomfort when using the seat for a long time. The second way is to use an air bag to automatically adjust the lumbar support, but it still has some defects, such as relatively large noise generated during inflation and deflation, which affects the user experience. In addition, the inflation and deflation speed of the air bag is slow, which cannot respond to the user's requirement for adjusting the waist support in time. TECHNICAL SOLUTION

[0004] In order to overcome the shortcomings of the prior art, the purpose of the embodiments of the present application is to provide an automatic adjustment method and system of seat support based on human seating state, which can automatically adjust the seat support according to the user's vital sign information.

[0005] To solve the above problems, the first aspect of the embodiments of the present application discloses an automatic adjustment method of seat support based on human seating state, which comprises the following steps:

[0006] In response to the start of the support automatic adjustment mode, receiving the vital sign data of the human body, and determining the pressure threshold value according to the vital sign data;

[0007] Driving the front and back movement of the support, until the support fits the human body and the fitting pressure value between the support and the human body meets the pressure threshold value;

[0008] Real-time receiving the fitting pressure value, and driving the movement of the support according to the size of the fitting pressure value and the pressure threshold value in real time.

[0009] As a preferred embodiment, in the first aspect of the embodiments of the present application, receiving the vital sign data of the human body and determining the pressure threshold value according to the vital sign data comprises:

[0010] Receiving the human body shape data and the sitting posture parameters obtained by the image acquisition device or the millimeter wave radar;

[0011] receiving human weight data acquired by a weighing sensor;

[0012] inputting the vital sign data into a pre-trained neural network model to obtain the pressure threshold;

[0013] alternatively,

[0014] inputting the vital sign data into a pre-fitted linear logistic regression model to obtain the pressure threshold.

[0015] As a preferred embodiment, in the first aspect of the embodiment of the present application, the fitting of the linear logistic regression model comprises:

[0016] creating a linear logistic regression model:

[0017] wherein Y is the predicted value of the linear logistic regression model, X1, X2, X3 and X4 are the actual height data, body width data, sitting posture data and weight data, respectively; are fitting coefficients, respectively;

[0018] obtaining a plurality of sample data, each of which comprises , wherein y i is the pressure threshold corresponding to the i-th sample data, x1 i is the height data corresponding to the i-th sample data, x2 i is the body width data corresponding to the i-th sample data, x3 i is the sitting posture data corresponding to the i-th sample data, and x4 i is the weight data corresponding to the i-th sample data;

[0019] fitting the linear logistic regression model using the sample data by least squares method to obtain the values of each fitting coefficient.

[0020] As a preferred embodiment, in the first aspect of the embodiment of the present application, the sitting posture parameter of the human body is obtained using an image acquisition device or a millimeter wave radar, comprising:

[0021] obtaining the position of the key points of the human body using the image acquisition device or the millimeter wave radar, and determining the sitting posture attribute according to the positional relationship between the key points of the human body;

[0022] determining the sitting posture parameter according to the sitting posture attribute and the attribute correlation table.

[0023] As a preferred embodiment, in the first aspect of the embodiment of the present application, the method further comprises:

[0024] The sitting posture parameter is received at a preset time interval, the pressure threshold is updated when the sitting posture parameter changes, and the movement of the support is driven according to the size of the real-time received fitting pressure value and the updated pressure threshold.

[0025] As a preferred embodiment, in the first aspect of the embodiment of the present application, the real-time receiving of the fitting pressure value comprises:

[0026] The fitting pressure value is obtained by real-time receiving the pressure signal collected by the pressure sensor installed on the support within a preset period and performing integral operation on the pressure signal.

[0027] As a preferred embodiment, in the first aspect of the embodiment of the present application, the real-time driving of the movement of the support according to the size of the fitting pressure value and the pressure threshold comprises:

[0028] According to the size of the fitting pressure value and the pressure threshold, the difference between the two is determined.

[0029] According to the positive and negative of the difference value and the absolute value of the difference value, the running direction and the running speed of the support are determined respectively.

[0030] According to the running speed, the support is driven to move in the running direction.

[0031] As a preferred embodiment, in the first aspect of the embodiment of the present application, when the absolute value of the difference between the fitting pressure value and the pressure threshold is greater than or equal to a preset difference value, the support is driven to move in the running direction at a first speed, and when the absolute value of the difference between the fitting pressure value and the pressure threshold is less than the preset difference value, the support is driven to move in the running direction in a manner of fixed fitting pressure value change rate.

[0032] As a preferred embodiment, in the first aspect of the embodiment of the present application, the real-time driving of the movement of the support according to the size of the fitting pressure value and the pressure threshold comprises:

[0033] According to the size of the fitting pressure value and the pressure threshold, the running direction and the running speed of the support are driven in real time by a PID algorithm.

[0034] As a preferred embodiment, in the first aspect of the embodiment of the present application, the real-time driving of the movement of the support according to the size of the fitting pressure value and the pressure threshold comprises:

[0035] When the support travels to a limit position, the fitting pressure value still does not match the pressure threshold, the support automatic adjustment mode is exited or / and a prompt information is sent.

