Health data detection method and device based on intelligent wearable device, equipment and medium

Abstract

The invention relates to the technical field of medical science and technology and data processing, and discloses a health data detection method, device and equipment based on intelligent wearable equipment and a medium, and the method comprises the steps: monitoring and obtaining vital sign data collected by a vital sign sensor within a preset time period in real time; obtaining preset health items, and extracting current health item data corresponding to the health items in the vital sign data; determining standard health item data and deteriorated health item data of the health items; analyzing the coincidence rate of the current health item data in the standard health item data or the worsening health item data, and obtaining a health item state result corresponding to the current health item data; and feeding back a health item state result and an analysis process of the health item state result. According to the invention, aiming at intelligent medical monitoring entities under medical science and technology and the like, the wearable device not only pays attention to rapid presentation of results, but also emphasizes recording of data in a data generation process, and the effects of accurately collecting, sorting and feeding back individual health item data are optimized.

Description

Technical Field

[0001] The present invention relates to the fields of medical technology and data processing technology, and in particular to a health data detection method, device, equipment and medium based on a smart wearable device. Background Art

[0002] Current wearable devices may still have some technical bottlenecks in hardware and software, which makes them unable to record and analyze all health data in real time and accurately. Especially for some complex and changeable physiological processes, such as changes in sleep cycles, the device may not be able to capture all the details and only provide the final results of the health items in the test, such as the results of a person's sleep quality and the results of a person's effective sleep duration, etc., without recording the specific process data in the result. Moreover, the original intention of the design of some wearable devices may be to provide convenient and instant health information rather than to conduct in-depth health data analysis. Therefore, in terms of functional design, they may pay more attention to the rapid presentation of results and ignore the recording of process data. Summary of the invention

[0003] The present invention provides a health data detection method, device, computer equipment and medium based on a smart wearable device to solve the technical problem that wearable devices in the prior art pay more attention to the rapid presentation of results but ignore the recording of process data.

[0004] In a first aspect, a health data detection method based on a smart wearable device is provided, comprising:

[0005] Real-time monitoring and acquisition of life feature data collected by life feature sensors within a preset time period;

[0006] Obtain preset health items and extract current health item data corresponding to the health items in the vital characteristics data;

[0007] Determine standard health item data and deteriorated health item data of health items;

[0008] Analyze the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data;

[0009] Feedback of health item status results and analysis process of health item status results.

[0010] In a second aspect, a health data detection device based on a smart wearable device is provided, comprising:

[0011] A collection module, used to monitor in real time and obtain life feature data collected by the life feature sensor within a preset time period;

[0012] An extraction module, used to obtain preset health items and extract current health item data corresponding to the health items in the vital characteristics data;

[0013] A determination module, used for determining standard health item data and deteriorated health item data of a health item;

[0014] An analysis module, used to analyze the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data;

[0015] The feedback module is used to feed back the health item status results and the analysis process of the health item status results.

[0016] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned health data detection method based on a smart wearable device when executing the computer program.

[0017] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned health data detection method based on a smart wearable device are implemented.

[0018] In the scheme implemented by the above-mentioned health data detection method, device, computer equipment and storage medium based on smart wearable devices, it is possible to monitor in real time and obtain the life feature data collected by the life feature sensor within a preset time period; obtain the preset health items, extract the current health item data corresponding to the health items in the life feature data; determine the standard health item data and the deteriorated health item data of the health items; analyze the overlap rate of the current health item data in the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data; feedback the health item status result and the analysis process of the health item status result. In the present invention, for the intelligent medical monitoring entities under medical technology, the wearable device is optimized to focus on the rapid presentation of results and emphasize the recording of data generation process data, optimize and improve health data, and accurately collect, organize and feedback the effect of individual health item data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0020] Figure 1is a schematic diagram of an application environment of a health data detection method based on a smart wearable device in one embodiment of the present invention;

[0021] Figure 2 is a flow chart of a health data detection method based on a smart wearable device in one embodiment of the present invention;

[0022] Figure 3 is a structural schematic diagram of a health data detection device based on a smart wearable device in one embodiment of the present invention;

