Method and system for evaluating motion monitoring effect of intelligent wearable device, and medium

Abstract

The invention provides an intelligent wearable device motion monitoring effect evaluation method and system and a medium. The method comprises the following steps: testing the intelligent wearable device to obtain motion parameter monitoring data and motion data quality monitoring data, processing according to the motion parameter monitoring data to obtain a motion parameter measurement deviation index and a motion mode identification accuracy evaluation factor, obtaining motion parameter measurement deviation indexes in different motion scenes, and evaluating the motion mode identification accuracy of the intelligent wearable device. A multi-scene recognition capability evaluation factor is obtained through processing, a motion monitoring accuracy evaluation index is obtained through processing in combination with a motion parameter measurement deviation index and a motion mode recognition accuracy evaluation factor, and a motion monitoring efficiency evaluation index is obtained through processing according to motion data quality monitoring data; and evaluating the motion monitoring effect of the wearable device according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index. Therefore, the purpose of intelligently evaluating the motion monitoring effect of the intelligent wearable device is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of motion monitoring of wearable devices, and in particular to a method, system and medium for evaluating the motion monitoring effect of smart wearable devices. Background Art

[0002] Smart wearable devices provide users with real-time motion monitoring services. Especially with the application of Beidou high-precision satellite positioning technology in the field of smart wearable devices, wearable devices can not only accurately monitor the user's motion trajectory, speed, number of steps and other key indicators, but also provide users with timely and accurate exercise guidance and suggestions. In order to further improve the performance of wearable devices and enable them to maintain high-precision operation in complex sports scenes, it is particularly important to accurately evaluate their motion monitoring effects. However, existing evaluation methods are often relatively simple, lacking comprehensiveness and systematicness, and cannot comprehensively consider multiple factors such as the accuracy and efficiency of motion monitoring, making it difficult to meet the needs of practical applications. At present, there is an urgent need for a comprehensive and effective method for evaluating the motion monitoring effects of smart wearable devices. Summary of the invention

[0003] The purpose of this application is to provide a method, system and medium for evaluating the motion monitoring effect of a smart wearable device, so as to achieve the purpose of evaluating the motion monitoring effect of a wearable device by evaluating the motion parameter measurement deviation, multi-scene recognition capability, motion pattern recognition accuracy and motion monitoring efficiency.

[0004] The present application also provides a method for evaluating the effect of motion monitoring of a smart wearable device, comprising the following steps: Test smart wearable devices to obtain motion parameter monitoring data and motion data quality monitoring data; Obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing; Obtaining a motion parameter measurement deviation index under different motion scenes, and combining the motion parameter measurement deviation index with a motion pattern recognition accuracy assessment factor to obtain a motion monitoring accuracy assessment index; Obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing; The motion monitoring effect of the wearable device is evaluated according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index.

[0005] Optionally, in the method for evaluating the effect of motion monitoring of a smart wearable device described in the present application, the step of testing the smart wearable device to obtain motion parameter monitoring data and motion data quality monitoring data includes: The sports parameter monitoring data includes step error data, sports distance error data, sports speed error data, sports intensity recognition accuracy, intelligent prompt accuracy and sports type recognition accuracy; The motion data quality monitoring data includes key data recording completeness rate, number of interruptions, percentage of missing segment duration, data update frequency and response delay data.

[0006] Optionally, in the method for evaluating the effect of motion monitoring of a smart wearable device described in the present application, the step of obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing includes: Obtaining a motion parameter measurement deviation index according to the step number error data, the motion distance error data and the motion speed error data; The exercise pattern recognition accuracy evaluation factor is obtained according to the exercise intensity recognition accuracy, intelligent prompt accuracy and exercise type recognition accuracy.

[0007] Optionally, in the method for evaluating the effect of motion monitoring of a smart wearable device described in the present application, obtaining the motion parameter measurement deviation index under different motion scenes, and combining the motion parameter measurement deviation index and the motion pattern recognition accuracy evaluation factor to obtain the motion monitoring accuracy evaluation index includes: Obtaining motion parameter measurement deviation indexes under different motion scenes, and obtaining multi-scene recognition capability evaluation factors according to the motion parameter measurement deviation indexes; The motion monitoring accuracy evaluation index is obtained according to the multi-scene recognition capability evaluation factor, the motion pattern recognition accuracy evaluation factor and the motion parameter measurement deviation index.

