Human body status detection method, device, terminal device and storage medium

Abstract

The present invention discloses a human body state detection method, apparatus, terminal device, and storage medium. The method acquires a user's heart rate data; based on a predetermined human body state domain, the human body state of the user is detected according to the heart rate data, wherein the human body state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value; and the user's environmental state is adjusted according to the human body state. The human body state domain is determined by the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value, and the acquired user's heart rate data is compared with the human body state domain to make an accurate judgment on the user's human body state, thereby meeting people's requirements for a comfortable life and improving human comfort.

Description

Technical Field

[0001] The present invention relates to the technical field of human body status monitoring, and in particular to a human body status detection method, apparatus, terminal equipment and storage medium. Background Art

[0002] In daily life, since everyone's physical fitness and living habits are different, their ability to respond to environmental stress is also different. Judging the human body state helps to adjust the environmental state in combination with the human body state. In particular, the current smart home system design can change the environmental state according to the judged human body state, which can dynamically meet people's requirements for a comfortable life and improve human comfort.

[0003] Therefore, it is necessary to propose a solution for detecting the human body state. Summary of the Invention

[0004] The main purpose of the present invention is to provide a human body state detection method, device, terminal equipment and storage medium, aiming to meet people's requirements for a comfortable life and improve the comfort of the human body.

[0005] To achieve the above object, the present invention provides a human body state detection method, which is applied to wearable devices and includes the following steps:

[0006] Get the user's heart rate data;

[0007] Based on a predetermined human body state domain, detecting the human body state of the user according to the heart rate data, wherein the human body state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value;

[0008] The state of the user's environment is adjusted according to the human body state.

[0009] Optionally, before the step of detecting the user's body state according to the heart rate data based on a predetermined body state domain, the step further includes:

[0010] Obtaining the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value;

[0011] Calculating an exercise heart rate threshold value according to the resting heart rate reference value and the maximum exercise heart rate value, and determining an exercise state domain according to the exercise heart rate threshold value and the maximum exercise heart rate value;

[0012] Calculating a sleep heart rate threshold value according to the resting heart rate reference value and the sleep heart rate minimum value, and determining a sleep state domain according to the sleep heart rate threshold value and the sleep heart rate minimum value;

[0013] The resting state domain is determined according to the exercise heart rate threshold and the sleep heart rate threshold, and the human body state domain includes the sleep state domain, the resting state domain and the exercise state domain.

[0014] Optionally, the step of detecting the user's body state according to the heart rate data based on a predetermined body state domain includes:

[0015] Determining the human body state domain of the heart rate data;

[0016] If the heart rate data is in the sleeping state domain, determining that the user is in the sleeping state;

[0017] If the heart rate data is in the resting state domain, determining that the user is in a resting state;

[0018] If the heart rate data is in the exercise state domain, it is determined that the user is in an exercise state.

[0019] Optionally, if the heart rate data is in the sleeping state domain, the step of determining that the user is in the sleeping state further includes:

[0020] Obtaining a sleep heart rate dataset of the user within a preset sleep monitoring time;

[0021] Calculating a mean of the sleeping heart rate data according to the sleeping heart rate data set;

[0022] If the mean of the sleep heart rate data is less than the sleep heart rate threshold, return to the step of obtaining the sleep heart rate data set of the user within the preset sleep monitoring time and subsequent steps until the number of executions reaches the sleep monitoring threshold, and output that the user is in a sleeping state.

[0023] Optionally, if the heart rate data is in the exercise state domain, the step of determining that the user is in the exercise state further includes:

[0024] Obtaining a heart rate data set of the user during a preset exercise monitoring period;

[0025] Calculating the mean of the exercise heart rate data according to the exercise heart rate data set;

[0026] If the mean of the exercise heart rate data is greater than the exercise heart rate threshold, return to the step of obtaining the user's exercise heart rate data set within the preset exercise monitoring time and subsequent steps until the number of executions reaches the exercise monitoring threshold, and output that the user is in exercise state.

[0027] Optionally, if the heart rate data is in the resting state domain, the step of determining that the user is in a resting state further includes:

[0028] Obtaining the user's resting heart rate data at intervals of a preset rest monitoring time;

[0029] Calculating a heart rate offset based on the resting heart rate data and a resting heart rate reference value, and determining whether the user's state has changed based on the heart rate offset;

[0030] If the state of the user changes, the preset rest monitoring time is adjusted and the process returns to the step of obtaining the user's heart rate data and subsequent steps until the user's human body state is determined.

[0031] Optionally, the step of adjusting the state of the user's environment according to the human body state includes:

[0032] Determining the user's physical condition;

[0033] If the user's body state is a motion state, a preset motion state instruction is sent to a smart device, wherein the smart device includes one or more of an air conditioner, a fresh air system, a player, an alarm clock, a lighting system, and a water dispenser, and the motion state instruction includes one or more of motion temperature, motion wind force, motion wind speed, water replenishment reminder, beverage type, and beverage quantity;

[0034] If the user's body state is a sleeping state, a preset sleeping state instruction is sent to the smart device, wherein the sleeping state instruction includes one or more of sleeping temperature, sleeping wind force, sleeping wind speed, light brightness and wake-up time.

