Wearable intelligent physical sign monitoring control method

Abstract

The invention relates to the technical field of medical wearable equipment monitoring control, in particular to a wearable intelligent physical sign monitoring control method. The method comprises the following steps: continuously monitoring a sitting posture pressure value of the intelligent seat; when the sitting posture pressure value is larger than a first threshold value, it is judged that the sitting posture is in a pressing state, and initial site fitting information is obtained; and obtaining a human body sitting posture form and carrying out adaptive posture adjustment on the intelligent seat according to the human body sitting posture form, so that the intelligent seat is matched with the human body sitting posture form, the initial sitting standby state reaches the optimal sitting posture form of the intelligent seat, and optimal sitting posture memory data is stored. Through a data processing technology, a real-time monitoring technology and an automatic control technology, human body sitting posture shape matching mapping is carried out on vital sign data detected by wearable intelligent sign equipment and site fitting information monitored by the intelligent seat, and self-adaptive posture adjustment is carried out on the intelligent seat; therefore, the automatic adjustment degree of the intelligent seat is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical wearable device monitoring and control, and in particular to a wearable intelligent vital sign monitoring and control method. Background Art

[0002] Existing wearable devices can monitor a variety of vital signs to achieve comprehensive monitoring of human health; and smart wearable devices integrate high-performance sensors, such as high-sensitivity liquid metal sensors and carbon nanotube-based electronic skin, which can effectively monitor subtle body movements and physiological changes; with the application of wearable devices in medical smart seats, the smart vital sign sensors integrated on the hand-worn positioning device are used to monitor key vital signs such as heart rate, blood oxygen and body temperature, and the real-time monitoring of human status is achieved through high-precision sensor technology; smart seats detect the surface pressure of the seat through pressure sensors, and automatically trigger vital sign signal acquisition and mobile terminal connection to achieve automated operation. However, the existing wearable intelligent vital sign monitoring and control methods fail to map the vital sign data detected by the wearable intelligent vital sign device with the site fitting information monitored by the intelligent seat to the human sitting posture, and thus lack adaptive posture adjustment of the smart seat, resulting in a low degree of automated adjustment of the smart seat. Summary of the invention

[0003] Based on this, it is necessary to provide a wearable intelligent vital sign monitoring and control method to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a wearable intelligent vital sign monitoring and control method is provided, the method comprising the following steps: Step S1: continuously monitoring the sitting posture pressure value of the smart seat; when the sitting posture pressure value is greater than a first threshold, determining that the sitting posture is in a pressure-holding state and obtaining initial position fitting information; Step S2: obtaining the sitting posture of the human body and adaptively adjusting the posture of the smart seat according to the sitting posture of the human body, so that the smart seat matches the sitting posture of the human body, reaches the optimal sitting posture of the smart seat from the initial sitting state and stores the optimal sitting posture memory data; Step S3: if the time of the sitting posture pressure state is greater than the preset sitting posture duration time, a dynamic vibration control signal is generated and the dynamic vibration control signal is responded to to provide a sedentary indicator light reminder; when it is monitored that the sitting posture pressure value decreases to zero and lasts until the preset seat idle time, the smart seat is restored to the initial ready-to-sit state; Step S4: When the monitored sitting pressure value increases from zero to the first threshold value, the real-time position fitting information is obtained; when the real-time position fitting information matches the initial position fitting information, the smart seat is adjusted according to the optimal sitting posture memory data, so that the smart seat is restored from the initial ready-to-sitting state to the optimal sitting posture.

[0005] The present invention continuously monitors the sitting pressure value of the smart seat, and when the sitting pressure value is greater than the first threshold, it is determined to be in a sitting pressure holding state and obtains the initial position fitting information. This step can accurately identify whether the user is in a sitting state by real-time monitoring of the sitting pressure value, and determine the start of the sitting posture by the set first threshold, and obtain the initial position fitting information at the same time, providing basic data for subsequent seat adjustment and user sitting posture analysis, ensuring that the smart seat can respond to the user's sitting posture changes in a timely manner. By acquiring the sitting posture of the human body and adaptively adjusting the posture of the smart seat according to the sitting posture of the human body, the smart seat can match the sitting posture of the human body, reach the optimal sitting posture of the smart seat from the initial ready-to-sit state and store the optimal sitting posture memory data. By analyzing the user's sitting posture, the smart seat can automatically adjust to adapt to the user's sitting posture, achieve the transition from the initial state to the optimal sitting posture, and record the optimal sitting posture data; such adaptive adjustment improves the user's comfort and provides support for the user's personalized sitting posture by storing memory data; if the time of the sitting posture pressure-holding state is greater than the preset sitting posture duration, a dynamic vibration control signal is generated and responded to the dynamic vibration control signal to provide a long-sitting indicator light reminder; when it is monitored that the sitting posture pressure value is reduced to zero and continues to the preset seat idle time, the smart seat is restored to the initial ready-to-sit state; by monitoring the duration of the sitting posture pressure-holding state, the user can be reminded through a vibration control signal when the user maintains the same sitting posture for a long time, thereby reducing the health risks caused by long-term sitting. At the same time, when the user leaves the seat, the smart seat can automatically restore to the initial state and prepare for the next use, thereby improving the use efficiency and response speed of the seat; when the sitting pressure value is monitored to increase from zero to the first threshold, the real-time site fitting information is obtained; when the real-time site fitting information matches the initial site fitting information, the smart seat is adjusted according to the optimal sitting posture memory data, so that the smart seat is restored from the initial ready-to-sit state to the optimal sitting posture; by monitoring the change of the sitting pressure value and the matching of the site fitting information, the user's sitting habits can be quickly identified when the user sits down again, and the seat can be adjusted according to the optimal sitting posture memory data to ensure that the user can quickly return to the optimal sitting posture set before, thereby improving the use experience and the intelligence level of the seat. Therefore, the present invention realizes the matching mapping of the vital sign data detected by the wearable intelligent vital sign device with the site fitting information monitored by the intelligent seat through data processing technology, real-time monitoring technology and automatic control technology, and realizes the adaptive posture adjustment of the intelligent seat, thereby improving the degree of automatic adjustment of the intelligent seat.

[0006] Preferably, step S1 comprises the following steps: Step S11: monitoring the seat cushion pressure distribution of the seat cushion area of ​​the smart seat to obtain a seat cushion pressure distribution value; monitoring the backrest support pressure of the backrest area of ​​the smart seat to obtain a backrest support pressure distribution value; monitoring the arm placement pressure of the armrest area of ​​the smart seat to obtain an arm placement pressure distribution value; Step S12: Integrate the seat cushion pressure distribution value, the backrest support pressure value and the arm placement pressure value to obtain the sitting posture pressure value; Step S13: when the sitting posture pressure value is greater than the first threshold, it is determined to be a sitting posture pressure holding state and the initial position fitting information is obtained; Step S14: Utilize the intelligent vital sign sensor to detect and acquire vital sign data.

[0007] The present invention monitors the pressure of the seat cushion area, backrest area and armrest area of ​​the smart chair respectively, and the system can obtain detailed seat cushion pressure distribution values, backrest support pressure values ​​and arm placement pressure values. These data provide accurate pressure information for subsequent sitting posture analysis and seat adjustment, ensuring comprehensive monitoring of the user's sitting posture; the seat cushion pressure distribution value, backrest support pressure value and arm placement pressure value are integrated to obtain a comprehensive sitting posture pressure value, so that the system can comprehensively evaluate the user's sitting posture state and provide accurate pressure data support for the adaptive adjustment of the smart chair; when the sitting posture pressure value exceeds the first threshold, it can accurately determine that the user is in a sitting posture holding pressure state, and obtain the initial position fitting information at this critical moment, which provides important reference data for the adaptive adjustment of the seat and the user's sitting posture comfort; using the intelligent vital sign sensor to detect and obtain the hand vital sign data, the system can monitor the user's health status in real time.

[0008] Preferably, step S13 includes the following steps: Step S131: when the sitting posture pressure value is greater than the first threshold, it is determined to be a sitting posture pressure holding state; Step S132: performing ischium pressure detection according to the cushion pressure distribution value to obtain ischium position information; Step S133: judging the back fit degree according to the backrest support pressure distribution value to obtain back position information; Step S134: identifying the arm placement range according to the arm placement pressure distribution value to extract arm position information; Step S135: Merge the sciatic site information, the back site information and the arm site information to obtain initial site fitting information.