[0023] Figure 4 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0024] Figure 5 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] The health data detection method based on the smart wearable device provided in the embodiment of the present invention can be applied in the following aspects: Figure 1 In the application environment, the client communicates with the server through the network. The server can monitor and obtain the life feature data collected by the life feature sensor within a preset time period in real time through the client; obtain the preset health item, extract the current health item data corresponding to the health item in the life feature data; determine the standard health item data and the deteriorated health item data of the health item; analyze the overlap rate of the current health item data in the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data; feedback the health item status result and the analysis process of the health item status result. In the present invention, for the intelligent medical monitoring entity under medical technology, the wearable device is optimized to focus on the rapid presentation of results, emphasize the recording of data generation process data, optimize and improve health data, accurately collect, organize and feedback the effect of individual health item data, wherein the client can be but not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server can be implemented with an independent server or a server cluster composed of multiple servers. The present invention is described in detail below through specific embodiments.

[0027] See also Figure 2 As shown, Figure 2A flow chart of a health data detection method based on a smart wearable device provided in an embodiment of the present invention includes the following steps:

[0028] S10: real-time monitoring and acquisition of life feature data collected by the life feature sensor within a preset time period;

[0029] The health data detection method based on smart wearable devices provided by the present invention can be applied to life feature detection in various application scenarios. Life feature detection is usually collected through life feature sensors in smart wearable devices, and life feature sensors collect life feature data. For example, in the field of medical technology applications, wearers usually monitor life feature data in real time through smart wearable devices. Of course, the health data detection method based on smart wearable devices is also applicable to financial scenarios and medical scenarios.

[0030] Vital sign sensors can continuously and accurately collect key vital signs including heart rate, blood pressure, body temperature, respiratory rate, etc., monitor these data in real time, and obtain and analyze them within a preset time period. Vital sign sensors are usually installed on wearable devices (such as smart watches and smart bracelets), and monitor heart rate and blood oxygen saturation through optical sensors on wearable devices (such as smart watches and smart bracelets), or monitor electrocardiograms through tiny electrodes attached to the skin. Usually, communication sensors transmit the collected data to smartphones, tablets or cloud servers in real time through wireless communication technologies such as Bluetooth and Wi-Fi, ensuring the immediacy and availability of data, so that medical staff or the wearer can view and analyze data anytime and anywhere. Of course, the supporting software platform (such as health APP, remote monitoring system) can receive, store and display the data from the vital sign sensor. The software platform has a user interface, which is convenient for the wearer to view his or her health trends and set alarm prompts to remind in time when the collected vital sign data is abnormal.

[0031] Wearers or medical staff can set the start and end time of monitoring on the software platform according to actual needs, that is, the preset time period. The preset time period can be a few minutes, a few hours, or even a few days or weeks, depending on the specific monitoring needs and purposes. Within the preset time period, the software platform will automatically filter and extract the vital signs data within the preset time period. Vital signs data are usually presented in the form of charts, curves or reports, which makes it easy for wearers or medical staff to intuitively understand the health status of individuals. The software platform can also perform in-depth analysis of the collected data, such as heart rate variability analysis, sleep quality assessment, etc. The analysis results can help the wearer better understand their health status and provide valuable diagnostic basis for medical staff.

[0032] Life sign sensors are devices used to detect human physiological indicators, which can reflect the life state and health of the human body. Life sign sensors include at least: temperature sensors, heart rate sensors, blood oxygen sensors, blood pressure sensors, breathing sensors, skin contact sensors, etc.

[0033] Temperature sensor is used to measure human body temperature, which is an important basis for evaluating whether there is a fever and the degree of fever. Blood oxygen sensor: It measures blood oxygenation through infrared and photoelectric technology to reflect the oxygen supply of the human body. Blood pressure sensor: It is used to measure blood pressure and evaluate the functional status of the cardiovascular system. Respiration sensor: It monitors the breathing rate and depth of breathing to reflect the respiratory function of the human body.

[0034] Heart rate sensors include ECG sensors and photoplethysmography (PPG) sensors. ECG sensors calculate heart rate and rhythm by monitoring the electrical activity of the heart; photoplethysmography (PPG) sensors use the principle of light reflection to detect the contraction and expansion of capillaries caused by heartbeats.

