CN109191803B

CN109191803B - Sitting posture detection method and system

Info

Publication number: CN109191803B
Application number: CN201810811567.5A
Authority: CN
Inventors: 郭延锐; 杨翔宇; 黄帅; 黄海川; 郭佳
Original assignee: Shenzhen Zhongyun Innovation Technology Co ltd
Current assignee: Hefei Yuji Technology Co.,Ltd.
Priority date: 2018-07-20
Filing date: 2018-07-20
Publication date: 2021-04-23
Anticipated expiration: 2038-07-20
Also published as: CN109191803A

Abstract

The invention relates to a sitting posture detection method and a system, wherein the method comprises the following steps: respectively acquiring at least two groups of measurement data from at least two capacitance sensors positioned at least two different levels through a main control module; judging the contact state of the user according to the at least two groups of measurement data through an analysis module on the main control module; the analysis module analyzes the sitting posture of the user according to the contact state and correspondingly outputs an electric signal for sitting posture reminding when the user is in an undesirable sitting posture after analysis. The invention adopts the capacitance sensor, and can well reduce the condition of detection failure by utilizing the characteristics of the capacitance sensor.

Description

Sitting posture detection method and system

Technical Field

The invention relates to the technical field of detection, in particular to a sitting posture detection method and system.

Background

Poor sitting posture easily causes cervical vertebra and lumbar vertebra diseases or vision deterioration and other problems. Therefore, in order to avoid physical injury of a user due to long-time sitting at a poor sitting posture, a chair capable of sensing the sitting posture adopted by the user and reminding the user of adopting a correct sitting posture is developed.

However, the existing sitting posture detecting device adopts a distance sensor or a pressure sensor based on invisible light, which often easily causes false alarm or misoperation. For example, the user covers the clothes on the distance sensor, resulting in detection that the user is always in a good posture against the backrest, so that the detection fails. For another example, when a user stacks a heavy object, such as a backpack with a book, on the pressure sensor, the detection device using the pressure sensor detects that the user is always in a good posture and is attached to the backrest, so that the detection is disabled. For example, chinese patent publication No. CN106820720A discloses a multi-sensor sitting posture detecting seat and a detecting method thereof, the present invention uses a pressure sensor to collect data to detect and judge whether a person sits down in the current state, if there is a prompt to keep a correct sitting posture, the present related parameters are read in, and system timing is started; the acquired data is sent to a controller for analysis and judgment, and sitting posture non-judgment, multi-action judgment and sedentary judgment are carried out; when the controller judges that the current state is sedentary, improper sitting posture and excessive movement, the vibrator starts to work to send out different warning signals and sends the current state to remote monitoring equipment such as a mobile phone APP of a guardian; the state of the child is timely adjusted through different warning signals, and a guardian can know the current information state of the child through remote equipment.

Disclosure of Invention

Aiming at the defects of the prior art, the invention provides a sitting posture detection method and a sitting posture detection system. Moreover, by analyzing the degree of dispersion of the measurement data, analyzing whether the measurement data is maintained by the user, and properly adjusting the relevant threshold value, the possibility of false alarm is greatly reduced compared with the prior art.

According to a preferred embodiment, a sitting posture detection method comprises: respectively acquiring at least two groups of measurement data from at least two capacitance sensors positioned at least two different levels through a main control module; judging the contact state of the user according to the at least two groups of measurement data through an analysis module on the main control module; the analysis module analyzes the sitting posture of the user according to the contact state and correspondingly outputs an electric signal for sitting posture reminding when the user is in an undesirable sitting posture after analysis.

According to a preferred embodiment, the process of determining the contact state of the user according to the at least two sets of measurement data by the analysis module comprises: the analysis module analyzes the acquired measurement data of each capacitive sensor to determine the distance mode of the corresponding capacitive sensor and judge the contact state according to the distance mode of each capacitive sensor; wherein the distance pattern comprises: a first mode when the measured data is equal to or less than a first judgment threshold, a second mode when the measured data is greater than the first judgment threshold and equal to or less than a second judgment threshold, and a third mode when the measured data is greater than the second judgment threshold; the contact state includes a first state corresponding to a user's sitting posture not being detected, a second state corresponding to a user's sitting posture being poor, and a third state corresponding to a user's sitting posture being good, and the first, second, and third states are determined as follows: when each of the at least two capacitive sensors is in the first mode, judging that the current contact state is the first state; when the number of the capacitive sensors in the third mode in the at least two sensors is smaller than the preset number and at least one capacitive sensor is in the second mode or the third mode, judging that the current contact state is the second state; and when the number of the capacitive sensors in the third mode in the at least two capacitive sensors is greater than or equal to the preset number, judging that the current contact state is the third state.

According to a preferred embodiment, the analysis module continuously collects the measurement data of each capacitive sensor for analysis, and when the dispersion degree of the measurement data of the corresponding capacitive sensor is continuously smaller than the dispersion degree threshold value and exceeds a first preset time, the first and second judgment threshold values of the corresponding capacitive sensor are reset based on the first long-term average value of the measurement data of the corresponding capacitive sensor in a first time period lasting for the first preset time.

According to a preferred embodiment, the analysis module collects measurement data from the respective capacitive sensor with a first sampling frequency for a first time period lasting a first preset time, before resetting the first and second decision thresholds of the respective capacitive sensor based on a long-term average of the measurement data of the respective capacitive sensor for the first time period lasting the first preset time, the analysis module collects measurement data from the respective capacitive sensor for a second preset time period with a second sampling frequency different from the first sampling frequency, in case a ratio of the second long-term average to the first long-term average of the measurement data measured in the second preset time period is within a range of the average ratio threshold and a degree of dispersion of the measurement data measured in the second preset time period is still less than the degree of dispersion threshold, the first and second decision thresholds of the respective capacitive sensor are reset based on a long-term average of the measurement data of the respective capacitive sensor over a first time period lasting a first preset time.

According to a preferred embodiment, the second sampling frequency is higher than the first sampling frequency, and the second preset duration is smaller than the first preset duration.