[0008] Optionally, in the method for evaluating the effect of motion monitoring of a smart wearable device described in the present application, the step of obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing includes: Obtaining a data integrity assessment factor based on the completeness rate of key data records, the number of interruptions, and the proportion of missing segment duration; Obtaining a motion monitoring efficiency evaluation index according to the data integrity evaluation factor and the data update frequency and response delay data processing; Optionally, in the method for evaluating the motion monitoring effect of a smart wearable device described in the present application, evaluating the motion monitoring effect of the wearable device according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index includes: Obtaining a motion monitoring effect evaluation index according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index; The motion monitoring effect evaluation index is compared with a preset motion monitoring effect evaluation index threshold. If the threshold comparison result does not meet the preset threshold comparison result requirement, a poor motion monitoring effect determination is performed.

[0009] In a second aspect, the present application provides a system for evaluating the effect of motion monitoring of a smart wearable device, the system comprising: a memory and a processor, wherein the memory stores a program of a method for evaluating the effect of motion monitoring of a smart wearable device, and when the program of the method for evaluating the effect of motion monitoring of a smart wearable device is executed by the processor, the following steps are implemented: Test smart wearable devices to obtain motion parameter monitoring data and motion data quality monitoring data; Obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing; Obtaining a motion parameter measurement deviation index under different motion scenes, and combining the motion parameter measurement deviation index with a motion pattern recognition accuracy assessment factor to obtain a motion monitoring accuracy assessment index; Obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing; The motion monitoring effect of the wearable device is evaluated according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index.

[0010] Optionally, in the smart wearable device motion monitoring effect evaluation system described in the present application, the testing of the smart wearable device to obtain motion parameter monitoring data and motion data quality monitoring data includes: The sports parameter monitoring data includes step error data, sports distance error data, sports speed error data, sports intensity recognition accuracy, intelligent prompt accuracy and sports type recognition accuracy; The motion data quality monitoring data includes key data recording completeness rate, number of interruptions, percentage of missing segment duration, data update frequency and response delay data.

[0011] Optionally, in the smart wearable device motion monitoring effect evaluation system described in the present application, the step of obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing includes: Obtaining a motion parameter measurement deviation index according to the step number error data, the motion distance error data and the motion speed error data; The exercise pattern recognition accuracy evaluation factor is obtained according to the exercise intensity recognition accuracy, intelligent prompt accuracy and exercise type recognition accuracy.

[0012] In the third aspect, the present application also provides a computer-readable storage medium, which stores a program for a method for evaluating the effect of motion monitoring of a smart wearable device. When the program for evaluating the effect of motion monitoring of a smart wearable device is executed by a processor, the steps of the method for evaluating the effect of motion monitoring of a smart wearable device as described in any one of the above items are implemented.

[0013] From the above, it can be seen that the present application provides a method, system and medium for evaluating the motion monitoring effect of a smart wearable device, which achieves the purpose of evaluating the motion monitoring effect of a wearable device by evaluating the motion parameter measurement deviation, multi-scene recognition capability, motion pattern recognition accuracy and motion monitoring efficiency.

[0014] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A flowchart of a method for evaluating the effect of sports monitoring on a smart wearable device provided in an embodiment of the present application; Figure 2 A flowchart of obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor of a method for evaluating the motion monitoring effect of a smart wearable device provided in an embodiment of the present application; Figure 3 A flow chart of obtaining a motion monitoring accuracy evaluation index for a method for evaluating motion monitoring effects of a smart wearable device provided in an embodiment of the present application; Figure 4 A flow chart of obtaining a motion monitoring efficiency evaluation index for a method for evaluating the motion monitoring effect of a smart wearable device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0018] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0019] Please refer to Figure 1 , Figure 1 The flowchart of the method for evaluating the effect of motion monitoring of a smart wearable device in some embodiments of the present application. The method for evaluating the effect of motion monitoring of a smart wearable device is used in a terminal device, such as a computer, a mobile phone terminal, etc. The method for evaluating the effect of motion monitoring of a smart wearable device comprises the following steps: S11. Test the smart wearable device to obtain motion parameter monitoring data and motion data quality monitoring data; S12, obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing; S13, obtaining a motion parameter measurement deviation index under different motion scenes, and combining the motion parameter measurement deviation index and the motion pattern recognition accuracy evaluation factor to obtain a motion monitoring accuracy evaluation index; S14, obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing; S15. Evaluate the motion monitoring effect of the wearable device according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index.