[0035] Skin contact sensors are based on physical contact and electrical signal conduction between the skin and the sensor. When the sensor contacts the skin, it detects small changes on the skin, such as temperature, humidity, conductivity, pressure, etc., and converts these changes into electrical signals for transmission and processing. For example: Electrocardiogram (ECG) sensors monitor the electrical activity of the heart and record ECG waveforms to assess the health of the heart pulse. Electrodes attached to the skin detect the electrical signals generated when the heart beats. These signals are amplified and filtered to form ECG waveforms. Photoplethysmography (PPG) sensors monitor heart rate and blood oxygen saturation. They use the principle of light reflection to detect the contraction and expansion of capillaries caused by the heartbeat. They measure heart rate and blood oxygen levels by emitting light to the skin and detecting changes in the intensity of the reflected light. Skin electrical sensors detect changes in the conductivity of the skin and are usually used to assess emotional changes, psychological reactions, etc. Based on the detection and measurement of skin electrical activity, when the body is stimulated by external stimuli, the skin electrical activity changes. Skin electrical sensors assess emotional states by measuring such changes.

[0036] After step S10, the method further includes: when the real-time monitoring fails to obtain the life sign data collected by the life sign sensor, detecting the connection status and current performance of the life sign sensor, and outputting an abnormal prompt. The life sign sensor collects life sign data for real-time monitoring. When the system fails to receive the data within the specified time, the abnormal detection process will be immediately triggered: first, if it is a problem with the connection status of the life sign sensor, the system will first check the physical connection between the sensor and the monitoring system, such as whether the cable is plugged in, whether the interface is loose, etc.; for wireless sensors, the system will check whether the wireless signal is stable and whether the connection is interrupted; if a connection problem is found, the system will output a prompt of "sensor connection abnormality". When the sensor connection abnormality is detected, the system will output a prompt of "sensor connection abnormality, please check the connection". Secondly, if it is a problem with the performance of the life sign sensor, then check whether the power supply of the life sign sensor is sufficient, whether the life sign sensor is in normal working state, etc. The system may try to send a test signal to the life sign sensor and wait for its response to determine whether the life sign sensor can work normally. When the sensor performance is detected to be abnormal, the system will output a prompt of "sensor performance abnormality, please check the sensor status". Among them, abnormal prompts can be output through the monitoring system's interface display, sound alarm, etc. For important abnormal prompts, the system can also send text messages, emails, etc. to notify the wearer.

[0037] Life characteristic data refers to various physiological indicators exhibited by organisms during life activities. These indicators can reflect the health status, physiological state and adaptability of organisms to the external environment. In this embodiment, it mainly includes heart rate, blood pressure, respiratory rate and body temperature. Heart rate refers to the number of heart beats per minute, which is an important indicator reflecting heart function. The heart rate range of normal adults is generally between 60 and 100 times / minute. Changes in heart rate can reflect the body's stress response and heart function status. Blood pressure refers to the pressure exerted on the blood vessel wall when blood flows in the blood vessels. It is a key indicator for assessing the health status of the cardiovascular system. The blood pressure of normal adults is usually maintained below 120 mmHg for systolic pressure and below 80 mmHg for diastolic pressure. Hypertension or hypotension may indicate health problems. Respiratory rate refers to the number of breaths per minute, which is an important indicator reflecting the function of the respiratory system. The normal respiratory rate of adults is about 12 to 20 times / minute. Abnormal respiratory rate may be related to respiratory diseases or problems in other parts of the body. Body temperature refers to the internal temperature of an organism and is an important indicator of metabolic and immune status. The normal body temperature of an adult is generally between 36 and 37 degrees Celsius. Abnormal body temperature may indicate infection, inflammation or other health problems.

[0038] S20: Obtaining a preset health item, and extracting current health item data corresponding to the health item in the vital characteristic data;

[0039] The preset health items are mainly preset by the wearer through the system's user interface (UI) or mobile application, based on personal health needs or doctor's advice. The preset health items include at least heart rate, blood pressure, blood oxygen saturation, body temperature, and sleep quality. When the wearer is a new user or a user who has not made personalized settings, the system will preset a set of basic health items based on general health monitoring standards. Basic health items usually cover the basic vital signs of the human body to ensure the comprehensiveness of basic health monitoring.