[0035] In addition, to achieve the above-mentioned object, the present invention further provides a human body state detection device, the human body state detection device comprising:

[0036] Acquisition module, used to obtain the user's heart rate data;

[0037] a determination module, configured to detect the user's body state according to the heart rate data based on a predetermined body state domain, wherein the body state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value;

[0038] The adjustment module is used to adjust the state of the user's environment according to the human body state.

[0039] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal device, which includes a memory, a processor, and a human body state detection program stored in the memory and runnable on the processor. When the human body state detection program is executed by the processor, the steps of the human body state detection method described above are implemented.

[0040] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a human body state detection program is stored. When the human body state detection program is executed by a processor, the steps of the human body state detection method described above are implemented.

[0041] Embodiments of the present invention propose a human state detection method, apparatus, terminal device, and storage medium. These methods acquire a user's heart rate data and, based on a predetermined human state domain, detect the user's human state according to the heart rate data. The human state domain is calculated using a resting heart rate baseline, a maximum exercise heart rate, and a minimum sleep heart rate. The human state domain is determined using the resting heart rate baseline, the maximum exercise heart rate, and the minimum sleep heart rate. The acquired user heart rate data is compared with the human state domain to accurately determine the user's human state. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a schematic diagram of the functional modules of the terminal device to which the human body state detection device of the present invention belongs;

[0043] Figure 2 1 is a flow chart of an exemplary embodiment of a method for detecting a human body state according to the present invention;

[0044] Figure 3 1 is a flow chart of another exemplary embodiment of the human body state detection method of the present invention;

[0045] Figure 4 for Figure 2 Specific flow diagram of step S20 in the embodiment;

[0046] Figure 5 This is a schematic diagram of heart rate collection in a sleeping state according to an embodiment of the present invention;

[0047] Figure 6 This is a schematic diagram of heart rate collection in exercise status according to an embodiment of the present invention;

[0048] Figure 7 Schematic diagram of human body states corresponding to different heart rates in an embodiment of the present invention;

[0049] Figure 8 Schematic diagram of a process for adaptively adjusting the home environment according to different human body states in an embodiment of the present invention.

[0050] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0052] The main solution of the embodiment of the present invention is to obtain the user's heart rate data; based on a predetermined human body state domain, detect the user's human body state according to the heart rate data, wherein the human body state domain is calculated using the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value. The human body state domain is determined based on the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value, and the obtained user's heart rate data is compared with the human body state domain to accurately determine the user's human body state.

[0053] Specifically, refer to Figure 1 , Figure 1 This is a schematic diagram of the functional modules of a terminal device to which the human state detection device of the present invention belongs. The human state detection device can be a device independent of the terminal device that can detect human state and can be hosted on the terminal device in the form of hardware or software. The terminal device can be a smart mobile terminal with data processing capabilities, such as a mobile phone or tablet computer, or a fixed terminal device or server with data processing capabilities.

[0054] In this embodiment, the terminal device to which the human body state detection apparatus belongs includes at least an output module 110 , a processor 120 , a memory 130 and a communication module 140 .

[0055] The memory 130 stores an operating system and a human state detection program. The human state detection device can store information such as the user's acquired heart rate data, a predetermined human state domain, the user's human state determined based on the heart rate data, a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value in the memory 130. The output module 110 can be a display screen, etc. The communication module 140 can include a Wi-Fi module, a mobile communication module, and a Bluetooth module, etc., and communicates with external devices or servers through the communication module 140.

[0056] When the human body state detection program in the memory 130 is executed by the processor, the following steps are implemented:

[0057] Get the user's heart rate data;

[0058] Based on a predetermined human body state domain, detecting the human body state of the user according to the heart rate data, wherein the human body state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value;

[0059] The state of the user's environment is adjusted according to the human body state.

[0060] Furthermore, when the human body state detection program in the memory 130 is executed by the processor, the following steps are also implemented:

[0061] Obtaining the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value;

[0062] Calculating an exercise heart rate threshold value according to the resting heart rate reference value and the maximum exercise heart rate value, and determining an exercise state domain according to the exercise heart rate threshold value and the maximum exercise heart rate value;

[0063] Calculating a sleep heart rate threshold value according to the resting heart rate reference value and the sleep heart rate minimum value, and determining a sleep state domain according to the sleep heart rate threshold value and the sleep heart rate minimum value;

[0064] The resting state domain is determined according to the exercise heart rate threshold and the sleep heart rate threshold, and the human body state domain includes the sleep state domain, the resting state domain and the exercise state domain.