According to a preferred embodiment, before the main control module correspondingly outputs the electric signal for prompting the sitting posture, the analysis module needs to judge the duration of the second state, and only when the duration of the second state exceeds a third preset duration, the main control module correspondingly outputs the electric signal for prompting the sitting posture.

According to a preferred embodiment, after the duration time of the second state exceeds a third preset time, the analyzing module checks the discrete degree of the corresponding measurement data of the corresponding capacitive sensor to determine the reliability degree of the second state, and when the reliability degree of the second state is greater than or equal to the reliability threshold, the main control module correspondingly outputs an electric signal for sitting posture reminding.

According to a preferred embodiment, the processing of checking, by the analysis module, the degree of dispersion of the corresponding measurement data of the respective capacitive sensor to determine the degree of reliability of the second state comprises: analyzing the first number of the capacitive sensors to be confirmed which are judged to be in the second mode and/or the third mode; finding out a second number of the corresponding capacitive sensors with the discrete degree of the measurement data larger than the discrete degree threshold value from the capacitive sensors to be confirmed; the degree of reliability is determined by the ratio of the second number to the first number.

According to a preferred embodiment, a sitting posture detection system, the system comprises: the main control module and the at least two capacitive sensors, wherein each capacitive sensor of the at least two capacitive sensors is respectively arranged on different horizontal heights of the backrest, the main control module comprises an analysis module,

the system collects at least two groups of measurement data from at least two capacitance sensors at least two different levels through a main control module; the system judges the contact state of the user according to the at least two groups of measurement data through an analysis module on the main control module; the analysis module analyzes the sitting posture of the user according to the contact state and correspondingly outputs an electric signal for prompting the sitting posture when the user is in an undesirable sitting posture after the analysis is carried out.

Drawings

FIG. 1 is a simplified schematic diagram of a preferred embodiment of the system of the present invention;

FIG. 2 is a block diagram of a preferred embodiment of the system of the present invention;

FIG. 3 is a first schematic graph of measurement data versus distance pattern for a capacitive sensor;

FIG. 4 is a second schematic graph of measurement data versus distance pattern for a capacitive sensor; and

fig. 5 is a third schematic diagram of measurement data versus distance pattern for a capacitive sensor.

List of reference numerals

100: the control circuit board 110: analysis module

120: the communication module 200: at least two capacitive sensors

210: first capacitive sensor 220: second capacitive sensor

300: the user mobile terminal 400: cloud server

500: the seat 510: back support

L1: first mark line L2: second marking line

L3: third mark line L4: fourth marking line

Detailed Description

The following detailed description is made with reference to the accompanying drawings.

Example 1

The present embodiment discloses a sitting posture detection method, which may be implemented by the system of the present invention and/or other alternative components. For example, the method of the present invention may be implemented using various components of the system of the present invention.

According to a preferred embodiment, a sitting posture detecting method may include: the main control module 100 collects at least two sets of measurement data from at least two capacitive sensors 200 located at least two different levels, respectively; the analysis module 110 of the main control module 100 determines the contact state of the user according to at least two sets of measurement data; and/or the analysis module 110 analyzes the sitting posture of the user according to the contact state and correspondingly outputs an electric signal for prompting the sitting posture when the user is in the bad sitting posture after the analysis. Referring to fig. 1 and 2, the main control module 100 is connected to at least two capacitive sensors 200. The output electrical signal for the sitting posture reminder may be input to a reminder device, such as at least one of a speaker, a display and a vibrator, for reminding the user to correct the bad sitting posture. When the capacitance sensor detects, even if some interfering substances are separated, the required data change can be collected, for example, the capacitance sensor is covered by clothes, and the user and the capacitance sensor are separated by clothes, although the data have deviation, the data can still be detected. Therefore, by adopting the capacitance sensor, the condition of detection failure can be well reduced by utilizing the characteristics of the capacitance sensor.

According to a preferred embodiment, the process of determining the contact state of the user by the analysis module 110 according to at least two sets of measurement data may include: the analysis module 110 analyzes the collected measurement data of each capacitive sensor to determine a distance pattern of the corresponding capacitive sensor and determine a contact state according to the distance pattern of each capacitive sensor. The distance pattern may include: a first mode when the measured data is equal to or less than a first judgment threshold, a second mode when the measured data is greater than the first judgment threshold and equal to or less than a second judgment threshold, and a third mode when the measured data is greater than the second judgment threshold. The contact state may include a first state, a second state, and a third state. The first state may correspond to a sitting position condition in which the user is not detected. The second state may correspond to a user being in a poor sitting position. The third state may correspond to a user in a good sitting position. The first, second and third states may be determined as follows: when each of the at least two capacitive sensors 200 is in the first mode, it is determined that the current contact state is the first state. And when the number of the capacitive sensors in the third mode in the at least two sensors is smaller than the preset number and at least one capacitive sensor is in the second mode or the third mode, judging that the current contact state is the second state. When the number of the capacitive sensors in the third mode is greater than or equal to the preset number, the current contact state is determined to be the third state.

According to a preferred embodiment, the analysis module 110 may continuously collect the measurement data of each capacitive sensor for analysis, and reset the first and second determination thresholds of the corresponding capacitive sensor based on the first long-term average of the measurement data of the corresponding capacitive sensor in the first time period lasting for the first preset time if the dispersion degree of the measurement data of the corresponding capacitive sensor is continuously less than the dispersion degree threshold for more than the first preset time.

According to a preferred embodiment, the analysis module 110 collects the measurement data from the corresponding capacitive sensor at a first sampling frequency for a first time period lasting a first preset time, the analysis module 110 collects the measurement data from the corresponding capacitive sensor for a second preset time period at a second sampling frequency different from the first sampling frequency before resetting the first and second decision thresholds of the corresponding capacitive sensor based on a long-term average of the measurement data of the corresponding capacitive sensor for the first time period, and the analysis module 110 collects the measurement data from the corresponding capacitive sensor for the first preset time period based on a second sampling frequency different from the first sampling frequency, and the measurement data from the corresponding capacitive sensor for the first time period is collected based on the measurement data of the corresponding capacitive sensor for the first time period lasting the first preset time period if a ratio of the second long-term average to the first long-term average is within a range of the average ratio threshold and a degree of dispersion of the measurement data measured for the second preset time period is still less than the dispersion threshold The long-term average resets the first and second decision thresholds of the respective capacitive sensor. The result distortion caused by the fixed sampling frequency can be reduced by different sampling frequencies. Various capacitance sensors for detecting sitting postures are affected by external environments, so that the reference for detecting the sitting postures has deviation, the accuracy of sitting posture monitoring is further affected, and the influences can be well eliminated.

