CN106580292B - Method for correcting measurement result of intelligent bracelet sensor - Google Patents

Abstract

A method for correcting the measurement result of a sensor of a smart wearable device, where ΔN is the difference between the actual measurement value N of the heart rate sensor and the display value N _s of the smart wearable device, ΔN=N-N _s , N _s is the heart rate value displayed by the smart wearable device after correction; mark ΔF as the difference between the actual measurement value F of the pressure sensor and the standard guidance pressure F ₀ , ΔF=F-F ₀ ; through the test, A function curve ΔN=g(ΔF) of ΔN with respect to ΔF is fitted, and the curve is stored in the storage module. Therefore, even when the user does not wear the smart wearable device correctly, the user can still obtain relatively accurate body parameters through effective calculation by the processor.

Description

A method for correcting the measurement results of a smart bracelet sensor

technical background

The invention relates to a method for debugging a smart wearable device, in particular to a method for debugging the accuracy of a functional module of the smart wearable device.

Background technique

At present, smart bracelets have been widely used in people's healthy life. In order to enable users to track their physical parameters and movement conditions in time, with the development of sensor technology, smart bracelets have basic timing and step counting in addition to basic timing and step counting. , innovatively integrates sensors that can monitor human body data, such as heart rate sensors, blood pressure sensors, blood oxygen sensors, etc. When the smart bracelet integrated with the above-mentioned multiple sensors is used, according to the user's feedback, there is a certain deviation between the detection result and the medical measurement result, and the deviation varies from person to person; There is a certain regularity in the deviation. In the current smart bracelets, the pressure sensor is used to directly measure the blood pressure and heart rate parameters of the human body, and it is not used as an auxiliary means to judge the measurement accuracy of the functional sensor.

At the same time, the applicant has described in another invention patent application an adjustment method for the correct wearing of the pressure sensor-based bracelet, which enables the user to adjust in a direction that can accurately measure human parameters when wearing the smart wearable device. However, most of the time, the wearing state that can measure relatively accurate human parameters is not the best way to experience the user's wearing. Therefore, it is very necessary to implement a relatively accurate way to measure the user's best experience of the wearing way. Human parameters.

SUMMARY OF THE INVENTION

According to the above technical problems, through experimental analysis, the influence of sensor factors is excluded, and the user experience is analyzed, and it is found that when the user wears the smart bracelet, the results measured by the sensor (such as heart rate, blood oxygen, blood pressure, etc.) , It is related to wearing habits. When the contact method between the smart bracelet and the wrist is different from that recommended by the manufacturer, the results measured by the sensor have regular deviations or irregular deviations. The present invention firstly finds the reasons for the above deviations (that is, the wearing habits of users) on the basis of the existence of deviations, and secondly proposes specific solutions for the above reasons. The calculation method of the data is improved so that the user can know whether the smart bracelet is correctly worn, and if the smart bracelet is not properly worn, the improvement in the correct wearing direction (this improvement has been reported in another invention patent of the applicant). disclosed in the application), even when the smart bracelet is not properly worn, the user can relatively accurately obtain his own body parameters through the sensor. The specific scheme of the present invention is as follows:

A method for correcting a measurement result of a sensor of a smart wearable device, the smart wearable device includes a heart rate sensor and a processor, and the smart bracelet further includes a pressure sensor 101; the method includes the following steps:

In step 1, the processor further includes a storage module, which stores the standard guide pressure F ₀ measured by the pressure sensor when the smart wearable device is worn correctly, the heart rate value N ₀ measured by human medical science, and the standard guide pressure measured by the pressure sensor when the smart wearable device is correctly worn. In the case where the heart rate value N is detected (that is, N is greater than 0), the minimum pressure value F _min and the maximum pressure value F _max measured by the pressure sensor when the smart wearable device is correctly worn;

Step 2, after the user wears the smart wearable device, the processor controls the pressure sensor to measure the actual pressure F between the smart wearable device and the user; the processor controls the heart rate sensor to measure the heart rate value N,

