Robot control method and device, medical service robot, and readable storage medium

Abstract

The present disclosure provides a robot control method and device, a medical service robot, and a readable storage medium, which belongs to the field of intelligent control technology. The method includes: in response to the robot's operating mode being a first mode, receiving physiological monitoring data for a user sent by a first device; if the physiological monitoring data shows that the user's physiological state is a first state, determining a first time node based on the physiological monitoring data; controlling the robot to enter a dormant state at the first time node; the first state is used to indicate the user's health; in response to the robot's operating mode being a second mode, controlling the robot to remain awake. The robot control method and device, the medical service robot, and the readable storage medium provided by the present disclosure reduce the robot's power consumption while ensuring the health and safety of the user, which is conducive to the long-term stable operation of the robot.

Description

Technical Field

[0001] The present disclosure belongs to the field of intelligent control technology, and more specifically, relates to a robot control method and device, a medical service robot, and a readable storage medium. Background Art

[0002] In recent years, medical and nursing service robots have been widely used in hospitals, nursing homes, rehabilitation centers, and homes, providing comprehensive medical and nursing services such as nursing care, entertainment companionship, and daily communication to the elderly, patients, and recovering people.

[0003] In order to provide comprehensive safety monitoring, medical service robots usually need to work continuously for 24 hours, which not only increases the energy consumption, but also accelerates the wear of the robot's mechanical parts, electronic components and sensors due to long-term continuous work. Summary of the invention

[0004] The purpose of the present disclosure is to provide a robot control method and device, a medical service robot, and a readable storage medium, which reduce the power consumption of the robot while ensuring the health and safety of the user, and are conducive to the long-term stable operation of the robot.

[0005] A first aspect of the embodiments of the present disclosure provides a robot control method, comprising:

[0006] In response to the robot operating mode being the first mode, receiving physiological monitoring data for the user sent by a first device; if the physiological monitoring data shows that the user's physiological state is the first state, determining a first time node based on the physiological monitoring data; at the first time node, controlling the robot to enter a dormant state; the first state is used to indicate that the user is healthy, and the first device is a physiological monitoring device;

[0007] In response to the operating mode of the robot being the second mode, the robot is controlled to maintain an awake state.

[0008] A second aspect of the embodiments of the present disclosure provides a robot control device, comprising:

[0009] a first processing module, configured to, in response to the robot operating mode being the first mode, receive physiological monitoring data for a user sent by a first device; if the physiological monitoring data shows that the user's physiological state is the first state, determine a first time node based on the physiological monitoring data; and control the robot to enter a dormant state at the first time node; the first state is used to indicate that the user is healthy;

[0010] The second processing module is used to control the robot to maintain a wake-up state in response to the robot's operating mode being the second mode.

[0011] According to a third aspect of the embodiments of the present disclosure, a medical service robot is provided, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above-mentioned robot control method when executing the computer program.

[0012] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned robot control method are implemented.

[0013] The robot control method and device, the medical care service robot, and the readable storage medium provided by the embodiments of the present disclosure have the following beneficial effects:

[0014] In the disclosed embodiment, the first device may be a health monitoring device. In the first mode, the user's physiological monitoring data may be obtained through the first device. If the user's physiological monitoring data shows that the user is in good health, the user's work and rest status may be further detected based on the user's physiological monitoring data. When the user is resting, the robot may be controlled to enter a dormant state to save power consumption. At the same time, according to the user's needs, the robot may also be set to work in the second mode. In the second mode, the robot remains awake to provide services to the user at any time.

[0015] The disclosed embodiment combines a robot and a health monitoring device to achieve a low power consumption mode of the robot. While ensuring the health and safety of the user, the power consumption of the robot is reduced, which is beneficial to the long-term stable operation of the robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A schematic diagram of a flow chart of a robot control method provided by an embodiment of the present disclosure;

[0018] Figure 2 A schematic diagram of the positional relationship between the first area and the second area provided in an embodiment of the present disclosure;

[0019] Figure 3 A structural block diagram of a robot control device provided by an embodiment of the present disclosure;

[0020] Figure 4 A structural block diagram of a robot control device provided by another embodiment of the present disclosure;

[0021] Figure 5 A schematic block diagram of a medical care service robot provided in one embodiment of the present disclosure;

[0022] In the figure:

[0023] 11 first area, 12 second area, 13 user, 14 robot. DETAILED DESCRIPTION

[0024] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0025] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0026] Please refer to Figure 1 , Figure 1 A schematic flow chart of a robot control method provided in an embodiment of the present disclosure, which is applied to a controller of the robot, includes:

[0027] S101: In response to the robot's operating mode being the first mode, receiving physiological monitoring data for the user sent by a first device; if the physiological monitoring data shows that the user's physiological state is the first state, determining a first time node based on the physiological monitoring data; at the first time node, controlling the robot to enter a sleep state; the first state is used to indicate user health.

