CN115153230A - Intelligent health seat and sitting posture identification method thereof - Google Patents

Abstract

The invention relates to the technical field of seats, in particular to an intelligent health seat and a sitting posture identification method thereof. The chair comprises a chair back, a chair seat, armrests arranged on two sides of the chair seat and a chassis arranged below the chair seat, wherein a pressure sensor is paved in the chair seat, and a plurality of pressure sensing points are distributed on the pressure sensor in an array manner; the lower extreme of seat support is connected and is equipped with the mainboard and the pressure sensor electricity is connected, and the mainboard acquires the pressure data on a plurality of pressure sensing point and compares with the pressure data under the accurate position of sitting state of predetermineeing, judges whether the user is in the incorrect position of sitting state. Among the above-mentioned technical scheme, when the user used this intelligent healthy seat, the physical data that the human body exerted on each sensing point under the position of sitting state at that time can accurately be gathered to a plurality of pressure sensing points of array distribution, and the mainboard receives these data and carries out corresponding one-to-one with the data on each pressure point under the correct position of sitting state to judge whether the user is in the improper position of sitting state.

Description

A kind of intelligent healthy seat and its sitting posture recognition method

technical field

The invention relates to the technical field of seats, in particular to an intelligent healthy seat and a method for recognizing its sitting posture.

Background technique

Office chairs are chairs that are convenient for work in daily work and social activities. According to ergonomic requirements, the existing office chair provides a corresponding support design for the user to maintain the correct sitting posture more easily. Despite this, there are still a considerable number of users who have little awareness of maintaining the correct sitting posture, and often work in the wrong sitting posture, such as hunchbacks and crossed legs. In addition, with the increase of office hours, the muscles of the waist and neck of the human body are prone to static fatigue. In the state of muscle fatigue, it is more difficult for users to maintain a correct sitting posture, and unconsciously, a loose and crooked sitting posture will appear, which is extremely detrimental to physical health in the long run. Therefore, there are two major pain points in chair design: 1. How to accurately identify the user's bad sitting posture and remind the user; 2. How to remind the user to exercise properly or give the muscles corresponding operations to relieve fatigue after a long sitting time.

There are many sitting posture recognition devices designed for teenagers on the market today. Most of them use infrared cameras to collect pictures of the upper torso posture of the human body, perform image analysis, and combine ultrasonic distance measurement to determine sitting posture. Such devices not only occupy desktop space, but also cannot guarantee the effect of sitting posture recognition, and are easily disturbed by environmental and human factors. For example, a Chinese patent document with publication number CN109117705B relates to a system and method for identifying sitting posture through a desk lamp, including a remote control terminal and several desk lamps, the remote control terminal simultaneously controls several desk lamps to work; each desk lamp corresponds to a unique remote control terminal identification sign; the table lamp is provided with: an infrared detection device for judging whether someone enters or leaves the monitoring range; an image acquisition device for acquiring a sitting image; a reminder device for issuing a reminder signal; and the remote control terminal A communication unit for communication connection; and an information input unit for acquiring external input information; the image acquisition device, the reminder device, and the information input unit are all connected to the communication unit; the infrared detection device is connected to the reminder device, and the information is input The unit is connected to the image acquisition device.

A Chinese patent document with publication number CN213097065U discloses a health seat. The seat cushion is provided with densely clothed pressure sensors, the upper part of the seat cushion and the inner side of the seatback are provided with densely clothed sheet vibration modules, and the inner surface of the seatback is provided with distance measurement. A sensor, a motor for adjusting the angle of the seat back is arranged at the connection between the seat seat and the seat back, and a controller is arranged on the lower side of the seat seat. By setting the pressure sensor and the distance measuring sensor on the seat, the present invention can match the detected pressure distribution data, the distance data between the user's back and the chair back, and combine with the human body sitting posture model established by the server to judge the sitting posture of the user and determine the sitting posture of the user in poor sitting posture. Timely reminders to adjust, realize automatic warning and improvement of sitting posture, and effectively avoid the harm of bad sitting posture to the body. At the same time, it can play a physical therapy role on the body through vibration massage and automatic adjustment of the angle of the backrest, which helps to reduce the adverse effects of prolonged sitting. In the above solution, there is no function of judging whether the user's sitting posture is correct, nor can it effectively remind the bad sitting posture.