According to a preferred embodiment, the second sampling frequency is higher than the first sampling frequency, and the second predetermined duration is less than the first predetermined duration. The checking adopts a short-time high-frequency mode, so that enough measurement data can be rapidly acquired for checking, the time gap is well utilized, and the result distortion caused by frequency fixation can be reduced.

According to a preferred embodiment, before the main control module 100 correspondingly outputs the electrical signal for the sitting posture reminder, the analysis module 110 needs to determine the duration of the second state, and only when the duration of the second state exceeds a third preset duration, the main control module 100 correspondingly outputs the electrical signal for the sitting posture reminder. Sometimes it may be that the user only slightly adjusts the down posture resulting in a transient second state, which if alerted upon finding the second state, can greatly degrade the user experience, creating a conflicting mood.

According to a preferred embodiment, after the duration time of the second state exceeds a third preset time period, the analyzing module 110 checks the discrete degree of the corresponding measurement data of the corresponding capacitive sensor to determine the reliability degree of the second state, and the main control module 100 correspondingly outputs the electric signal for the sitting posture reminding only when the reliability degree of the second state is greater than or equal to the reliability threshold.

According to a preferred embodiment, the process of checking the degree of dispersion of the corresponding measurement data of the respective capacitive sensor by the analysis module 110 to determine the degree of reliability of the second state comprises: analyzing the first number of the capacitive sensors to be confirmed which are judged to be in the second mode and/or the third mode; finding out a second number of the corresponding capacitive sensors with the discrete degree of the measurement data larger than the discrete degree threshold value from the capacitive sensors to be confirmed; the degree of reliability is determined by the ratio of the second number to the first number. The further away the user is from the backrest, the less and less discrete is detected due to measurement accuracy problems, and may in turn be below a discrete threshold. However, in this case, it is not easy to judge whether the actual sitting posture of the user deviates from the standard sitting posture too much. Therefore, some situations which are not easy to determine can be selectively excluded through the reliability threshold value, so that the frequency of reminding is reduced, and the user experience is improved.

Example 2

The present embodiment discloses a sitting posture detecting system, which is suitable for performing the steps of the method described in the present invention to achieve the desired technical effect. This embodiment may be a further improvement and/or a supplement to embodiment 1, and repeated contents are not described again. The preferred embodiments of the present invention are described in whole and/or in part in the context of other embodiments, which can supplement the present embodiment, without resulting in conflict or inconsistency.

According to a preferred embodiment, the system may comprise: a master control module 100 and at least two capacitive sensors 200. Each of the at least two capacitive sensors 200 may be respectively disposed at different levels of the backrest. The master control module 100 may include an analysis module 110. The system can collect at least two sets of measurement data from at least two capacitive sensors 200 located at least two different levels, respectively, through the main control module 100. The system can determine the contact state of the user according to at least two sets of measurement data by the analysis module 110 of the main control module 100. The analysis module 110 can analyze the sitting posture of the user according to the contact state and correspondingly output an electric signal for prompting the sitting posture by the main control module 100 when the user is in an unfavorable sitting posture. By this way, have several following beneficial technological effects at least: firstly, the characteristic of the capacitance sensor can be utilized to well reduce the detection failure condition; secondly, the sitting posture detection is realized only by arranging at least two groups of capacitance sensors on the backrest, the system cost can be reduced better, and the robustness of the system is improved.

Preferably, when the measurement data of the corresponding capacitive sensor is continuously smaller than the first determination threshold for more than a set time, the main control module 100 may set the capacitive sensor to a sleep state, and suspend the power supply circuit from supplying power to the capacitive sensor. However, when all of the capacitive sensors located above one capacitive sensor are not in sleep, the main control circuit does not set the capacitive sensor to the sleep state. For example, more than two capacitive sensors may be provided along the line connecting the shoulder and the waist of the human body. And at least one third capacitive sensor is also arranged between the first capacitive sensor and the second capacitive sensor, wherein the main control circuit does not set the second capacitive sensor to be in a dormant state under the condition that the measurement data of the second capacitive sensor is smaller than the first judgment threshold value within the set time but the measurement data of the first capacitive sensor and the measurement data of the third capacitive sensor are larger than the second judgment threshold value or the third judgment threshold value within the set time. For another example, the initial operating state of the third capacitive sensor is a sleep state, and the initial operating states of the first capacitive sensor and the second capacitive sensor are energized operating states. When, for example, an adult or an elderly person is sitting in the seat, the size of the seat ensures that the first capacitive sensor, which is located at a higher position on the seat back, is in a stressed state. When a child is seated in the seat, for example, the third capacitive sensor located lower may be in a pressed state and the first capacitive sensor located higher may be in a state of being out of contact with the human body due to a large difference in body size. In order to be adapted to the body type of the child, the third capacitive sensor which is slightly lower than the first capacitive sensor can be just adapted to the shoulder position of the child, namely the third capacitive sensor is used for replacing the first capacitive sensor to collect data, so that the seat can be suitable for sitting people with different body types. The set time can be set according to actual conditions or set by a sitting person.

According to a preferred embodiment, a sitting posture detection system may include: at least two capacitive sensors 200 and/or master control module 100 located at least two different levels. The master control module 100 may include an analysis module 110. The main control module 100 can collect at least two sets of measurement data from the at least two capacitive sensors 200 respectively and determine the contact state of the user by the analysis module 110 according to the at least two sets of measurement data. When the analysis module 110 obtains that the user is in an undesirable sitting posture according to the contact state analysis, the main control module 100 may correspondingly output an electrical signal for prompting the sitting posture.

