Health monitoring device and control method, control device and wearable device therefor

Abstract

The application discloses a health monitoring device and a control method, a control device and a wearable device thereof, the health monitoring device comprises a plurality of human parameter detection devices for detecting human information, the method comprises the following steps: outputting a calibration signal to the plurality of human parameter detection devices; starting first timing when the calibration feedback signal output by the human parameter detection device is acquired; when the calibration feedback signal matches the preset signal state, at least one first duration corresponding to the first timing is generated according to the duration of the first timing; and the calibration time difference corresponding to each human parameter detection device is determined according to the at least one first duration corresponding to each human parameter detection device. The technical scheme of the application aims to improve the accuracy of detecting human health information.

Description

Technical Field

[0001] This invention relates to the field of health monitoring devices, and in particular to a health monitoring device and its control method, control device, and wearable device. Background Technology

[0002] Currently, human health monitoring typically employs one or more detection devices for data collection. However, these devices use different data transmission paths, resulting in varying time differences in the transmission of the collected human health parameters across these paths. This time difference can affect the accuracy of the calculated health information. Summary of the Invention

[0003] The main objective of this invention is to propose a control method for a health monitoring device, which aims to improve the accuracy of detecting human health information.

[0004] To achieve the above objectives, the present invention proposes a health monitoring device control method, which is applied to a health monitoring device including multiple human parameter detection devices for detecting human information. The method includes the following steps:

[0005] Output calibration signals to multiple human body parameter detection devices;

[0006] The first timing begins upon receiving the calibration feedback signal from the human body parameter detection device;

[0007] When the calibration feedback signal matches the preset signal state, at least one corresponding first duration is generated according to the duration of the first timing.

[0008] The corresponding calibration time difference is determined based on at least one first duration corresponding to each human body parameter detection device.

[0009] Optionally, the step of outputting calibration signals to multiple human parameter detection devices includes:

[0010] Output calibration signals with a preset first frequency to multiple human body parameter detection devices;

[0011] The step of starting the first timing when the calibration feedback signal output by the human body parameter detection device is obtained includes:

[0012] The calibration feedback signal output by the human body parameter detection device is acquired according to a preset second frequency, and a first timing begins as soon as the calibration feedback signal is acquired; wherein, the preset second frequency is greater than the preset first frequency.

[0013] Optionally, the preset second frequency is greater than or equal to twice the preset first frequency.

[0014] Optionally, the preset signal state includes any one of the following states: starting rising edge, starting falling edge, peak, and trough.

[0015] Optionally, the step of determining the corresponding calibration time difference based on at least one first duration corresponding to each human body parameter detection device includes:

[0016] When the number of the first durations corresponding to each human body parameter detection device is one, the corresponding calibration time difference is determined according to the first duration corresponding to each human body parameter detection device.

[0017] When there are multiple first durations corresponding to each human body parameter detection device, the multiple first durations corresponding to each human body parameter detection device are added together to obtain a second duration, and the corresponding calibration time difference is determined based on at least one second duration corresponding to each human body parameter detection device.

[0018] Optionally, the number of the plurality of human body parameter detection devices is two, and the step of determining the corresponding calibration time difference based on the first duration corresponding to each human body parameter detection device includes:

[0019] The calibration time difference is determined by subtracting the first duration corresponding to the two human body parameter detection devices.

[0020] The step of determining the corresponding calibration time difference based on at least one second duration corresponding to each human body parameter detection device includes:

[0021] The calibration time difference is determined by subtracting the second duration corresponding to the two human body parameter detection devices.

[0022] Optionally, the two human parameter detection devices include an infrared non-destructive testing sensor and a sound acquisition sensor.

[0023] The present invention also proposes a control device, comprising:

[0024] Controller;

[0025] The memory stores a health monitoring device control program, which, when executed by the controller, implements the health monitoring device control method as described above.

[0026] The present invention also proposes a health detection device, including the control device described above.

[0027] The present invention also proposes a wearable device, characterized in that it includes the health monitoring device described above.