[0036] The second aspect of the embodiment of the present application discloses a seat support automatic adjustment system based on a human seating state, which comprises:

[0037] A collection unit is configured to collect the physical data of the human body and send the physical data to a controller.

[0038] A support association mechanism comprises a pressure sensor arranged on the support and an electric adjustment mechanism configured to drive the movement of the support frame.

[0039] The controller comprises a controller body and a motor drive chip, wherein the controller body is configured to receive the physical data of the human body, determine a pressure threshold value according to the physical data, and drive the forward and backward movement of the support in response to the start of the support automatic adjustment mode until the support is attached to the human body and the attachment pressure value between the support and the human body meets the pressure threshold value, and the controller body is configured to receive the attachment pressure value in real time and drive the movement of the support according to the size of the attachment pressure value and the pressure threshold value in real time.

[0040] The third aspect of the embodiment of the present application discloses a seat comprising the seat support automatic adjustment system based on the human seating state disclosed in the second aspect of the embodiment of the present application.

[0041] The fourth aspect of the embodiment of the present application discloses an electronic device installed on a seat, comprising a memory storing executable program code, a processor coupled to the memory, and the processor calling the executable program code stored in the memory for executing the seat support automatic adjustment method based on the human seating state disclosed in the first aspect of the embodiment of the present application.

[0042] The fifth aspect of the embodiment of the present application discloses a computer readable storage medium storing a computer program, wherein the computer program causes a computer to execute the seat support automatic adjustment method based on the human seating state disclosed in the first aspect of the embodiment of the present application.

[0043] The sixth aspect of the embodiment of the present application discloses a computer program product, which causes a computer to execute the seat support automatic adjustment method based on the human seating state disclosed in the first aspect of the embodiment of the present application when the computer program product runs on the computer. Advantages

[0044] Compared with the prior art, the embodiment of the present application has the following advantages:

[0045] The embodiment of the present application determines the pressure threshold meeting the user demand by collecting the sign information, and compares the fitting pressure value collected by the pressure sensor on the support with the pressure threshold based on real-time detection, so as to realize the automatic adjustment of the supporting force of the support, quickly adapt to the posture change of the user, keep the support and the corresponding part of the human body fitting, and improve the user comfort. BRIEF DESCRIPTION OF DRAWINGS

[0046] Fig. 1 is a flowchart of the method for automatically adjusting the seat support based on the human seating state according to the embodiment of the present application;

[0047] Fig. 2 is a structural schematic diagram of the intelligent seat according to the embodiment of the present application;

[0048] Fig. 3 is a structural schematic diagram of the electric waist support adjusting mechanism according to the embodiment of the present application;

[0049] Fig. 4 is a sectional view of Fig. 2;

[0050] Fig. 5 is a structural schematic diagram of the device for automatically adjusting the seat support based on the human seating state according to the embodiment of the present application;

[0051] Fig. 6 is a structural schematic diagram of the system for automatically adjusting the seat support based on the human seating state according to the embodiment of the present application;

[0052] Fig. 7 is a structural schematic diagram of the electronic device according to the embodiment of the present application. Embodiment of the present application

[0053] The specific embodiment is only an explanation of the embodiment of the present application, and is not a limitation of the embodiment of the present application. Those skilled in the art can make modifications to the embodiment without creative contribution after reading the present specification, and the modifications are protected by the patent law as long as they are within the scope of the claims of the embodiment of the present application.

[0054] To make the purpose, technical scheme and advantages of the embodiment of the present application more clear, the technical scheme of the embodiment of the present application will be described clearly and completely in combination with the drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, but not all the embodiments. Based on the embodiment in the embodiment of the present application, all the other embodiments obtained by those skilled in the art without creative contribution are within the protection scope of the embodiment of the present application.

[0055] The term "comprising" and its variants, such as "comprise" or "comprises," as used in the specification and claims of this application, are intended to mean including, but not limited to, for example, a process, method, system, product, or apparatus that comprises a list of steps or units without necessarily being limited to the list of steps or units as explicitly set forth.

[0056] In the embodiments of the present application, the word "exemplary" or "for example" is used to mean serving as an example, instance, or illustration. Any implementation or design solution described as "exemplary" or "for example" in the embodiments of the present application is not necessarily to be construed as preferred or advantageous over other implementations or design solutions. In fact, a word or phrase such as "exemplary" or "for example" is used in this specification in the sense of "-serving as an example, instance, or illustration." In the description of the embodiments of the present application, "comprising" means "including, but not limited to," and "comprises" means "includes, but is not limited to."