Preferably, the at least two capacitive sensors 200 may include a first capacitive sensor 210 and a second capacitive sensor 220. The first and/or second capacitive sensor 220 may comprise only a single sensing element, e.g., having only one probe. Alternatively, the first and/or second capacitive sensor 220 may be a sensing assembly including several sensing elements, and the measurement data may be obtained by averaging or weighted averaging of a plurality of probes to make the measurement data more accurate.

Preferably, the capacitive sensor may be mounted on the backrest 510 of the seat 500. Preferably, the measurement principle of the capacitive sensor is: the probe of the capacitance sensor is one polar plate, and the object to be measured forms the other polar plate of the capacitance sensor. Interaction of the object with the probe causes a change in capacitance of the capacitive sensor, which reflects the distance between the object and the probe. The object to be measured is, for example, a user, who approaches, touches or presses the probe with his hand or back, and the capacitance sensor measures a different value.

Preferably, the main control module 100 may complete the data calculation and the contact state determination process. The main control module 100 may upload the original measurement data and/or the determination result to the user mobile terminal 300 and/or the cloud server 400 by using at least one communication transmission method of bluetooth, WIFI, 4G, 5G, NB-IoT and ZigBee. When uploading the raw measurement data to the ue 300 and/or the cloud server 400, the system may request the ue 300 and/or the cloud server 400 to assist the main control module 100 to complete at least a part of the calculation task. The main control module 100 may be connected to the ue 300 and/or the cloud server 400 through the communication module 120. The communication module 120 may include at least one of a bluetooth module, a WIFI module, a 4G module, a 5G module, an NB-IoT module, and a ZigBee module. Preferably, the system requests the ue 300 and/or the cloud server 400 to assist the host 100 to complete at least a part of the computing task only when the current computing resource usage rate of the host 100 exceeds 80% and the duration exceeds 5 s. The user mobile terminal may be at least one of a dedicated handheld controller, a smart phone, a smart watch, smart glasses, a tablet computer, and a notebook computer. Cloud server 400 may be a single server or a cluster of servers.

Preferably, the system may be mounted on the back 510 of the chair 500. For example, the first capacitive sensor 210 may be mounted on the middle upper portion of the backrest 510. The second capacitive sensor 220 may be mounted at a position below the middle of the backrest 510. The main control module 100 may be installed in the interlayer of the backrest 510. The master control module 100 may be, for example, at least one of an application specific integrated circuit ASIC, FPGA, CPU, and general purpose computer that can be used to process data and/or transmit data.

Preferably, the main control module 100 may perform analysis by collecting measurement data of each capacitive sensor to determine a distance pattern of the corresponding capacitive sensor. The distance pattern may include: a first mode when the measured data is equal to or less than a first judgment threshold, a second mode when the measured data is greater than the first judgment threshold and equal to or less than a second judgment threshold, and a third mode when the measured data is greater than the second judgment threshold. Preferably, the first mode is generally when the user is not seated on the chair 500 or is seated on the chair 500, but is located a distance from the backrest 510 that is beyond the measurement range of the capacitive sensor. The second mode is typically where the user is within the measurement range of the capacitive sensor, but the measurement data indicates that the capacitive sensor is not yet positioned or is not as close to the backrest 510 as desired. The third mode is typically where the capacitive sensor is already fully seated against the backrest 510.

Preferably, the contact state may include a first state, a second state, and a third state. The contact state is judged in the following manner: when each of the at least two capacitive sensors 200 is in the first mode, determining that the current contact state is the first state; when the number of the capacitive sensors in the third mode in the at least two sensors is smaller than the preset number and at least one capacitive sensor is in the second mode or the third mode, judging that the current contact state is the second state; and/or when the number of the capacitive sensors in the third mode is greater than or equal to the preset number, determining that the current contact state is the third state. The invention divides the distance between the user and the sensor into three modes, not only can judge the contact state, but also can judge the state when the user is not in contact, and the invention distinguishes three specific states for identifying the sitting posture of the user by combining different modes of at least two capacitive sensors.

Preferably, when the contact state is the first state, it indicates that the user is not detected, and when the contact state is the second state, the analysis module 110 analyzes that the user is in a bad sitting posture according to the contact state, and the main control module 100 correspondingly outputs an electrical signal for prompting the sitting posture. For example, assuming that the at least two sensors include the first capacitive sensor 210 and the second capacitive sensor 220, the preset number is set to two. When both the first and second capacitive sensors 220 are in the first mode, it is determined that the current contact state is the first state. When one of the first and second capacitive sensors 220 is in the second or third mode and the other is in the first mode, it is determined that the current contact state is the second state. The current contact state is determined to be the third state only if both the first and second capacitive sensors 220 are in the third mode. For another example, it is assumed that the at least two sensors include first, second, third, fourth, and fifth capacitive sensors, and the preset number is set to four. And when the first, second, third, fourth and fifth capacitive sensors are all in the first mode, judging that the current contact state is the first state. And when the number of the capacitive sensors in the third mode in the first, second, third, fourth and fifth capacitive sensors is less than four, but at least one capacitive sensor is in the second mode or the third mode, judging that the current contact state is the second state. When the number of the capacitive sensors in the third mode among the first, second, third, fourth, and fifth capacitive sensors is equal to or greater than four, that is, four or five, it is determined that the current contact state is the third state. Preferably, the corresponding capacitive sensor may refer to at least one of the at least two capacitive sensors 200.

Preferably, in order to avoid the defect of unstable data of the capacitive sensor, the analysis module 110 is utilized to help correct and improve the accuracy of the system for judging the mode.