Step 3, denote ΔN as the difference between the actual measurement value N of the heart rate sensor and the display value N _s of the smart wearable device, ΔN=N-N _s , and N _s is the corrected smart wearable device The displayed heart rate value; mark ΔF as the difference between the actual measurement value F of the pressure sensor and the standard guide pressure F ₀ , ΔF=F-F ₀ ; through experiments, the function curve ΔN of ΔN about ΔF is fitted =g(ΔF), and store the curve in the storage module;

Step 4, when the actual pressure F measured by the pressure sensor, the processor first calculates ΔF according to ΔF=F-F ₀ , and then retrieves the function curve ΔN=g(ΔF) in the storage module, The ΔN value is obtained, and finally N _s is calculated according to ΔN=N-N _s , and the N _s is used as the corrected heart rate value displayed by the smart wearable device.

Further, when there are at least two pressure sensors, and the at least two pressure sensors include a left pressure sensor and a right pressure sensor, the method includes the following steps: Step 1, the processor further includes a storage module, the storage The module stores the standard guiding pressures F ₀₁ and F ₀₂ measured by the pressure sensor when the smart wearable device is worn correctly, the heart rate value N ₀ measured by the human body medicine, and the detectable heart rate value N (that is, N is greater than 0). In this case, the minimum pressure value F _min1 and the maximum pressure value F _max1 measured by the left pressure sensor when the smart wearable device is correctly worn, and the minimum pressure measured by the right pressure sensor when the smart wearable device is correctly worn value F _min2 and maximum pressure value F _max2 ;

Step 2, after the user wears the smart wearable device, the processor controls the left pressure sensor and the right pressure sensor to measure the actual pressures F ₁ and F ₂ between the smart wearable device and the user; the processing The controller controls the heart rate sensor to measure the heart rate value N;

Step 3, denote ΔN as the difference between the actual measurement value N of the heart rate sensor and the display value N _s of the smart wearable device, ΔN=N-N _s , and N _s is the corrected smart wearable device The displayed heart rate value; mark ΔF ₁ as the difference between the actual measurement value F ₁ of the left pressure sensor and the standard guide pressure F ₀₁ , ΔF ₁ = F ₁ - F ₀₁ ; mark ΔF ₂ as the left pressure The difference between the actual measurement value F ₂ of the sensor and the standard guide pressure F ₀₂ , ΔF ₂ = F ₂ - F ₀₂ ; through experiments, the function curve of ΔN about ΔF is fitted ΔN=h (ΔF ₁ , ΔF ₂ ), and store the curve in the storage module;

Step 4, when the actual pressure F ₁ measured by the left pressure sensor and the actual pressure F ₂ measured by the right pressure sensor, the processor firstly bases on ΔF ₁ = F ₁ - F ₀₁ and ΔF ₂ = F ₂ - F ₀₂ calculates ΔF ₁ and ΔF ₂ , then calls the function curve ΔN=h (ΔF ₁ , ΔF ₂ ) in the storage module to obtain the ΔN value, and finally calculates N according to ΔN=N-N _{s s} , and use the N _s as the corrected heart rate value displayed by the smart wearable device.

Further, in the above two methods, ΔF can be redefined, and when the measurement error of the pressure sensor is allowed, F ₀ in the above ΔF=F-F ₀ can be replaced with a range value [F ₀ -ΔF ₀ , F ₀ +ΔF ₀ ] is sufficient, and the same applies to ΔF ₁ , ΔF ₂ , . . . , ΔF _n .

Further, the above-mentioned heart rate sensor can be replaced by a blood pressure sensor, a blood oxygen sensor or an electrocardiogram sensor.

Therefore, even when the user does not wear the smart wearable device correctly, the user can still obtain relatively accurate body parameters through effective calculation by the processor.

Description of drawings

Figure 1 is a schematic diagram of a smart bracelet with a pressure sensor.

Figure 2 is a schematic diagram of a smart bracelet with two pressure sensors.

Figure 3 is a schematic diagram of a smart bracelet with three pressure sensors.

Figure 4 is a schematic diagram of a smart bracelet with four pressure sensors.