[0028] In this embodiment, the robot is specifically a medical care service robot, and the users of the robot may include the elderly, patients, and people who need special care. The medical care service robot can provide users with daily life care, health monitoring and management, emotional companionship and entertainment, safety protection and emergency services. Among them, in terms of daily life care, for the elderly or patients with limited mobility or weak self-care ability, medical and nursing service robots can provide auxiliary services for self-care, such as assisting with dressing, washing, eating, etc., to help them maintain basic living ability; in terms of health monitoring and management, medical and nursing service robots can be equipped with various sensors, such as blood pressure monitors, heart rate monitors, etc., to monitor the physiological indicators of the elderly in real time, such as blood pressure, heart rate, blood oxygen, etc., and transmit the data to doctors or family members so that corresponding measures can be taken in time; in terms of emotional companionship and entertainment, medical and nursing service robots have voice interaction functions, and can chat, tell stories, play music and other interactive activities with the elderly or patients, provide them with emotional companionship and support, and relieve loneliness and anxiety; in terms of safety protection and emergency services, medical and nursing service robots can monitor the living environment of the elderly or patients in real time, such as safety hazards such as smoke and falls, and quickly contact rescue agencies or family members once abnormal conditions are found to provide timely rescue services for the elderly or patients.

[0029] The first device can be a health monitoring device such as a smart bracelet or smart headband worn by the user of the robot. The first device can monitor the user's heart rate, blood pressure, blood oxygen saturation, sleep quality and other physiological monitoring data in real time. The first device can be a device installed on the medical service robot or a separately purchased device.

[0030] The robot may include multiple working modes. In the first mode, the robot may obtain the user's physiological monitoring data through the first device. The physiological monitoring data may represent the user's physiological state. If the user's physiological monitoring data shows that the user's physiological state is the first state (that is, the user is in good health), there is no need to perform real-time monitoring of the user. For example, the robot may be controlled to enter a sleep state when the user is resting. On the one hand, this may allow the robot to rest and reduce the robot's power consumption. On the other hand, it may prevent the noise from the robot's operation from interfering with the user's rest.

[0031] Therefore, the user's work and rest status can be further detected based on the user's physiological monitoring data. If the user's heart rate is detected to gradually decrease and remain stable, and the breathing rate and depth are stable, it indicates that the user is in a sleeping state. At a certain time point (e.g., the first time node) after the user is detected to be in a sleeping state, the robot can be controlled to enter a dormant state, and other functions except physiological monitoring and voice wake-up can be turned off to save power consumption.

[0032] Among them, the user's physiological state can be obtained by judging whether the user's physiological monitoring data falls within the second set range, and the second set range may include a second set range of heart rate, a second set range of blood pressure, and a second set range of blood oxygen saturation. If the user's heart rate data falls within the second set range of heart rate, the user's blood pressure data falls within the second set range of blood pressure, and the user's blood oxygen saturation falls within the second set range of blood oxygen saturation according to the physiological monitoring data, it indicates that the user's physiological state is the first state, that is, the user is healthy; otherwise, the user's physiological state is the second state, that is, the user is physically abnormal. In order to ensure accurate judgment of the user's physiological state, it is necessary to continuously monitor the physiological monitoring data within a period of time (for example, the first set time) for multiple times. If the number of times that the physiological monitoring data exceeds the second set range within the first set time is less than the set threshold, the user's physiological state is judged to be the first state, otherwise the user's physiological state is judged to be the second state.

[0033] The second setting range can be obtained by using a statistical method, that is, by counting the heart rate data, blood pressure data and blood oxygen saturation of multiple users of the same age group and the same medical history during normal awake hours, to obtain a second setting range of heart rate, a second setting range of blood pressure and a second setting range of blood oxygen saturation. The normal awake hours are awake hours when the user is in good physical condition.