[0065] Furthermore, when the human body state detection program in the memory 130 is executed by the processor, the following steps are also implemented:

[0066] Determining the human body state domain of the heart rate data;

[0067] If the heart rate data is in the sleeping state domain, determining that the user is in the sleeping state;

[0068] If the heart rate data is in the resting state domain, determining that the user is in a resting state;

[0069] If the heart rate data is in the exercise state domain, it is determined that the user is in an exercise state.

[0070] Furthermore, when the human body state detection program in the memory 130 is executed by the processor, the following steps are also implemented:

[0071] Obtaining a sleep heart rate dataset of the user within a preset sleep monitoring time;

[0072] Calculating a mean of the sleeping heart rate data according to the sleeping heart rate data set;

[0073] If the mean of the sleep heart rate data is less than the sleep heart rate threshold, return to the step of obtaining the sleep heart rate data set of the user within the preset sleep monitoring time and subsequent steps until the number of executions reaches the sleep monitoring threshold, and output that the user is in a sleeping state.

[0074] Furthermore, when the human body state detection program in the memory 130 is executed by the processor, the following steps are also implemented:

[0075] Obtaining a heart rate data set of the user during a preset exercise monitoring period;

[0076] Calculating the mean of the exercise heart rate data according to the exercise heart rate data set;

[0077] If the mean of the exercise heart rate data is greater than the exercise heart rate threshold, return to the step of obtaining the user's exercise heart rate data set within the preset exercise monitoring time and subsequent steps until the number of executions reaches the exercise monitoring threshold, and output that the user is in exercise state.

[0078] Furthermore, when the human body state detection program in the memory 130 is executed by the processor, the following steps are also implemented:

[0079] Obtaining the user's resting heart rate data at intervals of a preset rest monitoring time;

[0080] Calculating a heart rate offset based on the resting heart rate data and a resting heart rate reference value, and determining whether the user's state has changed based on the heart rate offset;

[0081] If the state of the user changes, the preset rest monitoring time is adjusted and the process returns to the step of obtaining the user's heart rate data and subsequent steps until the user's human body state is determined.

[0082] Furthermore, when the human body state detection program in the memory 130 is executed by the processor, the following steps are also implemented:

[0083] Determining the user's physical condition;

[0084] If the user's body state is a motion state, a preset motion state instruction is sent to a smart device, wherein the smart device includes one or more of an air conditioner, a fresh air system, a player, an alarm clock, a lighting system, and a water dispenser, and the motion state instruction includes one or more of motion temperature, motion wind force, motion wind speed, water replenishment reminder, beverage type, and beverage quantity;

[0085] If the user's body state is a sleeping state, a preset sleeping state instruction is sent to the smart device, wherein the sleeping state instruction includes one or more of sleeping temperature, sleeping wind force, sleeping wind speed, light brightness and wake-up time.

[0086] This embodiment, through the above-mentioned solution, specifically obtains the user's heart rate data; based on a predetermined human body state domain, detects the user's human body state according to the heart rate data, wherein the human body state domain is calculated using a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value. The human body state domain is determined based on the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value, and the obtained user's heart rate data is compared with the human body state domain to accurately determine the user's human body state.

[0087] Based on the above terminal device architecture but not limited to the above architecture, an embodiment of the method of the present invention is proposed.

[0088] The execution subject of the method of this embodiment may be a human body state detection device or terminal equipment, etc. This embodiment takes a human body state detection device as an example.

[0089] Reference Figure 2 , Figure 2 1 is a flow chart of an exemplary embodiment of a human body state detection method of the present invention. The human body state detection method includes:

[0090] Step S10, obtaining the user's heart rate data;

[0091] In daily life, due to the differences in physical fitness and living habits, the ability to respond to environmental stress varies from person to person, and different states of the human body can be reflected by heart rate data. Before obtaining the user's current heart rate data, the user's heart rate data is detected by a heart rate detection sensor, wherein the heart rate detection sensor is connected to the wearable device.

[0092] Specifically, in an embodiment of the present invention, a heart rate sensor is additionally installed within a wearable device to obtain the user's heart rate data. When a person is asleep, their metabolic rate slows, resulting in a lower heart rate. When a person is exercising, their metabolic rate speeds up, resulting in a higher heart rate. The heart rate sensor detects the person's current heart rate, converts the detected heart rate into an electrical signal, and transmits it to the wearable device's processor through A / D conversion, thereby determining the user's physical condition.

[0093] Step S20, based on a predetermined human body state domain, detecting the human body state of the user according to the heart rate data, wherein the human body state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value;

[0094] Furthermore, before performing human body state detection, it is necessary to first determine the human body state domain of the current user. The human body state domain mainly includes the sleep state domain, the resting state domain, and the exercise state domain. This human body state domain is calculated based on the collected resting heart rate baseline value, the highest exercise heart rate value, and the lowest sleep heart rate value. After establishing the human body state domain of the current user, the user's human body state can be determined based on the acquired user's heart rate data, and then adjusted in combination with the current environmental state to make the user's environment more suitable for the human body state. If it is determined that the exercise state exceeds the user's human body load, the user can be reminded to take a rest. If it is determined that the user is in a sleeping state, the smart devices in the current environment that determine factors such as temperature, lighting, and volume can be adjusted to improve the user's comfort.