[0028] In this invention, calibration signals are first output to multiple human parameter detection devices. Upon receiving calibration feedback signals from these devices, a first timing cycle begins. When the calibration feedback signal matches a preset signal state, at least one corresponding first duration is generated based on the duration of the first timing cycle. Then, based on the at least one first duration corresponding to each human parameter detection device, a corresponding calibration time difference is determined. In this way, the time difference between the output signals of multiple human parameter detection devices can be determined using calibration signals, and the corresponding calibration time difference can be obtained. When judging human health information through human parameters, substituting the corresponding calibration time difference into the calculation can reduce the impact of time errors in the output signals of multiple human parameter detection devices, thereby improving the accuracy of detecting human health information. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0030] Figure 1 This is a flowchart of the method steps of an embodiment of the health monitoring device control method of the present invention;

[0031] Figure 2 This is a flowchart of the method steps of another embodiment of the health monitoring device control method of the present invention;

[0032] Figure 3 This is a flowchart of the method steps for another embodiment of the health monitoring device control method of the present invention;

[0033] Figure 4 This is a flowchart of the method steps in another embodiment of the health monitoring device control method of the present invention.

[0034] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0036] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0037] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0038] This invention proposes a control method for a health monitoring device, which is applied to a health monitoring device including multiple human parameter detection devices for detecting human information.

[0039] Reference Figure 1 In one embodiment of the present invention, the health monitoring device control method includes the following steps:

[0040] S100: Output calibration signals to multiple human body parameter detection devices;

[0041] S200. Upon receiving the calibration feedback signal output by the human body parameter detection device, the first timing begins.

[0042] S300. When the calibration feedback signal matches the preset signal state, at least one corresponding first duration is generated according to the duration of the first timing.

[0043] S400. Determine the corresponding calibration time difference based on at least one first duration corresponding to each human body parameter detection device.

[0044] In this embodiment, before the user uses the health monitoring device or before the device leaves the factory, the health monitoring device can calibrate the time taken by multiple human parameter detection devices to detect human information, thereby improving the accuracy of the obtained multiple human parameters and making the subsequent judgment of human health status more accurate when the health monitoring device is working. When the health monitoring device starts calibration, multiple human parameter detection devices can enter the data acquisition mode, collect human parameters, and receive calibration signals. Each human parameter detection device will output a corresponding calibration feedback signal. It can be understood that in this embodiment, the duration of outputting calibration signals to multiple human parameter detection devices can be set in the range of 10 to 30 seconds. The resulting calibration time difference can calibrate the human parameters collected within the range of 10 to 30 seconds. This is applicable to wearable devices with health detection times in the range of 10 to 30 seconds. If the health detection time is too short, it may not be able to detect all the data. If the health detection time is too long, it may affect the user experience. Therefore, this embodiment selects a calibration time difference in the range of 10 to 30 seconds. Of course, this solution does not limit the time range to 10 to 30 seconds.

[0045] Specifically, when a calibration feedback signal is received from the human parameter detection device, the first timing can begin, for example, starting when the calibration feedback signal is received, with an initial timing duration of 0 seconds. Furthermore, when the calibration feedback signal matches a preset signal state, at least one corresponding first duration can be generated based on the duration of the first timing. For example, if the first timing is 1 millisecond when a match between the calibration feedback signal and the preset signal state is detected, then the first duration is the first timing when the calibration feedback signal matches the preset signal state minus the initial timing, which is 1 millisecond. It can be understood that if the duration of the output calibration signal is set to 30 seconds, within 30 seconds, the calibration feedback signal may have multiple states matching the preset signal state; therefore, each time a match between the calibration feedback signal and the preset signal state is detected, a first duration is generated.

[0046] Since the calibration involves multiple human parameter detection devices, the preset signal can be selected from the common states of the calibration feedback signals output by multiple human parameter detection devices, such as peaks or troughs. This embodiment does not impose any restrictions. After obtaining at least one first duration corresponding to each human parameter detection device, the corresponding calibration time difference can be determined. Taking two human parameter detection devices as an example, if the duration of the output calibration signal is set to 30 seconds, the difference between the at least one first duration corresponding to the two human parameter detection devices can be obtained one by one, resulting in at least one time difference value. Adding the at least one time difference value gives the calibration time difference between the two human parameter detection devices within the 30-second duration. Using this calibration time difference as a calibration standard, when the health monitoring device is working and calculating human health information, the calibration time difference can be substituted to improve the accuracy of detecting human health information. For example, measuring human blood pressure requires calculation based on the pulse wave transmission time, which can be calculated using heart sound signals and pulse waves from the fingers or wrists. Heart sounds and pulse waves from the fingers or wrists can be detected using human parameter detection devices, such as a sound sensor to collect heart sounds and an infrared non-destructive sensor to collect pulse waves from the fingers or wrists. The method described in this embodiment reduces errors in blood pressure calculation caused by time errors in the transmission paths of the sound sensor and the infrared non-destructive sensor. When human parameters from two or more detection devices are needed to determine health information, the above explanation can also be used to reduce errors and improve accuracy; further details will not be provided here.