[0034] In addition, in some cases, the robot can also be controlled to enter a partial sleep state. For example, the user is watching TV, and the physiological monitoring data shows that the user is awake, but according to the first device worn by the user (the first device is usually equipped with an accelerometer and a gyroscope, which can be used for user posture detection), it can be obtained that the user is sitting still. At this time, the fall detection function module in the robot can be turned off, that is, the robot is controlled to enter a partial sleep state.

[0035] In some cases, the robot can exit the dormant state or partial dormant state. For example, when the robot is in the dormant state, if the user's work and rest state is detected to be awake according to the physiological monitoring data, the robot can be controlled to exit the dormant state. For another example, when the robot is in a partial dormant state with the fall detection function module turned off, if the user is detected to be walking according to the first device worn by the user, the robot can be controlled to exit the partial dormant state.

[0036] In the second mode, the robot can be controlled to stay awake, and all functional modules are turned on to provide services to users at any time. It can be concluded that the operating power consumption of the first mode is less than that of the second mode.

[0037] S102: In response to the robot's operating mode being the second mode, controlling the robot to remain in an awake state.

[0038] In this embodiment, according to user needs, the robot can also be set to work in the second mode. In the second mode, the robot remains awake to provide services to the user at any time.

[0039] Users can set the robot's operating mode according to actual needs. For example, if the physical examination report of user A shows that the user has no obvious physical abnormalities, it means that the user is in good physical condition. The first mode can be selected. When the user is resting, the robot automatically enters the dormant state. The physical examination report of another user B shows that the user B has abnormal items, indicating that the user B is in poor physical condition. The second mode can be selected to monitor user B in real time so that an alarm can be issued in time when an abnormality occurs.

[0040] From the above, it can be concluded that the embodiment of the present disclosure combines the robot and the health monitoring device to achieve a low power consumption mode of the robot, thereby reducing the power consumption of the robot while ensuring the health and safety of the user.

[0041] In one embodiment of the present disclosure, determining a first time node based on physiological monitoring data includes:

[0042] At a plurality of second time points, receiving physiological monitoring data of the user sent by the first device;

[0043] In response to the physiological monitoring data received at N consecutive second time nodes all being within a first set range, the N+1th second time node is determined as the first time node.

[0044] In this embodiment, the second time node may be a plurality of time nodes specified by the user, or may be a plurality of time nodes set in a cycle. Considering that the user's heart rate will slow down, blood pressure will decrease, and blood oxygen saturation will remain relatively stable when the user is resting, the first setting range may include a first setting range of heart rate and a first setting range of blood pressure. If the user's heart rate data falls within the first setting range of heart rate and the user's blood pressure data falls within the first setting range of blood pressure according to the physiological monitoring data, it indicates that the user may be in a sleeping state. If the physiological monitoring data for multiple consecutive times (N times) all indicate that the user is in a sleeping state, the robot is controlled to enter a dormant state at the next second time node (the N+1th second time node), that is, the N+1th second time node is determined as the first time node. Among them, the first setting range of heart rate is included in the second setting range of heart rate, and the first setting range of blood pressure is included in the second setting range of blood pressure.

[0045] For example, the user's physiological monitoring data can be monitored every 5 minutes for 100 consecutive minutes (that is, the second time nodes are 20). If the 20 monitoring results all show that the user's heart rate falls within the first set range of the heart rate and the user's blood pressure falls within the first set range of the blood pressure, it indicates that the user is in a sleeping state. At this time, the robot can be controlled to enter a dormant state at the 105th minute (that is, the 21st second time node).

[0046] The first set range of heart rate and the first set range of blood pressure can be obtained based on statistical data, that is, the heart rate data and blood pressure data of multiple users of the same age group and the same medical history during normal sleep periods are statistically analyzed to obtain the first set range of heart rate and the first set range of blood pressure. The normal sleep period is the sleep period when the user is in good physical condition.

[0047] For example, user A is 65 years old and suffers from mild hypertension. 100 patients aged between 60 and 70 who are diagnosed with mild hypertension by doctors can be selected as research samples. Their heart rate and blood pressure data are counted during normal sleep periods, that is, when they are not ill, not taking medication and feeling well, to obtain a first set range for heart rate and a first set range for blood pressure.

[0048] It can be concluded from the above that this embodiment can ensure that the user enters a stable sleep state by tracking the physiological monitoring data at N consecutive second time nodes, thereby determining a first time node that conforms to reality.

[0049] In one embodiment of the present disclosure, the robot control method further includes:

[0050] In response to the robot being in a dormant state and the physiological monitoring data exceeding a first set range, the robot is controlled to exit the dormant state.