[0040] The current health item data is the health item data collected within the current preset time period.

[0041] S30: determining standard health item data and deteriorated health item data of the health item;

[0042] Specifically, the standard health item data is the normal value specified in the vital characteristics data, for example, the heart rate range of a normal adult is generally 60 to 100 times / minute, the blood pressure of a normal adult is usually maintained below 120 mmHg for systolic pressure and below 80 mmHg for diastolic pressure, the normal respiratory rate of an adult is approximately 12 to 20 times / minute, and the body temperature of a normal adult is generally between 36 and 37 degrees Celsius. The deteriorated health item data is data beyond the standard health item data, and the deteriorated health item data is unhealthy data, which means that the wearer's body function has problems, for example, the abnormal heart rate range of an adult is lower than 60 times / minute or higher than 100 times / minute, the abnormal blood pressure of an adult is above 120 mmHg for systolic pressure and above 80 mmHg for diastolic pressure, the abnormal respiratory rate of an adult is approximately below 12 times / minute or above 20 times / minute, and the abnormal body temperature of an adult is below 36 degrees Celsius or above 37 degrees Celsius.

[0043] Of course, some wearers have special physiques, and their life characteristics data may not be applicable to the standard health data of normal adults, because it is necessary to customize the standard health data. By obtaining the historical cases of the data tester and the prescribed health data of the health items in the data tester's location; adjusting the prescribed health data according to the historical cases of the data tester, and determining the customized standard health data and customized deterioration health data of the data tester's health items according to the adjustment results. Of course, determine the reasonable value of each health item, based on large model data evaluation of different countries and regions, obtain different types of reasonable value data of human health items, which are used for value evaluation under different conditions, use different health items to judge the left and right values, and establish a health item benchmark library under each person's unique characteristics.

[0044] S40: analyzing the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtaining the health item status result corresponding to the current health item data;

[0045] According to the range or threshold of the standard health item data and the deteriorated health item data, analyze whether the current health item data is within the range or threshold of the standard health item data and the deteriorated health item data, and judge whether the current health item data is within the normal range, or whether it exceeds the normal range or reaches the deterioration standard. A high overlap rate (close to 100%) indicates that the wearer's health status is highly consistent with the standard or deteriorated state. If the overlap rate with the standard data is high, it indicates that the wearer is in good health; if the overlap rate with the deteriorated data is high, it indicates that there is a problem with the wearer's health status. A low overlap rate (far below 100%) indicates that the wearer's health status is different from the standard or deteriorated state, and further medical evaluation or intervention is required. According to the analysis results of the overlap rate, personalized health management suggestions can be provided to the wearer. For example, for wearers with a high overlap rate with the standard data, they can be advised to continue to maintain a healthy lifestyle; for wearers with a high overlap rate with the deteriorated data, they need to be reminded to pay attention to their health status and may need to take medical measures. When analyzing the overlap rate, the impact of wearer differences on the results should be considered. There are differences in health status and physiological characteristics between different wearers, so the analysis results vary from person to person.

[0046] After step S40, the method further includes: obtaining a health item status solution based on the analysis of the health item status result; feeding back the health item status result, the health item status solution, and the analysis process of the health item status result. Associating the health item status result with the health item status solution; when a trigger signal of the health item status result is detected, displaying the health item status solution. When a preset health item start signal is detected, displaying the health item status result and the analysis process of the health item status result; when a preset health item shutdown signal is detected, monitoring the preset health item start signal in real time, and storing the health item status result and the analysis process of the health item status result.

[0047] It should be noted that the health status solution sets specific health goals based on personal health conditions and needs, such as lowering blood pressure, controlling blood sugar, gaining or losing weight, etc. Develop a detailed health plan to achieve health goals, including adjustments in diet, exercise, sleep management and mental health, regular physical examinations and monitoring, risk management and prevention, etc.

[0048] Diet adjustment: through balanced diet, ensure that the diet contains enough vegetables, fruits, whole grains and high-quality protein, reduce the intake of greasy, high-sugar and high-salt foods. Maintain regular and quantitative eating habits and avoid overeating, which helps to maintain the stability of blood sugar and body weight. Ensure sufficient water intake every day to promote metabolism and waste discharge.