[0047] In this invention, calibration signals are first output to multiple human parameter detection devices. Upon receiving calibration feedback signals from these devices, a first timing cycle begins. When the calibration feedback signal matches a preset signal state, at least one corresponding first duration is generated based on the duration of the first timing cycle. Then, based on the at least one first duration corresponding to each human parameter detection device, a corresponding calibration time difference is determined. In this way, the time difference between the output signals of multiple human parameter detection devices can be determined using calibration signals, and the corresponding calibration time difference can be obtained. When judging human health information through human parameters, substituting the corresponding calibration time difference into the calculation can reduce the impact of time errors in the output signals of multiple human parameter detection devices, thereby improving the accuracy of detecting human health information.

[0048] It is important to understand that the human body parameter detection device outputs valid data at a certain frequency during operation. Therefore, the calibration signal output to the human body parameter detection device and the frequency of acquiring the calibration feedback signal need to be set accordingly.

[0049] Therefore, in one embodiment, the step of outputting calibration signals to multiple human parameter detection devices includes:

[0050] S110. Output a calibration signal with a preset first frequency to multiple human body parameter detection devices;

[0051] The step of starting the first timing when the calibration feedback signal output by the human body parameter detection device is obtained includes:

[0052] S210. Acquire the calibration feedback signal output by the human body parameter detection device according to a preset second frequency, and start the first timing when the calibration feedback signal is acquired; wherein, the preset second frequency is greater than the preset first frequency.

[0053] In this embodiment, the frequency of the calibration signal output to the multiple human parameter detection devices can be a preset first frequency. The preset first frequency can be set according to the frequency of the effective data output by the human parameter detection devices during actual operation. For example, if the frequency of the effective data output by the human parameter detection devices is within 500Hz, the preset first frequency can be set to 1000Hz, or it can be set to greater than 500Hz. In this way, the effective data output by the human parameter detection devices and the calibration feedback signal can be distinguished. The specific preset first frequency can also be adjusted according to user needs, and there is no limitation here.

[0054] Because the calibration feedback signal may have multiple states that match the preset signal state, sampling the calibration feedback signal at a certain frequency can improve sampling accuracy and avoid missing states that do not match the preset signal state. The sampling frequency of the calibration feedback signal can be set to a frequency greater than a preset first frequency. For example, if the preset first frequency is set to 1000Hz, then the preset second frequency can be set to 2000Hz. The specific preset second frequency can be adjusted according to user needs; this embodiment does not impose any limitations. This allows for more accurate acquisition of the preset signal state of the calibration feedback signal, improving the accuracy of subsequent calculations.

[0055] In one embodiment, the preset second frequency is greater than or equal to twice the preset first frequency.

[0056] In this embodiment, setting the preset second frequency to be greater than or equal to twice the preset first frequency can improve the completeness of the preset signal state acquisition of the calibration feedback signal. If the preset second frequency is set to be greater than the preset first frequency but less than twice the preset first frequency, it may be impossible to completely acquire all the preset signal states of the calibration feedback signal, resulting in errors in the subsequent calculation of the calibration time difference.

[0057] In one embodiment, the preset signal state includes any one of the following states: starting rising edge, starting falling edge, peak, and trough.

[0058] In this embodiment, any of the following states—the initial rising edge, the initial falling edge, the peak, and the trough—can be used as the preset signal state. These states are easily detected in the calibration feedback signal, thus improving detection accuracy and preventing errors in the calculation of the calibration time difference due to the inability to detect the preset signal state. Therefore, the preset signal state can also be any other specific common state among the calibration feedback signals output by multiple human parameter detection devices, such as a state that occurs once within a signal cycle.

[0059] In one embodiment, the step of determining the corresponding calibration time difference based on at least one first duration corresponding to each human body parameter detection device includes:

[0060] S410. When the number of the first durations corresponding to each human body parameter detection device is one, determine the corresponding calibration time difference based on the first duration corresponding to each human body parameter detection device.