[0051] In an embodiment, when the robot is in a dormant state, other functions except physiological monitoring and voice wake-up can be turned off. For example, the robot's moving parts (wheels, joints, etc.) will stop working in dormant state to reduce mechanical wear and energy consumption; parts that interact with the user, such as display screens, will be turned off in dormant state to save power and reduce interference.

[0052] When it is monitored that the physiological monitoring data exceeds the first set range, it is judged that the user's rest is over or the physiological monitoring data is abnormal. At this time, it is necessary to control the robot to exit the sleep state and further judge whether the user's physiological monitoring data falls into the second set range. If it falls into the second set range, it indicates that the user's rest is over and the physiological monitoring data is normal; otherwise, if the user's physiological monitoring data exceeds the second set range, it indicates that the physiological monitoring data is abnormal, and it is necessary to issue a prompt message in time to remind the user to take medicine in time or send an alarm notification to the user's emergency contact, automatically dial an emergency number, etc.

[0053] It can be concluded from the above that, when the physiological monitoring data is detected to be beyond the first set range, the present embodiment can control the robot to exit the dormant state in time, thereby ensuring timely monitoring of the user's health.

[0054] In one embodiment of the present disclosure, the robot control method further includes:

[0055] The third time node is determined based on the historical physiological monitoring data of the user.

[0056] A first prompt message is sent to the user at a third time point; the first prompt message is used to remind the user to take medicine.

[0057] In response to confirmation information input by the user in response to the first prompt information, the medication mechanism is controlled to perform a medication action.

[0058] In this embodiment, the robot is also equipped with a medication reminder function to remind the user to take medicine at a set time point (i.e., the third time node). At the same time, the robot is also equipped with an intelligent medication mechanism (such as an automatic medicine box, an intelligent medicine bottle, etc.) to perform medication actions and distribute the medicine to the user. The medication action can be to open a specific grid of the automatic medicine box and release the medicine to a position that is convenient for the user to take.

[0059] In this embodiment, a suitable third time node can be determined based on the user's historical physiological monitoring data (such as blood pressure, heart rate, blood sugar, etc.), and a first prompt message is issued at the third time node to remind the user to take medicine. Specifically, a fourth time node when the user's physical condition is poor can be obtained by analyzing the historical physiological monitoring data, and the user is reminded to take medicine at the third time node before the fourth time node (for example, half an hour). For example, if the physiological monitoring data shows that the user's blood sugar is high around 3 o'clock after lunch, the user can be reminded to take medicine around 2:30.

[0060] The first prompt information can be sent to the user's mobile phone app or the first device worn by the user, or can be reminded by voice or screen display. After receiving the first prompt information, the user can enter confirmation information through the mobile phone app or click the confirmation button on the robot to inform the robot that it is ready to take the medicine. At this time, the robot's controller controls the drug delivery mechanism to deliver the medicine to the user.

[0061] Furthermore, the determination of the third time node also needs to consider the medication interval, which can be obtained according to the doctor's order or drug instructions. For example, according to the doctor's order, the medication interval of a certain drug is 6 hours, and the time difference between the third time node obtained from the historical physiological monitoring data and the last medication is less than 6 hours, then the third time node is postponed for a corresponding period of time, and the medication interval is not less than 6 hours.

[0062] Among them, medical order data can be input through the user's mobile phone app or display screen, and the drug instructions can be obtained by scanning the QR code on the drug packaging. The medication instructions in the drug instructions include the number of times per day, the amount taken each time, etc. The amount taken each time is usually expressed in kg / mg of body weight. Therefore, the amount of medication taken each time can be obtained by combining the user's weight and the drug instructions.

[0063] It can be concluded from the above that this embodiment determines the optimal medication time based on the user's physiological monitoring data, which helps to better monitor and manage the patient's health status compared to the traditional fixed medication time.

[0064] In one embodiment of the present disclosure, the historical physiological monitoring data of the user includes physiological monitoring data of multiple dates.

[0065] Determining a third time node based on historical physiological monitoring data of the user includes:

[0066] Draw the user's health curve based on historical physiological monitoring data.

[0067] The abnormal period of each date is determined based on the health curve; the abnormal period is a period containing a specified extreme point of the health curve, and the specified extreme point is a maximum point or a minimum point of the health curve.

[0068] The intersection of the abnormal time periods of each date is determined as the first time period.

[0069] A third time node is determined based on the first time period.