Preferably, for the first time of use, it is recommended to first stop for more than a first preset time, initialize the system, and calibrate each capacitive sensor by using the analysis module 110. After the initialization is completed, the system or the main control module 100 instructs the user to demonstrate the first state, the second state and the third state, and the main control module 100 correspondingly completes data acquisition of the three contact states for performing initialization training on the system. Preferably, the user can input at least one of age, sex, and weight through the user moving terminal 300, and the user moving terminal 300 adjusts the first and second judgment thresholds according to the at least one of age, sex, and weight, and sends the adjusted first, second, and third judgment thresholds to the main control module 100 for updating. For example, the system or the main control module 100 instructs the user to demonstrate the first state, the second state and/or the third state through voice indication of a speaker and/or through an image of a display screen. The system or master control module 100 instructs the user to demonstrate the first state by instructing the user not to sit in the chair 500. The system or master control module 100 can instruct the user to perform at least three postures when instructing the user to demonstrate the second posture, the first posture in which the user sits in a humpback posture on the chair 500 without the back resting on the backrest 510, the second posture in which the user rests in the lumbar region against the backrest 510 but leans forward without resting on the backrest 510, and the third posture in which the user rests in the shoulder region against the backrest 510 but does not rest in the lumbar region against the backrest 510. The system or master control module 100 instructs the user to demonstrate the third state by instructing the user to sit upright and will allow the user to exert their maximum force to fully seat the back against the backrest 510. Preferably, the system or the main control module 100 may instruct the user to demonstrate that the order of the contact state may be the first state, the third state and the second state. The zero value of each capacitive sensor is determined by demonstrating the first state, and the first judgment threshold and the second judgment threshold of each capacitive sensor are determined by demonstrating the second state and the third state, so that preliminary training is completed. Preferably, the system or the main control module 100 can instruct the user to repeatedly demonstrate the first state, the second state and the third state at least twice in sequence, and the latter demonstration process is used for checking and confirming the accuracy of the previous teaching and correcting the previous teaching result by using the latter teaching process.

Preferably, the main control module may include a storage medium, at least historical data of the user in preset days is stored in the storage medium, comparison is performed according to the historical data and measurement data of the current user, and when the comparison results in user change, if information of the current user is recorded before, switching to the first and second judgment thresholds of the current user for judging the contact state; if the current user information is not recorded before, the voice reminds the current user to register in the user mobile terminal 300, and the system initialization tuning is completed.

Preferably, since the capacitive sensors are susceptible to external mechanical motion interference, environmental change interference, and installation location influence, the first and second determination thresholds of each capacitive sensor are dynamically adjusted using a long-term average LTA, i.e., long term average, where LTA is an average of measurement data collected within a preset time period. In practical cases, the weighted average may also be weighted by a parameter, such as a constant or a ratio with other data, so as to make the tuning setup more flexible. The LTA functions to calibrate the system, i.e., to eliminate the malfunction of the system based on the mode determination of the initial setting due to certain factors. The specific factors may include at least one of weight covering, aging of the capacitive sensor, and external environmental changes, in addition to deformation of the coating of the backrest 510 each time the user abuts the backrest 510. The external environment change is, for example, an electric field environment change or a temperature condition change. In particular, the capacitive sensor has high sensitivity and is sensitive to external electromagnetic environment, so it is important to calibrate the system through LTA.

