Interaction method, interaction device, electronic device, and storage medium

Abstract

The application discloses an interaction method, an interaction device, an electronic device and a storage medium. The interaction method comprises the following steps: acquiring first health data collected by an electronic device; acquiring second health data of a wearable device when the first health data does not meet a preset standard; and calibrating the electronic device by using the second health data when a deviation between the first health data and the second health data is not within a preset range. In the interaction method, the wearable device is woken up to detect and obtain the second health data when the first health data does not meet the preset standard, the first health data and the second health data are compared, and the electronic device is calibrated by using the second health data when a deviation between the first health data and the second health data is not within a preset range. Therefore, the detection accuracy of the electronic device is improved, the number of data transmission between the electronic device and the wearable device is reduced, and additional power consumption of the electronic device and the wearable device is avoided.

Description

Technical Field

[0001] This application relates to the field of electronic technology, and more particularly to an interaction method, interaction device, electronic device, and storage medium. Background Technology

[0002] With the development of technology, smart devices such as smartwatches are widely used in daily life. However, due to the limitations of the built-in sensors in smartwatches, the accuracy of the health data detected by smartwatches is relatively low. Wearable devices, which are used in conjunction with smartwatches, can be used to detect relevant health data more accurately. How to improve the accuracy of data detected by smartwatches through wearable devices has become a problem to be solved. Summary of the Invention

[0003] This application provides an interaction method, an interaction device, an electronic device, and a storage medium.

[0004] This application provides an interaction method for an electronic device, the interaction method comprising:

[0005] Acquire the first health data collected by the electronic device;

[0006] If the first health data does not meet the preset standard, the second health data from the wearable device is obtained;

[0007] When the deviation between the first health data and the second health data is not within a preset range, the electronic device is calibrated using the second health data.

[0008] This application provides an interactive device, the interactive device comprising:

[0009] The acquisition module is used to acquire first health data collected by the electronic device, and to acquire second health data from the wearable device when the first health data does not meet a preset standard.

[0010] A calibration module is used to calibrate the electronic device using the second health data when the deviation between the first health data and the second health data is not within a preset range.

[0011] This application provides an electronic device, which includes a detection device and a processor; the detection device is used to detect first health data; the processor is used to acquire the first health data collected by the electronic device, and to acquire second health data from a wearable device when the first health data does not meet a preset standard, and to calibrate the electronic device with the second health data when the deviation between the first health data and the second health data is not within a preset range.

[0012] In the interaction method, interaction device, and electronic device of this application, if the first health data collected by the electronic device does not meet a preset standard, the wearable device can be woken up to detect and obtain second health data. Furthermore, the first and second health data can be compared, and if the deviation between the two is not within a preset range, the electronic device can be calibrated using the second health data. This not only improves the accuracy of the health data detected by the electronic device but also reduces the number of data transmissions between the electronic device and the wearable device, avoiding additional power consumption for both.

[0013] In some embodiments, this application provides a non-volatile computer-readable storage medium storing a computer program that, when executed by one or more processors, implements the interaction method of any of the above embodiments.

[0014] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0015] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, wherein:

[0016] Figure 1 This is a flowchart illustrating the interaction method of an embodiment of this application;

[0017] Figure 2 This is a schematic diagram of the interactive device according to an embodiment of this application;

[0018] Figure 3 This is a perspective view of the electronic device and wearable device according to the embodiments of this application;

[0019] Figure 4 This is a flowchart illustrating the interaction method of the embodiments of this application.

[0020] Figure 5 This is a flowchart illustrating the interaction method of an embodiment of this application;

[0021] Figure 6 This is a flowchart illustrating the interaction method of an embodiment of this application;

[0022] Figure 7 This is a flowchart illustrating the interaction method of an embodiment of this application.

[0023] Explanation of main components and symbols:

[0024] Electronic device 100, detection device 10, memory 11, processor 12, interactive device 200, acquisition module 21, calibration module 22, control module 23, wearable device 300, detection unit 31, Bluetooth module 32. Detailed Implementation

[0025] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0026] The following disclosure provides many different embodiments or examples for implementing different structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. In addition, various specific examples of processes and materials are provided in this application, but those skilled in the art will recognize the application of other processes and / or the use of other materials.

[0027] Please see Figure 1 This application provides an embodiment for an electronic device 100 (such as...) Figure 3 The interaction methods (shown) include:

[0028] Step S10: Acquire the first health data collected by the electronic device 100;

[0029] Step S20: When the first health data does not meet the preset standard, acquire the second health data from the wearable device 300;

[0030] Step S30: When the deviation between the first health data and the second health data is not within a preset range, calibrate the electronic device 100 with the second health data.