[0095] Step S30: adjusting the state of the user's environment according to the human body state.

[0096] Determining the user's physical condition;

[0097] If the user's body state is a motion state, a preset motion state instruction is sent to a smart device, wherein the smart device includes one or more of an air conditioner, a fresh air system, a player, an alarm clock, a lighting system, and a water dispenser, and the motion state instruction includes one or more of motion temperature, motion wind force, motion wind speed, water replenishment reminder, beverage type, and beverage quantity;

[0098] If the user's body state is a sleeping state, a preset sleeping state instruction is sent to the smart device, wherein the sleeping state instruction includes one or more of sleeping temperature, sleeping wind force, sleeping wind speed, light brightness and wake-up time.

[0099] Specifically, if the wearable interface indicates exercise status, the smart home control system will adjust the air conditioning and fresh air system, play exercise music and videos, set an alarm to remind you to replenish water, and pre-order the appropriate type and quantity of beverages based on your current state. It will then monitor the changes in your state after the home environment is adjusted in real time and fine-tune the environment.

[0100] If the wearable interface indicates a sleeping state, the smart home control system will adjust the air conditioning, fresh air system, light brightness, set alarms, etc. according to the sleeping state to create an environment that is more suitable for sleeping. It will then monitor the changes in the human body state after the home environment is adjusted in real time and fine-tune the environment.

[0101] In this embodiment, the user's heart rate data is acquired; based on a predetermined human state domain, the user's human state is detected from the heart rate data, wherein the human state domain is calculated using a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value. The human state domain is determined based on the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value, and the acquired user's heart rate data is compared with the human state domain to accurately determine the user's human state.

[0102] Reference Figure 3 , Figure 3 This is a flow chart of another exemplary embodiment of the human body state detection method of the present invention. Figure 2 In the embodiment shown, in this embodiment, before the step of detecting the user's body state according to the heart rate data based on a predetermined body state domain, the body state detection method further includes:

[0103] Step S01, obtaining the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value;

[0104] When a user uses a wearable device, the smart home server can set the heart rate value collected when the user is at rest as the resting heart rate baseline value P0, and the highest heart rate value collected when the user is exercising as the highest exercise heart rate value P0. max , the lowest heart rate value collected when the user is sleeping is taken as the maximum heart rate value P min Since the resting heart rate of different people is different, and the resting heart rate of the human body is also different in different environments, it needs to be recalibrated every time it is worn or when the environment changes.

[0105] Step S02, calculating an exercise heart rate threshold value based on the resting heart rate reference value and the maximum exercise heart rate value, and determining an exercise state domain based on the exercise heart rate threshold value and the maximum exercise heart rate value;

[0106] Furthermore, the resting heart rate reference value P0 and the exercise heart rate maximum value P max Then, the exercise heart rate value P1 can be calculated based on the resting heart rate baseline value and the maximum exercise rate value, that is:

[0107] P1=P0+(P max -P0)*α

[0108] Here, α is the heart rate intensity coefficient. In the embodiment of the present invention, α is set to 80%, that is, a heart rate higher than 80% of the maximum heart rate is considered to be an exercise state, and a heart rate lower than 80% of the resting heart rate is considered to be a sleep state.

[0109] After calculating the exercise heart rate threshold P1, you can calculate the exercise heart rate threshold P1 and the maximum exercise heart rate P max Determine the motion state domain.

[0110] Step S03, calculating a sleep heart rate threshold value according to the resting heart rate reference value and the sleep heart rate minimum value, and determining a sleep state domain according to the sleep heart rate threshold value and the sleep heart rate minimum value;

[0111] Determine the resting heart rate baseline value P0 and the lowest heart rate value P during sleep min Then, the resting heart rate reference value P0 and the sleeping heart rate threshold P min Calculate the sleeping heart rate threshold P2, that is:

[0112] P2=P0-(P0-P min )*α

[0113] Here, α is the heart rate intensity coefficient. In the embodiment of the present invention, α is set to 80%, that is, a heart rate higher than 80% of the maximum heart rate is considered to be an exercise state, and a heart rate lower than 80% of the resting heart rate is considered to be a sleep state.

[0114] After calculating the sleep heart rate threshold P2, you can calculate the sleep heart rate threshold P2 and the sleep heart rate minimum value P min Determines the sleep state domain.

[0115] Step S04 : determining a resting state domain according to the exercise heart rate threshold and the sleep heart rate threshold, wherein the human body state domain includes the sleep state domain, the resting state domain, and the exercise state domain.

[0116] After calculating the exercise heart rate threshold P1 and the sleep heart rate threshold P2, you can then use the resting state domain based on the exercise heart rate threshold P1 and the sleep heart rate threshold P2. The resting state domain includes the resting heart rate baseline value. The human body state domain is composed of the sleep state domain, the resting state domain, and the exercise state domain. By comparing the detected user's current heart rate data with the boundary values of each sleep state domain, the resting state domain, and the exercise state domain, you can quickly determine the user's human body state.