SUMMARY OF THE INVENTION

In order to solve the above problems, the purpose of the present invention is to provide an intelligent healthy seat and a method for recognizing its sitting posture.

In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: comprising a chair back, a chair seat, armrests arranged on both sides of the chair seat, and a chassis arranged under the chair seat, characterized in that: A pressure sensor is laid, and a plurality of pressure sensing points are arranged in an array on the pressure sensor; the lower end of the seat is connected with a main board that is electrically connected to the pressure sensor, and the main board obtains the pressure on the plurality of pressure sensing points The data is compared with the preset pressure data in the correct sitting posture to determine whether the user is in an incorrect sitting posture.

In the above technical solution, when the user uses the smart health seat, the multiple pressure sensing points distributed in the array can accurately collect the physical data that the human body exerts on each sensing point in the current sitting posture state, and the main board receives the data and communicates with it. The data on each pressure point in the correct sitting posture is compared one by one, so as to determine whether the user is in an incorrect sitting posture. Specifically, the motherboard is loaded with a deep learning algorithm, which can effectively identify bad sitting posture, and the identification method is more reliable. , can more effectively correct the sitting posture. After identifying a bad sitting posture, the seat can vibrate or sound to remind the user, so that it can consciously correct the sitting posture, which has better intelligence and the function of maintaining human health.

Preferably, the plurality of pressure sensing points include a plurality of strong correlation points and a plurality of weak correlation points, wherein the strong correlation points can directly sense pressure and transmit the pressure data to the main board, and the weak correlation points assist in identifying users of different body types . In this technical solution, the array points are divided into strong correlation points and weak correlation points in the neural network training, and the strong correlation points have higher weights in the neural network training, so that the sitting posture classification model generated by the training has better generalization ability. Usability, can adapt to most users, while reducing program redundancy. Weak association points are also weighted to make the model adapt to special cases such as users who are too large.

Preferably, the plurality of pressure sensing points are evenly distributed in a rectangular array, and the weakly associated points are distributed on the sides of the rectangular array. In this technical solution, the rectangular array of multiple pressure sensing points can more directly and effectively fit the pressure range of the buttocks and upper thighs pressing on the seat cushion. Among them, the strong association points can directly reflect the user's sitting state, and the weak association points are distributed on the sides to assist in reflecting the user's body shape.

Preferably, the seat includes a seat plate and a seat cushion covering the outside of the seat plate, the pressure sensor is laid flat on the upper end surface of the seat plate, two sides of the pressure sensor are connected with cables, and the row The wire is plugged into the motherboard. In this technical solution, the pressure sensor is directly laid on the seat plate instead of in the seat cushion, which can facilitate installation and subsequent maintenance, and can preserve the integrity of the seat cushion and ensure comfort. The pressure sensor is connected to the motherboard through a cable, which has better stability.

Preferably, the pressure sensor is a thin film pressure sensor, and is a PET silver paste or carbon paste circuit diaphragm. In this technical solution, the thickness of the thin-film pressure sensor is as low as hundreds of nanometers to tens of micrometers, and it has the properties of high precision, good creep, and strong anti-interference ability. The environment is simple to manufacture, which is conducive to the realization of structure/perception integrated manufacturing.

Preferably, the main board is a PCB board and is installed in a box body; the outer side of the box body is provided with a button electrically connected to the PCB board, which is suitable for opening or closing the PCB board, and setting the massage time and mode. In this technical solution, the box body can protect the PCB board from external interference, and the buttons are convenient to control the intelligent operation of the seat, which is extremely convenient.