[0009] By setting a first threshold, the present invention enables the system to accurately identify the user's sitting pressure-holding state, providing a basis for subsequent site information acquisition and seat adjustment; in the sitting pressure-holding state, the system detects the sciatic pressure through the seat cushion pressure distribution value, obtains the sciatic site information, and ensures that the seat's support and pressure distribution for the sciatic area are optimized; in the sitting pressure-holding state, the system determines the degree of back fit based on the backrest support pressure value; obtains the back site information to achieve personalized adjustment of the back support and improve sitting comfort; in the sitting pressure-holding state, the system identifies the arm placement range through the arm placement pressure value, and extracts the arm site information so as to accurately adjust the armrest area to ensure comfortable arm placement; the system merges the sciatic site information, back site information and arm site information to obtain initial site fit information, providing comprehensive site data for the smart seat, and achieving accurate adaptation and optimization of the user's sitting posture.

[0010] Preferably, step S135 includes the following steps: Step S1351: extracting the ischium compression strength value from the ischium position information; Step S1352: marking the back fitting area on the back site information to generate the back fitting area; Step S1353: perform arm contact feature detection on the arm position information to obtain arm contact features; perform structural texture recognition on the arm contact features to obtain arm structural texture data.

[0011] The present invention can quantify the pressure condition of the ischial area by extracting the ischial compression strength value, and provide accurate data support for adjusting the shape and hardness of the cushion, so as to reduce the ischial pressure and improve the comfort of sitting posture; the back fitting area is marked by the back site information, so as to identify and generate the back fitting area, and the intelligent seat can be adaptively adjusted according to the user's back contour to ensure that the back is properly supported and improve the comfort and health of the sitting posture; by detecting the arm contact characteristics in the arm site information and identifying the arm structure texture data, it can analyze the contact between the arm and the armrest in detail, so as to accurately adjust the shape and position of the armrest to ensure the comfort and support of the arm placement.

[0012] Preferably, step S14 includes the following steps: Step S141: using a temperature sign sensor to obtain hand temperature data; using a pulse sign sensor to obtain hand pulse data; Step S142: analyzing the muscle fiber orientation of the arm structure texture data to obtain the arm muscle fiber orientation; determining the arm blood vessel distribution data according to the arm muscle fiber orientation; and moving the infusion positioning mechanism to the target position according to the arm blood vessel distribution data; Step S143: measuring the arm blood vessel area temperature according to the hand temperature data and the arm blood vessel distribution data to obtain the arm blood vessel area temperature value; Step S144: determine the vital sign status based on the hand pulse data and the arm blood vessel area temperature value to generate vital sign data.

[0013] The present invention obtains hand temperature data and hand pulse data respectively through a temperature sign sensor and a pulse sign sensor, thereby collecting key vital sign information and providing accurate data support for subsequent health monitoring; by performing muscle fiber orientation analysis on the arm structure texture data, the arm blood vessel distribution data can be determined, and the infusion positioning mechanism can be moved to the target position accordingly, thereby improving the accuracy and efficiency of the infusion operation; by combining the hand temperature data and the arm blood vessel distribution data, the temperature value of the arm blood vessel area can be calculated, thereby accurately monitoring and evaluating the health status of the blood vessels; based on the hand pulse data and the arm blood vessel area temperature value, the vital sign status can be judged and vital sign data can be generated, which provides data support for real-time monitoring of the user's health status.

[0014] Preferably, step S144 includes the following steps: Step S1441: extracting the hand pulse frequency from the hand pulse data; when the hand pulse frequency shows abnormal rhythm information, it is determined to be an abnormal rhythm sign state; Step S1442: abnormal temperature recognition is performed on the temperature value of the blood vessel area of ​​the arm to obtain the abnormal temperature of the blood vessel area; when the abnormal temperature of the blood vessel area is continuously high, it is determined to be a high temperature sign state; Step S1443: Integrate the abnormal rhythm sign status and the high temperature sign status to obtain vital sign data.

[0015] The present invention extracts pulse frequency from hand pulse data, can accurately monitor hand pulse frequency, and when abnormal rhythm information is detected, it is determined as an abnormal rhythm sign state, and abnormal conditions of the cardiovascular system are discovered in time; abnormal temperature recognition is performed on the temperature value of the arm blood vessel area, and abnormal temperature in the blood vessel area can be detected, and when continuous high temperature occurs, it is determined as a high temperature sign state, and abnormal vital signs are identified; by integrating the abnormal rhythm sign state and the high temperature sign state, comprehensive vital sign data can be generated, providing key information for medical monitoring, and ensuring the assessment of the user's health status.

[0016] Preferably, step S2 comprises the following steps: Step S21: starting a human sitting posture recognition program to obtain a human sitting posture, wherein the human sitting posture includes a sciatic part shape, a back bending shape, and a muscle tissue deformation shape; Step S22: adjusting the seat sciatic contact angle of the smart seat according to the sciatic part shape to obtain the seat sciatic contact angle value; Step S23: adjusting the curvature of the seat back of the smart seat according to the curvature of the back to obtain the curvature of the seat back; Step S24: adjusting the cushion hardness of the smart seat according to the muscle tissue deformation morphology to obtain cushion hardness parameters; Step S25: storing the optimal sitting posture data of the seat ischium contact angle value, the seat back curvature and the seat cushion hardness parameters to generate the optimal sitting posture memory data.

[0017] By starting a human sitting posture morphology recognition program, the present invention can comprehensively acquire the morphology of the ischial part, the back curvature morphology and the muscle tissue deformation morphology, so as to provide accurate human sitting posture data for personalized adjustment of the intelligent seat; by adjusting the ischial contact angle of the intelligent seat according to the morphology of the ischial part, the contact surface between the seat and the user can be optimized, and the sitting comfort and support effect can be improved; by adjusting the backrest curvature of the intelligent seat according to the back curvature morphology, it can be ensured that the seat back matches the back curve of the user, and the naturalness and comfort of the sitting posture can be enhanced; by adjusting the seat cushion hardness of the intelligent seat according to the muscle tissue deformation morphology, the seat cushion support that adapts to the user's body pressure distribution can be provided, and the discomfort caused by long-term sitting can be reduced; the seat ischial contact angle value, the seat back curvature and the seat cushion hardness parameters are stored as optimal sitting posture morphology data, and the user's optimal sitting posture memory data is generated and saved, so as to facilitate the seat to be quickly adjusted to the user's preferred sitting posture state.

[0018] Preferably, step S21 includes the following steps: Step S211: using a monocular camera to collect images of the back of a human body in the back fitting area, and performing three-dimensional reconstruction of the image of the back of the human body to obtain a three-dimensional structure of the back of the human body; Step S212: measuring the back scoliosis angle of the three-dimensional structure of the human back to generate the back curvature shape; Step S213: identifying the compression shape of the ischial part of the three-dimensional structure of the back of the human body according to the ischial compression strength value; Step S214: using the pressure sensor array to detect the uniformity of regional muscle pressure on the back fitting area to obtain the regional muscle pressure uniformity; Step S215: performing muscle tissue deformation morphology recognition on the three-dimensional structure of the human back according to the regional muscle pressure uniformity.