[0057] The embodiments of the present application determine the pressure threshold meeting the user demand by collecting the sign information, and compare the fitting pressure value collected by the pressure sensor on the support with the pressure threshold based on real-time detection, so as to realize the automatic adjustment of the supporting force of the support, quickly adapt to the posture change of the user, keep the support and the corresponding part of the human body fitting, improve the comfort of the user, which will be described in detail below in combination with the drawings. Embodiments

[0058] Please refer to FIG. 1, which is a flowchart of the method for automatically adjusting the seat support based on the seating state of the human body according to the embodiments of the present application. The execution subject of the embodiments of the present application includes software and hardware structures. The hardware structure mainly includes a controller, which can receive the pressure signal sent by the sensor, control the action of the support automatic adjustment, etc. The software part mainly includes some control logic, such as the determination of the preset pressure threshold, the comparison between the pressure signal and the preset pressure threshold, whether to start the support automatic adjustment mode, whether to control the action of the support automatic adjustment, and the PID algorithm, etc. Please refer to FIG. 1, which can include the following steps:

[0059] S110, in response to the start of the support automatic adjustment mode, receiving the sign data of the human body, and determining the pressure threshold according to the sign data.

[0060] The sign data of the human body in the embodiments of the present application mainly includes the body shape data, the sitting posture parameter, and the weight data. The body shape data includes the height data and the body width data. The weight data refers to the weight data of the human body. The sitting posture parameter is used to represent the sitting posture type of the user on the seat, for example, the sitting posture type can be the upright sitting type, the legs open and knees apart type, the legs folded type, the legs slanted type, the feet crossed type, the feet inward type, the kneeling type, the cross-legged type, etc. A certain value can be given to each sitting posture type, for example, the upright sitting type is set to 5, the feet crossed type is set to 8, etc.

[0061] For the collection of different physical parameters, different sensors can be used, for example, the body size data and the sitting posture parameters of the human body can be acquired by an image acquisition device such as a camera. In this way, the image acquisition device needs to be installed in front of the seat, which loses the universality of the intelligent seat.

[0062] Therefore, in the preferred embodiment of the present application, as shown in FIG. 2, a millimeter wave radar 240 can be installed below the front side of the seat surface of the intelligent seat 200. When the user stands in front of the intelligent seat 200, the millimeter wave radar 240 can be started to collect the body size data of the human body. When the user sits on the intelligent seat 200, the sitting posture parameters can be collected.

[0063] For example, when the user starts the support automatic adjustment mode, the user can be reminded to stand in front of the seat to collect the height data and the width data by voice. After the collection is completed, the user can be reminded to sit on the seat to collect the sitting posture parameters by voice again. At the same time, the weight sensor 230 on the seat surface can collect the weight data of the user.

[0064] The support automatic adjustment mode can be started manually, for example, by a button, a remote controller, etc. Alternatively, the support automatic adjustment mode can be started by default after the seat support automatic adjustment system is powered on.

[0065] When the millimeter wave radar collects the body size data and the sitting posture parameters of the human body, the radar point cloud data of the human body can be acquired first. Then, the human body imaging model can be generated based on the point cloud data. Further, the human body skeletal joint can be obtained through the human body imaging model, so as to determine the height and the width of the human body and the corresponding sitting posture parameters.

[0066] For the sitting posture parameters, part of the human body skeletal joints can be selected as the key points of the human body, for example, the corresponding position relationship of the foot joint, the knee joint, the elbow joint, the shoulder joint, etc. Based on the corresponding attribute association table, the sitting posture parameters of the human body can be basically determined. For example, when the left foot joint or / and the left knee joint is located to the right of the right foot joint or / and the right knee joint, it can be regarded as the cross-legged type.

[0067] Since the physical data of each user is different, the support force (fitting pressure) between the user and the support member is also not necessarily the same. Therefore, in the preferred embodiment of the present application, the pressure threshold value that can meet the needs of most users can be determined according to the physical data of the user. When the fitting pressure value reaches the pressure threshold value, the support member is controlled to stop moving. When the user's posture changes, for example, moves forward or backward relative to the seat surface, the support member is adaptively adjusted to the position where the fitting pressure value between the user and the support member reaches the pressure threshold value.

[0068] There are various ways to determine the pressure threshold, and the pressure threshold can be determined by a neural network model, for example. The neural network model is trained by a plurality of physical sample data of a plurality of people, and the parameters of the neural network model are fitted by using a back propagation algorithm, so as to complete the training of the neural network model. The trained neural network model can be stored in the memory corresponding to the controller. When the physical data of the target user is collected and sent to the controller, the controller calls the trained neural network model and inputs the physical data into the neural network model to obtain the pressure threshold.

[0069] In the embodiments of the present application, the pressure threshold can also be determined by a linear logistic regression model. Specifically, it can include the following steps:

[0070] First, create a linear logistic regression model according to the number of physical data:

[0071] Where Y is the predicted value of the linear logistic regression model, X1, X2, X3, and X4 are the actual height data, body width data, posture data, and weight data, respectively. are the fitting coefficients.

[0072] In some other embodiments, some physical data can also be added or reduced, for example, the body width data can be deleted, or other physical data such as age can be added.