Preferably, the chair back includes a backboard and a back pad covering the backboard. The backboard is provided with a neck massager on the upper part of the backboard and a waist massager on the lower part of the backboard. The neck massager and the waist massager are electrically connected to the PCB board, and the buttons can control the opening and closing of the neck massager and the waist massager. In this technical solution, the arrangement of the neck massager and the waist massager can facilitate physical therapy for the user, especially after the user sits for a long time and the muscles are in a fatigued state, the massager can relieve fatigue and achieve the purpose of considering the user's health.

Preferably, a vibration motor and a buzzer are integrated on the PCB board, and are arranged in the box, suitable for starting to remind the user when the user is in an incorrect sitting posture or starting and reminding the user to get up after the user has been sitting for a long time. In this technical solution, specifically, the PCB board has a sedentary reminder and recognition function. After the user has been seated for 1 hour, the sedentary reminder function will be turned on, and the PCB board will send commands to the vibration motor, and the seat will vibrate rhythmically to remind the user to leave. seat and perform appropriate activities. If the user does not leave after the sedentary reminder function is turned on for 5 minutes, the buzzer will sound "Di, Di, Di, Di, Di" 5 times as a reminder. If the user still does not get up, the PCB board will send instructions to the massager, and the seat will activate the massage function for 10 minutes of massage, which can fully relax the user's waist and neck muscles. Then enter the next cycle.

Preferably, a Bluetooth module is also integrated on the PCB board, which is suitable for users to control the opening and closing of the neck massager and the waist massager through a mobile phone, and to set the massage time and massage mode. In this technical solution, the Bluetooth module on the PCB board can be wirelessly connected with the mobile phone APP, so that the user can more conveniently control the massage function of the seat through the mobile phone.

A method for recognizing sitting posture, using the above-mentioned intelligent healthy seat, is characterized in that: the method comprises the following steps:

Step S1: when the user is in a sitting position, use the embedded pressure sensor to obtain the pressure data applied by the user's buttocks and legs on the seat surface;

Step S2: Determine the pressure distribution area features of different postures of the user from the pressure data;

Step S3: Match the determined feature with a preset sitting posture discrimination strategy to obtain the sitting posture category of the user.

In the above technical solution, the intelligent healthy seat uses a thin film pressure sensor combined with an artificial intelligence algorithm to recognize the sitting posture, does not occupy the desktop space, and has a high recognition accuracy.

Specifically, in step S1, the membrane pressure sensor includes at least 8 pressure sensing points, and the level signal of each pressure sensing point constitutes pressure distribution array point data. In step S2, FIG. 5 is an image obtained by overlapping the force data images of all sitting postures, which can reflect the areas where the seat surface is subjected to more force under various sitting postures. Among them, the letter represents the horizontal position of the array point, the number represents the vertical position of the array point, the A1, B1, C1, D1, B2, C2, B3, C3 array points are strong correlation points, A2, D2, A3, D3 are weak correlation points point. In step S3, a sitting posture classification model based on machine learning is trained by inputting large-scale training samples, and the relevant data rules of each sitting posture category in the trained sitting posture classification model constitute the above sitting posture discrimination strategy; the determined pressure distribution area features are input The pre-trained sitting posture classification model based on machine learning is used to obtain the sitting posture category of the user.

The bad sitting postures that can be identified by the deep learning algorithm in the above are the oblique sitting posture, the forward sitting posture, the Erlang-legged sitting posture, the backward sitting posture, the side sitting forward leaning posture, the side sitting backward sitting posture and the cross-legged sitting posture. Most of the backward sitting postures are relatively loose. Most users with such bad sitting postures prefer to lean forward with their shoulders, hold their chests, and lean on the back of a chair or sofa. Such a sitting posture can easily cause the pelvis to tilt backwards, which in turn leads to lumbar disc herniation. , cervical discomfort, shortness of breath and other problems. Sitting with the head tilted forward is very common and is characterized by a hunched back with the head extended forward. Due to the large curve of the upper back, the pressure on the neck will be high. When office workers go to work, most of them will maintain this sitting position, and the center of the pelvis will move forward, which can easily cause headaches and cervical spine problems. Erlang’s leg sitting posture is also very common. When the Erlang’s legs are lifted, the force on the left and right sides of the buttocks is uneven, one side of the ischium is high and the other side is low, and the angles of the lumbar spine and spine have changed, which can easily lead to the dislocation of the pelvis, lumbar spine and spine, causing scoliosis. , Lumbar disc herniation, etc. Doing this for a long time will lead to high and low shoulders when walking. Sitting obliquely can lead to one high and one low sitting bone height, unbalanced pelvic center of gravity and other problems, which in turn can lead to scoliosis and even walking high and low.