[0031] Please see Figure 2 This application provides an interactive device 200, which includes an acquisition module 21 and a calibration module 22. The interactive method of this application can be implemented by the interactive device 200. For example, steps S10 and S20 can be implemented by the acquisition module 21 of the interactive device 200, and step S30 can be implemented by the calibration module 22 of the interactive device 200.

[0032] Alternatively, the acquisition module 21 is used to acquire the first health data collected by the electronic device 100, and to acquire the second health data of the wearable device 300 when the first health data does not meet the preset standard; the calibration module 22 is used to calibrate the electronic device 100 with the second health data when the deviation between the first health data and the second health data is not within the preset range.

[0033] Please see Figure 3 This application also provides an electronic device 100, which includes a detection device 10 and a processor 12. The detection device 10 can be used to detect first health data, and the processor 12 can be used to acquire the first health data collected by the electronic device 100, acquire second health data from the wearable device 300, and calibrate the electronic device 100 with the second health data when the deviation between the first health data and the second health data is not within a preset range. The electronic device 100 may also include a memory 11, which can be used to store computer programs.

[0034] Specifically, the electronic device 100 in this application embodiment can be a small smart mobile terminal such as a smartwatch or smart bracelet. The wearable device 300 in this application embodiment can exist as an accessory to the electronic device 100. For example, when the electronic device 100 is a smartwatch, the wearable device 300 can be a smart watchband connected to the smartwatch. Of course, the wearable device 300 can also exist as other independent accessories and can be worn on any part of the user's limbs.

[0035] When a user wears the wearable device 300, the built-in detection unit 31 of the wearable device 300 has a detection function, which can be used to assist in detecting relevant information of the user. For example, the detection unit 31 may contain various types of sensors to detect the user's corresponding health data. The wearable device 300 also has a built-in communication module that can be used to communicate with the electronic device 100 to transmit data. For example, the wearable device 300 may have a built-in Bluetooth module 32, which can perform data transmission tasks with the electronic device 100.

[0036] Specifically, the embodiments of this application do not limit the specific forms of the electronic device 100 and the wearable device 300, but require that the wearable device 300 can connect to and communicate with the electronic device 100. In particular, the connection does not necessarily refer to a physical connection. In addition, the electronic device 100 mentioned below can be a smartwatch, and the corresponding wearable device 300 exists as an accessory to the electronic device 100, i.e., the smartwatch.

[0037] Thanks to the advancements in modern technology, smartwatches, as small electronic devices 100, not only possess the functions of traditional watches but also add intelligent features such as monitoring user physiological information and sleep patterns, making calls, and video calls. However, due to space limitations within the electronic device 100, the performance of the detection device 10 installed within it is restricted. Furthermore, the area of ​​contact between the electronic device 100 and the user is relatively small. Moreover, sensor drift within the detection device 10 is common during prolonged use. Therefore, relying solely on the user's health data collected by the electronic device 100 to analyze the user's health status has low accuracy.

[0038] In this embodiment, the wearable device 300, which is an accessory to the electronic device 100, can exist in the form of a smart watchband. Because the smart watchband fits the user's wrist better, a more powerful detection unit 31 can be installed on the wearable device 300, thus providing more powerful detection functions specifically for detecting relevant health data. However, compared to the electronic device 100, the wearable device 300 has higher power consumption. If the user's health data is always detected by the wearable device 300 and then synchronized to the electronic device 100, the battery life of both the electronic device 100 and the wearable device 300 cannot be guaranteed.

[0039] Therefore, the method provided in this application can be used to enable the electronic device 100 to selectively wake up the wearable device 300 to detect health data, so as to ensure the accuracy of the health data detected by the electronic device 100 while ensuring the battery life of the electronic device 100 and the wearable device 300.

[0040] Specifically, in step S10, the processor 12 in the electronic device 100 can acquire the first health data of the user collected by the detection device 10 collected by the electronic device 100. The first health data can be the user's heart rate, blood pressure, blood oxygen saturation and other values ​​that can reflect the user's health status to a certain extent. That is to say, there can be multiple health data.

[0041] In step S20, the preset standard can be the medically recognized normal range of a certain first health data. That is, when a certain first health data meets the preset standard, it is considered that the user's first health data is not abnormal. When a certain first health data does not meet the preset standard, it can be considered that the first health data may be abnormal.