[0073] Secondly, a plurality of sample data are collected to obtain a sample set, each sample data including , wherein y i is the pressure threshold corresponding to the i-th sample data, x1 i is the height data corresponding to the i-th sample data, x2 i is the body width data corresponding to the i-th sample data, x3 i is the posture data corresponding to the i-th sample data, and x4 i is the weight data corresponding to the i-th sample data.

[0074] It should be noted that the sample data covers various actual possible situations as much as possible, especially for the posture, to ensure the universality of the fitted linear logistic regression model. For example, a plurality of intervals can be set based on the height data or the weight data, for example, the height data in the sample set needs to ensure that there is a sample in every 5cm interval between 150cm-190cm, the weight data in the sample set needs to ensure that there is a sample in every 5kg interval between 40kg-100kg, and each posture type has not less than 5 related samples. Since height, body width and weight are numerical values, each posture type can be converted into a numerical value by assignment.

[0075] In addition, a plurality of linear logistic regression models can be fitted according to user preferences. For example, the user preferences can be set as moderate force, relatively large force, and relatively small force, and different linear regression models are fitted for the three different user preference types. In use, the user can select the corresponding preference type according to the user's own needs, and then obtain a satisfactory fitting pressure.

[0076] Of course, only one linear logistic regression model with moderate force can be fitted, and a certain percentage can be appropriately increased or decreased based on the fitting result to obtain a fitting pressure suitable for users with relatively large force or relatively small force.

[0077] Finally, the linear logistic regression model is fitted using sample data to obtain the values of the fitting coefficients. For example, the linear logistic regression model can be fitted by the least squares method to finally obtain the values of the fitting coefficients. .

[0078] When the pressure threshold is a fixed value, especially near the fixed value, the motor driving the support member is prone to repeated action, and even enters a dead loop and cannot find the position corresponding to the fixed value. Therefore, in general, the pressure threshold is set as a range value, so the fixed pressure threshold can be modified as a range value here, for example, a certain preset value is added or / and subtracted based on the pressure threshold to obtain a pressure threshold range, for example, assuming that the pressure threshold P0 is 10000 mN, the rule is P max =P0+1000, P min =P0-1000, then the pressure threshold range corresponding to P0 is [9000, 11000].

[0079] S120, in response to the start of the support automatic adjustment mode, driving the forward and backward movement of the support member until the support member is fitted to the human body and the fitting pressure value between the support member and the human body satisfies the pressure threshold.

[0080] The support member can be a waist support fitted to the waist of the human body, a headrest fitted to the head of the human body, of course, it can also be a backrest fitted to the back of the human body, or a combination of a plurality of these support members, such as a combination of a waist support and a headrest, or a combination of a backrest and a headrest.

[0081] In a preferred embodiment of the present application, the forward and backward movement of the support member is realized by an electric drive, so as to ensure the speed, accuracy and stability of the movement, and at the same time, the noise can be reduced to the maximum. Illustratively, the controller can drive the motor of the electric adjustment assembly through the motor drive chip, so that the motor directly or through a certain transmission assembly drives the movement of the corresponding support member.

[0082] The application takes the driving of the front and rear movement of the lumbar support as an example to explain and illustrate the principle of automatic adjustment of the support, and the automatic adjustment of other supports is similar to it.

[0083] The electric adjustment assembly of the lumbar support is referred to as an electric lumbar support adjustment mechanism. Please refer to FIGS. 2-4. The electric lumbar support adjustment mechanism 220 can include a motor 221 and a transmission assembly 222 (for example, including a worm gear assembly and a lead screw, etc.). The controller sends a driving signal to the motor through a motor driving chip. After the motor receives the driving signal (including the movement direction and the movement speed), it determines whether to rotate forward or backward according to the movement direction and determines the rotation speed according to the running speed, thereby driving the front and rear movement of the lumbar support 210 through the transmission assembly.

[0084] A pressure sensor is installed on the lumbar support to sense the force generated by the contact between the lumbar support and the user's waist, which corresponds to the support force on the user's waist. The support force can be used to further determine whether the sitting posture of the user is comfortable and healthy, etc. The pressure sensor can be a thin film pressure sensor or other types of pressure sensors.

[0085] In order to more accurately obtain the fitting pressure value, in the preferred embodiment of the application, the pressure signals collected by the pressure sensor within a preset period (for example, 1s) can be integrated to obtain the fitting pressure value corresponding to the preset period. In other embodiments, the pressure signal collected by the pressure sensor can be directly read as the fitting pressure value, or multiple pressure sensors can be provided to obtain the average value of the pressure signals collected by these pressure sensors, or the pressure signals of each pressure sensor within a preset period are integrated and then averaged. The integral operation is set in the software in the controller, which can integrate each pressure signal within a preset period to obtain a comprehensive pressure value, which is referred to as the fitting pressure value.