[0049] Exercise is done by choosing appropriate sports, such as walking, running, swimming, yoga, etc., according to personal physique and preferences. Then maintain regular exercise, such as at least 150 minutes of moderate-intensity aerobic exercise or 75 minutes of high-intensity aerobic exercise per week, and adding strength training to improve muscle strength and endurance. It is also necessary to regularly record exercise conditions, including exercise type, time and intensity, so as to adjust the exercise plan in time.

[0050] Sleep management ensures that you get enough sleep every day. For example, adults generally need 7-9 hours of sleep. Maintaining good sleeping habits, keeping a regular schedule, and creating a quiet and comfortable sleeping environment can help improve sleep quality. Avoiding sleep quality disturbances, such as using electronic devices and drinking caffeinated beverages before going to bed, may affect sleep.

[0051] Mental health By learning to regulate your emotions and stress, you can relax yourself through meditation, deep breathing, and communicating with friends and family. Maintaining a positive attitude and being full of enthusiasm and hope for life will help improve your overall health. Seek professional mental health support when needed, such as psychological counseling or therapy.

[0052] Regular physical examination and monitoring Choose appropriate physical examination items according to your age, gender, medical history and other factors, and have regular physical examinations to understand your health status. Record physiological indicators such as weight, blood pressure, blood sugar, as well as daily exercise, diet and sleep conditions to detect potential health problems in a timely manner.

[0053] Risk Management and Prevention Learn how to prevent common diseases, such as washing hands frequently, wearing masks, and getting vaccinated. When facing health problems, consult doctors or professionals in a timely manner. Develop emergency response plans, such as responding to health risks such as sudden outbreaks.

[0054] After the health item is turned on, the improved and optimized device is ready to start executing its own tasks. During the execution of the task, it monitors and obtains health item information in real time and generates corresponding health item data. When the connection information it sets cannot be obtained, it can prompt the user with reasonable reminders. For example, if the user is far away and data cannot be obtained normally, the user receives the prompt information. We can optimize the operation according to the prompt information. After continuous operation without problems, we can perform subsequent data acquisition.

[0055] Users can choose different health check items at any time and in different environments according to their needs, and determine which health items they are mainly concerned about. Users only need to turn on the health check items they need to pay attention to. After turning on, users can see their historical data at any time. When the check results are completed, they can also turn off the health check items, achieving out-of-the-box capability.

[0056] S50: Feedback of health item status results and analysis process of the health item status results.

[0057] Based on the current health data and the currently acquired health status results, the collated data will be promptly fed back to the wearer in the form of a report. The report should include the measurement results of various health indicators and their corresponding normal ranges or reference values, so that the wearer can better understand their health status and identify and prevent health items that do not meet the requirements. Based on the measurement results, the current health status is explained, and existing problems or potential risks are pointed out. Personalized health suggestions are provided, such as adjusting diet, increasing exercise, improving sleep, etc., to help individuals improve their health.

[0058] By presetting the health management terminal, upload the health item status results and the analysis process of the health item status results to the health management terminal, and the health management terminal verifies the correctness of the health item status results and the analysis process of the health item status results; obtains the inspection results of the health management terminal and displays feedback. The obtained health item status results can also be authorized to their own health managers based on personal permissions. They can give themselves advice in turn based on the above data, so as to continuously improve their own health. The health management terminal mainly refers to the health management software platform or the health manager terminal.

[0059] The present invention will address the wearer's shortcomings in health detection. When the wearer puts on the device, after turning on the detection function, the wearer can set the specific items he wants to check. For example, if the process information of sleep talking is turned on, it will record the time when the trigger starts, the duration of the trigger, and the trigger cycle, etc.; if the process information of heart rate is turned on, the average rate at the minute level will be recorded. After turning it on, it will record the entire process based on the user's health status. The specific process information can be set according to the user's settings, and the saved time range can be set. Through the recorded data within this time range, a health report description of the user can be given.