Figure 5 is a graph of the function of ΔN=g(ΔF) stored in the processor of the smart bracelet.

Figure 6 is a schematic diagram of a smart watch with two pressure sensors.

Detailed ways

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments, however, can be embodied in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The drawings are merely schematic illustrations of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repeated descriptions will be omitted.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of the embodiments of the present invention. However, those skilled in the art will appreciate that the technical solutions of the present invention may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be employed. In other instances, well-known structures, methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the present invention.

With the development of battery technology and sensor technology, smart bracelets can install more and more sensors to measure the physical parameters of the human body, so that users can judge their physical conditions through commonly used wearing tools (such as smart bracelets). , in order to timely make a targeted exercise plan. Functional sensors in smart bracelets include but are not limited to heart rate sensors, blood pressure sensors, blood oxygen sensors, etc. These functional sensors can measure and transmit real-time data for one or some parameters of the human body. Smart bracelets are becoming more and more powerful, but the way users wear them makes the detection results of many functional sensors inaccurate. On the basis of installing the above functional sensors, the present invention installs at least one pressure sensor on the surface of the smart wristband in contact with the wrist, and judges whether the user wears the smart wristband correctly through the pressure sensor, and guides the user according to whether the wristband is correctly worn or not. The user adjusts to the correct way of wearing, or directly performs correction and calculation through the data of the pressure sensor to obtain a relatively accurate measurement value of the functional sensor.

Example 1

The smart bracelet includes a processor and a functional sensor. The functional sensors include one or more of a heart rate sensor, a blood pressure sensor, a blood oxygen sensor, and an electrocardiogram sensor. The smart bracelet also includes a pressure sensor 101 (as shown in FIG. 1 ). Show).

The measurement data of the pressure sensor can reflect the tightness of the smart bracelet and whether the smart bracelet is properly worn. In judging whether the user is wearing the smart bracelet correctly:

First of all, when the smart bracelet leaves the factory, the manufacturer compares the data measured by the functional sensor (such as heart rate value, blood oxygen value, blood pressure value or ECG value) with the medical measurement data, and concludes that the data measured by the functional sensor is consistent with the medical measurement data. When the value of the measured data is the closest, it is considered that the user is wearing correctly, and we record the state that the user is wearing correctly as state A, assuming the value F ₀ of the pressure sensor at this time, the value F ₀ reflects that the user is wearing correctly, that is, it is in state A.

Or in addition, for various parameters of the human body, such as heart rate, blood pressure or ECG value, some parameters are medically allowed to have partial measurement deviations or the parameters themselves allow partial deviations. The existence of deviations will not lead to guidance of human exercise guidance or life guidance. Error, for such parameters, after obtaining the correct value F ₀ of the above-mentioned pressure sensor user wearing, according to the allowable deviation of medicine, the allowable deviation ΔF ₀ of the measured value of the functional sensor is obtained according to the experiment, that is, when the measured value of the pressure sensor is When the value is [F ₀ -ΔF ₀ , F ₀ +ΔF ₀ ], we also consider the user to be in state A.

Secondly, in the method of instructing the user to wear the smart bracelet correctly, the judgment is also based on the data measured by the functional sensor. For parameters that are not allowed to have deviations in medicine, when the value F < F ₀ actually measured by the pressure sensor, the processor judges that the wearing is too loose according to the comparison result, and the processor can control the display screen to display "wearing too loose" at the same time; When the value actually measured by the pressure sensor is F > F ₀ , the processor judges that the wearing is too tight according to the comparison result, and the processor can control the display screen to display "wearing too tight" at the same time. For the parameters with partial deviations allowed in medicine, when the value F < F ₀ -ΔF ₀ actually measured by the pressure sensor, the processor judges that the wearing is too loose according to the comparison result, and the processor can simultaneously control the display to display "wearing has been worn". When the value actually measured by the pressure sensor is F > F ₀ +ΔF ₀ , the processor judges that the wearing is too tight according to the comparison result, and the processor can control the display screen to display “wearing too tight” at the same time. Through the prompts, the user can easily find the length of the strap when the user wears it correctly by adjusting the strap of the smart bracelet, so as to adjust to the state A that the tightness is appropriate and the human parameters can be measured correctly.