[0042] Since there can be multiple primary health data points, the preset standard varies depending on the different primary health data points obtained in step S10. For example, when the wearable device 300 measures the user's resting heart rate, the preset standard is that the primary health data is within the range of greater than 50 beats / minute and less than 100 beats / minute; when the wearable device 300 measures the user's blood pressure, the preset standard is that the primary health data representing the user's systolic blood pressure is within the range of greater than 90 mmHg and less than 14 mmHg, and the primary health data representing the user's diastolic blood pressure is within the range of greater than 60 mmHg and less than 90 mmHg; when the wearable device 300 measures the user's blood oxygen saturation, the preset standard becomes that the primary health data is within the range of greater than 90%.

[0043] It's easy to understand that the three scenarios above are merely illustrative examples and do not constitute a limitation on the primary health data or preset standards. In reality, there are multiple primary health data points, and the preset standards are determined based on the specific primary health data point being measured.

[0044] When the first health data obtained in step S10 does not meet the preset standard, it indicates that the user's physiological indicator may be abnormal. However, since it cannot be ruled out that the abnormality of the first health data is caused by the abnormality of the detection device 10 of the electronic device 100, the electronic device 100 can obtain the second health data measured on the wearable device 300 through the processor 12, and then compare the difference between the first health data and the second health data for subsequent processing.

[0045] One way to obtain the second health data is through Bluetooth communication. Bluetooth is a low-cost, short-range wireless technology that establishes a communication environment for mobile devices. Specifically, Bluetooth can be Bluetooth Low Energy (BLE), which significantly reduces power consumption and cost compared to classic Bluetooth while maintaining the same communication range. Of course, other wireless communication methods such as Zigbee can also be used.

[0046] In step S30, when the second health data collected on the wearable device 300 is obtained according to step S20, the deviation between the first health data and the second health data can be analyzed. When it is confirmed that the deviation between the first health data and the second health data is not within the preset range, it can be considered that the detection device 10 on the electronic device 100 is abnormal, so as to make the measured first health data invalid. At this time, the electronic device 100 can be calibrated based on the second health data.

[0047] In particular, the preset range can be set according to actual needs. For example, the preset range can be set to the deviation between the first health data and the second health data within 0-20%.

[0048] In the interaction method, interaction device 200, and wearable device 300 of this application embodiment, when the first health data does not meet the preset standard, the wearable device 300 is woken up to perform detection to obtain the second health data. Then, the first health data and the second health data are compared. When the deviation between the two is not within the preset range, the electronic device 100 is calibrated with the second health data. This not only improves the detection accuracy of the electronic device 100, but also reduces the number of data transmissions between the electronic device 100 and the wearable device 300, avoiding additional power consumption for both the electronic device 100 and the wearable device 300.

[0049] Please see Figure 4 In some implementations, when the first health data does not meet a preset standard, the second health data of the wearable device 300 is acquired (step S20), including:

[0050] Step S21: Control the wearable device 300 to run the detection function to obtain secondary health data.

[0051] In some implementations, the acquisition module 21 is used to control the wearable device 300 to run a detection function to acquire second health data.

[0052] In some implementations, the processor 12 is used to control the wearable device 300 to run detection functions to obtain second health data.

[0053] Specifically, the wearable device 300 has a built-in detection unit 31 that is more powerful and has higher detection accuracy than the electronic device 100, and the electronic device 100 and the wearable device 300 can communicate via Bluetooth.

[0054] In step S21, when the first health data collected by the electronic device 100 does not meet the preset standard, the electronic device 100 controls the wake-up of the wearable device 300 via Bluetooth connection, and causes the built-in detection unit 31 on the wearable device 300 to start running to perform the detection function, so that the wearable device 300 can detect and collect the second health data. Then, the electronic device 100 can control the wearable device 300 to send the second health data to itself via Bluetooth communication, thereby obtaining the second health data.

[0055] In this way, the detection unit 31 on the wearable device 300 is only woken up by the electronic device 100 at a specific time to perform the detection function, and the electronic device 100 can easily interact with the wearable device 300 through Bluetooth communication.

[0056] Please see Figure 5In some implementations, the interaction method may further include:

[0057] Step S40: When the deviation between the first health data and the second health data is within a preset range, keep the wearable device 300 in a sleep state and control the electronic device 100 to continue operating.

[0058] In some embodiments, the interactive device 200 further includes a control module 23, which is used to keep the wearable device 300 in a sleep state and control the electronic device 100 to continue operating when the deviation between the first health data and the second health data is within a preset range.