[0060] It can be seen that in the above scheme, for the intelligent medical monitoring entity under medical technology, firstly, the life feature data collected by the life feature sensor within the preset time period is obtained through real-time monitoring; the preset health items are obtained, and the current health item data corresponding to the health items in the life feature data are extracted; the standard health item data and the deteriorated health item data of the health items are determined; the overlap rate of the current health item data in the standard health item data or the deteriorated health item data is analyzed, and the health item status result corresponding to the current health item data is obtained; the health item status result and the analysis process of the health item status result are fed back. The present invention optimizes the wearable device, which not only pays attention to the rapid presentation of results, but also emphasizes the recording of data in the data generation process, optimizes and improves health data, and accurately collects, organizes and feeds back individual health item data.

[0061] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0062] In one embodiment, a health data detection device based on a smart wearable device is provided, and the health data detection device based on a smart wearable device corresponds one-to-one to the health data detection method based on a smart wearable device in the above embodiment. Figure 3 As shown, the health data detection device based on the smart wearable device includes a collection module 101, an extraction module 102, a determination module 103, an analysis module 104, and a feedback module 105. The detailed description of each functional module is as follows:

[0063] The collection module 101 is used to monitor in real time and obtain the life feature data collected by the life feature sensor within a preset time period;

[0064] An extraction module 102 is used to obtain a preset health item and extract current health item data corresponding to the health item in the vital characteristic data;

[0065] A determination module 103, used to determine standard health item data and deteriorated health item data of a health item;

[0066] The analysis module 104 is used to analyze the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data;

[0067] The feedback module 105 is used to feed back the health item status results and the analysis process of the health item status results.

[0068] In one embodiment, the apparatus further comprises:

[0069] The signal detection module is used to display the health item status result and the analysis process of the health item status result when a preset health item start signal is detected; when a preset health item shutdown signal is detected, the preset health item start signal is monitored in real time, and the health item status result and the analysis process of the health item status result are stored.

[0070] In one embodiment, the apparatus further comprises:

[0071] A solution analysis module is used to obtain a health item status solution based on the health item status result analysis;

[0072] The solution feedback module is used to feedback the health item status results, health item status solutions and the analysis process of the health item status results.

[0073] In one embodiment, the apparatus further comprises:

[0074] An association module, used to associate health item status results with health item status solutions;

[0075] The first display module is used to display the health item status solution when a trigger signal of the health item status result is detected.

[0076] In one embodiment, the apparatus further comprises:

[0077] The upload module is used to preset the health management terminal, upload the health item status results and the analysis process of the health item status results to the health management terminal, and the health management terminal verifies the correctness of the health item status results and the analysis process of the health item status results;

[0078] The second display module is used to obtain the test results of the health management terminal and provide feedback display.

[0079] In one embodiment, the apparatus further comprises:

[0080] The abnormal module is used to monitor in real time the life sign data collected by the life sign sensor, detect the connection status and current performance of the life sign sensor, and output abnormal prompts.

[0081] In one embodiment, the determination module 103 is specifically configured to:

[0082] Obtain the historical medical records of the data tester and the prescribed health item data of the health items in the location of the data tester;

[0083] The prescribed health item data are adjusted according to the historical cases of the data tester, and the customized standard health item data and customized deteriorated health item data of the data tester's health items are determined according to the adjustment results.

[0084] The present invention provides a health data detection device based on a smart wearable device, which first monitors and obtains the life feature data collected by the life feature sensor within a preset time period in real time; obtains the preset health item, extracts the current health item data corresponding to the health item in the life feature data; determines the standard health item data and the deteriorated health item data of the health item; analyzes the overlap rate of the current health item data in the standard health item data or the deteriorated health item data, and obtains the health item status result corresponding to the current health item data; and feeds back the health item status result and the analysis process of the health item status result. The present invention optimizes the wearable device, which not only focuses on the rapid presentation of results, but also emphasizes the recording of data in the data generation process, optimizes and improves health data, and accurately collects, organizes and feeds back individual health item data.

[0085] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0086] For the specific definition of the health data detection device based on smart wearable devices, please refer to the definition of the health data detection method based on smart wearable devices mentioned above, which will not be repeated here. Each module in the above-mentioned health data detection device based on smart wearable devices can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0087] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client through a network connection. When the computer program is executed by the processor, it realizes the functions or steps of a service-side method for health data detection based on a smart wearable device.