[0061] S420. When there are multiple first durations corresponding to each human body parameter detection device, the multiple first durations corresponding to each human body parameter detection device are added together to obtain a second duration, and the corresponding calibration time difference is determined according to at least one second duration corresponding to each human body parameter detection device.

[0062] In this embodiment, if only one state in the calibration feedback signal output by each human body parameter detection device matches the preset signal state, then, as described in the above embodiment, the number of first durations corresponding to each human body parameter detection device is one; the corresponding calibration time difference can then be determined by calculation based on the first duration corresponding to each human body parameter detection device. If multiple states in the calibration feedback signal output by each human body parameter detection device match the preset signal state, then, as described in the above embodiment, the number of first durations corresponding to each human body parameter detection device is multiple. Adding the multiple first durations of each human body parameter detection device to obtain the second duration, multiple human body parameter detection devices correspond to multiple second durations; then, by calculation based on the multiple second durations, the calibration time difference between multiple human body parameter detection devices can be determined. Specifically, the calibration time difference between multiple human body parameter detection devices can be obtained by subtraction, or it can be calculated using machine learning; no limitation is imposed here.

[0063] In one embodiment, the number of the plurality of human body parameter detection devices is two, and the step of determining the corresponding calibration time difference based on the first duration corresponding to each human body parameter detection device includes:

[0064] S411. After subtracting the first durations corresponding to the two human body parameter detection devices, determine the calibration time difference;

[0065] The step of determining the corresponding calibration time difference based on at least one second duration corresponding to each human body parameter detection device includes:

[0066] S421. The calibration time difference is determined by subtracting the second duration corresponding to the two human body parameter detection devices.

[0067] In this embodiment, when human health information needs to be determined through two human parameters, the number of human parameter detection devices can be set to two. The specific human parameters detected by each device can be determined based on the human health information the user needs to detect. For example, to detect a user's blood pressure information, the pulse wave transmission time needs to be determined by the pulse wave and heart sound signal from the finger or wrist to calculate the blood pressure information. In this case, two human parameter detection devices can be selected to collect the pulse wave and heart sound signal from the finger or wrist. The corresponding calibration time difference is determined based on the first duration corresponding to each human parameter detection device. Specifically, this can be achieved by subtracting the first durations corresponding to the two human parameter detection devices. Similarly, the corresponding calibration time difference is determined based on at least one second duration corresponding to each human parameter detection device. Alternatively, the calibration time difference between the two human parameter detection devices can be calculated using machine learning or other methods; no limitation is imposed here.

[0068] In one embodiment, the two human parameter detection devices include an infrared non-destructive testing sensor and a sound acquisition sensor.

[0069] In this embodiment, when there are two human parameter detection devices, an infrared non-destructive testing sensor can be used to collect pulse waves from the fingers or wrists, and a sound acquisition sensor can be used to collect heart sound signals. The sound acquisition sensor includes, but is not limited to, microphones, accelerometers, or VPUs (voice amplifiers) and other sound data acquisition devices, placed on the user's chest to collect the user's heart sound signals. Thus, the pulse wave transmission time can be determined using the pulse waves from the fingers or wrists and the heart sound signals, thereby calculating the user's blood pressure information. The pulse wave transmission time is the time difference between the peak point of the first heart sound and the peak point of the main pulse wave in the same cardiac cycle. Since the two sensors are different and have different data transmission paths, the time difference between the transmission of the collected heart sound and pulse wave data in their respective paths is also different. Therefore, this solution obtains a calibration time difference through calibration and substitutes this calibration time difference into the calculation formula for the pulse wave transmission time, which can reduce errors and improve the accuracy of detecting human health information.

[0070] Understandably, when other human health information needs to be determined through two other human parameters, the corresponding human parameter detection device can also be selected. For example, pulse wave transmission time can also be determined through electrocardiogram (ECG) signals and pulse waves from the fingers or wrists. In this case, an ECG sensor can be selected to collect ECG signals, and an infrared non-destructive testing sensor can be selected to collect pulse waves from the fingers or wrists.

[0071] The present invention also proposes a control device.

[0072] In one embodiment, the control device includes a controller;

[0073] The memory stores a health monitoring device control program, which, when executed by the controller, implements the health monitoring device control method as described above.

[0074] In this embodiment, the controller can be a digital signal processor (DSP), a field-programmable gate array (FPGA), a microprocessor, an MCU, or other electronic components. The memory can be an E2PROM or DDR3 type memory, which can store the control program for the health monitoring device.