[0117] This embodiment adopts the above scheme, specifically by obtaining the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value; calculating the exercise heart rate threshold value based on the resting heart rate baseline value and the maximum exercise heart rate value, and determining the exercise state domain based on the exercise heart rate threshold value and the maximum exercise heart rate value; calculating the sleep heart rate threshold value based on the resting heart rate baseline value and the minimum sleep heart rate value, and determining the sleep state domain based on the sleep heart rate threshold value and the minimum sleep heart rate value; determining the resting state domain based on the exercise heart rate threshold value and the sleep heart rate threshold value, and the human body state domain includes the sleep state domain, the resting state domain, and the exercise state domain. The human body state domain is composed of the sleep state domain, the resting state domain, and the exercise state domain. By comparing the detected user's current heart rate data with the boundary values of each sleep state domain, the resting state domain, and the exercise state domain, the user's human body state can be quickly determined.

[0118] Reference Figure 4 , Figure 4 for Figure 2 The specific flow chart of step S20 in the embodiment. Figure 2 In the embodiment shown, in this embodiment, the above step S20 includes:

[0119] Step S201, determining the human body state domain in which the heart rate data is located;

[0120] After obtaining the user's current heart rate data, the heart rate data is compared with the boundary thresholds of the sleep state domain, the resting state domain or the exercise state domain, that is, the range of the heart rate data is determined. If the heart rate data is between the lowest sleep heart rate value and the sleep heart rate threshold, the heart rate data is in the sleep state domain; if the heart rate data is between the sleep heart rate threshold and the exercise heart rate threshold, the heart rate data is in the resting state domain; if the heart rate data is between the exercise heart rate threshold and the highest exercise heart rate value, the heart rate data is in the exercise state domain.

[0121] Step S202: if the heart rate data is in the sleeping state domain, determining that the user is in the sleeping state;

[0122] If the heart rate data is in the sleep state domain, it is preliminarily determined that the user is in a sleep state. Further heart rate data of the user can be collected to accurately judge the user's human body state, including:

[0123] Obtaining a sleep heart rate dataset of the user within a preset sleep monitoring time;

[0124] Calculating a mean of the sleeping heart rate data according to the sleeping heart rate data set;

[0125] If the mean of the sleep heart rate data is less than the sleep heart rate threshold, return to the step of obtaining the sleep heart rate data set of the user within the preset sleep monitoring time and subsequent steps until the number of executions reaches the sleep monitoring threshold, and output that the user is in a sleeping state.

[0126] Reference Figure 5 , Figure 5 FIG. 1 is a schematic diagram of heart rate collection in a sleeping state according to an embodiment of the present invention. Figure 5 As shown in FIG, when a person is in a sleeping state, the heart rate data will be low. In the embodiment of the present invention, the preset sleep monitoring time is 10 seconds, that is, the heart rate data is collected every 1 second. After collecting 10 times, the user's sleep heart rate data set is obtained, and then the current sleep heart rate data mean P2' is calculated, that is:

[0127]

[0128] Where x is the heart rate detected per second. The current sleep heart rate data mean is compared with the sleep heart rate threshold P2. If the current sleep heart rate data mean is less than the sleep heart rate threshold P2, it is determined that the user is in a sleep state at this time. The wearable device will continue to collect the current sleep heart rate data mean of the next time period as the new P2', and then compare it with the sleep heart rate threshold P2. This process will continue for the next time period. If the time determined to be in a sleep state exceeds a certain time period, the wearable device will determine that the human body has entered a deep sleep state and the wearable device will indicate the status. If the time determined to be in a sleep state does not exceed a certain time period, the wearable device will not take any action.

[0129] Step S203: if the heart rate data is in the resting state domain, determining that the user is in a resting state;

[0130] If the heart rate data is in the resting state domain, it is preliminarily determined that the user is in a resting state. Further heart rate data of the user can be collected to accurately judge the user's human body state, including:

[0131] Obtaining the user's resting heart rate data at intervals of a preset rest monitoring time;

[0132] Calculating a heart rate offset based on the resting heart rate data and a resting heart rate reference value, and determining whether the user's state has changed based on the heart rate offset;

[0133] If the state of the user changes, the preset rest monitoring time is adjusted and the process returns to the step of obtaining the user's heart rate data and subsequent steps until the user's human body state is determined.

[0134] As one implementation method, when the user is at rest, the heart rate sensor measures the heart rate every ten minutes to conserve power. Once an abnormal heart rate value (high or low) is detected, indicating a possible change in the current state, the heart rate sensor measures the heart rate every two minutes, responding quickly to more accurately obtain the current heart rate value. Here, when the heart rate offset |P-P0|>ò (ò can be 10), the heart rate sensor responds quickly.

[0135] Step S204: If the heart rate data is in the exercise state domain, it is determined that the user is in an exercise state.