[0088] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the client side of a health data detection method based on a smart wearable device

[0089] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0090] Real-time monitoring and acquisition of life feature data collected by life feature sensors within a preset time period;

[0091] Obtain preset health items and extract current health item data corresponding to the health items in the vital characteristics data;

[0092] Determine standard health item data and deteriorated health item data of health items;

[0093] Analyze the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data;

[0094] Feedback of health item status results and analysis process of health item status results.

[0095] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0096] Real-time monitoring and acquisition of life feature data collected by life feature sensors within a preset time period;

[0097] Obtain preset health items and extract current health item data corresponding to the health items in the vital characteristics data;

[0098] Determine standard health item data and deteriorated health item data of health items;

[0099] Analyze the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data;

[0100] Feedback of health item status results and analysis process of health item status results.

[0101] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0102] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0103] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0104] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A health data detection method based on a smart wearable device, characterized in that: include: Real-time monitoring and acquisition of life feature data collected by life feature sensors within a preset time period; Obtain preset health items and extract current health item data corresponding to the health items in the vital characteristics data; Determine standard health item data and deteriorated health item data of health items; Analyze the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data; Feedback of health item status results and analysis process of health item status results.

2. The health data detection method based on the smart wearable device according to claim 1, characterized in that: After the step of feeding back the health item status result and the analysis process of the health item status result, the method further includes: When a preset health item start signal is detected, the health item status result and the analysis process of the health item status result are displayed; When a preset health item closing signal is detected, a preset health item opening signal is monitored in real time, and the health item status result and the analysis process of the health item status result are stored.

3. The health data detection method based on the smart wearable device according to claim 1, characterized in that: After the step of analyzing the overlap rate of the current health item data with the standard health item data or the deteriorated health item data and obtaining the health item status result corresponding to the current health item data, the method further includes: Obtain health item status solutions based on health item status result analysis; Feedback on health item status results, health item status solutions, and the analysis process of health item status results.

4. The health data detection method based on the smart wearable device according to claim 2, characterized in that: After the steps of feeding back the health item status result, the health item status solution and the analysis process of the health item status result, the method further includes: Associating health item status results with health item status solutions; When a trigger signal of a health item status result is detected, a health item status solution is displayed.

5. The health data detection method based on the smart wearable device according to claim 1, characterized in that: After the step of feeding back the health item status result and the analysis process of the health item status result, the method further includes: A health management terminal is preset to upload the health item status results and the analysis process of the health item status results to the health management terminal, and the health management terminal verifies the correctness of the health item status results and the analysis process of the health item status results; Obtain the test results from the health management end and display them as feedback.

6. The health data detection method based on the smart wearable device according to claim 1, characterized in that: After the step of real-time monitoring and acquiring the life sign data collected by the life sign sensor within a preset time period, the method further includes: When real-time monitoring fails to obtain life sign data collected by the life sign sensor, the connection status and current performance of the life sign sensor are detected, and an abnormal prompt is output.

7. The health data detection method based on the smart wearable device according to claim 1, characterized in that: The step of determining standard health item data and deteriorated health item data of the health item comprises: Obtain the historical medical records of the data tester and the prescribed health item data of the health items in the location of the data tester; The prescribed health item data are adjusted according to the historical cases of the data tester, and the customized standard health item data and customized deteriorated health item data of the data tester's health items are determined according to the adjustment results.

8. A health data detection device based on a smart wearable device, characterized in that: include: A collection module, used to monitor in real time and obtain life feature data collected by the life feature sensor within a preset time period; An extraction module, used to obtain preset health items and extract current health item data corresponding to the health items in the vital characteristics data; A determination module, used for determining standard health item data and deteriorated health item data of a health item; An analysis module, used to analyze the overlap rate of the current health item data with the standard health item data or the deteriorated health item data, and obtain the health item status result corresponding to the current health item data; The feedback module is used to feed back the health item status results and the analysis process of the health item status results.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the health data detection method based on the smart wearable device as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the steps of the health data detection method based on the smart wearable device as described in any one of claims 1 to 7 are implemented.

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