The algorithm does not need to input the user's body index data (such as weight, height, gender, etc.) in advance to identify the user's sitting posture.

Description of drawings

FIG. 1 is a schematic diagram of an exploded structure of an intelligent healthy seat.

FIG. 2 is a schematic diagram of the installation of the neck massager and the waist massager.

FIG. 3 is a schematic plan view of a pressure sensor.

FIG. 4 is a schematic diagram of the distribution of strong correlation points on the pressure sensor.

Figure 5 is an image obtained by overlapping the force data images of all sitting postures.

Figure 6 is a force data image of a sitting posture.

Fig. 7 is the force data image of the oblique sitting posture.

Figure 8 is a force data image of a forward leaning sitting posture.

FIG. 9 is a force data image of a backward leaning sitting posture.

Fig. 10 is the force data image of the drooping legs in Erlang's leg sitting posture.

Figure 11 is a force data image of one leg resting on the other leg in Erlang's leg sitting posture.

Fig. 12 is a force data image of a sitting posture of sitting sideways and leaning forward.

Fig. 13 is an image of force data of a sitting posture of sitting sideways and reclining.

Figure 14 is an image of force data in a cross-legged sitting posture.

Detailed ways

The following describes in detail the embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary, and are intended to explain the present invention and should not be construed as limiting the present invention.

In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", " The orientation or positional relationship indicated by "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "clockwise", "counterclockwise", etc. The orientation or positional relationship shown in the figures is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a reference to the present invention. Invention limitations.

In addition, the terms "first" and "second" are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, a feature defined as "first", "second" may expressly or implicitly include one or more of that feature. In the description of the present invention, unless otherwise specified, "plurality" means two or more, unless otherwise expressly defined.

In the present invention, unless otherwise expressly specified and limited, the terms "installed", "connected", "connected", "fixed" and other terms should be understood in a broad sense, for example, it may be a fixed connection or a detachable connection , or integrally connected; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or the internal communication between the two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

In the present invention, unless otherwise expressly specified and limited, a first feature "on" or "under" a second feature may include the first and second features in direct contact, or may include the first and second features Not directly but through additional features between them. Also, the first feature being "above", "over" and "above" the second feature includes the first feature being directly above and obliquely above the second feature, or simply means that the first feature is level higher than the second feature. The first feature is "below", "below" and "below" the second feature includes the first feature being directly below and diagonally below the second feature, or simply means that the first feature has a lower level than the second feature.

Example 1:

As shown in Figures 1 to 3, an intelligent health seat includes a seat back 1, a seat, armrests 2 arranged on both sides of the seat, and a chassis 3 arranged under the seat. The seat is laid in the seat. There is a pressure sensor 4, and a plurality of pressure sensing points 5 are arranged in an array on the pressure sensor 4; the lower end of the seat is connected with a main board that is electrically connected to the pressure sensor 4, and the main board obtains a plurality of pressure sensing points The pressure data on 5 is compared with the pressure data in the preset correct sitting posture to determine whether the user is in an incorrect sitting posture.

In the above technical solution, when the user uses the smart health seat, the multiple pressure sensing points distributed in the array can accurately collect the physical data that the human body exerts on each sensing point in the current sitting posture state, and the main board receives the data and communicates with it. The data on each pressure point in the correct sitting posture is compared one by one, so as to determine whether the user is in an incorrect sitting posture. Specifically, the motherboard is loaded with a deep learning algorithm, which can effectively identify bad sitting posture, and the identification method is more reliable. , can more effectively correct the sitting posture. After identifying a bad sitting posture, the seat can vibrate or sound to remind the user, so that it can consciously correct the sitting posture, which has better intelligence and the function of maintaining human health.