Preferably, the analysis module 110 continuously collects the measurement data of each capacitive sensor for analysis, and resets the first and second determination thresholds of the corresponding capacitive sensor based on the first long-term average of the measurement data of the corresponding capacitive sensor in the first time period lasting for the first preset time if the dispersion degree of the measurement data of the corresponding capacitive sensor is continuously less than the dispersion degree threshold for more than the first preset time. For example, it is assumed that the system includes the first capacitive sensor 210 and the second capacitive sensor 220, the first preset time is 10s, the reference value measured by each capacitive sensor is zero, the first judgment threshold and the second judgment threshold of the first capacitive sensor 210 before calibration are 0.04 and 0.2, respectively, and the first judgment threshold and the second judgment threshold of the second capacitive sensor 220 before calibration are 0.03 and 0.19, respectively. After power-on, the chair 500 remains stationary until initialization is complete. When the system is initialized, the analysis module 110 continuously collects the measurement data of the first and second capacitive sensors 220 for analysis, because the measurement data of the first and second capacitive sensors 220 are kept still, the dispersion degree of the measurement data of the first and second capacitive sensors 220 is continuously less than the dispersion degree threshold value for more than 10s, and within the 10s, the first long-term average value of the measurement data of the first capacitive sensor 210 is 0.005, and the first long-term average value of the measurement data of the second capacitive sensor 220 is 0.01. In this case, the long-term average of the measurement data collected within 10s may be added to the original first and second determination thresholds as new first and second determination thresholds. For the first capacitive sensor 210, the first and second determination thresholds thereof may be increased to 0.045 and 0.205, respectively, based on the first long-term average value 0.005 of the measurement data of the first capacitive sensor 210. For the second capacitive sensor 220, the first and second decision thresholds thereof may be increased to 0.04 and 0.2, respectively, based on the first long-term average value 0.01 of the measurement data of the second capacitive sensor 220. Therefore, initial data deviation caused by non-uniform placement positions and interference of an external electromagnetic environment when a product leaves a factory, data failure in full range caused by aging of the capacitive sensor and initial data drift caused by covering of a heavy object on the back cushion can be effectively reduced. For another example, in the event that the user leaves, he or she places an item of clothing on the backrest 510, just covering the first capacitive sensor 210. The first capacitive sensor 210 obtained by the analysis module 110 may be always in the second mode or the third mode due to the influence of the clothes, and the touch state of the user is obtained as the second state, but the second state is not effective because the user does not actually sit on the seat 500, which results in the out-of-position detection. Ideally, the chair 500 is at full rest when no user is on the chair 500. Factors that affect the change in the measurement data may include at least one of temperature, humidity, air pressure, ambient electromagnetic field, and a coating material coated over the capacitive sensor. However, the data fluctuations caused by the influence of these factors on the measurement data of the capacitive sensor and the influence of the user are different. Particularly in the presence of a user, the measurement data fluctuates due to heartbeat fluctuation, foot trembling, fine-tuning posture, hand movement and head movement, and the fluctuation range is relatively larger. That is, it is not a human factor that the degree of dispersion of the measurement data is smaller than the threshold degree of dispersion, and it is a factor of the user that the degree of dispersion of the measurement data is equal to or larger than the threshold degree of dispersion. According to the invention, through judging the discrete degree, the change or the maintenance of the measurement data can be well judged to be caused by a user or caused by external factors, and the detection of an invalid second state and/or third state is avoided, so that the sitting posture detection is more accurate. Meanwhile, whether the first judgment threshold value and the second judgment threshold value need to be reset or not is judged by utilizing the discrete degree, so that the judgment threshold value can be prevented from being updated mistakenly, and subsequent detection results are prevented from being wrong. In the actual operation process, designers select different types of capacitive sensors, which may have different corresponding measurement accuracy, interference resistance and the like, and different discrete degree thresholds. Therefore, after the designer selects the model of the capacitive sensor, the designer can measure and set a reference discrete degree threshold value through experiments. Through this preferred embodiment, at least beneficial technical effects can be achieved: firstly, data deviation caused by improper position of the capacitive sensor during installation can be avoided; some capacitive sensors have high sensitivity and are therefore high in mounting technology, and if the capacitive sensors are placed incorrectly, the capacitive sensors are extruded by a large force when leaving factories, and the influence can be eliminated in this way; secondly, the influence of the external electromagnetic environment on the capacitive sensor can be effectively avoided, the capacitive sensor is sensitive to the external electromagnetic environment, such as radio frequency interference, high voltage static electricity, surge voltage and other interference can cause the data of the capacitive sensor to fluctuate or deviate, and the data can rise or fall relative to the constant environment, and the error can be eliminated by adopting the method; thirdly, the problem of insensitive detection caused by aging of the capacitive sensor is relieved; considering that the capacitive sensor is installed in the backrest 510, due to the material characteristics of the back cushion and the capacitive sensor, after the capacitive sensor is used for a period of time, the sensitivity and the measuring range of the capacitive sensor can be changed, and the mode can dynamically adjust the threshold value of the system for data processing, so that the aging problem of the capacitive sensor is relieved; fourthly, detection errors caused by the fact that a user places clothes on the backrest 510 can be prevented, the user can possibly place clothes, pillows and other objects on a detection part in the process of actually using the seat, and influences of data changes of the capacitive sensor on detection result judgment except for a human body can be effectively filtered through the method. Preferably, the degree of Dispersion, the english name Measures of Dispersion, refers to the degree of difference between the values of the variables by observing them randomly. The dispersion degree can reflect the difference between the observation individuals, so that the representative height of the index of the distribution center to each observation variable value can be reflected. There are many indexes that can be used to measure the degree of difference between observed variable values, and the most common ones in statistical analysis and inference are range differences, mean differences, and standard deviations. The variance, the standard deviation, the mean deviation, and the like are absolute quantities of numerical values, and the influence of the numerical measurement unit cannot be avoided, for example, a data set with a standard deviation of 10 may reflect a small fluctuation for a data set with a large numerical magnitude, but may also have a large fluctuation for a data set with a small numerical magnitude. Therefore, according to the present invention, the inventors have creatively proposed that these statistics can be combined with mean or median, etc. as required to effectively assess the dispersion of the data set. For example, the standard deviation is divided by the mean to obtain the coefficient of variation, reflecting the degree of dispersion in the unit mean. The coefficient of variation is that when the discrete degrees of two sets of data need to be compared, if the difference between the measurement scales of the two sets of data is too large or the data dimensions are different, the standard deviation is directly used for comparison, and the influence of the measurement scales and the dimensions should be eliminated, and the coefficient of variation can do this, which is the ratio of the standard deviation of the original data to the average of the original data. The coefficient of variation has no dimension, so that objective comparison can be carried out. In fact, the coefficient of variation, like the range, standard deviation, and variance, can be considered to be an absolute value reflecting the degree of dispersion of the data. And comparing the measured discrete degree with the discrete degree, for example, comparing the discrete degree based on the coefficient of variation, setting the discrete degree threshold to be 15%, and setting the discrete degree of the measurement data of the first capacitive sensor to be 8-10% and exceeding a first preset time. The discrete degree of the measurement data of the second capacitive sensor is 20-23%. The analysis module 110 continuously collects the measurement data of each capacitive sensor for analysis, and resets the first and second determination thresholds of the first capacitive sensor based on the first long-term average of the measurement data of the first capacitive sensor in the first time period lasting for the first preset time since the dispersion degree of the measurement data of the first capacitive sensor is continuously smaller than the dispersion degree threshold for more than the first preset time. And if the discrete degree of the measurement data of the second capacitive sensor is greater than the discrete degree threshold value, the first and second judgment threshold values are not reset.

According to a preferred embodiment, the distance mode is described below in terms of measurement data of a single capacitive sensor, see fig. 3, fig. 3 with 10ms on the abscissa and the corresponding measurement range of the capacitive sensor on the ordinate, which may be normalized data. The larger the measured value is, the larger the capacitance is, the closer the human body is to the capacitance sensor or the larger the contact area between the human body and the capacitance sensor is, the larger the capacitance is, and the larger the measured value is. The first marker line L1 represents a trace of a long-term average value, the second marker line L2 is a signal line plotted for measurement data generated by the capacitive sensor, and the third marker line L3 is a determination signal of whether or not the capacitive sensor is in the second mode, and is 0 when not in the second mode and is 1 when in the second mode. The fourth marker line L4 is a determination signal indicating whether the capacitive sensor is in the third mode, and is 0 when not in the third mode and is 1 when in the third mode. Assume that the first judgment threshold is 0.02 and the second judgment threshold is 0.24. In fig. 3, the user is approaching the capacitive sensor slowly, the measurement data of the capacitive sensor exceeds the first decision threshold between abscissas 1-11, and the second mode is generated. The user continues to approach the capacitive sensor beyond the second decision threshold between abscissa 101 and 111, the third mode occurs, after which the user gradually moves away from the capacitive sensor, about less than the first decision threshold after abscissa 591, and the second mode disappears. Assume that the first preset time is 10 s. Then, the analysis module 110 continuously collects the measurement data of the capacitive sensor for analysis, and when the dispersion degree of the measurement data of the capacitive sensor is continuously smaller than the dispersion degree threshold value and exceeds the first preset time by 10s, the first and second judgment threshold values of the corresponding capacitive sensor are reset based on the first long-term average value of the measurement data of the corresponding capacitive sensor in the first time period lasting for the first preset time, so as to be used as the judgment reference for the next detection. Due to size limitations, subsequent measurements and variations of the first marker line L1 are not shown in fig. 3, later on in isolation in fig. 4. Referring to fig. 4, fig. 4 has the abscissa unit of 10ms and the ordinate unit of the measurement range of the corresponding capacitive sensor. In the vicinity of the position with the abscissa of 1, the capacitance sensor exceeds 0.02, the measurement is about 0.09, the data is kept for more than 10s in the second mode, the dispersion degree of the measurement data in the period of time is analyzed, and the dispersion degree is continuously smaller than the dispersion degree threshold value, so that the data change caused by the user is not considered, the condition is considered to be the initial data drift of the capacitance sensor caused by fatigue of a covering object or the capacitance sensor and interference of the external electromagnetic environment, and at the moment, the first judgment threshold value and the second judgment threshold value of the capacitance sensor are reset on the basis of the average value of the measurement data of the capacitance sensor in the period of time, for example, the first judgment threshold value is set to be 0.11, and the second judgment threshold value is set to be 0.26; this avoids the interference of the external environment to the initial situation. Referring again to fig. 3, assuming that an object initially covers the backrest 510, the system changes the first determination threshold after 10 seconds; the user then sits in the chair against the backrest 510 and goes into the third mode after a short second mode between 1211 and 1233 on the abscissa; the user then moves away and the capacitive sensor returns to the second mode.