[0070] In this embodiment, a specific implementation method for determining the third time node based on the user's historical physiological monitoring data is given. Specifically, a health curve can be drawn based on the user's historical physiological monitoring data. The health curve can reflect the changing pattern of the user's health status over time and intuitively display the fluctuation of the user's physiological state. The maximum or minimum points on the health curve (for example, points where blood pressure is abnormally elevated) represent significant changes or abnormalities in the user's physiological state. The time period containing these maximum or minimum points (that is, the abnormal time period) can be considered as a time period when the user's health status is unstable or requires special attention. In the multiple dates corresponding to the historical monitoring data, the abnormal time periods included may be different. By taking the intersection of the abnormal time periods of multiple dates, multiple first time periods can be obtained. Determining the third time node based on the multiple first time periods can unify the medication time for each day.

[0071] Among them, the abnormal period of each date determined based on the health curve can be described in detail as follows:

[0072] Determine the specified extreme points of the health curve for each date.

[0073] The time point corresponding to the designated extreme value point is reduced by a fourth time length to obtain a first endpoint of the abnormal period, and the time point corresponding to the designated extreme value point is increased by a fourth time length to obtain a second endpoint of the abnormal period.

[0074] A period between the first endpoint and the corresponding second endpoint is determined as an abnormal period.

[0075] In this embodiment, by reducing or increasing the fourth time length by the time point corresponding to the specified extreme value point, the first endpoint and the second endpoint are obtained respectively, and the period between the first endpoint and the second endpoint is the abnormal period. For example, if the time point corresponding to the specified extreme value point is 8:20 and the fourth time length is 30 minutes, then the abnormal period corresponding to the specified extreme value point is 7:50~8:50.

[0076] On the basis of obtaining multiple first time periods, determining the third time node based on the first time period can be described in detail as follows:

[0077] A fourth time period is selected from the plurality of first time periods based on a specified rule.

[0078] A third time node is selected from the fourth time period.

[0079] In this embodiment, the specified rules can be obtained according to the doctor's order or the drug instructions. For example, according to the doctor's order, a certain drug needs to be taken twice a day, then a time period in the morning and a time period in the afternoon can be selected from multiple first time periods as two fourth time periods. The earliest time node is selected from the fourth time period as the third time node. If the user does not take the medicine on time at the third time node, the first reminder message can be sent again after a delay of a set time to remind the user to take the medicine.

[0080] It can be concluded from the above that this embodiment scientifically determines the third time node based on the user's historical physiological monitoring data, and provides the user with more accurate and personalized health management services.

[0081] In one embodiment of the present disclosure, the robot control method further includes:

[0082] In response to a call request sent by the second device and the physiological monitoring data of the user is within a first set range, a first instruction is sent to the first device within a second time period, and the first instruction is used to instruct the first device to send a vibration prompt message.

[0083] A voice prompt message is issued in a third time period after the second time period.

[0084] In this embodiment, the second device can be a mobile phone of a family member of the user, and the first device can be a health monitoring device such as a smart bracelet or a smart headband. When a family member of the user calls the user's mobile phone, the user may miss the call because the mobile phone is not with him. To avoid the above problem, the robot in this embodiment can establish a Bluetooth or Wi-Fi connection with the user's mobile phone. If it is detected that the user does not answer the call within the second set time, a prompt message is issued to remind the user to answer the call in time.

[0085] Furthermore, if it is determined through the user's physiological monitoring data that the user is resting (that is, the user's physiological monitoring data is within the first set range), at this time, in order to avoid suddenly waking up the user and causing a series of stress reactions such as accelerated heartbeat and increased blood pressure, the present embodiment first sends a first instruction to the first device, and the first device sends a vibration prompt message to slowly wake up the user, and then prompts the user to answer the call in time through a voice prompt message.

[0086] It can be concluded from the above that this embodiment avoids missed calls by establishing a connection between the robot and the user's mobile phone. At the same time, it avoids suddenly waking up the user and causing impact on the user's health by linking with the first device.

[0087] In one embodiment of the present disclosure, the robot control method further includes:

[0088] In response to the user moving from the first area to the second area and the light intensity in the second area being less than the first threshold, a second instruction is sent to a third device, the second instruction being used to instruct the third device to turn on; the third device is a lighting device in the second area.

[0089] In response to the user leaving the first area for a duration greater than a third duration, a third instruction is sent to a fourth device, the third instruction being used to instruct the fourth device to shut down; the fourth device is a lighting device in the first area.