[0059] In some implementations, the processor 12 is used to keep the wearable device 300 in a sleep state and control the electronic device 100 to continue operating when the deviation between the first health data and the second health data is within a preset range.

[0060] Specifically, in order to save power consumption of electronic device 100 and wearable device 300, in step S40, when it is determined that the deviation between the first health data and the second health data is within a preset range, the detection device 10 of electronic device 100 is considered to be in normal working condition. At this time, the first health data is considered to be valid, indicating that the user's corresponding physiological indicators are abnormal.

[0061] The first health data can then be further processed by other applications in the electronic device 100, such as saving the first health data, plotting the first health data curve, and issuing warning prompts.

[0062] Furthermore, when the deviation between the first health data and the second health data is within a preset range, it indicates that the electronic device 100 can continue to run the built-in detection device 10 to detect the user's physiological indicators. At the same time, in order to save power consumption, the processor 12 controls the detection unit 31 in the wearable device 300 to stop working and puts the wearable device 300 into a sleep state.

[0063] In this way, by comparing the deviation between the first health data and the second health data, and comparing the deviation with the preset range, different processing methods are adopted, so as to ensure the accuracy of the data detected by the electronic device 100, while also saving the power consumption of the electronic device 100 and the wearable device 300.

[0064] Please see Figure 6 In some embodiments, calibrating the electronic device 100 with second health data (step S30) includes:

[0065] Step S31: Communicate with wearable device 300 to receive second health data;

[0066] Step S32: Calibrate the detection device 10 of the electronic device 100 according to the second health data.

[0067] In some implementations, the calibration module 22 is used to communicate with the wearable device 300 to receive second health data, and to calibrate the detection device 10 of the electronic device 100 based on the second health data.

[0068] In some implementations, the processor 12 is used to communicate with the wearable device 300 to receive second health data, and to calibrate the detection device 10 of the electronic device 100 based on the second health data.

[0069] Specifically, in step S31, the electronic device 100 can wirelessly transmit data to the wearable device 300 via Bluetooth to receive the second health data sent by the wearable device 300. In step S32, the calibration of the detection device 10 can be achieved by: compensating for the first health data detected by the detection device 10 of the electronic device 10 based on the second health data, thereby calibrating the first health data with a large deviation, and achieving the purpose of calibrating the detection device 10 of the electronic device 100.

[0070] Thus, by comparing the deviation between the first health data and the second health data, and by performing calibration measures such as compensating the first health data based on the received second health data when the deviation is not within a preset range, the detection device 10 of the electronic device 100 can be calibrated.

[0071] Please see Figure 7 In some implementations, the interaction method may further include:

[0072] Step S50: When the first health data meets the preset standard, keep the wearable device 300 in a sleep state and control the electronic device 100 to continue operating.

[0073] In some implementations, step S50 can be implemented by the control module 23. That is, the control module 23 is used to keep the wearable device 300 in a sleep state and control the electronic device 100 to continue operating when the first health data meets the preset standard.

[0074] In some implementations, the processor 12 is used to keep the wearable device 300 in a sleep state and control the electronic device 100 to continue operating when the first health data meets a preset standard.

[0075] Specifically, after processing in step S10, in step S50, when it is determined that the first health data meets the preset standard, in order to save the power consumption of electronic device 100 and wearable device 300, the wearable device 300, which is in a sleep state, can be controlled to remain in sleep state, and the electronic device 100 can continue to run until the first health data obtained does not meet the preset standard, at which point the electronic device 100 will perform further processing.

[0076] Thus, by keeping the wearable device 300 in a sleep state when the first health data meets the preset standard, the power consumption of the wearable device 300 can be saved and the battery life of the wearable device 300 can be improved; controlling the electronic device 100 to continue to operate can enable the detection device 10 in the electronic device 100 to detect the user's physiological indicators in real time.

[0077] This application provides a non-volatile computer-readable storage medium storing a computer program, which, when executed by one or more processors 12, causes the processors 12 to perform the interaction method of any of the above embodiments.

[0078] For example, when a computer program is executed by processor 12, processor 12 may perform the following steps:

[0079] Step S10: Acquire the first health data collected by the electronic device 100;

[0080] Step S20: When the first health data does not meet the preset standard, acquire the second health data from the wearable device 300;

[0081] Step S30: When the deviation between the first health data and the second health data is not within a preset range, calibrate the electronic device 100 with the second health data.