[0086] Before the support automatic adjustment mode is started, the support is located at an initial position, which is set according to the actual situation, for example, the initial position of the lumbar support or the headrest is fitted to the chair back. When the support automatic adjustment mode is turned off, the support is reset and returns to the initial position.

[0087] When the user starts the support automatic adjustment, the controller compares the real-time collected fitting pressure value with the pressure threshold value (or pressure threshold value range). If the collected fitting pressure value is greater than the set pressure threshold value range, the controller controls the motor drive chip to make the motor drive the waist support to move backward, thereby reducing the pressure between the waist support and the human waist. After the waist support moves backward to a certain position, the fitting pressure value is within the set pressure threshold value range. If the fitting pressure value is less than the set pressure threshold value range, the controller controls the motor to drive the waist support to move forward, thereby increasing the pressure between the waist support and the human waist. After the waist support moves forward to a certain position, the fitting pressure value is within the set pressure threshold value range.

[0088] S130, real-time receiving the fitting pressure value, and driving the movement of the support according to the size of the fitting pressure value and the pressure threshold value.

[0089] According to the size of the fitting pressure value and the pressure threshold value, the operation direction and the operation speed of the support can be determined based on the difference value and the absolute value of the difference value.

[0090] Still taking the waist support as an example, according to the size of the fitting pressure value and the pressure threshold value, the difference value is determined. The difference value has positive and negative, and the positive and negative of the difference value is used to determine the running direction of the waist support, and the absolute value of the difference value is used to determine the running speed. If the difference value is positive, it means that the fitting pressure value is greater than the pressure threshold value, and the controller controls the motor drive chip to make the motor drive the waist support to move backward. If the difference value is negative, it means that the fitting pressure value is less than the pressure threshold value, and the controller controls the motor drive chip to make the motor drive the waist support to move forward. The greater the absolute value of the difference value, the farther the waist support needs to move to reach the target support position, so the motor can be controlled to run at a faster speed, and vice versa.

[0091] If the pressure threshold value is a range value, then the difference value and the absolute value of the difference value between the fitting pressure value and the two end points of the pressure threshold value range need to be compared. If the difference value between the fitting pressure value and the two end points of the pressure threshold value range is positive and negative, or one of the difference values is 0, it means that the fitting pressure value is within the pressure threshold value range, and the waist support does not move. If the difference values between the fitting pressure value and the two end points of the pressure threshold value range are both positive (or both negative), the difference value between the fitting pressure value and the pressure threshold value is positive (or negative), corresponding to the running direction of the waist support, and then the smaller one of the absolute values of the two positive or negative values is determined as the running speed.

[0092] For example, assuming the pressure threshold range is 100000 mN (millinewton) - 120000 mN (millinewton), and the fitting pressure value is 140000 mN (millinewton), the difference between the fitting pressure value and the two endpoints of the pressure threshold range is 20000 mN and 40000 mN respectively, both of which are positive values, indicating that the fitting pressure value is greater than the pressure threshold range, and the controller needs to control the motor drive chip to drive the motor to move the waist support backward, and the running speed is determined based on the smaller value between the two (i.e. taking 20000 mN as the absolute value of the difference between the fitting pressure value and the pressure threshold).

[0093] The running speed can be achieved in the form of setting an associated table according to the absolute value of the difference, for example, when the absolute value of the difference is 10000 mN - 20000 mN, the speed of the motor can be controlled at 500 r / s, when the absolute value of the difference is 20000 mN - 30000 mN, the speed of the motor can be controlled at 600 r / s, and so on.

[0094] In a preferred embodiment of the present application, in order to avoid the use of a fixed running speed causing a poor experience for the user, for example, at the beginning, the absolute value of the difference is large, at this time the running speed of the motor is fast, and if the absolute value of the difference becomes small later, the motor is still controlled at this running speed, which will cause discomfort to the human body. In this case, a critical point can be set, for example, a preset difference is set, when the absolute value of the difference between the fitting pressure value and the pressure threshold is greater than or equal to the preset difference, the waist support is driven at a larger speed (denoted as the first speed, which can be determined based on the above-mentioned associated table of the absolute value of the difference and the running speed) to move at a corresponding running direction, and when the absolute value of the difference between the fitting pressure value and the pressure threshold is less than the preset difference, the waist support is driven to move in the running direction according to the change rate of the fitting pressure value, and during the movement of the waist support, the change amount of the fitting pressure value per unit time is ensured to be the same, so as to reduce the discomfort of the human body to the increase or decrease of the pressure.

[0095] In some other embodiments, if the fitting pressure value still does not match the pressure threshold when the waist support reaches the limit position, the automatic adjustment mode of the support is exited or / and a reminder information is sent.

[0096] In some other embodiments, the running direction and running speed of the support can also be precisely controlled by a PID algorithm. Specifically, the fitting pressure value is input into the PID algorithm set in the controller, compared with the pre-stored pressure threshold in the controller, and then the running direction and running speed of the waist support are driven in real time by the PID algorithm.