[0019] The present invention uses a monocular camera to collect images of the back of the human body in the back fitting area, and performs three-dimensional reconstruction of the image of the human body's back to obtain the three-dimensional structure of the human body's back. This step can accurately capture and construct the three-dimensional shape of the human back through the monocular camera combined with the three-dimensional reconstruction technology; this method not only improves the efficiency of data collection, but also due to the application of three-dimensional reconstruction technology, can more accurately reflect the complex structure and details of the human back, and provide an accurate three-dimensional model basis for subsequent analysis and evaluation; the back scoliosis angle of the three-dimensional structure of the human back is measured to generate the back curvature shape; by measuring the scoliosis angle in the three-dimensional structure of the human back, the curvature shape of the back is accurately evaluated; it enables quantitative analysis of the health status of the back, and timely detection of potential spinal problems, such as scoliosis, etc.; according to the sciatic compression strength value, the sciatic compression morphology of the three-dimensional structure of the human back is identified, and by analyzing the sciatic compression strength value, the sciatic compression morphology of the human back is analyzed. The pressure pattern of the sciatic area of ​​the human back can be effectively identified; the impact of long-term sitting on the sciatic area of ​​the human body can be evaluated; the regional muscle pressure uniformity of the back fitting area is detected by using a pressure sensor array to obtain the regional muscle pressure uniformity; the pressure distribution of the back muscles is accurately detected through the pressure sensor array, thereby evaluating the uniformity of muscle pressure; this step is important for identifying areas of muscle tension, preventing muscle strain and pain, and also helps to optimize the back support design and improve comfort; the muscle tissue deformation morphology of the three-dimensional structure of the human back is identified according to the regional muscle pressure uniformity, and the regional muscle pressure uniformity is analyzed, thereby identifying the deformation morphology of the muscle tissue of the human back and clarifying the changes in muscle tissue under different pressures.

[0020] Preferably, step S3 comprises the following steps: Step S31: Preset the sitting posture duration according to the vital sign data. If the vital sign data is in an abnormal rhythmic sign state, the sitting posture duration is set to 30 minutes; if the vital sign data is in a high temperature sign state, the sitting posture duration is set to 20 minutes; Step S32: continuously monitoring the time of the sitting posture pressure-holding state. If the time of the sitting posture pressure-holding state is greater than the preset sitting posture duration time and the vital sign data is in an abnormal rhythmic sign state, low-frequency vibration control is performed on the smart seat and a low-frequency vibration control signal is generated. Step S33: If the time of the sitting posture pressure-holding state is greater than the preset sitting posture duration time, and the vital sign data is a high temperature sign state, high-frequency vibration control is performed on the smart seat, and a high-frequency vibration control signal is generated; Step S34: merging the low-frequency vibration control signal and the high-frequency vibration control signal into a smart seat vibration control signal to obtain a dynamic vibration control signal; and providing a sedentary indicator light reminder according to the dynamic vibration control signal; Step S35: setting the seat idle time according to the vital sign data. If the vital sign data is in an abnormal rhythmic sign state, the seat idle time is set to 15 minutes; if the vital sign data is in a high temperature sign state, the seat idle time is set to 10 minutes; Step S36: continuously monitor the sitting posture pressure value, and when it is monitored that the sitting posture pressure value decreases to zero and lasts until the preset seat idle time, adjust the smart seat to the initial ready-to-sit state.

[0021] The present invention presets the sitting posture duration according to the vital sign data. If the vital sign data is in an abnormal rhythmic sign state, the sitting posture duration is set to 30 minutes; if the vital sign data is in a high temperature sign state, the sitting posture duration is set to 20 minutes; by analyzing the vital sign data, the sitting posture duration can be intelligently adjusted. For users in an abnormal rhythmic sign state, the physical burden caused by frequent changes in sitting posture can be reduced by extending the sitting posture duration; for users in a high temperature sign state, the discomfort caused by overheating can be reduced by shortening the sitting posture duration, thereby improving the user's comfort and health protection. The sitting posture holding pressure state time is continuously monitored. If the sitting posture holding pressure state time is greater than the preset sitting posture duration time, and the vital sign data is in an abnormal rhythmic sign state, the smart seat is subjected to low-frequency vibration control and a low-frequency vibration control signal is generated. This step can monitor the sitting posture holding pressure state and the vital sign data, and can remind the user to change the sitting posture through low-frequency vibration when the user maintains the same sitting posture for a long time, thereby reducing the health risks that may be caused by the abnormal rhythmic sign state, and the generation of the low-frequency vibration control signal provides accurate control instructions for the smart seat. If the time of the sitting posture holding pressure state is greater than the preset sitting posture duration time, and the vital sign data is in the high temperature sign state, the smart seat is subjected to high-frequency vibration control and a high-frequency vibration control signal is generated. This step can quickly remind the user to change the sitting posture when the user is in the high temperature sign state through high-frequency vibration control to reduce the adverse effects of high temperature on the body. At the same time, the generation of high-frequency vibration control signals ensures that the smart seat can respond quickly and execute control commands. The low-frequency vibration control signal and the high-frequency vibration control signal are combined into the smart seat vibration control signal to obtain a dynamic vibration control signal; the sedentary indicator light reminder is performed according to the dynamic vibration control signal, and by combining vibration control signals of different frequencies, the dynamic adjustment of the vibration mode of the smart seat is realized to adapt to different user states and needs; at the same time, the reminder function of the sedentary indicator light provides users with intuitive sedentary warnings, which helps users adjust their sitting posture in time and reduce the health risks caused by sitting for a long time. The seat idle time is set according to the vital signs data. If the vital signs data shows an abnormal rhythmic sign state, the seat idle time is set to 15 minutes; if the vital signs data shows a high temperature sign state, the seat idle time is set to 10 minutes. By setting different seat idle times, the seat idle reminder time can be intelligently adjusted according to the user's vital signs state. For users with abnormal rhythmic sign states, frequent seat adjustments can be reduced by extending the seat idle time; for users with high temperature signs, more frequent user activities can be promoted by shortening the seat idle time, thereby reducing the impact of high temperature on the body.The sitting pressure value is continuously monitored. When the sitting pressure value is detected to be reduced to zero and lasts until the preset seat idle time, the smart seat is adjusted to the initial ready-to-sit state. By monitoring the changes in the sitting pressure value, the seat state can be adjusted in time when the user leaves the seat, reducing unnecessary support for the user who has left the seat, improving the seat's utilization efficiency and energy conservation. At the same time, the adjustment of the initial ready-to-sit state also provides users with convenient preparation for reuse.

[0022] Preferably, step S4 comprises the following steps: Step S41: when it is monitored that the sitting posture pressure value increases from zero to a first threshold, a real-time position fitting detection is performed on the sciatic position information, the back position information and the arm position information to obtain real-time position fitting information; Step S42: evaluating the site alignment matching degree of the real-time site alignment information and the initial site alignment information to obtain a site matching degree value; Step S43: When the site matching degree value is greater than or equal to the preset site matching degree value, the smart seat is adjusted according to the sitting posture memory data so that the smart seat is restored from the initial ready-to-sit state to the optimal sitting posture.

[0023] When the present invention monitors that the sitting pressure value increases from zero to a first threshold value, real-time site fitting detection is performed on the ischial site information, back site information and arm site information to obtain real-time site fitting information; specifically, by starting the site fitting detection when the sitting pressure value reaches a specific threshold value, it can ensure that the fitting state of key sites is captured in the initial stage when the user sits down; the acquisition of such real-time site fitting information provides an accurate data basis for the subsequent site fitting matching degree evaluation, so that the smart seat can respond to the user's sitting posture changes in a timely manner and provide more personalized support. The real-time site fitting information and the initial site fitting information are evaluated for site fitting matching degree to obtain the site matching degree value; by comparing the user's current site fitting state with the initial state, the user's sitting posture change can be quantified to obtain the site matching degree value; the smart seat can accurately identify whether the user's sitting posture deviates from the optimal state set initially, providing an important reference basis for the next step of seat adjustment, ensuring that the user's sitting posture can be optimized in time; when the site matching degree value is greater than or equal to the preset site matching degree value, the smart seat is adjusted according to the sitting posture memory data, so that the smart seat is restored from the initial sitting state to the optimal sitting posture; by setting the threshold of the site matching degree value, the smart seat can automatically adjust according to the sitting posture memory data when the user's sitting posture matches the optimal sitting posture sufficiently. Such a design not only improves the intelligence level of the seat, but also ensures that the user can quickly obtain the best sitting posture support when sitting down, reduces physical discomfort caused by improper sitting posture, and improves the user's long-term sitting experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of the steps of a wearable intelligent vital sign monitoring and control method; Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart; Figure 3 for Figure 1 Detailed implementation steps of step S4 in FIG. The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0026] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0027] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0028] To achieve this, please refer to Figures 1 to 3 , a wearable intelligent vital sign monitoring and control method, the method comprising the following steps: Step S1: continuously monitor the sitting pressure value of the smart seat; when the sitting pressure value is greater than a first threshold, determine that it is in a sitting pressure holding state and obtain initial position fitting information; use the smart vital sign sensor to detect and obtain hand vital sign data; Step S2: starting a human sitting posture recognition program to obtain a human sitting posture; performing adaptive posture adjustment on the smart seat according to the human sitting posture, so that the smart seat matches the human sitting posture, reaches an optimal sitting posture of the smart seat from an initial ready-to-sit state and stores optimal sitting posture memory data; Step S3: if the time of the sitting posture pressure state is greater than the preset sitting posture duration time, a dynamic vibration control signal is generated and a sedentary indicator light is used in response to the dynamic vibration control signal to remind the user of the long-term sitting state; when it is detected that the sitting posture pressure value is reduced to zero and lasts until the preset seat idle time, the smart seat is adjusted to the initial ready-to-sit state; Step S4: When the monitored sitting pressure value increases from zero to the first threshold value, the real-time position fitting information is obtained; when the real-time position fitting information matches the initial position fitting information, the smart seat is adjusted according to the optimal sitting posture memory data, so that the smart seat is restored from the initial ready-to-sitting state to the optimal sitting posture.