[0082] Specifically, in the interaction method provided in this application, via step S10, the processor 12 can acquire the first health data collected by the electronic device 100; via step S20, when it is determined that the first health data does not meet the preset standard, the electronic device 100 wakes up the detection unit 31 in the wearable device 300 to perform the detection function, and then acquires the second health data collected by the wearable device 300 through Bluetooth communication; via step S30, when it is determined that the deviation between the first health data and the second health data is not within the preset range, that is, the deviation is too large, the detection device 10 of the electronic device 100 can be calibrated according to the received second health data.

[0083] In addition, in this interactive method, step S40 can be used to compare the deviation between the first health data and the second health data. When the deviation is within a preset range, the wearable device 300 can be controlled to go into sleep mode while the electronic device 100 continues to operate. Alternatively, step S50 can be used to keep the wearable device 300 in sleep mode while the electronic device 100 continues to operate when the first health data obtained in step S10 meets the preset standard.

[0084] In this way, the wearable device 300 can be woken up at the appropriate time to perform the detection function, which not only ensures the accuracy of the data detected by the electronic device 100, but also saves the power consumption of the electronic device 100 and the wearable device 300, and improves the battery life of the electronic device 100 and the wearable device 300.

[0085] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), etc.

[0086] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0087] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. An interaction method applied to an electronic device, characterized in that, The interaction method comprises: acquiring first health data collected by the electronic device; the first health data comprises multiple physiological health data; when the first health data meets a preset standard, keeping a wearable device in a dormant state and controlling the electronic device to continue running; the wearable device is an accessory of the electronic device; when the first health data does not meet the preset standard, waking up the wearable device for detection and acquiring second health data of the wearable device; the second health data is used to determine a reason why the first health data does not meet the preset standard; the reason comprises that the first health data is abnormal or a detection device of the electronic device is abnormal; when a deviation between the first health data and the second health data is not within a preset range, calibrating the detection device of the electronic device with the second health data.

2. The interaction method of claim 1, wherein, The acquiring second health data of the wearable device when the first health data does not meet the preset standard comprises: controlling the wearable device to run a detection function to acquire the second health data.

3. The interaction method of claim 1, wherein, The interaction method comprises: when the deviation between the first health data and the second health data is within the preset range, keeping the wearable device in the dormant state and controlling the electronic device to continue running.

4. The interaction method of claim 1, wherein, The calibrating the electronic device with the second health data comprises: communicating with the wearable device to receive the second health data; calibrating the detection device of the electronic device according to the second health data.

5. An interactive device, characterized by The interaction device comprises: an acquiring module, configured to acquire first health data collected by an electronic device; the first health data comprises multiple physiological health data; the acquiring module is further configured to, when the first health data meets a preset standard, keep a wearable device in a dormant state and control the electronic device to continue running; when the first health data does not meet the preset standard, wake up the wearable device for detection and acquire second health data of the wearable device; the wearable device is an accessory of the electronic device; the second health data is used to determine a reason why the first health data does not meet the preset standard; the reason comprises that the first health data is abnormal or a detection device of the electronic device is abnormal; a calibrating module, configured to, when a deviation between the first health data and the second health data is not within a preset range, calibrate the detection device of the electronic device with the second health data.

6. An electronic device, comprising: The electronic device comprises a detection device and a processor; the detection device is configured to detect first health data; the first health data comprises multiple physiological health data; the processor is configured to acquire first health data collected by an electronic device; the processor is further configured to, when the first health data meets a preset standard, keep a wearable device in a dormant state and control the electronic device to continue running; when the first health data does not meet the preset standard, wake up the wearable device for detection and acquire second health data of the wearable device; the wearable device is an accessory of the electronic device. The second health data is used to determine a reason why the first health data does not meet the preset standard; the reason includes that the first health data is abnormal, or a detection device of the electronic device is abnormal; The processor is further configured to calibrate the detection device of the electronic device with the second health data when a deviation between the first health data and the second health data is not within a preset range. 7.The electronic device of claim 6, wherein, The processor is configured to control the wearable device to run a detection function to obtain the second health data. 8.The electronic device of claim 6, wherein, The processor is configured to keep the wearable device in a dormant state and control the electronic device to continue running when the deviation between the first health data and the second health data is within the preset range. 9.The electronic device of claim 6, wherein, The processor is configured to communicate with the wearable device to receive the second health data, and calibrate the detection device of the electronic device according to the second health data.

10. A non-transitory computer readable storage medium storing a computer program, characterized in that, The computer program, when executed by one or more processors, implements the interaction method of any one of claims 1-4.

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