[0097] In addition, the sitting posture change of the user can be detected in a time manner. When the sitting posture of the user does not change, the current pressure threshold is continuously used for control. If the sitting posture of the user changes, the new sitting posture parameter is combined with other physical data of the user to re-determine the pressure threshold, and the pressure threshold is updated. Then, the position of the support member is controlled according to the comparison between the updated pressure threshold and the real-time acquired fitting pressure value.

[0098] Embodiment two

[0099] Referring to FIG. 5, FIG. 5 is a structural schematic diagram of a seat support member automatic adjustment device based on a human seating state according to an embodiment of the present application. As shown in FIG. 5, the seat support member automatic adjustment device based on the human seating state can include:

[0100] The receiving unit 310 is configured to receive physical data of a human body in response to the start of the support automatic adjustment mode, and determine a pressure threshold according to the physical data;

[0101] The adjustment unit 320 is configured to drive the front and back movement of the support member until the fitting pressure value between the support member and the human body satisfies the pressure threshold.

[0102] The driving unit 330 is configured to receive the fitting pressure value in real time, and drive the movement of the support member according to the size of the fitting pressure value and the pressure threshold in real time.

[0103] Preferably, the receiving unit 310 includes:

[0104] receiving human body size data and sitting posture parameters acquired by the image acquisition device or the millimeter wave radar;

[0105] receiving human body weight data acquired by the weighing sensor;

[0106] inputting the physical data into a pre-trained neural network model to obtain the pressure threshold; or inputting the physical data into a pre-fitted linear logistic regression model to obtain the pressure threshold.

[0107] The fitting of the linear logistic regression model includes:

[0108] creating a linear logistic regression model:

[0109] wherein Y is the predicted value of the linear logistic regression model, X1, X2, X3 and X4 are the actual height data, body width data, sitting posture data and weight data, respectively; are the fitting coefficients, respectively;

[0110] obtaining a plurality of sample data, each sample data including wherein yi is a pressure threshold corresponding to the i-th sample data, x1 i is height data corresponding to the i-th sample data, x2 i is body width data corresponding to the i-th sample data, x3 i is sitting posture data corresponding to the i-th sample data, x4 i is weight data corresponding to the i-th sample data;

[0111] The linear logistic regression model is fitted using the sample data by least squares method to obtain the value of each fitting coefficient.

[0112] Preferably, the image acquisition device or millimeter wave radar is used to obtain the sitting posture parameters of the human body, including:

[0113] The image acquisition device or millimeter wave radar is used to obtain the position of the key points of the human body, and the sitting posture attribute is determined according to the positional relationship between the key points.

[0114] The sitting posture parameters are determined according to the sitting posture attribute and the attribute correlation table.

[0115] Preferably, the time interval can also be preset to receive the sitting posture parameters, and when the sitting posture parameters change, the pressure threshold is updated, and the movement of the support is driven according to the size of the real-time received fitting pressure value and the updated pressure threshold.

[0116] Preferably, the driving unit 330 includes:

[0117] The pressure signal collected by the pressure sensor installed on the support within a preset period is received in real time, and the pressure signal is integrated to obtain the fitting pressure value;

[0118] According to the size of the fitting pressure value and the pressure threshold, the difference between the two is determined;

[0119] According to the positive and negative of the difference and the absolute value of the difference, the running direction and the running speed of the support are determined respectively;

[0120] According to the running speed, the support is driven to move in the running direction.

[0121] Preferably, when the absolute value of the difference between the fitting pressure value and the pressure threshold is greater than or equal to a preset difference, the support is driven to move in the running direction at a first speed, and when the absolute value of the difference between the fitting pressure value and the pressure threshold is less than the preset difference, the support is driven to move in the running direction in a fixed fitting pressure value change rate.

[0122] Of course, the running direction and speed of the support can also be driven in real time by the PID algorithm according to the size of the fitting pressure value and the pressure threshold value.

[0123] Preferably, when the fitting pressure value still does not match the pressure threshold value when the support travels to the limit position, the support automatic adjustment mode is exited or / and a reminder information is sent.

[0124] Embodiment three

[0125] Referring to FIG. 6, FIG. 6 is a structural schematic diagram of a seat support automatic adjustment system based on human seating state according to an embodiment of the present application. As shown in FIG. 6, the seat support automatic adjustment system based on human seating state can include:

[0126] The acquisition unit 410 is configured to acquire the physical data of the human body and send the physical data to the controller. The acquisition unit mainly includes a millimeter wave radar 411 and a weighing sensor 412. The millimeter wave radar 411 can acquire height data, body width data and sitting posture parameters in the physical data, and the weighing sensor 412 can acquire weight signals in the physical data. The millimeter wave radar 411 can communicate with the controller through wired or wireless means, for example, the millimeter wave radar 411 can communicate with the controller wirelessly through a 60GHz wireless transceiver 413. The weighing sensor 412 sends the weight signals to the controller through wired means. The controller obtains the weight data by integrating the weight signals in a preset time period through an integral operation algorithm.