[0029] The present invention continuously monitors the sitting pressure value of the smart seat, and when the sitting pressure value is greater than the first threshold, it is determined to be in a sitting pressure holding state and obtains the initial position fitting information. This step can accurately identify whether the user is in a sitting state by real-time monitoring of the sitting pressure value, and determine the start of the sitting posture by the set first threshold, and obtain the initial position fitting information at the same time, providing basic data for subsequent seat adjustment and user sitting posture analysis, ensuring that the smart seat can respond to the user's sitting posture changes in a timely manner. By acquiring the sitting posture of the human body and adaptively adjusting the posture of the smart seat according to the sitting posture of the human body, the smart seat can match the sitting posture of the human body, reach the optimal sitting posture of the smart seat from the initial ready-to-sit state and store the optimal sitting posture memory data. By analyzing the user's sitting posture, the smart seat can automatically adjust to adapt to the user's sitting posture, achieve the transition from the initial state to the optimal sitting posture, and record the optimal sitting posture data; such adaptive adjustment improves the user's comfort and provides support for the user's personalized sitting posture by storing memory data; if the time of the sitting posture pressure-holding state is greater than the preset sitting posture duration, a dynamic vibration control signal is generated and responded to the dynamic vibration control signal to provide a long-sitting indicator light reminder; when it is monitored that the sitting posture pressure value is reduced to zero and continues to the preset seat idle time, the smart seat is restored to the initial ready-to-sit state; by monitoring the duration of the sitting posture pressure-holding state, the user can be reminded through a vibration control signal when the user maintains the same sitting posture for a long time, thereby reducing the health risks caused by long-term sitting. At the same time, when the user leaves the seat, the smart seat can automatically restore to the initial state and prepare for the next use, thereby improving the use efficiency and response speed of the seat; when the sitting pressure value is monitored to increase from zero to the first threshold, the real-time site fitting information is obtained; when the real-time site fitting information matches the initial site fitting information, the smart seat is adjusted according to the optimal sitting posture memory data, so that the smart seat is restored from the initial ready-to-sit state to the optimal sitting posture; by monitoring the change of the sitting pressure value and the matching of the site fitting information, the user's sitting habits can be quickly identified when the user sits down again, and the seat can be adjusted according to the optimal sitting posture memory data to ensure that the user can quickly return to the optimal sitting posture set before, thereby improving the use experience and the intelligence level of the seat. Therefore, the present invention realizes the matching mapping of the vital sign data detected by the wearable intelligent vital sign device with the site fitting information monitored by the intelligent seat through data processing technology, real-time monitoring technology and automatic control technology, and realizes the adaptive posture adjustment of the intelligent seat, thereby improving the degree of automatic adjustment of the intelligent seat.

[0030] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a flow chart of a wearable intelligent vital sign monitoring and control method according to the present invention. In this example, the wearable intelligent vital sign monitoring and control method includes the following steps: Step S1: continuously monitoring the sitting posture pressure value of the smart seat; when the sitting posture pressure value is greater than a first threshold, determining that the sitting posture is in a pressure-holding state and obtaining initial position fitting information; In the embodiment of the present invention, flexible fabric pressure sensors are arranged in the intelligent seat, and these sensors are scientifically distributed in the seat, seat side wings, backrest, backrest side wings and shoulder areas; specifically, the seat is paved with pressure sensors, and multiple pressure sensing points are arranged in an array on the pressure sensor; for example, the thin film pressure sensor includes 8 pressure sensing points, and the level signal of each pressure sensing point constitutes the pressure distribution array point data; the main board is electrically connected to the pressure sensor to obtain the pressure data on multiple pressure sensing points; the main board receives these data and compares them with the data on each pressure point in the correct sitting state, so as to determine whether the user is in an incorrect sitting state. The main board is loaded with a deep learning algorithm, which can effectively identify bad sitting postures; when the pressure value exceeds the preset first threshold, such as setting the preset first threshold to 10kPa; and through the multi-dimensional mechanical feature extraction module based on time series analysis, the mechanical features of human sitting posture and movement changes are extracted from the processed signal, and it is determined to be a sitting posture holding pressure state; at the same time, the intelligent recognition algorithm module is used to judge the state of the person according to the mechanical features, including sitting posture classification, and obtain the initial site fitting information. The millimeter-wave radar sensor transmits a linear frequency-modulated continuous wave signal within the detection area and collects the radar echo reflected from the stationary human chest surface; the received radar echo is then mixed with the transmitted waveform and low-pass filtered, and the original radar data is obtained after analog-to-digital conversion; the original radar data is subjected to a fast Fourier transform, and the static target echo is filtered out using a moving target display algorithm to obtain a vital sign point phase signal containing human breathing and heartbeat movement information; the phase signal is then filtered to obtain the breathing signal waveform and heartbeat signal waveform of the object under test, and then peak search or frequency domain processing is performed on the breathing signal waveform and heartbeat signal waveform to obtain the respiratory rate and heart rate; the breathing signal waveform and heartbeat signal waveform are subjected to time domain and frequency domain data processing to extract vital sign feature information and build a vital sign feature database.

[0031] Step S2: obtaining the sitting posture of the human body and adaptively adjusting the posture of the smart seat according to the sitting posture of the human body, so that the smart seat matches the sitting posture of the human body, reaches the optimal sitting posture of the smart seat from the initial sitting state and stores the optimal sitting posture memory data; In the embodiment of the present invention, a video recognition technology, such as a sitting posture monitoring technology based on a YOLOv5 model, is used to collect images of human sitting postures to obtain sitting posture information of human bodies in different scenes; the YOLOv5 model is used for training and weight model construction to realize intelligent detection and classification recognition of human sitting postures in images; wherein YOLOv5 is a target detection model that can quickly and accurately identify different objects in the picture and has high performance and accuracy. An array pressure sensor is used to collect pressure distribution data between the human-chair contact surface, and the pressure distribution data is specifically used as sample data of different sitting postures, and is input into a convolutional neural network for training to construct a sitting posture recognition model; the real-time collected pressure distribution data between the human-chair contact surface is input into the sitting posture recognition model for iterative calculation to obtain the sitting posture corresponding to the current user; the current sitting posture determined by the sitting posture recognition model is used to generate control information, and the corresponding sitting posture adjustment module composed of an air pump and an air bag is controlled to adjust the sitting posture, thereby achieving adaptive adjustment of the sitting posture. Flexible array pressure sensors are arranged in the smart seat to collect pressure distribution data on the human-chair contact surface; these data are used to construct a multi-dimensional comfort evaluation system by real-time monitoring of the pressure distribution of the contact between the human body and the seat and combining the mechanical properties of the materials to construct a multi-dimensional comfort evaluation system; in the memory position control method and process of the smart seat, the seat cushion force area detection sensor, seat cushion pressure sensor, and backrest pressure sensor on the seat respectively detect the corresponding data; the controller analyzes the approximate optimal seat adjustment position based on height, weight, and the degree of squeezing on the backrest, and automatically adjusts it according to the analysis results. After the adjustment is completed, the optimal sitting posture memory data is stored.