According to a preferred embodiment, the analysis module 110 collects the measurement data from the corresponding capacitive sensor at a first sampling frequency for a first time period lasting a first preset time, the analysis module 110 collects the measurement data from the corresponding capacitive sensor for a second preset time period at a second sampling frequency before resetting the first and second decision thresholds of the corresponding capacitive sensor based on a long-term average of the measurement data of the corresponding capacitive sensor for the first time period, the analysis module 110 resets the corresponding electrical power based on the long-term average of the measurement data of the corresponding capacitive sensor for the first time period, if a ratio of the second long-term average to the first long-term average of the measurement data measured for the second preset time period is within a mean ratio threshold range and a degree of dispersion of the measurement data measured for the second preset time period is less than a still degree of dispersion threshold value, the corresponding electrical power being collected from the corresponding capacitive sensor for the first time period lasting the first preset time period First and second decision thresholds for the capacitance sensor; the second sampling frequency is higher than the first sampling frequency, but the second preset duration is less than the first preset duration. Because the process that the user adjusts the sitting posture midway is likely to be short, the result measured last time is verified in a short-time high-frequency mode, the gap time is utilized for quick verification, and the signal reduction error caused by single-frequency sampling can be reduced. For example, the first preset time period may be 2s or 3 s. The second preset time period may be 0.5s or 1 s. The first sampling frequency may be 50Hz or 100 Hz. The second sampling frequency may be 200Hz or 300 Hz.

According to a preferred embodiment, the duration of the second state needs to exceed a third preset time period before the main control module 100 correspondingly outputs the electric signal for the sitting posture reminding. Preferably, after the duration of the second state needs to exceed the third preset time period, the analyzing module 110 checks the discrete degree of the corresponding measurement data of the corresponding capacitive sensor to determine the reliability degree of the second state, and the main control module 100 correspondingly outputs the electric signal for the sitting posture reminder when the reliability degree of the second state is greater than or equal to the reliability threshold. Preferably, the process of checking the degree of dispersion of the corresponding measurement data of the respective capacitive sensor by the analysis module 110 to determine the degree of reliability of the second state comprises: and analyzing the first number of the to-be-confirmed capacitive sensors which are judged to be in the second mode and/or the third mode, finding out a second number of the capacitive sensors of which the dispersion degree of the corresponding measurement data is greater than the dispersion degree threshold value from the to-be-confirmed capacitive sensors, and determining the reliability degree according to the ratio of the second number to the first number. The larger the ratio, the higher the degree of reliability. The greater the reliability threshold is set, the less the probability of false positives, but the higher the probability of false negatives. For example, assuming that the system includes two capacitive sensors, the reliability threshold is set to 50%, and the third preset duration is 2 s. The first capacitive sensor 210 is in the second mode and the second capacitive sensor 220 is in the third mode. The first number is two. After 2s, the degree of dispersion of the corresponding measurement data of the respective capacitive sensor is checked by the analysis module 110 to determine the degree of reliability of the second state. The discrete degree of the measurement data used for determining that the first capacitive sensor 210 is in the second mode is smaller than the discrete degree threshold, and the discrete degree of the measurement data used for determining that the second capacitive sensor 220 is in the third mode is greater than the discrete degree threshold, the second number is one, the reliability degree is 50%, and the reliability degree is greater than or equal to the set reliability threshold, at this time, it is determined that the body of the user leans forward, and the main control module 100 correspondingly outputs an electric signal for sitting posture reminding. If the reliability threshold is set to 100%, it cannot be determined whether the measured data of the first capacitive sensor 210 in the second mode is discrete or not due to human factors because the discrete degree is smaller than the discrete degree threshold, and in order to reduce false alarm, the main control module 100 does not output an electrical signal for sitting posture reminding when the reliability degree is lower than 100%. Preferably, the reliability threshold is set in a manner of being 50% or more. Although many patent technologies and products thereof for preventing diseases of the spine and lumbar vertebra and preventing myopia by correcting bad sitting posture, such as sitting posture correction brackets or posture correction braces, etc. have emerged at present. However, these products often have the common disadvantage that the user, once wearing or using the corrective product, must be highly restrained and always maintain the correct posture, leaving the user in a forced, uncomfortable condition, which over time may be psychologically repulsive and thus result in the user intentionally not using the product. Especially for persons with poor continence, such as primary and secondary school students, the correction product is often used by parents who lay aside as soon as they leave. Thus, there is no mention about the effect of preventing lumbar spine diseases or myopia by correcting sitting posture. Therefore, the reliability threshold is set to be greater than or equal to 50%, even greater than or equal to 80% or 100%, so that the reminding frequency can be reduced, the rejection psychology of the user can be relieved, the user can use the method more naturally, and the user experience is improved.