[0127] The support-related mechanism 420 includes a pressure sensor 422 arranged on the support and an electric adjustment mechanism 421 for driving the movement of the support frame.

[0128] The controller can include a controller body 431, a motor drive chip 432 and related software programs installed on the controller body. The software programs can include an integral operation algorithm 4311 and a PID algorithm 4312, etc. On one hand, the controller body receives the physical data sent by the acquisition unit 410 and determines the pressure threshold value according to the physical data. On the other hand, the controller body receives the pressure signals collected by the pressure sensor on the support and calculates the fitting pressure value through the integral operation algorithm. Then, the fitting pressure value and the pressure threshold value are input into the PID algorithm 4312 to obtain the running direction and speed of the support. The controller controls the electric adjustment mechanism 421 to drive the movement of the support through the motor drive chip 432 according to the running direction and speed.

[0129] The embodiment of the present application also provides a seat, which can be an office chair, a car seat or the like, and the seat comprises the seat support automatic adjustment system based on the human seating state and other necessary structures, and the other necessary structures can adopt the existing conventional technology, which will not be described herein.

[0130] In other embodiments, the seat support automatic adjustment method can also be applied to other furniture such as a smart bed or the like.

[0131] Embodiment four

[0132] Referring to FIG. 7, FIG. 7 shows a structural schematic diagram of an electronic device that can be used to implement the embodiment of the present application. As shown in FIG. 7, the electronic device comprises at least one processor 510, and a memory such as a ROM (Read-Only Memory) 520, a RAM (Random Access Memory) 530 or the like in communication connection with the at least one processor 510, wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 510 can execute various appropriate actions and processes according to the computer program stored in the ROM 520 or the computer program loaded from the storage unit 580 to the RAM 530. In the RAM 530, various programs and data required for the operation of the electronic device can also be stored. The processor 510, the ROM 520 and the RAM 530 are connected to each other through a bus 540. An I / O (Input / Output) interface 550 is also connected to the bus 540.

[0133] A plurality of components in the electronic device are connected to the I / O interface 550, including an input unit 560 such as a keyboard, a mouse or the like, an output unit 570 such as various types of displays, speakers or the like, a storage unit 580 such as a magnetic disk, an optical disk or the like, and a communication unit 590 such as a network card, a modem, a wireless communication transceiver or the like. The communication unit 590 allows the electronic device to exchange information / data with other devices through a computer network such as the Internet or / and various telecommunication networks.

[0134] The processor 510 can be various general-purpose or / and special-purpose processing components with processing and computing capabilities. Some examples of the processor 510 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller or the like. The processor 510 executes one or more steps of the seat support automatic adjustment method based on the human seating state described in the above embodiment one.

[0135] In some embodiments, a method for automatic adjustment of a seat support based on a human seating state can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 580. In some embodiments, parts or all of the computer program can be loaded onto or / and installed in an electronic device via, e.g., ROM 520 or / and communication unit 590. When the computer program is loaded into RAM 530 and executed by processor 510, one or more steps of a method for automatic adjustment of a seat support based on a human seating state as described above in Embodiment One can be performed. Alternatively, in other embodiments, processor 510 can be configured to perform a method for automatic adjustment of a seat support based on a human seating state by any other suitable means, e.g., with the aid of firmware.

[0136] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, in integrated circuitry, in field programmable gate arrays (FPGAs), in application specific integrated circuits (ASICs), in application specific standard products (ASSPs), in system on a chip systems (SOCs), in load programmable logic devices (CPLDs), in computer hardware, in firmware, in software, or in combinations thereof. These various embodiments can be implemented in one or more computer programs that are executable on a programmable system including at least one programmable processor that can be special or general purpose, that can receive data and instructions from, and

[0137] Computer programs used to implement embodiments of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed, implements the functions / acts specified in the flowcharts or / and block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as part of a standalone software package, or entirely on a remote machine or server.

[0138] In the context of embodiments of the present application, a computer- readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0139] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0140] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), blockchain network, and the Internet.

[0141] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0142] The above describes in detail the seat support automatic adjustment method and system based on the human seating state disclosed by the present application. The principles and implementation modes of the present application are described by applying specific examples. The above example is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for automatically adjusting a seat support based on a seated state of a human body, the method comprising: determining a seated state of a human body; and adjusting a seat support based on the seated state of the human body. It comprises the following steps: In response to the start of the support automatic adjustment mode, the body sign data of the human body is received, and the pressure threshold value is determined according to the sign data; Drive the front and back movement of the support until the support is fitted to the human body and the fitting pressure value between the support and the human body meets the pressure threshold value; Real-time receive the fitting pressure value, and drive the movement of the support according to the size of the fitting pressure value and the pressure threshold value in real time.