[0136] If the heart rate data is in the exercise state domain, it is preliminarily determined that the user is in an exercise state. Further heart rate data of the user can be collected to accurately judge the user's human body state, including:

[0137] Obtaining a heart rate data set of the user during a preset exercise monitoring period;

[0138] Calculating the mean of the exercise heart rate data according to the exercise heart rate data set;

[0139] If the mean of the exercise heart rate data is greater than the exercise heart rate threshold, return to the step of obtaining the user's exercise heart rate data set within the preset exercise monitoring time and subsequent steps until the number of executions reaches the exercise monitoring threshold, and output that the user is in exercise state.

[0140] Reference Figure 6 , Figure 6 FIG. 1 is a schematic diagram of collecting heart rate in a motion state according to an embodiment of the present invention. Figure 6 As shown, when a person is in motion, the heart rate data will be high. In the embodiment of the present invention, the preset motion monitoring time is 10 seconds, that is, the heart rate data is collected every 1 second. After collecting 10 times, the user's exercise heart rate data set is obtained, and then the current exercise heart rate data mean P1' is calculated, that is:

[0141]

[0142] Where x is the heart rate detected per second. The current mean value of the exercise heart rate data is compared with the exercise heart rate threshold P1. If the current mean value of the exercise heart rate data is less than the exercise heart rate threshold P1, it is determined that the user is in an exercise state at this time. The wearable device will continue to collect the current mean value of the exercise heart rate data for the next time period as the new P1', and then compare it with the exercise heart rate threshold P1. This process will continue for the next time period. When the time determined to be in an exercise state exceeds a certain time period, the wearable device believes that the human body has been in an exercise state for a long time, and the wearable device will give the status. When the time determined to be in an exercise state does not exceed a certain time period, the wearable device will not take any action.

[0143] This embodiment uses the above solution to determine whether the heart rate data is in the sleeping state domain, the resting state domain, or the exercise state domain within the human body state domain; if the heart rate data is in the sleeping state domain, the user is determined to be in a sleeping state; if the heart rate data is in the resting state domain, the user is determined to be in a resting state; and if the heart rate data is in the exercise state domain, the user is determined to be in an exercise state. A preliminary judgment of the user's human body state is made based on the user's heart rate data, and further collection and monitoring are performed to obtain the user's human body state over a period of time, thereby making an accurate judgment of the user's human body state.

[0144] In addition, an embodiment of the present invention further provides a human body state detection device, the human body state detection device comprising:

[0145] Acquisition module, used to obtain the user's heart rate data;

[0146] a determination module, configured to detect the user's body state according to the heart rate data based on a predetermined body state domain, wherein the body state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value;

[0147] The adjustment module is used to adjust the state of the user's environment according to the human body state.

[0148] Most current smart home system designs in China rely on various sensors to monitor the environment, make corresponding judgments, and implement corresponding measures to change the state of the environment, dynamically meeting people's needs for a comfortable life. However, the environment is not equivalent to the human body's actual senses and physical state. If we combine the actual human state with the data from environmental sensors, make comprehensive judgments, and then implement measures, we can provide a better user experience.

[0149] Specifically, heart rate calibration can be performed while the device is worn (at rest). The smart home server can set the currently collected heart rate value as the heart rate baseline value, P0. As we know, resting heart rates vary from person to person, and from environment to environment. Therefore, recalibration is required each time the device is worn or when the environment changes.

[0150] When resting, the heart rate sensor measures your heart rate every ten minutes to conserve power. If an abnormal heart rate (high or low) is detected, indicating a possible change in your current state, the sensor measures your heart rate every two minutes, responding quickly and providing a more accurate reading. The sensor responds quickly when the heart rate offset |P-P0| > ò (ò can be 10).

[0151] Reference Figure 7 , Figure 7 Schematic diagram of human body states corresponding to different heart rates in an embodiment of the present invention. Figure 7 As shown, here the highest heart rate in the exercise state is recorded as P max , the exercise heart rate threshold is recorded as P1, and the lowest heart rate in the sleeping state is recorded as P min , the sleeping heart rate threshold is recorded as P2.

[0152] Exercise heart rate threshold P1=P0+(P max -P0)*α

[0153] Sleeping heart rate threshold P2 = P0-(P0-P min )*α

[0154] Among them, α is the heart rate intensity coefficient, which can be set to 80% here. That is, when the heart rate is higher than 80% of the maximum heart rate, it is considered to be an exercise state, and when the heart rate is lower than 80% of the resting heart rate, it is considered to be a sleep state.

[0155] When the human body is in a moving state, the heart rate will be relatively high at this time. Take the average value of the heart rate collected at this time (assuming the heart rate is collected for 10 seconds), that is where x is the heart rate detected per second. When the average heart rate P1’ > P1 (the moving heart rate threshold), the wearable device determines that it is in the moving state at this time. The wearable device will continue to collect the average heart rate of the next time period as the new P1’, and then compare it with the moving heart rate threshold P1. It will continue like this in the next time period. When the time t in the determined moving state exceeds a certain time period △t, the wearable device believes that the human body has been in the moving state for a long time, and the wearable device gives a status. When the time t in the determined moving state does not exceed a certain time period △t, the wearable device does not act.