Further, the plurality of pressure sensing points 5 include a plurality of strong correlation points and a plurality of weak correlation points, wherein the strong correlation points can directly sense pressure and transmit pressure data to the main board, and the weak correlation points help identify users of different body types. In this technical solution, the array points are divided into strong correlation points and weak correlation points in the neural network training, and the strong correlation points have higher weights in the neural network training, so that the sitting posture classification model generated by the training has better generalization ability. Usability, can adapt to most users, while reducing program redundancy. Weak association points are also weighted to make the model adaptable to special cases such as users who are too large.

Further, the plurality of pressure sensing points 5 are evenly distributed in a rectangular array, and the weakly associated points are distributed on the sides of the rectangular array. In this technical solution, the plurality of pressure sensing points 5 in a rectangular array can more directly and effectively fit the pressure range of the buttocks and upper thighs pressing on the seat cushion. Among them, the strong association points can directly reflect the user's sitting state, and the weak association points are distributed on the sides to assist in reflecting the user's body shape.

Further, the seat includes a seat plate 6 and a cushion 7 covering the outside of the seat plate 6. The pressure sensor 4 is laid flat on the upper end surface of the seat plate 6, and two sides of the pressure sensor 4 are connected with cables. 8. The cable 8 is plugged into the main board. In this technical solution, the pressure sensor 4 is directly laid on the seat plate 6 instead of in the seat cushion 7 , which can facilitate installation and subsequent maintenance, and can preserve the integrity of the seat cushion and ensure comfort. The pressure sensor 4 is connected to the main board through the cable 8, and the stability is better.

Further, the pressure sensor 4 is a thin film pressure sensor, and is a PET silver paste or carbon paste circuit diaphragm. In this technical solution, the thickness of the thin-film pressure sensor is as low as hundreds of nanometers to tens of micrometers, and it has the properties of high precision, good creep, and strong anti-interference ability. The environment is simple to manufacture, which is conducive to the realization of structure/perception integrated manufacturing.

Further, the main board is a PCB board 100, and is installed in a box body 9; the outer side of the box body 9 is provided with a button 10 electrically connected to the PCB board 100, which is suitable for opening or closing the PCB board 100, and setting the massage time and mode. . In this technical solution, the box body 9 can protect the PCB board 100 from external interference, and the buttons are convenient to control the intelligent operation of the seat, which is extremely convenient.

Further, the seat back 1 includes a backboard 11 and a back pad covering the backboard 11 . The backboard 11 is provided with a neck massager 400 on the upper part of the backboard 11 , and a neck massager 400 on the lower part of the backboard 11 . The waist massager 500, the neck massager 400 and the waist massager 500 are electrically connected to the PCB board 100, and the buttons 10 can control the opening and closing of the neck massager 400 and the waist massager 500. In this technical solution, the arrangement of the neck massager 400 and the waist massager 500 can facilitate the physical therapy of the user, especially after the user has been sitting for a long time and the muscles are in a fatigued state, the massager can relieve the fatigue and achieve the purpose of considering the user's health. . It should be noted here that the massage heads of the two massagers have a hot compress function.

Further, a vibration motor and a buzzer are integrated on the PCB board 100, and are arranged in the box body 9, suitable for starting and reminding the user when the user is in an incorrect sitting posture or starting and reminding the user to get up after the user has been sitting for a long time. In this technical solution, specifically, the PCB board 100 has a sedentary reminder and recognition function. After the user sits for 1 hour, the sedentary reminder function will be turned on. The PCB board 100 sends a command to the vibration motor, and the seat will vibrate rhythmically to remind the user. The user leaves the seat and performs the appropriate activity. If the user does not leave after the sedentary reminder function is turned on for 5 minutes, the buzzer will sound "beep, beep, beep, beep, beep" 5 times as a reminder. If the user still does not get up, the PCB board 100 will send an instruction to the massager, and the seat will activate the massage function to perform a 10-minute massage, which can fully relax the user's waist and neck muscles. Then enter the next cycle.