[0090] In this embodiment, the robot is combined with the smart home to improve the intelligence level of the user's living environment. Figure 3 , taking the user as an elderly person living alone as an example, the robot always follows the user to monitor the user in real time. The first area can be the bedroom of the user's home, and the second area can be the living room of the user's home. If it is detected that the user moves from the first area to the second area, and the light in the second area is dim (that is, the light intensity is less than the first threshold), the second instruction can be sent to control the lighting equipment in the second area to automatically turn on and provide necessary lighting. At the same time, if it is detected that the user leaves the first area for a long time (greater than the third time length), the third instruction can be sent to control the lighting equipment in the first area to automatically turn off to avoid wasting electricity. Among them, the monitoring of the first area and the second area can be achieved through an indoor positioning system (such as Wi-Fi positioning, Bluetooth positioning, ultra-wideband (UWB) positioning, etc.), and the robot determines the user's position change by receiving positioning signals.

[0091] The duration of the user leaving the first area can be determined according to the duration of the user staying in the second area. If the user stays in the second area for longer than the third duration, the lighting devices in other areas (including the first area) can be turned off. In addition, the robot in this embodiment is also equipped with a voice function. The user can tell the robot to turn on or off the lighting device through voice signals. The combination of multiple functions can provide users with more humane services.

[0092] It can be concluded from the above that this embodiment intelligently turns on or off the lighting equipment in the corresponding area according to the user's activity area, which can achieve the effect of energy saving and improving the comfort of the living environment.

[0093] In one embodiment of the present disclosure, the robot control method further includes:

[0094] In response to the user's physiological monitoring data showing that the user's work and rest state changes from an awake state to a sleeping state, a control parameter of the fifth device is adjusted from a first parameter to a second parameter.

[0095] In this embodiment, the same method as the above embodiment can be used to determine the user's work and rest state by determining whether the user's physiological monitoring data falls within the first set range of heart rate and the first set range of blood pressure. Specifically, if the user's heart rate data falls within the first set range of heart rate and the user's blood pressure data falls within the first set range of blood pressure according to the physiological monitoring data, it indicates that the user may be in a sleeping state; otherwise, the user is determined to be awake.

[0096] The fifth device may be a smart home device such as a smart lighting device, a smart air conditioner or a smart curtain. Taking a smart lighting device as an example, the first parameter may be a larger brightness parameter, which is suitable for the awake state, and the second parameter may be a soft, low-brightness lighting parameter, which is more suitable for the sleeping environment. Taking a smart air conditioner as an example, considering that the body temperature of the user will decrease when the user is in a sleeping state, the temperature parameter of the smart air conditioner may be increased after the user is detected to enter a sleeping state, that is, the second parameter is greater than the first parameter.

[0097] It can be concluded from the above that this embodiment takes into account the different needs of users in the awake state and the sleeping state, and adjusts the control parameters of the smart home based on the user's physiological monitoring data, which can further improve the monitoring effect.

[0098] Corresponding to the robot control method of the above embodiment, Figure 3 This is a block diagram of a robot control device provided by an embodiment of the present disclosure. For ease of explanation, only the parts related to the embodiment of the present disclosure are shown. Figure 3 The robot control device 20 includes: a first processing module 21 and a second processing module 22.

[0099] Among them, the first processing module 21 is used to receive physiological monitoring data for the user sent by the first device in response to the robot's operating mode being the first mode; if the physiological monitoring data shows that the user's physiological state is the first state, determine the first time node based on the physiological monitoring data; control the robot to enter a sleep state at the first time node; the first state is used to indicate the health of the user.

[0100] The second processing module 22 is used for controlling the robot to maintain a wake-up state in response to the operation mode of the robot being the second mode.

[0101] In one embodiment of the present disclosure, the first processing module 21 is specifically used for:

[0102] At multiple second time nodes, physiological monitoring data of the user sent by the first device is received.

[0103] In response to the physiological monitoring data received at N consecutive second time nodes all being within a first set range, the N+1th second time node is determined as the first time node.

[0104] In one embodiment of the present disclosure, the first processing module 21 is specifically used for:

[0105] In response to the robot being in a dormant state and the physiological monitoring data exceeding a first set range, the robot is controlled to exit the dormant state.

[0106] refer to Figure 4 In one embodiment of the present disclosure, the robot control device 20 further includes a third processing module 23, which is used to:

[0107] The third time node is determined based on the historical physiological monitoring data of the user.