[0156] When the human body is in a sleeping state, the heart rate will be relatively low at this time. Take the average value of the heart rate collected at this time (assuming the heart rate is collected for 10 seconds), that is where x is the heart rate detected per second. When the average heart rate P2’ < P2 (the sleeping heart rate threshold), the wearable device determines that it is in the sleeping state at this time. The wearable device will continue to collect the average heart rate of the next time period as the new P2’, and then compare it with the sleeping heart rate threshold P2. It will continue like this in the next time period. When the time t in the determined sleeping state exceeds a certain time period △t, the wearable device believes that the human body has entered the deep sleep state, and the wearable device gives a status. When the time t in the determined sleeping state does not exceed a certain time period △t, the wearable device does not act.

[0157] Refer to Figure 8 , Figure 8 which is the schematic flow chart of adaptively adjusting the home environment according to different human body states in the embodiments of the present invention. As Figure 8 shown, if the wearable interface gives a moving state, the smart home control system will adjust the air conditioner, fresh air system, play sports music and videos, set an alarm to remind to supplement water, and reserve the appropriate types and quantities of beverages according to the current human body state, etc. Then, it will monitor in real time the change of the human body state after adjusting the home environment and make fine-tuning of the environment;

[0158] If the wearable interface gives a sleeping state, the smart home control system will adjust the air conditioner, fresh air system, and light brightness through the sleeping state adjustment, reserve an alarm, etc., to create a more suitable sleeping environment state. Then, it will monitor in real time the change of the human body state after adjusting the home environment and make fine-tuning of the environment.

[0159] In this embodiment, the human body's state is determined by detecting changes in heart rate under different conditions. This is then combined with various environmental sensors to make a comprehensive judgment and adjust the environmental state in real time, providing the ability to adaptively identify the human body's state. Because each person's physiological condition and physical fitness vary, their heart rate also varies. This patent uses a heart rate detection algorithm to adaptively identify the human body's state. Smart wearable devices serve as a platform to carry this information, working in conjunction with smart home systems to enable people to have a better life experience.

[0160] In addition, an embodiment of the present invention also proposes a terminal device, which includes a memory, a processor, and a human body state detection program stored in the memory and runnable on the processor. When the human body state detection program is executed by the processor, the steps of the human body state detection method described above are implemented.

[0161] Since the human body state detection program adopts all the technical solutions of all the aforementioned embodiments when executed by the processor, it has at least all the beneficial effects brought by all the technical solutions of all the aforementioned embodiments, which will not be described one by one here.

[0162] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a human body state detection program is stored. When the human body state detection program is executed by a processor, the steps of the human body state detection method described above are implemented.

[0163] Since the human body state detection program adopts all the technical solutions of all the aforementioned embodiments when executed by the processor, it has at least all the beneficial effects brought by all the technical solutions of all the aforementioned embodiments, which will not be described one by one here.

[0164] Compared to existing technologies, the human body state detection method, apparatus, terminal device, and storage medium proposed in embodiments of the present invention obtain a user's heart rate data; based on a predetermined human body state domain, the user's human body state is detected according to the heart rate data. The human body state domain is calculated using a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value. The human body state domain is determined using the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value. The obtained user's heart rate data is compared with the human body state domain to accurately determine the user's human body state.

[0165] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0166] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0167] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, controlled terminal, or network device, etc.) to execute the method of each embodiment of the present application.

[0168] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for detecting a human body state, characterized in that: The human body state detection method is applied to a wearable device, and the human body state detection method includes the following steps: Get the user's heart rate data; Based on a predetermined human state domain, detecting the human state of the user according to the heart rate data, wherein the human state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value, wherein the maximum exercise heart rate value is the highest heart rate value collected when the user is in an exercise state, and the minimum sleep heart rate value is the lowest heart rate value collected when the user is in a sleep state; Adjusting the state of the user's environment according to the human body state; Before the step of detecting the user's body state based on the heart rate data based on a predetermined body state domain, the method further includes: Obtaining the resting heart rate baseline value, the maximum exercise heart rate value, and the minimum sleep heart rate value; Calculating an exercise heart rate threshold value according to the resting heart rate reference value and the maximum exercise heart rate value, and determining an exercise state domain according to the exercise heart rate threshold value and the maximum exercise heart rate value; Calculating a sleep heart rate threshold value according to the resting heart rate reference value and the sleep heart rate minimum value, and determining a sleep state domain according to the sleep heart rate threshold value and the sleep heart rate minimum value; determining a resting state domain according to the exercise heart rate threshold and the sleep heart rate threshold, wherein the human body state domain includes the sleep state domain, the resting state domain, and the exercise state domain; The resting heart rate reference value is P0, and the maximum exercise heart rate value is P max , the lowest sleeping heart rate is P min , the heart rate intensity coefficient is α, the exercise heart rate threshold is P1, the sleep heart rate threshold is P2, P1=P0+(P max -P0)*α, P2=P0-(P0-P min )*α.