[0075] The present invention also proposes a health monitoring device. The specific structure of the health monitoring device is as described in the above embodiments. Since this wearable device adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be described in detail here.

[0076] In one embodiment, the health monitoring device may also include, but is not limited to, a graphics processor, a display module, a wireless communication module, and a motion sensor. The graphics processor can draw graphical content and drive the display module to display the graphics. The display module can be electrically connected to a controller; the controller can control the graphics processor to drive the display module to display corresponding human health information. The wireless communication module can also be electrically connected to the controller, and can also communicate with external devices, outputting blood pressure information signals from the controller to the external devices. The wireless communication module can be, but is not limited to, a Bluetooth module, a WiFi module, a 4G mobile communication module, etc. The display module can display human health information in the form of images, videos, UI, etc. The motion sensor module includes, but is not limited to, an accelerometer and a gyroscope, for detecting the user's motion data.

[0077] The present invention also proposes a wearable device, including the health monitoring device as described above. The specific structure of the health monitoring device is as described in the above embodiments. Since this wearable device adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.

[0078] In one embodiment, the wearable device can be a watch, a breast patch, or clothing—items worn close to the body. The health monitoring device within such a wearable device can collect and detect human information with high accuracy. For individuals with conditions such as hypertension, the wearable device allows for quick monitoring of their health status.

[0079] The above description is merely an optional embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention's specification and drawings under the technical concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A control method for a health monitoring device, applied to a health monitoring device, characterized in that, The health monitoring device includes multiple human parameter detection devices for detecting human information, and the method includes the following steps: Output calibration signals to multiple human body parameter detection devices; The first timing begins upon receiving the calibration feedback signal from the human body parameter detection device; When the calibration feedback signal matches the preset signal state, at least one corresponding first duration is generated according to the duration of the first timing. Based on at least one first duration corresponding to each human body parameter detection device, a corresponding calibration time difference is determined; The human body parameter detection device includes a human body parameter detection device for collecting pulse waves from the fingers or wrists and a human body parameter detection device for collecting heart sound signals.

2. The health monitoring device control method as described in claim 1, characterized in that, The step of outputting calibration signals to multiple human parameter detection devices includes: Output calibration signals with a preset first frequency to multiple human body parameter detection devices; The step of starting the first timing when the calibration feedback signal output by the human body parameter detection device is obtained includes: The calibration feedback signal output by the human body parameter detection device is acquired according to a preset second frequency, and a first timing begins as soon as the calibration feedback signal is acquired; wherein, the preset second frequency is greater than the preset first frequency.

3. The health monitoring device control method as described in claim 2, characterized in that, The preset second frequency is greater than or equal to twice the preset first frequency.

4. The health monitoring device control method as described in claim 1, characterized in that, The preset signal state includes any one of the following states: starting rising edge, starting falling edge, peak, and trough.

5. The health monitoring device control method as described in claim 1, characterized in that, The step of determining the corresponding calibration time difference based on at least one first duration corresponding to each human body parameter detection device includes: When the number of the first durations corresponding to each human body parameter detection device is one, the corresponding calibration time difference is determined according to the first duration corresponding to each human body parameter detection device. When there are multiple first durations corresponding to each human body parameter detection device, the multiple first durations corresponding to each human body parameter detection device are added together to obtain a second duration, and the corresponding calibration time difference is determined based on at least one second duration corresponding to each human body parameter detection device.

6. The health monitoring device control method as described in claim 5, characterized in that, The number of the multiple human parameter detection devices is two, and the step of determining the corresponding calibration time difference based on the first duration corresponding to each human parameter detection device includes: The calibration time difference is determined by subtracting the first duration corresponding to the two human body parameter detection devices. The step of determining the corresponding calibration time difference based on at least one second duration corresponding to each human body parameter detection device includes: The calibration time difference is determined by subtracting the second duration corresponding to the two human body parameter detection devices.

7. The health monitoring device control method as described in claim 6, characterized in that, The two human body parameter detection devices include an infrared non-destructive testing sensor and a sound acquisition sensor.

8. A control device, characterized in that, include: Controller; The memory stores a health monitoring device control program, which, when executed by the controller, implements the health monitoring device control method as described in any one of claims 1-7.

9. A health monitoring device, characterized in that, Includes the control device as described in claim 8.

10. A wearable device, characterized in that, Includes the health monitoring device as described in claim 9.

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