Example 2

On the basis of Example 1, when using a pressure sensor, because the contact area between the smart bracelet and the human body is relatively large, a pressure sensor is often not enough to determine whether the user is really wearing it correctly. Therefore, it is necessary to connect the smart bracelet and human skin. A plurality of pressure sensors 101 are provided on the contact surface (FIGS. 2, 3 and 4 show the cases with two, three and four pressure sensors, respectively). Preferably, the plurality of pressure sensors are evenly arranged around the functional sensor or evenly arranged on the surface of the smart bracelet that is in contact with the skin.

Take two pressure sensors as an example (as shown in Figure 2), which are respectively denoted as left and right pressure sensors, similar to Embodiment 1, in judging whether the user is wearing the smart bracelet correctly:

First of all, when the smart bracelet leaves the factory, the manufacturer compares the data measured by the functional sensor (such as heart rate value, blood oxygen value, blood pressure value or ECG value) with the medical measurement data, and concludes that the data measured by the functional sensor is consistent with the medical measurement data. When the value of the measured data is the closest, it is considered that the user is wearing it correctly, and we denote the correct state of the user as state A, assuming that the values of the left and right pressure sensors are F ₀₁ and F ₀₂ respectively, and the two measured values reflect The user wears it correctly, that is, it is in state A.

Or in addition, for various parameters of the human body, such as heart rate, blood pressure or ECG value, some parameters are medically allowed to have partial measurement deviations or the parameters themselves allow partial deviations. The existence of deviations will not lead to guidance of human exercise guidance or life guidance. Error, for such parameters, after obtaining the correct values F ₀₁ and F ₀₂ worn by the user of the above-mentioned pressure sensor, according to the allowable deviation of medicine, the allowable deviation ΔF ₀₁ and ΔF ₀₂ of the measured value of the functional sensor are obtained according to the experiment, namely When the measured value of the left pressure sensor is [F ₀₁ -ΔF ₀₁ , F ₀₁ +ΔF ₀₁ ], and the measured value of the right pressure sensor is [F ₀₂ -ΔF ₀₂ , F ₀₂ +ΔF ₀₂ ], we also consider that the user in state A.

Secondly, in the method of instructing the user to wear the smart bracelet correctly, the judgment is also based on the data measured by the functional sensor. For medically intolerant parameters:

1) When the actual measured value of the left pressure sensor is F ₁ < F ₀₁ or F ₁ > F ₀₁ , no matter what the actual measured value of the right pressure sensor is, the processor will judge according to the comparison result that the left side of the bracelet is too loosely worn or not. The left side is too tight, and the processor can simultaneously control the display to display "the left side is too loose" or "the left side is too tight".

2) When the actual measured value of the right pressure sensor is F ₂ < F ₀₂ or F ₂ > F ₀₂ , no matter what the actual measured value of the left pressure sensor is, the processor will judge according to the comparison result that the right side of the bracelet is too loosely worn or not. The right side is too tight, and the processor can simultaneously control the display to display "the right side is too loose" or "the right side is too tight".

Of course, when the measured values of the left pressure sensor and the right pressure sensor are not correct values, the processor judges the tightness of the left and right sides at the same time, and can control the display to simultaneously display such as "wearing on the left is too loose" and "wearing on the right" too tight" prompt.

And for the parameters that are medically tolerated with partial deviation:

1) When the actual measured value of the left pressure sensor is F ₁ < F ₀₁ -ΔF ₀₁ or F ₁ > F ₀₁ +ΔF ₀₁ , no matter what the actual measured value of the right pressure sensor is, the processor will judge the bracelet according to the comparison result. The left side is too loose or the left side is too tight, and the processor can control the display screen to display "the left side is too loose" or "the left side is too tight".

2) When the actual measured value of the right pressure sensor is F ₂ < F ₀₂ -ΔF ₀₂ or F ₂ > F ₀₂ +ΔF ₀₂ , no matter what the actual measured value of the left pressure sensor is, the processor will judge the bracelet according to the comparison result. The right side is too loose or the right side is too tight, and the processor can control the display screen to display "the right side is too loose" or "the right side is too tight".