2. The human body state detection method according to claim 1, wherein: The step of detecting the user's body state according to the heart rate data based on a predetermined body state domain includes: Determining the human body state domain of the heart rate data; If the heart rate data is in the sleeping state domain, determining that the user is in the sleeping state; If the heart rate data is in the resting state domain, determining that the user is in a resting state; If the heart rate data is in the exercise state domain, it is determined that the user is in an exercise state.

3. The human body state detection method according to claim 2, wherein: If the heart rate data is in the sleeping state domain, then after the step of determining that the user is in the sleeping state, the method further includes: Obtaining a sleep heart rate dataset of the user within a preset sleep monitoring time; Calculating a mean of the sleeping heart rate data according to the sleeping heart rate data set; If the mean of the sleep heart rate data is less than the sleep heart rate threshold, return to the step of obtaining the sleep heart rate data set of the user within the preset sleep monitoring time and subsequent steps until the number of executions reaches the sleep monitoring threshold, and output that the user is in a sleeping state.

4. The human body state detection method according to claim 2, wherein: If the heart rate data is in the exercise state domain, then after the step of determining that the user is in the exercise state, the method further includes: Obtaining a heart rate data set of the user during a preset exercise monitoring period; Calculating the mean of the exercise heart rate data according to the exercise heart rate data set; If the mean of the exercise heart rate data is greater than the exercise heart rate threshold, return to the step of obtaining the user's exercise heart rate data set within the preset exercise monitoring time and subsequent steps until the number of executions reaches the exercise monitoring threshold, and output that the user is in exercise state.

5. The human body state detection method according to claim 2, wherein: If the heart rate data is in the resting state domain, the step of determining that the user is in a resting state further includes: Obtaining the user's resting heart rate data at intervals of a preset rest monitoring time; Calculating a heart rate offset based on the resting heart rate data and a resting heart rate reference value, and determining whether the user's state has changed based on the heart rate offset; If the state of the user changes, the preset rest monitoring time is adjusted and the process returns to the step of obtaining the user's heart rate data and subsequent steps until the user's human body state is determined.

6. The human body state detection method according to claim 1, wherein: The step of adjusting the state of the user's environment according to the human body state includes: Determining the user's physical condition; If the user's body state is a motion state, a preset motion state instruction is sent to a smart device, wherein the smart device includes one or more of an air conditioner, a fresh air system, a player, an alarm clock, a lighting system, and a water dispenser, and the motion state instruction includes one or more of motion temperature, motion wind force, motion wind speed, water replenishment reminder, beverage type, and beverage quantity; If the user's body state is a sleeping state, a preset sleeping state instruction is sent to the smart device, wherein the sleeping state instruction includes one or more of sleeping temperature, sleeping wind force, sleeping wind speed, light brightness and wake-up time.

7. A human body state detection device, characterized in that: The human body state detection device comprises: Acquisition module, used to obtain the user's heart rate data; a determination module, configured to detect the user's human state according to the heart rate data based on a predetermined human state domain, wherein the human state domain is calculated by a resting heart rate baseline value, a maximum exercise heart rate value, and a minimum sleep heart rate value, wherein the maximum exercise heart rate value is the highest heart rate value collected when the user is in an exercise state, and the minimum sleep heart rate value is the lowest heart rate value collected when the user is in a sleep state; An adjustment module, configured to adjust the state of the user's environment according to the human body state; The judgment module is further used to obtain the resting heart rate reference value, the maximum exercise heart rate value and the minimum sleep heart rate value; calculate the exercise heart rate threshold value according to the resting heart rate reference value and the maximum exercise heart rate value, and determine the exercise state domain according to the exercise heart rate threshold value and the maximum exercise heart rate value; calculate the sleep heart rate threshold value according to the resting heart rate reference value and the minimum sleep heart rate value, and determine the sleep state domain according to the sleep heart rate threshold value and the minimum sleep heart rate value; determine the resting state domain according to the exercise heart rate threshold value and the sleep heart rate threshold, and the human body state domain includes the sleep state domain, the resting state domain and the exercise state domain; wherein the resting heart rate reference value is P0, the maximum exercise heart rate value is P max , the lowest sleeping heart rate is P min , the heart rate intensity coefficient is α, the exercise heart rate threshold is P1, the sleep heart rate threshold is P2, P1=P0+(P max -P0)*α, P2=P0-(P0-P min )*α.

8. A terminal device, characterized in that: The terminal device includes a memory, a processor, and a human body state detection program stored in the memory and executable on the processor. When the human body state detection program is executed by the processor, the steps of the human body state detection method as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a human body state detection program, which, when executed by a processor, implements the steps of the human body state detection method according to any one of claims 1 to 6.

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