[0108] A first prompt message is sent to the user at a third time point; the first prompt message is used to remind the user to take medicine.

[0109] In response to confirmation information input by the user in response to the first prompt information, the medication mechanism is controlled to perform a medication action.

[0110] In one embodiment of the present disclosure, the historical physiological monitoring data of the user includes physiological monitoring data of multiple dates, and the third processing module 23 is specifically used to:

[0111] Draw the user's health curve based on historical physiological monitoring data.

[0112] The abnormal period of each date is determined based on the health curve; the abnormal period is a period containing a specified extreme point of the health curve, and the specified extreme point is a maximum point or a minimum point of the health curve.

[0113] The intersection of the abnormal time periods of each date is determined as the first time period.

[0114] A third time node is determined based on the first time period.

[0115] In one embodiment of the present disclosure, the third processing module 23 is specifically used to:

[0116] In response to a call request sent by the second device and the physiological monitoring data of the user is within a first set range, a first instruction is sent to the first device within a second time period, and the first instruction is used to instruct the first device to send a vibration prompt message.

[0117] A voice prompt message is issued in a third time period after the second time period.

[0118] In one embodiment of the present disclosure, the third processing module 23 is specifically used to:

[0119] In response to the user moving from the first area to the second area and the light intensity in the second area being less than the first threshold, a second instruction is sent to a third device, the second instruction being used to instruct the third device to turn on; the third device is a lighting device in the second area.

[0120] In response to the user leaving the first area for a duration greater than a third duration, a third instruction is sent to a fourth device, the third instruction being used to instruct the fourth device to shut down; the fourth device is a lighting device in the first area.

[0121] See also Figure 5 , Figure 5 This is a schematic block diagram of a medical care service robot provided by an embodiment of the present disclosure. Figure 5 The medical care service robot 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303 and one or more memories 304. The processor 301, input device 302, output device 303 and memory 304 communicate with each other through a communication bus 305. The memory 304 is used to store computer programs, and the computer program includes program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. Among them, the processor 301 is configured to call the program instructions to execute the functions of each module / unit in the above-mentioned device embodiments, such as Figure 3 The functions of modules 21 to 22 are shown.

[0122] It should be understood that in the embodiment of the present disclosure, the processor 301 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0123] The input device 302 may include a touch panel, a fingerprint collection sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.

[0124] The memory 304 may include a read-only memory and a random access memory, and provide instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0125] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of the robot control method provided in the embodiments of the present disclosure, and can also execute the implementation methods of the medical and nursing service robot described in the embodiments of the present disclosure, which will not be repeated here.

[0126] In another embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by the processor, all or part of the processes in the above-mentioned embodiment method are implemented, and the computer program can also be completed by instructing the relevant hardware through the computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0127] The computer-readable storage medium may be an internal storage unit of the medical care service robot of any of the aforementioned embodiments, such as a hard disk or memory of the medical care service robot. The computer-readable storage medium may also be an external storage device of the medical care service robot, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the medical care service robot. Furthermore, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the medical care service robot. The computer-readable storage medium is used to store computer programs and other programs and data required by the medical care service robot. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0128] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0129] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the medical and nursing service robot and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0130] In the several embodiments provided in the present application, it should be understood that the disclosed medical care service robots and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or it can be an electrical, mechanical or other form of connection.

[0131] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present disclosure.

[0132] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0133] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present disclosure, and these modifications or replacements should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A robot control method, characterized in that: include: In response to the operation mode of the robot being the first mode, receiving physiological monitoring data of the user sent by the first device; If the physiological monitoring data shows that the user's physiological state is a first state, determining a first time node based on the physiological monitoring data; controlling the robot to enter a dormant state at the first time node; the first state is used to indicate that the user is healthy, and the first device is a physiological monitoring device; In response to the operation mode of the robot being the second mode, controlling the robot to remain in the awake state; Also includes: Determining a third time node based on the user's historical physiological monitoring data; Sending a first prompt message to the user at a third time point; the first prompt message is used to remind the user to take medicine; In response to confirmation information input by the user in response to the first prompt information, controlling the medication mechanism to perform a medication action; The historical physiological monitoring data of the user includes physiological monitoring data of multiple dates, and determining the third time node based on the historical physiological monitoring data of the user includes: Draw a health curve of the user based on the historical physiological monitoring data; Determine the abnormal period of each date based on the health curve; the abnormal period is a period containing a specified extreme point of the health curve, and the specified extreme point is a maximum point or a minimum point of the health curve; The intersection of the abnormal periods of each date is determined as the first period; Determine the third time node based on the first time period; The abnormal periods for each date determined based on the health curve include: Determine the designated extreme points of the health curve for each date; The time point corresponding to the specified extreme value point is reduced by a fourth time length to obtain a first endpoint of the abnormal period, and the time point corresponding to the specified extreme value point is increased by a fourth time length to obtain a second endpoint of the abnormal period; determining a period between a first endpoint and a corresponding second endpoint as an abnormal period; Determining the third time node based on the first time period can be described in detail as follows: Selecting a fourth time period from the plurality of first time periods based on a specified rule; Selecting a third time node from a fourth time period; Also includes: In response to the user's physiological monitoring data showing that the user's daily routine changes from an awake state to a sleeping state, a control parameter of a fifth device is adjusted from a first parameter to a second parameter; the fifth device is a smart lighting device, a smart air conditioner or a smart curtain.