[0032] Step S3: if the time of the sitting posture pressure state is greater than the preset sitting posture duration time, a dynamic vibration control signal is generated and the dynamic vibration control signal is responded to to provide a sedentary indicator light reminder; when it is monitored that the sitting posture pressure value decreases to zero and lasts until the preset seat idle time, the smart seat is restored to the initial ready-to-sit state; In the embodiment of the present invention, a pressure sensor is used to continuously monitor the sitting pressure value. When it is detected that the time of the sitting pressure state exceeds the preset sitting duration, for example, 30 minutes, the time detection circuit on the main board will generate a dynamic vibration control signal; the dynamic vibration control signal is transmitted to the vibration motor through one of the five pins, and the vibration motor generates vibration in response to the signal, which serves as a reminder of sitting for a long time; at the same time, the three prompt lights show different colors as time goes by. The prompt lights are connected through the pins on the main board. As time goes by, they change from green to yellow and finally to red, which reminds the user that he has been sitting for a long time; the pressure sensor continuously monitors the sitting pressure value, and when it is detected that the pressure value is reduced When the idle time reaches zero, that is, the user leaves the seat, the time detection module starts timing, and the preset seat idle time is set to 5 minutes, for example; when the duration reaches the preset value, the controller receives the signal from the time detection module, determines the seat state according to the signal, and sends a command to the motor through the control algorithm to adjust the smart seat to the initial standby state; in the specific implementation, the controller sends commands to the translation motor, longitudinal motor, angle adjustment motor, horizontal locker, longitudinal locker, and backrest locker to adjust them in the order of horizontal, longitudinal and backrest; after the adjustment is completed, the controller sends a command to the central control screen, and the central control screen displays a prompt that the adjustment is successful, confirming that the seat has been adjusted to the initial standby state.

[0033] Step S4: When the monitored sitting pressure value increases from zero to the first threshold value, the real-time position fitting information is obtained; when the real-time position fitting information matches the initial position fitting information, the smart seat is adjusted according to the optimal sitting posture memory data, so that the smart seat is restored from the initial ready-to-sitting state to the optimal sitting posture.

[0034] In the embodiment of the present invention, a pressure sensing pad provided in the seat is used, in which a flexible fabric pressure sensor is embedded, to continuously monitor the sitting pressure value. When the pressure value increases from zero to a first threshold value, such as 10 kPa, the sensor transmits the captured pressure change data to the central processor; the central processor receives the pressure data from the pressure sensing pad and compares it with the preset first threshold value to determine whether the pressure value reaches the threshold value. The central processing unit matches and compares the pressure distribution data collected in real time with the stored initial position fitting information, and completes this by comparing and analyzing the feature vector of the real-time data with the feature vector of the initial data to determine whether the user has returned to the initial sitting position; if the real-time position fitting information matches the initial position fitting information successfully, the central processing unit generates a control signal to adjust the smart seat based on the stored optimal sitting position memory data; the control signal is transmitted to the seat adjustment mechanism through a wired or wireless network interface, and the smart seat includes a motor and a pneumatic system, which realizes the shape adjustment of the seat by controlling the inflation and deflation of the air bag and the automatic adjustment of the motor; the system repeats the above steps at a preset frequency, such as 5 times / second, to ensure that the user maintains a correct sitting position; through the precise control of the air pump and the airbag, the seat angle, backrest angle and other parameters of the smart seat are adjusted to match the user's optimal sitting position; during the adjustment process, the value range and adjustment step of the seat angle and the backrest angle are controlled according to the preset parameters to ensure the comfort and safety of the seat adjustment.

[0035] Preferably, step S1 comprises the following steps: Step S11: monitoring the seat cushion pressure distribution of the seat cushion area of ​​the smart seat to obtain a seat cushion pressure distribution value; monitoring the backrest support pressure of the backrest area of ​​the smart seat to obtain a backrest support pressure distribution value; monitoring the arm placement pressure of the armrest area of ​​the smart seat to obtain an arm placement pressure distribution value; Step S12: Integrate the seat cushion pressure distribution value, the backrest support pressure value and the arm placement pressure value to obtain the sitting posture pressure value; Step S13: when the sitting posture pressure value is greater than the first threshold, it is determined to be a sitting posture pressure holding state and the initial position fitting information is obtained; Step S14: Utilize the intelligent vital sign sensor to detect and acquire vital sign data.

[0036] In the embodiment of the present invention, in the cushion area, the Xseoner LX100 / 210 series pressure sensor is used. The sensor is a flexible fabric, and the sensor array is installed on the fabric. Each small square represents a measuring point with a length and width of 12.7mm, and the pressure range is 0.7-27Kpa. The sensor converts the pressure signal into an electrical signal, filters and quantizes it through the data acquisition system, and finally performs digital signal analysis and processing through the computer, outputs body pressure data, and quantifies and visualizes the pressure distribution; in the backrest area, the Xseoner series pressure sensor is also used, arranged on the backrest surface, for real-time collection of human body pressure distribution signals. The high-precision signal processing module amplifies, filters and digitizes the received human body pressure distribution signal; in the armrest area: a flexible capacitive pressure sensor is installed, including two flexible plates distributed in parallel on the left and right, and a flexible dielectric is arranged between the two plates to monitor the arm placement pressure in real time; the pressure sensor data of the seat cushion, backrest and armrest area are integrated through the data acquisition card and the 32-bit microcontroller, the data acquisition card collects the electrical signals of each sensor, and the microcontroller processes these signals to calculate the sitting pressure value; when the sitting pressure value is greater than the preset first threshold, for example 1.5kPa, the intelligent recognition algorithm module determines the person's state according to the mechanical characteristics, including sitting classification, seat leaving detection and physiological state assessment; if the pressure value exceeds this threshold, the system determines it as a sitting pressure holding state and records the site fitting information at this time; use intelligent vital sign sensors, such as millimeter wave radar sensors or infrared sensors, to detect hand vital sign data. The millimeter-wave radar sensor emits a linear frequency-modulated continuous wave signal and collects the radar echo reflected from the stationary human chest surface. It then performs mixing and low-pass filtering, and obtains the original radar data after analog-to-digital conversion. The infrared sensor monitors the infrared radiation data emitted by the target individual, calculates the body temperature, and outputs the body temperature monitoring results.

[0037] Preferably, step S13 includes the following steps: Step S131: when the sitting posture pressure value is greater than the first threshold, it is determined to be a sitting posture pressure holding state; Step S132: performing ischium pressure detection according to the cushion pressure distribution value to obtain ischium position information; Step S133: judging the back fit degree according to the backrest support pressure distribution value to obtain back position information; Step S134: identifying the arm placement range according to the arm placement pressure distribution value to extract arm position information; Step S135: Merge the sciatic site information, the back site information and the arm site information to obtain initial site fitting information.

[0038] In an embodiment of the present invention, a pressure sensor array is used to monitor the seat cushion pressure distribution of the seat cushion area of ​​the smart seat; specifically, Xseoner LX100 / 210 series pressure sensors are used, which can convert pressure signals into electrical signals, and filter and quantize them through a data acquisition system; when the collected pressure value exceeds a preset first threshold, such as 10kPa, the system automatically determines that the user is in a sitting and pressure-holding state; the pressure data of the ischium area is collected by the pressure sensors arranged on the seat cushion, and the specific position and pressure condition of the ischium are identified by analyzing these data; specifically, the proportion of pressure sensor detection values ​​is calculated and compared with the sitting posture recognition model to obtain the ischium site information. Pressure sensors are arranged in the backrest area of ​​the smart seat to monitor the back support pressure value; by analyzing these data, the system can determine the degree of fit between the back and the seat, such as through the fully automatic fit to the human back smart seat interactive method, the control terminal generates a standard thrust value according to the body weight value and the number of back fitting modules, and controls the movement of the back fitting module until the actual thrust value matches the standard thrust value, thereby obtaining the back position information; flexible capacitive pressure sensors are installed in the armrest area of ​​the smart seat to monitor the arm placement pressure value; by analyzing these data, the range and position of the arm placement are identified; specifically, the arm position information is extracted through vital signs detection technology; the sciatic position information, back position information and arm position information are integrated to form a complete sitting pressure holding state fit position information; through the integration module in the smart seat system, the information of each position is summarized to form the sitting posture information, and a one-to-one mapping relationship is established with the user identity information.