Further, the PCB board 100 is also integrated with a Bluetooth module, which is suitable for users to control the opening and closing of the neck massager 400 and the waist massager 500 through a mobile phone, and to set the massage time and massage mode. In this technical solution, the Bluetooth module on the PCB board can be wirelessly connected with the mobile phone APP, so that the user can more conveniently control the massage function of the seat through the mobile phone.

Embodiment 2:

As shown in Figures 4-14, a sitting posture recognition method adopts the intelligent healthy seat in the first embodiment, and the method includes the following steps:

Step S1: when the user is in a sitting position, use the embedded pressure sensor 4 to obtain the pressure data applied by the user's buttocks and legs on the seat surface;

Step S2: Determine the pressure distribution area features of different postures of the user from the pressure data;

Step S3: Match the determined feature with a preset sitting posture discrimination strategy to obtain the sitting posture category of the user.

In the above technical solution, the intelligent healthy seat uses a thin film pressure sensor combined with an artificial intelligence algorithm to recognize the sitting posture, does not occupy the desktop space, and has a high recognition accuracy.

Specifically, in step S1, the membrane pressure sensor includes at least 8 pressure sensing points, and the level signal of each pressure sensing point constitutes pressure distribution array point data. In step S2, FIG. 5 is an image obtained by overlapping the force data images of all sitting postures, which can reflect the areas where the seat surface is subjected to more force under various sitting postures. Among them, the letter represents the horizontal position of the array point, the number represents the vertical position of the array point, the A1, B1, C1, D1, B2, C2, B3, C3 array points are strong correlation points, A2, D2, A3, D3 are weak correlation points point. In step S3, a sitting posture classification model based on machine learning is trained by inputting large-scale training samples, and the relevant data rules of each sitting posture category in the trained sitting posture classification model constitute the above sitting posture discrimination strategy; the determined pressure distribution area features are input The pre-trained sitting posture classification model based on machine learning is used to obtain the sitting posture category of the user.

The bad sitting postures that can be identified by the deep learning algorithm in the above are the oblique sitting posture, the forward sitting posture, the Erlang-legged sitting posture, the backward sitting posture, the side sitting forward leaning posture, the side sitting backward sitting posture and the cross-legged sitting posture. Most of the backward sitting postures are relatively loose. Most users with such bad sitting postures prefer to lean forward with their shoulders, hold their chests, and lean on the back of a chair or sofa. Such a sitting posture can easily cause the pelvis to tilt backwards, which in turn leads to lumbar disc herniation. , cervical discomfort, shortness of breath and other problems. Sitting with the head tilted forward is very common and is characterized by a hunched back with the head extended forward. Due to the large curve of the upper back, the pressure on the neck will be high. When office workers go to work, most of them will maintain this sitting position, and the center of the pelvis will move forward, which can easily cause headaches and cervical spine problems. Erlang’s leg sitting posture is also very common. When the Erlang’s legs are lifted, the force on the left and right sides of the buttocks is uneven, the ischium is high on one side and the other is low, and the angles of the lumbar spine and spine have changed, which can easily lead to the dislocation of the pelvis, lumbar spine and spine, causing scoliosis. , Lumbar disc herniation, etc. Doing this for a long time will lead to high and low shoulders when walking. Sitting obliquely can lead to problems such as one high and one low sitting bone height, unbalanced pelvic center of gravity, etc., which in turn leads to scoliosis and even walking with high and low feet.

The algorithm does not need to input the user's body index data (such as weight, height, gender, etc.) in advance to identify the user's sitting posture.

The specific application of the above recognition method is to take the seated posture recognition of Erlang's leg of the right foot as an example, as shown in Figure 11, where C1 and D1 are strongly associated points, and the coordinates of these two points or one of them is identified as empty as the main condition. , the weak association point D2 is an auxiliary identification, which can be D1, D2 empty to meet the identification conditions, or C1, D2 empty or C1, D1, D2 empty to judge the sitting posture, each of which is an equal condition.