Of course, when the measured values of the left pressure sensor and the right pressure sensor are not within the range ([F ₀₁ -ΔF ₀₁ , F ₀₁ +ΔF ₀₁ ] and [F ₀₂ -ΔF ₀₂ , F ₀₂ +ΔF ₀₂ ]) At the same time, the processor judges the tightness of the left and right sides at the same time, and can control the display screen to display prompts such as "wearing too loose on the left" and "wearing too tight on the right" at the same time.

In this way, the user can know whether the bracelet is properly worn (that is, in state A) according to the wearing instruction (or prompt) of the bracelet, and further make correct adjustments to approach state A.

Example 3

On the basis of the above Embodiment 1, the user can correct the incorrectly worn smart bracelet according to the prompt, so that each functional sensor of the smart bracelet can measure the parameters of the human body more accurately.

In actual use, correct wearing (the above state A) can ensure that the various functional sensors of the smart bracelet can more accurately measure the parameters of the human body. However, the "correct wearing" state A is not the most comfortable wearing for the user. state. Correct wearing is a common state, but each user is an individual, and the wearing of the smart bracelet is selective on the individual's wrist and skin. In simple terms, the state A that can measure accurately is likely not to be liked by the user. The wearing state of , we denote the wearing state that the user likes as state B. When the user is forced to correct to the state A to get the accurate measurement value, the good wearing experience will be lost. Therefore, it is necessary to correct the measurement data in the state B, so that although in the state B, the same can still be obtained. The accuracy of the data measured by each functional sensor in state A. In this regard, the following method for correcting the measurement results of the smart bracelet sensor is proposed:

When the smart bracelet leaves the factory, the manufacturer compares the data measured by the functional sensor with the data measured by the medical device, and concludes that when the data measured by the functional sensor is the closest to the data measured by the medical device, it is considered that the user is wearing it correctly. The correct state is denoted as state A, assuming the value F ₀ of the pressure sensor at this time, the value F ₀ reflects that the user is wearing it correctly, that is, state A.

When the pressure value F actually measured by the pressure sensor is not equal to F ₀ , the heart rate value measured by the heart rate sensor (here, the heart rate sensor in the functional sensor is taken as an example) N, and the heart rate data measured by the human body medicine is N ₀ . At this time, N ₀ and N is not equal in value, and the inequality reflects the problem that the user's measurement data in state B is inaccurate.

As shown in FIG. 5 , within the pressure range [F _min , F _max ] where heart rate values can be detected (where F _min and F _max are the minimum and maximum pressures at which effective heart rate values can be detected, and are lower than F _min or Heart rate values higher than F _max have no reference meaning), describe the relationship between ΔN and ΔF through experimental measurements (ΔN is the difference between the actual measured value N and the smart bracelet display value N _s , ΔN=N- N _s , N _s is the heart rate value displayed by the revised smart bracelet). The description method can be to measure the point value, and then fit the curve to obtain the function curve of ΔN about ΔF, ΔN=g(ΔF).

When the pressure sensor obtains the value F, the processor calculates the pressure F ₀ in state A (F ₀ is the parameter identified by the smart bracelet when it leaves the factory, and each smart bracelet has a fixed F ₀ ) and the difference between F ΔF= F-F ₀ , according to the above-mentioned function curve ΔN=g (ΔF) and the measured N value, calculate N _s according to ΔN=N- N _s , and display the value of N _s on the display screen as the corrected value Numeric value, that is, the value that the user can see.

Therefore, when the measured value of the pressure sensor is within the range of [F _min , F _max ], even if the user fails to wear the smart bracelet in the correct state (ie state A) for comfort or other reasons, the feedback from the pressure sensor will And the operation of the processor, the user can still get the more accurate value of the functional sensor.