2. The robot control method according to claim 1, characterized in that: The determining the first time node based on the physiological monitoring data includes: At a plurality of second time points, receiving physiological monitoring data of the user sent by the first device; In response to the physiological monitoring data received at N consecutive second time nodes all being within a first set range, the N+1th second time node is determined as the first time node.

3. The robot control method according to claim 1, characterized in that: Also includes: In response to the robot being in a dormant state and the physiological monitoring data exceeding a first set range, the robot is controlled to exit the dormant state.

4. The robot control method according to claim 1, characterized in that: Also includes: In response to a call request sent by the second device, and the physiological monitoring data of the user is within a first set range, a first instruction is sent to the first device within a second time period, wherein the first instruction is used to instruct the first device to send a vibration prompt message, and the second device is a call device; A voice prompt message is issued in a third time period after the second time period.

5. The robot control method according to claim 1, characterized in that: Also includes: In response to a user moving from a first area to a second area, and the light intensity in the second area is less than a first threshold, a second instruction is sent to a third device, wherein the second instruction is used to instruct the third device to turn on; the third device is a lighting device in the second area; In response to the user leaving the first area for a duration greater than a third duration, a third instruction is sent to a fourth device, wherein the third instruction is used to instruct the fourth device to shut down; the fourth device is a lighting device in the first area.

6. A robot control device, implementing the robot control method according to any one of claims 1 to 5, characterized in that: include: A first processing module, configured to receive physiological monitoring data of a user sent by a first device in response to the operation mode of the robot being the first mode; If the physiological monitoring data shows that the user's physiological state is a first state, a first time node is determined based on the physiological monitoring data; at the first time node, the robot is controlled to enter a dormant state; the first state is used to indicate that the user is healthy; A second processing module, configured to control the robot to remain in a wake-up state in response to the operation mode of the robot being the second mode; The third processing module is used for: Determining a third time node based on the user's historical physiological monitoring data; Sending a first prompt message to the user at a third time point; the first prompt message is used to remind the user to take medicine; In response to confirmation information input by the user in response to the first prompt information, controlling the medication mechanism to perform a medication action; The user's historical physiological monitoring data includes physiological monitoring data of multiple dates, and the third processing module is specifically further used for: Draw the user's health curve based on historical physiological monitoring data; Determine the abnormal period of each date based on the health curve; the abnormal period is the period containing the specified extreme point of the health curve, and the specified extreme point is the maximum point or minimum point of the health curve; The intersection of the abnormal periods of each date is determined as the first period; Determine a third time node based on the first time period; The abnormal periods for each date determined based on the health curve include: Determine the designated extreme points of the health curve for each date; The time point corresponding to the specified extreme value point is reduced by a fourth time length to obtain a first endpoint of the abnormal period, and the time point corresponding to the specified extreme value point is increased by a fourth time length to obtain a second endpoint of the abnormal period; determining a period between a first endpoint and a corresponding second endpoint as an abnormal period; Determining the third time node based on the first time period can be described in detail as follows: Selecting a fourth time period from the plurality of first time periods based on a specified rule; Selecting a third time node from a fourth time period; In response to the user's physiological monitoring data showing that the user's daily routine changes from an awake state to a sleeping state, a control parameter of a fifth device is adjusted from a first parameter to a second parameter; the fifth device is a smart lighting device, a smart air conditioner or a smart curtain.

7. A medical care service robot, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

Images