2. The method of claim 1, wherein, Receiving the body sign data of the human body, and determining the pressure threshold value according to the sign data, comprises: Receiving the body shape data and sitting posture parameters of the human body obtained by the image acquisition device or millimeter wave radar; Receiving the weight data of the human body obtained by the weighing sensor; The sign data is input into the pre-trained neural network model to obtain the pressure threshold value; or the sign data is input into the pre-fitted linear logistic regression model to obtain the pressure threshold value.

3. The method of claim 2, wherein the seat support is automatically adjusted based on the body seating state. The fitting of the linear logistic regression model comprises: Create a linear logistic regression model: ； Wherein, Y is the predicted value of linear logistic regression model, X1, X2, X3, X4 are actual height data, body width data, sitting posture data and weight data respectively; Respectively for the fitting coefficient; acquiring a plurality of sample data, each sample data comprising wherein, y i is a pressure threshold value corresponding to the i-th sample data, x1 i is height data corresponding to the i-th sample data, x2 i is body width data corresponding to the i-th sample data, x3 i is sitting posture data corresponding to the i-th sample data, x4 i is weight data corresponding to the i-th sample data; The sample data is used to fit the linear logistic regression model by least square method to obtain the value of each fitting coefficient.

4. The method of claim 2, wherein the seat support is automatically adjusted based on the body seating state. Using the image acquisition device or millimeter wave radar to obtain the sitting posture parameters of the human body, comprising: Using the image acquisition device or millimeter wave radar to obtain the position of the key points of the human body, and determining the sitting posture attribute according to the position relationship between the key points of the human body; Determine the sitting posture parameters according to the sitting posture attribute and the attribute correlation table.

5. The method of claim 2, wherein the seat support is automatically adjusted based on the body seating state. The method further comprises: Receiving the sitting posture parameters at a preset time interval, updating the pressure threshold value when the sitting posture parameters change, and driving the movement of the support according to the size of the real-time received fitting pressure value and the updated pressure threshold value.

6. The method of automatically adjusting a seat support based on a seated state of an occupant according to any one of claims 1-5, wherein, The real-time receiving of the fitting pressure value comprises: Real-time receive the pressure signal collected by the pressure sensor installed on the support in a preset period, and integrate the pressure signal to obtain the fitting pressure value.

7. The method of automatically adjusting a seat support based on a seated state of an occupant according to any one of claims 1-5, wherein, According to the size of the fitting pressure value and the pressure threshold value, real-time drive the movement of the support, comprising: According to the size of the fitting pressure value and the pressure threshold value, determine the difference value of the two; According to the positive and negative of the difference value and the absolute value of the difference value, determine the running direction and running speed of the support respectively; According to the running speed, drive the support to move in the running direction.

8. The method of claim 7, wherein the seat support is automatically adjusted based on the body seating state. When the absolute value of the difference value of the fitting pressure value and the pressure threshold value is greater than or equal to a preset difference value, drive the support to move in the running direction at a first speed; when the absolute value of the difference value of the fitting pressure value and the pressure threshold value is less than the preset difference value, drive the support to move in the running direction in a fixed fitting pressure value change rate.

9. The method of automatically adjusting a seat support based on a seated state of an occupant according to any one of claims 1-5, wherein, According to the size of the fitting pressure value and the pressure threshold value, real-time drive the movement of the support, comprising: According to the size of the fitting pressure value and the pressure threshold value, the running direction and the running speed of the support are driven in real time by PID algorithm.

10. The method of automatically adjusting a seat support based on a seated state of an occupant according to any one of claims 1-5, wherein, According to the size of the fitting pressure value and the pressure threshold value, real-time drive the movement of the support, comprising: When the support member travels to the limit position, and the fitting pressure value still does not match the pressure threshold value, the support automatic adjustment mode is exited or / and a prompt information is sent.

11. A seat support automatic adjustment system based on human seating state, characterized by, It comprises: The acquisition unit is configured to acquire the vital sign data of the human body and send the vital sign data to the controller. The support member associated mechanism comprises a pressure sensor arranged on the support member and an electric adjustment mechanism for driving the support frame to move; The controller comprises a controller body and a motor driving chip, the controller body is configured to receive the vital sign data of the human body, determine the pressure threshold value according to the vital sign data, and drive the front and back movement of the support member in response to the start of the support automatic adjustment mode until the support member fits the human body and the fitting pressure value between the support member and the human body satisfies the pressure threshold value, and real-time receive the fitting pressure value and drive the movement of the support member according to the size of the fitting pressure value and the pressure threshold value.

12. A seat, characterized by It comprises the seat support member automatic adjustment system based on the human body seating state of claim 11.

13. An electronic device mounted on a seat, characterized by comprising: It comprises a memory storing executable program codes, a processor coupled with the memory, and the processor invokes the executable program codes stored in the memory to execute the seat support member automatic adjustment method based on the human body seating state of any one of claims 1-10.

14. A computer-readable storage medium, characterized in that, It stores a computer program, wherein the computer program enables the computer to execute the seat support member automatic adjustment method based on the human body seating state of any one of claims 1-10. 15.

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