Similarly, when there are 2 pressure sensors, by means of experiments and curve fitting, we can get:

ΔN=h(ΔF ₁ , ΔF ₂ ), where ΔF ₁ is the difference between the actual measurement value F of the left pressure sensor and the wristband factory guide data F ₀₁ of the left pressure sensor ΔF ₁ =F- F ₀₁ , where The ΔF ₂ pass is the difference between the actual measurement value F of the right pressure sensor and the wristband factory guide data F ₀₂ of the right pressure sensor, ΔF ₂ =F-F ₀₂ .

Further, when there are N pressure sensors, ΔN=h (ΔF ₁ , ΔF ₂ , . . . , ΔF _n ) can be obtained by means of experiments and curve fitting.

Example 4

On the basis of the above Embodiment 2, using the algorithm of Embodiment 3, it is only necessary to redefine the above ΔF, that is, it is only necessary to replace the F ₀ in the above ΔF=F-F ₀ with the range value [F ₀ -ΔF ₀ , F ₀ +ΔF ₀ ] is sufficient, and the same applies to ΔF ₁ , ΔF ₂ , . . . , ΔF _n .

Example 5

The smart bracelet in the above-mentioned Embodiments 1-4 can be replaced with any smart wearable device including functional sensors that can measure human parameters, such as a smart watch (as shown in FIG. 6 ).

The following takes the smart bracelet as an example to describe in detail the structure of the smart bracelet that implements the methods of the foregoing embodiments 1-3. A smart bracelet that can adjust the tightness based on the prompt of a pressure sensor, the smart bracelet includes one or more of a heart rate sensor, a blood pressure sensor, and a blood oxygen sensor, and the smart bracelet also includes at least one pressure sensor 101 (As shown in Figures 1-4), when there are multiple pressure sensors, the multiple pressure sensors are evenly arranged on the surface of the bracelet in contact with the human body;

The processor including one or more of a heart rate sensor, a blood pressure sensor, and a blood oxygen sensor is connected to the smart bracelet, and the at least one pressure sensor is connected to the processor;

The at least one pressure sensor can detect the pressure between the smart bracelet and the human body;

The processor includes a storage module in which the standard guide pressure F ₀ of each pressure sensor is stored;

The processor includes a comparison module, the comparison module can compare the data F measured by the pressure sensor with the standard guide pressure F ₀ of the corresponding pressure sensor in the storage module;

The smart bracelet further includes a display screen, and the processor can display the tightness of the user's wearing according to the result of the above comparison.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions described in the foregoing embodiments can still be modified, or some or all of the technical features thereof can be equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention. scope.

Claims (6)