The word "module" as used herein describes any type of hardware, software, or combination of hardware and software that is capable of performing the functions associated with the "module".

It should be noted that the above-mentioned embodiments are exemplary, and that those skilled in the art, having benefit of the present disclosure, may devise various arrangements that are within the scope of the present disclosure and that fall within the scope of the invention. It should be understood by those skilled in the art that the present specification and figures are illustrative only and are not limiting upon the claims. The scope of the invention is defined by the claims and their equivalents.

Claims

1. A sitting posture detecting method, comprising:

at least two groups of measurement data are respectively acquired from at least two capacitance sensors (200) positioned at least two different horizontal heights through a main control module (100), and each capacitance sensor of the at least two capacitance sensors (200) is respectively arranged at the different horizontal heights of the backrest;

judging the contact state of a user according to the at least two groups of measurement data through an analysis module (110) on the main control module (100);

the analysis module (110) analyzes the sitting posture of the user according to the contact state, and correspondingly outputs an electric signal for prompting the sitting posture when the user is in an undesirable sitting posture after analysis;

the at least two capacitive sensors (200) comprise a first capacitive sensor (210) and a second capacitive sensor (220);

the processing of the analysis module (110) to determine the contact state of the user according to the at least two sets of measurement data comprises:

the analysis module (110) analyzes the acquired measurement data of each capacitive sensor to determine the distance mode of the corresponding capacitive sensor and judge the contact state according to the distance mode of each capacitive sensor;

wherein the distance pattern comprises: a first mode when the measured data is equal to or less than a first judgment threshold, a second mode when the measured data is greater than the first judgment threshold and equal to or less than a second judgment threshold, and a third mode when the measured data is greater than the second judgment threshold;

the contact state includes a first state corresponding to a user's sitting posture not being detected, a second state corresponding to a user's sitting posture being poor, and a third state corresponding to a user's sitting posture being good, and the first, second, and third states are determined as follows:

when each of the at least two capacitive sensors (200) is in the first mode, determining that the current contact state is the first state;

when the number of the capacitive sensors in the third mode in the at least two sensors is smaller than the preset number and at least one capacitive sensor is in the second mode or the third mode, judging that the current contact state is the second state;

when the number of the capacitive sensors in the third mode in the at least two capacitive sensors (200) is greater than or equal to the preset number, judging that the current contact state is the third state;

after the duration time of the second state exceeds a third preset time, the discrete degree of corresponding measurement data of the corresponding capacitive sensor is checked through the analysis module (110) to determine the reliability degree of the second state, and when the reliability degree of the second state is greater than or equal to a reliability threshold value, the main control module (100) correspondingly outputs an electric signal for sitting posture reminding;

the processing of the checking of the degree of dispersion of the corresponding measurement data of the respective capacitive sensor by the analysis module (110) to determine the degree of reliability of the second state comprises:

analyzing the first number of the capacitive sensors to be confirmed which are judged to be in the second mode and/or the third mode;

finding out a second number of the corresponding capacitive sensors with the discrete degree of the measurement data larger than the discrete degree threshold value from the capacitive sensors to be confirmed;

the degree of reliability is determined by the ratio of the second number to the first number.

2. The method of claim 1, wherein the analysis module (110) continuously collects the measurement data of each capacitive sensor for analysis, and resets the first and second decision thresholds of the corresponding capacitive sensor based on a first long-term average of the measurement data of the corresponding capacitive sensor for a first time period lasting a first preset time if a degree of dispersion of the measurement data of the corresponding capacitive sensor continues to be less than a degree of dispersion threshold for more than the first preset time.

3. The method of claim 2, wherein the analysis module (110) collects the measurement data from the corresponding capacitive sensor at a first sampling frequency for a first time period lasting a first preset time, wherein the analysis module (110) collects the measurement data from the corresponding capacitive sensor for a second preset time period using a second sampling frequency different from the first sampling frequency before resetting the first and second decision thresholds for the corresponding capacitive sensor based on the long-term average of the measurement data for the corresponding capacitive sensor for the first time period lasting the first preset time, wherein the ratio of the second long-term average to the first long-term average of the measurement data measured for the second preset time period is within a threshold range of the mean ratio and wherein the degree of dispersion of the plurality of measurement data measured for the second preset time period remains less than the threshold of the degree of dispersion, the first and second decision thresholds of the respective capacitive sensor are reset based on a long-term average of the measurement data of the respective capacitive sensor over a first time period lasting a first preset time.

4. The method of claim 3, wherein the second sampling frequency is higher than the first sampling frequency, and wherein the second predetermined duration is less than the first predetermined duration.

5. The method according to claim 4, wherein the analysis module (110) needs to determine the duration of the second state before the main control module (100) correspondingly outputs the electrical signal for the sitting posture reminder, and the main control module (100) correspondingly outputs the electrical signal for the sitting posture reminder only when the duration of the second state exceeds a third preset duration.

6. A sitting posture detection system, the system comprising: a main control module (100) and at least two capacitive sensors (200), wherein each capacitive sensor of the at least two capacitive sensors (200) is respectively arranged on different horizontal heights of the backrest, the main control module (100) comprises an analysis module (110),

the system collects at least two groups of measurement data from at least two capacitance sensors (200) positioned at least two different levels through a main control module (100);

the system judges the contact state of a user according to the at least two groups of measurement data through an analysis module (110) on a main control module (100);

the analysis module (110) analyzes the sitting posture of the user according to the contact state, and correspondingly outputs an electric signal for prompting the sitting posture when the user is in an undesirable sitting posture after the analysis module obtains the sitting posture of the user;

7. The system of claim 6, wherein the analysis module (110) continuously collects the measurement data of each capacitive sensor for analysis, and resets the first and second decision thresholds of the corresponding capacitive sensor based on a first long-term average of the measurement data of the corresponding capacitive sensor over a first time period lasting a first preset time if a degree of dispersion of the measurement data of the corresponding capacitive sensor continues to be less than a degree of dispersion threshold for more than the first preset time.