[0039] Preferably, step S135 includes the following steps: Step S1351: extracting the ischium compression strength value from the ischium position information; Step S1352: marking the back fitting area on the back site information to generate the back fitting area; Step S1353: perform arm contact feature detection on the arm position information to obtain arm contact features; perform structural texture recognition on the arm contact features to obtain arm structural texture data.

[0040] In an embodiment of the present invention, a pressure sensor array is used to monitor the sciatic region, such as the Xseoner LX100 / 210 series pressure sensor, and the pressure signal is converted into an electrical signal; filtering and quantization encoding are performed through a data acquisition system, and finally digital signal analysis and processing are performed through a computer to output the sciatic compression strength value; specifically, the sciatic compression strength value is extracted by calculating the electrical signal strength of the pressure sensor in the sciatic region, and the value reflects the pressure distribution in the sciatic region; the hanging action of the human arm is monitored by an infrared sensor monitoring mechanism installed on the seat back plate, and the back support pressure value is collected by the pressure sensor; by analyzing these data, the degree of fit between the back and the seat is determined, and the back fit area is marked in the software; specifically, through the fully automatic fit human back intelligent seat interaction method, the control terminal generates a standard thrust value according to the weight value and the number of back fit modules, and controls the movement of the back fit module until the actual thrust value matches the standard thrust value, thereby generating a back fit area; a flexible capacitive pressure sensor is installed in the armrest area to monitor the arm placement pressure value. By analyzing these data, the system identifies the range and position of the arm placement, thereby obtaining the arm contact characteristics; specifically, the arm position information is extracted through the vital signs detection technology in the smart seat solution; further, computer vision technology is used to perform structural texture recognition on the arm contact characteristics to obtain the arm structural texture data; this process involves identifying 32 points on the human arm, and analyzing the arm posture and structural texture by identifying the position of the points.

[0041] Preferably, step S14 includes the following steps: Step S141: using a temperature sign sensor to obtain hand temperature data; using a pulse sign sensor to obtain hand pulse data; Step S142: analyzing the muscle fiber orientation of the arm structure texture data to obtain the arm muscle fiber orientation; determining the arm blood vessel distribution data according to the arm muscle fiber orientation; and moving the infusion positioning mechanism to the target position according to the arm blood vessel distribution data; Step S143: measuring the arm blood vessel area temperature according to the hand temperature data and the arm blood vessel distribution data to obtain the arm blood vessel area temperature value; Step S144: determine the vital sign status based on the hand pulse data and the arm blood vessel area temperature value to generate vital sign data.

[0042] In the embodiment of the present invention, a non-contact infrared temperature sensor, such as MLX90614, is used. The sensor can measure the temperature of the human body surface, including the temperature of the hand; the sensor calculates the temperature by detecting the infrared radiation emitted by the human body and transmits the data to the microcontroller unit for processing; a photoplethysmogram (PPG) sensor, such as MAX30100, is used. The sensor can measure the pulse by detecting the change in blood volume; the sensor emits light and calculates the pulse rate and heart rate by detecting the change in the intensity of the reflected light. The arm structure texture is analyzed by ultrasonic image technology, and the direction of muscle fibers is identified by ultrasonic image arm artery detection and elasticity analysis technology; the structure of blood vessels and surrounding tissues is displayed by ultrasonic images to determine the distribution of blood vessels in the arm; the ultrasonic image is processed by ultrasonic image analysis software, such as OpenCV, an image processing library based on Python, to identify the contour of the blood vessels and calculate the position and distribution of the blood vessels; according to the arm blood vessel distribution data, the infusion positioning mechanism is moved to the target position; this process is realized by mechanical arm control technology, and the mechanical arm automatically adjusts the position according to the preset blood vessel position data to ensure that the infusion needle is accurately inserted into the blood vessel. The temperature of the arm blood vessel area is calculated through an algorithm by combining the hand temperature data and the arm blood vessel distribution data. For example, the weighted average method is used to calculate the average temperature value of the blood vessel area according to the density of blood vessel distribution and the temperature of different hand areas. The hand pulse data and the arm blood vessel area temperature value are combined with a machine learning algorithm to judge the status of vital signs. Specifically, a decision tree is used to judge the user's cardiovascular health status and generate vital signs data based on changes in pulse frequency, rhythm and blood vessel area temperature.

[0043] Preferably, step S144 includes the following steps: Step S1441: extracting the hand pulse frequency from the hand pulse data; when the hand pulse frequency shows abnormal rhythm information, it is determined to be an abnormal rhythm sign state; Step S1442: abnormal temperature recognition is performed on the temperature value of the blood vessel area of ​​the arm to obtain the abnormal temperature of the blood vessel area; when the abnormal temperature of the blood vessel area is continuously high, it is determined to be a high temperature sign state; Step S1443: Integrate the abnormal rhythm sign status and the high temperature sign status to obtain vital sign data.

[0044] In an embodiment of the present invention, a photoplethysmogram (PPG) sensor, such as MAX30100, is used to collect hand pulse data; the pulse is measured by detecting changes in blood volume, and heart rate and heart rate variability (HRV) data can be provided; the PPG signal is preprocessed, including filtering and denoising, to improve signal quality. A low-pass filter is used to remove high-frequency noise, such as a Butterworth filter, with a cutoff frequency set to 1Hz to reduce noise caused by electromyographic interference, etc.; a fast Fourier transform (FFT) is applied to perform spectrum analysis on the preprocessed PPG signal to extract the pulse frequency. FFT can convert a time domain signal into a frequency domain signal, thereby identifying the frequency component representing the pulse wave; the extracted pulse frequency is detected for abnormal rhythm information, such as by setting a threshold to determine whether the pulse frequency is within the normal range, for example, the normal adult resting heart rate is 60-100 beats / minute, and if it exceeds this range, it is determined to be an abnormal rhythm sign state. A non-contact infrared temperature sensor, such as MLX90614, is used to obtain temperature data of the arm blood vessel area. The sensor can measure the temperature of the human body surface, including the temperature of the arm blood vessel area; identify abnormal temperatures for the collected temperature data, and determine whether persistent high temperature occurs by setting a temperature threshold; for example, the normal body temperature range is set to 36.1°C to 37.2°C, and anything outside this range is considered abnormal; through continuous monitoring and data analysis, determine whether abnormal temperature in the blood vessel area persists. If the results of multiple consecutive measurements are higher than the normal range, it is determined to be a high temperature sign state; integrate the abnormal rhythm sign state and the high temperature sign state to obtain vital sign data; use the decision tree algorithm to classify the integrated data and determine the vital sign state. The decision tree makes classification decisions by constructing a tree model, where each node represents a test of an attribute, each branch represents the result of the test, and the leaf node represents the category decision; through the analysis of the above model, vital sign data containing abnormal rhythm sign states and high temperature sign states are generated.

[0045] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes: Step S21: starting a human sitting posture recognition program to obtain a human sitting posture, wherein the human sitting posture includes a sciatic part shape, a back bending shape, and a muscle tissue deformation shape; Step S22: adjusting the seat sciatic contact angle of the smart seat according to the sciatic part shape to obtain the seat sciatic contact angle value; Step S23: adjusting the curvature of the seat back of the smart seat according to the curvature of the back to obtain the curvature of the seat back; Step S24: adjusting the cushion hardness of the smart seat according to the muscle tissue deformation morphology to obtain cushion hardness parameters; Step S25: storing the optimal sitting posture data of the seat ischium contact angle value, the seat back curvature and the seat cushion hardness parameters to generate the optimal sitting posture memory data.