1. A method for correcting a sensor measurement result of a smart wearable device, the smart wearable device comprising a heart rate sensor and a processor, the smart wearable device further comprising a pressure sensor (101); the method comprises the following steps : In step 1, the processor further includes a storage module, which stores the standard guide pressure F ₀ measured by the pressure sensor when the smart wearable device is worn correctly, the heart rate value N ₀ measured by human medical science, and the standard guide pressure measured by the pressure sensor when the smart wearable device is correctly worn. In the case of detecting the heart rate value N, the minimum pressure value F _min and the maximum pressure value F _max measured by the pressure sensor when the smart wearable device is correctly worn; Step 2, after the user wears the smart wearable device, the processor controls the pressure sensor to measure the actual pressure F between the smart wearable device and the user; the processor controls the heart rate sensor to measure the heart rate value N, Step 3, denote ΔN as the difference between the heart rate value N actually measured by the heart rate sensor and the display value N _s of the smart wearable device, ΔN=N-N _s , and N _s is the corrected smart wearable device. The heart rate value displayed by the wearable device; mark ΔF as the difference between the actual measurement value F of the pressure sensor and the standard guide pressure F ₀ , ΔF=F-F ₀ ; through experiments, the function of ΔN about ΔF is fitted Curve ΔN=g(ΔF), and store the curve in the storage module; Step 4, when the actual pressure measured by the pressure sensor is F, the processor first calculates ΔF according to ΔF=F-F ₀ , and then retrieves the function curve ΔN=g(ΔF) in the storage module , obtain the ΔN value, and finally calculate N _s according to ΔN=NN _s , and use the N _s as the corrected heart rate value displayed by the smart wearable device. 2. The method for revising the sensor measurement result of a smart wearable device according to claim 1, wherein ΔF can be redefined, and when the measurement error of the pressure sensor is allowed, the above ΔF=F-F The F ₀ in ₀ is replaced by the range value [F ₀ -ΔF ₀ , F ₀ +ΔF ₀ ]; the ΔF ₀ is the allowable deviation of the pressure sensor measurement value. 3 . The method for revising sensor measurement results of a smart wearable device according to claim 1 , wherein the heart rate sensor can be replaced with a blood pressure sensor, a blood oxygen sensor or an electrocardiogram sensor. 4 . 4. A method for correcting a sensor measurement result of a smart wearable device, the smart wearable device comprising a heart rate sensor and a processor, the smart wearable device further comprising at least two pressure sensors (101), the at least two The pressure sensors include a left pressure sensor and a right pressure sensor; the method includes the following steps: Step 1, the processor further includes a storage module, which stores the standard guiding pressures F ₀₁ and F ₀₂ measured by the pressure sensor when the smart wearable device is worn correctly, and the heart rate value N ₀ measured by human medicine. , and under the condition that the heart rate value N can be detected, the minimum pressure value F _min1 and the maximum pressure value F _max1 measured by the left pressure sensor when the smart wearable device is correctly worn, and when the smart wearable device is correctly worn The minimum pressure value F _min2 and the maximum pressure value F _max2 measured by the right pressure sensor; Step 2, after the user wears the smart wearable device, the processor controls the left pressure sensor and the right pressure sensor to measure the actual pressures F ₁ and F ₂ between the smart wearable device and the user; the processing The controller controls the heart rate sensor to measure the heart rate value N; Step 3, denote ΔN as the difference between the heart rate value N actually measured by the heart rate sensor and the display value N _s of the smart wearable device, ΔN=N-N _s , and N _s is the corrected smart wearable device. The heart rate value displayed by the wearable device; mark ΔF ₁ as the difference between the actual measurement value F ₁ of the left pressure sensor and the standard guide pressure F ₀₁ , ΔF ₁ = F ₁ - F ₀₁ ; mark ΔF ₂ as the The difference between the actual measurement value F ₂ of the left pressure sensor and the standard guide pressure F ₀₂ , ΔF ₂ = F ₂ - F ₀₂ ; through experiments, the function curve of ΔN about ΔF is fitted ΔN=h (ΔF ₁ , ΔF ₂ ), and store the curve in the storage module; Step 4, when the actual pressure measured by the left pressure sensor is F ₁ , and the actual pressure measured by the right pressure sensor is F ₂ , the processor first calculates according to ΔF ₁ = F ₁ - F ₀₁ and ΔF ₂ = F ₂ - F ₀₂ calculate ΔF ₁ and ΔF ₂ , and then call the function curve ΔN=h (ΔF ₁ , ΔF ₂ ) in the storage module to obtain the ΔN value, and finally calculate according to ΔN=N-N _s N _s is obtained, and the N _s is used as the corrected heart rate value displayed by the smart wearable device. 5 . The method for revising the sensor measurement result of a smart wearable device according to claim 4 , wherein ΔF ₁ and ΔF ₂ can be redefined, and when the measurement error of the pressure sensor is allowed, the above ΔF can be redefined. 6 . ₁ = F ₀₁ in F ₁ - F ₀₁ is replaced by a range value [F ₀₁ -ΔF ₀₁ , F ₀₁ +ΔF ₀₁ ], ΔF ₂ = F ₀₂ in F ₂ - F ₀₂ is replaced by a range value [F ₀₂ -ΔF ₀₂ , F ₀₂ +ΔF ₀₂ ]; the ΔF ₀₁ and ΔF ₀₂ are the allowable deviations of the measured values of the left and right pressure sensors. 6 . The method for revising a sensor measurement result of a smart wearable device according to claim 4 , wherein the heart rate sensor can be replaced with a blood pressure sensor, a blood oxygen sensor or an electrocardiogram sensor. 7 .