In this specific embodiment, an intelligent healthy seat uses a thin-film pressure sensor combined with a deep learning algorithm to recognize the sitting posture, and prompts the user to correct it through feedback such as vibration and beep, which does not occupy the desktop space, and the recognition method is more reliable and can be more efficient. Correct sitting posture effectively. In addition, for the problem of long-term sitting fatigue, this seat has the functions of massage, hot compress and APP + button control, which can relieve long-term sitting fatigue, more intelligent and have better comfort.

In the description of this specification, description with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples", etc., mean specific features described in connection with the embodiment or example , structure, material or feature is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Although the embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and those of ordinary skill in the art will not depart from the principles and spirit of the present invention Variations, modifications, substitutions, and alterations to the above-described embodiments are possible within the scope of the present invention without departing from the scope of the present invention.

Claims (10)

1. The utility model provides a healthy seat of intelligence, includes back of the chair (1), seat support, and sets up in handrail (2) of seat support both sides, and sets up in chassis (3) of seat support below, its characterized in that: a pressure sensor (4) is laid in the chair seat, and a plurality of pressure sensing points (5) are distributed on the pressure sensor (4) in an array manner; the lower extreme of seat support is connected and is equipped with the mainboard with pressure sensor (4) electricity is connected, and the mainboard acquires the pressure data on a plurality of pressure sensing point (5) and compares with the pressure data under the accurate position of sitting state of predetermineeing, judges whether the user is in the improper position of sitting state.

2. The intelligent health seat of claim 1, wherein: the pressure sensing points (5) comprise a plurality of strong association points and a plurality of weak association points, wherein the strong association points can directly sense pressure and transmit pressure data to the mainboard, and the weak association points assist in identifying users with different body types.

3. The intelligent health seat of claim 2, wherein: the pressure sensing points (5) are uniformly distributed in a rectangular array, and the weak association points are distributed on the side edge of the rectangular array.

4. The intelligent health seat of claim 1, wherein: the seat support comprises a seat plate (6) and a cushion (7) covering the outer side of the seat plate (6), the pressure sensor (4) is paved on the upper end face of the seat plate (6), flat cables (8) are connected and arranged on two sides of the pressure sensor (4), and the flat cables (8) are inserted into the main board.

5. The intelligent health seat of claim 4, wherein: the pressure sensor (4) is a film pressure sensor and is a PET silver paste or carbon paste line diaphragm.

6. The intelligent health seat of claim 4, wherein: the main board is a PCB (100) and is arranged in a box body (9); the outer side of the box body (9) is provided with a key (10) which is electrically connected with the PCB (100) and is suitable for opening or closing the PCB (100) and setting massage time and modes.

7. The intelligent health seat of claim 6, wherein: back of the chair (1) is including backplate (11), and covers the back of the body pad outside backplate (11), the installation is equipped with neck massager (400) that are in backplate (11) upper portion on backplate (11), and waist massager (500) that are in backplate (11) lower part, neck massager (400) are connected with PCB board (100) electricity with waist massager (500), button (10) can control opening and close of neck massager (400) and waist massager (500).

8. The intelligent health seat of claim 7, wherein: the PCB (100) is integrated with a vibration motor and a buzzer, is arranged in the box body (9), and is suitable for being started to remind a user when the user is in an incorrect sitting posture or being started and reminding the user to get up after the user sits for a long time.

9. The intelligent health seat of claim 8, wherein: the PCB (100) is further integrated with a Bluetooth module, and the Bluetooth module is suitable for a user to control the opening and closing of the neck massager (400) and the waist massager (500) through a mobile phone and set massage time and a massage mode.

10. A sitting posture identifying method using the intelligent health seat as claimed in claims 1 to 5, characterized in that: the method comprises the following steps:

step S1: when a user is in a sitting posture state, pressure data applied to the surface of the seat by the buttocks and the legs of the user are acquired by using the embedded pressure sensor (4);

step S2: determining pressure distribution area characteristics of different gestures of the user from the pressure data;

and step S3: and matching the determined characteristics with a preset sitting posture judgment strategy to obtain the sitting posture category of the user.

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