[0046] In an embodiment of the present invention, a system based on video recognition technology is used, such as the OpenCV library combined with the OpenPose algorithm, to monitor and identify the sitting posture of the human body in real time; the shape of the sciatic part, the shape of the back curvature and the deformation shape of the muscle tissue are captured by computer vision technology, including information such as the position, angle and curve of the body; machine learning technology, such as the decision tree algorithm, is used to analyze the shape data of the sciatic part to determine the optimal value of the sciatic contact angle; the servo motor of the smart seat is controlled to adjust the seat according to the optimal angle value obtained by the algorithm to adapt to the shape of the sciatic part of the user; the sitting posture recognition technology based on the depth image is used to extract the key point angle and depth information of the back curvature shape for analyzing the fit of the back; the curvature of the smart seat backrest is adjusted according to the analysis results to match the back curvature shape of the user to ensure that the back is properly supported; the long short-term memory network (LSTM) is used to calculate the curvature of the backrest of the smart seat; the LSTM image is used to calculate the curvature of the back ... TM) analyzes the time series data of muscle tissue deformation morphology to predict the muscle tissue's demand for cushion softness and hardness; changes the cushion's softness and hardness by adjusting the air pump or mechanical structure in the smart seat to adapt to the user's muscle tissue deformation morphology; adopts a sitting posture data storage method to store the seat bone contact angle value, seat back curvature and cushion softness and hardness parameters in the memory of the smart seat; the memory includes a pre-divided storage pool for storing sitting posture data for a preset number of storage days, each subspace is used to store the sitting posture data of a certain date, including a first data area for storing the sitting posture data at each preset time point every day; through the micro control unit of the smart seat cushion, the sitting posture data is obtained from the pressure sensor, the sitting posture data is detected, and the vibration device is controlled to vibrate when an abnormal sitting posture of the user is detected, and the optimal sitting posture morphology data is stored in the internal flash to generate the optimal sitting posture memory data.

[0047] Preferably, step S21 includes the following steps: Step S211: using a monocular camera to collect images of the back of a human body in the back fitting area, and performing three-dimensional reconstruction of the image of the back of the human body to obtain a three-dimensional structure of the back of the human body; Step S212: measuring the back scoliosis angle of the three-dimensional structure of the human back to generate the back curvature shape; Step S213: identifying the compression shape of the ischial part of the three-dimensional structure of the back of the human body according to the ischial compression strength value; Step S214: using the pressure sensor array to detect the uniformity of regional muscle pressure on the back fitting area to obtain the regional muscle pressure uniformity; Step S215: performing muscle tissue deformation morphology recognition on the three-dimensional structure of the human back according to the regional muscle pressure uniformity.

[0048] In the embodiment of the present invention, a monocular camera is used to collect images by aiming at the fitting area on the back of the human body. Specifically, a camera with a CMOS sensor is used for exposure. The electron-hole pairs generated by light irradiation are separated due to the existence of the PPD electric field, completing the generation and storage of charges. After image acquisition, the OpenCV library is used for image preprocessing, including denoising and enhancement, to improve the accuracy of subsequent three-dimensional reconstruction; the structured light method is applied to project a sinusoidal fringe pattern onto the back of the human body through a projector, and the deformed fringe pattern is captured by the camera. The fringe pattern is demodulated using the phase shift method to obtain depth information; the SIFT algorithm is used to extract feature points and match them, and the camera focal length is calculated using the similar triangle method, and finally three-dimensional reconstruction is achieved. Using deep learning algorithms, such as CNN, the spine in the three-dimensional structure is segmented and detected to determine the terminal vertebrae and apical vertebrae of the spine; according to the Cobb angle measurement method, the upper edge of the vertebral body of the upper terminal vertebra and the lower edge of the vertebral body of the lower terminal vertebra are determined, vertical lines are drawn, and the intersection angle of the two vertical lines, namely the Cobb angle, is calculated to evaluate the curvature of the spine; the pressure data of the sciatic area is collected through a pressure sensor array, the pressure value is combined with the three-dimensional structure data of the human back, and the image matching algorithm is used to identify the pressure shape of the sciatic area; the pressure sensor array is arranged in the back fitting area to collect muscle pressure data, and the regional muscle pressure uniformity is calculated through data analysis; the standard deviation of the pressure value is calculated using a statistical analysis method to evaluate the uniformity of the pressure distribution, and the smaller the specific standard deviation, the more uniform the pressure distribution; the deformation of the muscle under different pressure distributions is identified by combining the regional muscle pressure uniformity data and the three-dimensional structure data of the human back; the dynamic changes of the muscle tissue under different sitting postures are analyzed to identify the deformation shape of the muscle tissue.

[0049] Preferably, step S3 comprises the following steps: Step S31: Preset the sitting posture duration according to the vital sign data. If the vital sign data is in an abnormal rhythmic sign state, the sitting posture duration is set to 30 minutes; if the vital sign data is in a high temperature sign state, the sitting posture duration is set to 20 minutes; Step S32: continuously monitoring the time of the sitting posture pressure-holding state. If the time of the sitting posture pressure-holding state is greater than the preset sitting posture duration time and the vital sign data is in an abnormal rhythmic sign state, low-frequency vibration control is performed on the smart seat and a low-frequency vibration control signal is generated. Step S33: If the time of the sitting posture pressure-holding state is greater than the preset sitting posture duration time, and the vital sign data is a high temperature sign state, high-frequency vibration control is performed on the smart seat, and a high-frequency vibration control signal is generated; Step S34: merging the low-frequency vibration control signal and the high-frequency vibration control signal into a smart seat vibration control signal to obtain a dynamic vibration control signal; and providing a sedentary indicator light reminder according to the dynamic vibration control signal; Step S35: setting the seat idle time according to the vital sign data. If the vital sign data is in an abnormal rhythmic sign state, the seat idle time is set to 15 minutes; if the vital sign data is in a high temperature sign state, the seat idle time is set to 10 minutes; Step S36: continuously monitor the sitting posture pressure value, and when it is monitored that the sitting posture pressure value decreases to zero and lasts until the preset seat idle time, adjust the smart seat to the initial ready-to-sit state.

[0050] In the embodiment of the present invention, the heart rate health detection mechanism 18 and the sitting posture detection mechanism 9 are used to collect vital sign data, and the data is analyzed by the control device to determine whether it is an abnormal rhythm sign state or a high temperature sign state; specifically, if the heart rate health detection mechanism 18 detects an abnormal heart rate, such as a heart rate exceeding 100 times / minute, the sitting posture duration is set to 30 minutes through the control device; if the body temperature is detected to be too high, such as exceeding 37.5°C, the sitting posture duration is set to 20 minutes; the pressure sensor array is used to continuously monitor the time of the sitting pressure holding state. If the monitored time exceeds the preset sitting posture duration, and the vital sign data is in an abnormal rhythmic sign state, the control device starts low-frequency vibration control; specifically, the control device adjusts the frequency of the vibration motor to 5Hz to generate a low-frequency vibration control signal; if the sitting posture holding pressure state time exceeds the preset sitting posture duration, and the vital sign data is in a high temperature sign state, the control device adjusts the frequency of the vibration motor to 20Hz to generate a high-frequency vibration control signal to remind the user to change the sitting posture or take a rest; the control device combines the low-frequency and high-frequency vibration control signals to form a dynamic vibration control signal. According to the dynamic vibration control signal, the vibration motor at the bottom of the seat is controlled to vibrate accordingly, and the long-sitting indicator light is activated to remind the user, such as by flashing the LED light at the bottom of the seat body to remind the user; the control device sets the seat idle time according to the latest vital sign data, such as heart rate and body temperature. If the vital sign data is in an abnormal rhythmic sign state, the seat idle time is set to 15 minutes; if it is in a high temperature sign state, it is set to 10 minutes; a pressure sensor array is used to continuously monitor the sitting pressure value, and when the sitting pressure value is detected to be reduced to zero and lasts until the preset seat idle time, the control device sends a signal to the seat adjustment motor to adjust the smart seat to the initial ready-to-sit state; in specific implementation, the control device uses the electric seat memory function to automatically move the seat to a preset initial position, such as a "zero gravity" position.

[0051] As an example of the present invention, refer to Figure 3 As shown, in this example, step S4 includes: Step S41: when it is monitored that the sitting posture pressure value increases from zero to a first threshold, a real-time position fitting detection is performed on the sciatic position information, the back position information and the arm position information to obtain real-time position fitting information; Step S42: evaluating the site alignment matching degree of the real-time site alignment information and the initial site alignment information to obtain a site matching degree value; Step S43: When the site matching degree value is greater than or equal to the preset site matching degree value, the smart seat is adjusted according to the sitting posture memory data so that the smart seat is restored from the initial ready-to-sit state to the optimal sitting posture.

[0052] In an embodiment of the present invention, a pressure sensor array is used to monitor the sciatic site information, back site information and arm site information in real time; for example, the pressure sensors are controlled by an Arduino single-chip microcomputer to collect data, and these sensors are arranged in the sciatic support area, back support area and armrest area of ​​the smart seat. The data is read by an analog / digital converter (ADC) and then transmitted to a microcontroller unit through serial communication. The microcontroller unit uses embedded software to analyze the pressure value to determine the user's real-time site fit information. The real-time site fit information is compared with the initial site fit information stored in the microcontroller unit, which is collected and saved when the user first adjusts to the optimal sitting posture; a pattern recognition algorithm, such as a support vector machine (SVM), is used to evaluate the matching degree of the real-time site fit information and the initial site fit information, and the evaluation result is a site matching degree value, which indicates the matching degree between the current sitting posture and the optimal sitting posture. If the site matching degree value is greater than or equal to the preset site matching degree value, for example, the threshold is set to 0.8, the smart seat will automatically adjust according to the sitting posture memory data; using the electric seat memory function, the microcontroller unit sends instructions to the seat's electric adjustment motors, which control the seat's ischium contact angle, backrest curvature and cushion hardness; through the fully automatic human back-fitting smart seat interaction method, the control terminal automatically matches the corresponding sitting posture information according to the user's identity information, and the sitting posture information controls the movement of the back fitting module to quickly adjust the seat to the optimal sitting posture.

[0053] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0054] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A wearable intelligent vital sign monitoring and control method, characterized in that: Applied to a medical smart chair, the smart chair is provided with a hand-wearable device, the hand-wearable positioning device is provided with an intelligent vital sign sensor and an infusion positioning mechanism, and the wearable-based intelligent vital sign monitoring and control method comprises the following steps: Step S1: continuously monitoring the sitting posture pressure value of the smart seat; when the sitting posture pressure value is greater than a first threshold, determining that the sitting posture is in a pressure-holding state and obtaining initial position fitting information; Step S2: obtaining the sitting posture of the human body and adaptively adjusting the posture of the smart seat according to the sitting posture of the human body, so that the smart seat matches the sitting posture of the human body, and reaches the optimal sitting posture of the smart seat from the initial sitting state, and stores the optimal sitting posture memory data; Step S3: if the time of the sitting posture pressure state is greater than the preset sitting posture duration time, a dynamic vibration control signal is generated and the dynamic vibration control signal is responded to to provide a sedentary indicator light reminder; when it is monitored that the sitting posture pressure value decreases to zero and lasts until the preset seat idle time, the smart seat is restored to the initial ready-to-sit state; Step S4: When the monitored sitting pressure value increases from zero to the first threshold value, the real-time position fitting information is obtained; when the real-time position fitting information matches the initial position fitting information, the smart seat is adjusted according to the optimal sitting posture memory data, so that the smart seat is restored from the initial ready-to-sitting state to the optimal sitting posture.

2. The wearable intelligent vital sign monitoring and control method according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: monitoring the seat cushion pressure distribution of the seat cushion area of ​​the smart seat to obtain a seat cushion pressure distribution value; monitoring the backrest support pressure of the backrest area of ​​the smart seat to obtain a backrest support pressure distribution value; monitoring the arm placement pressure of the armrest area of ​​the smart seat to obtain an arm placement pressure distribution value; Step S12: Integrate the seat cushion pressure distribution value, the backrest support pressure value and the arm placement pressure value to obtain the sitting posture pressure value; Step S13: when the sitting posture pressure value is greater than the first threshold, it is determined to be a sitting posture pressure holding state and the initial position fitting information is obtained; Step S14: Utilize the intelligent vital sign sensor to detect and acquire vital sign data.

3. The wearable intelligent vital sign monitoring and control method according to claim 2 is characterized in that: Step S13 includes the following steps: Step S131: when the sitting posture pressure value is greater than the first threshold, it is determined to be a sitting posture pressure holding state; Step S132: performing ischium pressure detection according to the cushion pressure distribution value to obtain ischium position information; Step S133: judging the back fit degree according to the backrest support pressure distribution value to obtain back position information; Step S134: identifying the arm placement range according to the arm placement pressure distribution value to extract arm position information; Step S135: Merge the sciatic site information, the back site information and the arm site information to obtain initial site fitting information.

4. The wearable intelligent vital sign monitoring and control method according to claim 3 is characterized in that: Step S135 includes the following steps: Step S1351: extracting the ischium compression strength value from the ischium position information; Step S1352: marking the back fitting area on the back site information to generate the back fitting area; Step S1353: Perform arm contact feature detection on the arm position information to obtain arm contact features; perform structural texture recognition on the arm contact features to obtain arm structural texture data.

5. The wearable intelligent vital sign monitoring and control method according to claim 4 is characterized in that: The intelligent vital sign sensor includes a temperature vital sign sensor and a pulse vital sign sensor, wherein step S14 includes the following steps: Step S141: using a temperature sign sensor to obtain hand temperature data; using a pulse sign sensor to obtain hand pulse data; Step S142: analyzing the muscle fiber orientation of the arm structure texture data to obtain the arm muscle fiber orientation; determining the arm blood vessel distribution data according to the arm muscle fiber orientation; and moving the infusion positioning mechanism to the target position according to the arm blood vessel distribution data; Step S143: measuring the arm blood vessel area temperature according to the hand temperature data and the arm blood vessel distribution data to obtain the arm blood vessel area temperature value; Step S144: determine the vital sign status based on the hand pulse data and the arm blood vessel area temperature value to generate vital sign data.

6. The wearable intelligent vital sign monitoring and control method according to claim 5 is characterized in that: Step S144 includes the following steps: Step S1441: extracting the hand pulse frequency from the hand pulse data; when the hand pulse frequency shows abnormal rhythm information, it is determined to be an abnormal rhythm sign state; Step S1442: abnormal temperature recognition is performed on the temperature value of the blood vessel area of ​​the arm to obtain the abnormal temperature of the blood vessel area; when the abnormal temperature of the blood vessel area is continuously high, it is determined to be a high temperature sign state; Step S1443: Integrate the abnormal rhythm sign status and the high temperature sign status to obtain vital sign data.

7. The wearable intelligent vital sign monitoring and control method according to claim 6 is characterized in that: Step S3 includes the following steps: Step S31: Preset the sitting posture duration according to the vital sign data. If the vital sign data is in an abnormal rhythmic sign state, the sitting posture duration is set to 30 minutes; if the vital sign data is in a high temperature sign state, the sitting posture duration is set to 20 minutes; Step S32: Continuously monitor the time of the sitting pressure-holding state. If the time of the sitting pressure-holding state is greater than the preset sitting duration time and the vital sign data is in an abnormal rhythm sign state, the smart seat is subjected to low-frequency vibration control and a low-frequency vibration control signal is generated.

8. The wearable intelligent vital sign monitoring and control method according to claim 7 is characterized in that: Step S3 also includes the following steps: Step S33: If the time of the sitting posture pressure-holding state is greater than the preset sitting posture duration time, and the vital sign data is a high temperature sign state, high-frequency vibration control is performed on the smart seat, and a high-frequency vibration control signal is generated; Step S34: merging the low-frequency vibration control signal and the high-frequency vibration control signal into a smart seat vibration control signal to obtain a dynamic vibration control signal; and providing a sedentary indicator light reminder according to the dynamic vibration control signal; Step S35: setting the seat idle time according to the vital sign data. If the vital sign data is in an abnormal rhythmic sign state, the seat idle time is set to 15 minutes; if the vital sign data is in a high temperature sign state, the seat idle time is set to 10 minutes; Step S36: continuously monitor the sitting posture pressure value, and when it is monitored that the sitting posture pressure value decreases to zero and lasts until the preset seat idle time, adjust the smart seat to the initial ready-to-sit state.

9. The wearable intelligent vital sign monitoring and control method according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: when it is monitored that the sitting posture pressure value increases from zero to a first threshold, a real-time position fitting detection is performed on the sciatic position information, the back position information and the arm position information to obtain real-time position fitting information; Step S42: evaluating the site alignment matching degree of the real-time site alignment information and the initial site alignment information to obtain a site matching degree value; Step S43: When the site matching degree value is greater than or equal to the preset site matching degree value, the smart seat is adjusted according to the sitting posture memory data so that the smart seat is restored from the initial ready-to-sit state to the optimal sitting posture.

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