[0020] It should be noted that the present application achieves the purpose of evaluating the motion monitoring effect of wearable devices by evaluating the motion parameter measurement deviation, multi-scene recognition capability, motion pattern recognition accuracy and motion monitoring efficiency.

[0021] According to an embodiment of the present invention, the step of testing the smart wearable device to obtain motion parameter monitoring data and motion data quality monitoring data includes: The sports parameter monitoring data includes step error data, sports distance error data, sports speed error data, sports intensity recognition accuracy, intelligent prompt accuracy and sports type recognition accuracy; The motion data quality monitoring data includes key data recording completeness rate, number of interruptions, percentage of missing segment duration, data update frequency and response delay data.

[0022] It should be noted that the accuracy of exercise intensity recognition can be expressed by the ratio of the number of accurate exercise intensity recognitions to the total number of tests, the accuracy of smart prompts can be expressed by the ratio of the number of accurate smart prompts to the total number of tests, the accuracy of exercise type recognition can be expressed by the ratio of the number of accurate exercise type recognitions to the total number of tests, and the completeness rate of key data records can be expressed by the ratio of the number of complete records to the total number of tests.

[0023] Please refer to Figure 2 , Figure 2 The present invention is a flowchart of obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor of a method for evaluating motion monitoring effects of a smart wearable device in some embodiments of the present invention. According to an embodiment of the present invention, obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing includes: S21, obtaining a motion parameter measurement deviation index according to the step number error data, the motion distance error data and the motion speed error data; S22, obtaining a motion pattern recognition accuracy evaluation factor according to the motion intensity recognition accuracy, the intelligent prompt accuracy and the motion type recognition accuracy.

[0024] It should be noted that the calculation formula of the motion parameter measurement deviation index is: ; in, Measure the deviation index for motion parameters, , and They are step error data, motion distance error data and motion speed error data respectively. , and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database); The calculation formula of the motion pattern recognition accuracy evaluation factor is: ; in, is the evaluation factor for motion pattern recognition accuracy, , and They are exercise intensity recognition accuracy, smart prompt accuracy, and exercise type recognition accuracy. , and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0025] Please refer to Figure 3 , Figure 3 The present invention is a flowchart of obtaining a motion monitoring accuracy evaluation index of a method for evaluating motion monitoring effects of a smart wearable device in some embodiments of the present application. According to an embodiment of the present invention, obtaining a motion parameter measurement deviation index under different motion scenes, and combining the motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor to obtain a motion monitoring accuracy evaluation index includes: S31, obtaining motion parameter measurement deviation indexes under different motion scenes, and obtaining a multi-scene recognition capability evaluation factor according to the motion parameter measurement deviation indexes; S32, obtaining a motion monitoring accuracy evaluation index according to the multi-scenario recognition capability evaluation factor, the motion pattern recognition accuracy evaluation factor, and the motion parameter measurement deviation index.

[0026] It should be noted that the calculation formula of the multi-scenario recognition capability evaluation factor is: ; in, is the multi-scenario recognition capability evaluation factor, i=1,...n, is the motion parameter measurement deviation index corresponding to the i-th motion scene, The average value of the deviation index of the motion parameter measurement for n motion scenes; The calculation formula of the motion monitoring accuracy evaluation index is: ; in, is the motion monitoring accuracy evaluation index, and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0027] Please refer to Figure 4 , Figure 4 The flowchart of obtaining the motion monitoring efficiency evaluation index of the method for evaluating the motion monitoring effect of the smart wearable device in some embodiments of the present application. According to an embodiment of the present invention, the obtaining the motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing includes: S41, obtaining a data integrity assessment factor according to the key data record integrity rate, the number of interruptions and the ratio of missing segment duration; S42. Obtain a motion monitoring efficiency evaluation index according to the data integrity evaluation factor and the data update frequency and response delay data processing.

[0028] It should be noted that the calculation formula of the data integrity assessment factor is: ; in, is the data integrity assessment factor, , and They are the completeness rate of key data records, the number of interruptions, and the proportion of missing fragment duration. , and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database); The calculation formula of the motion monitoring efficiency evaluation index is: ; in, is the motion monitoring efficiency evaluation index, is the data update frequency, In response to delayed data, and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0029] According to an embodiment of the present invention, the step of evaluating the motion monitoring effect of the wearable device according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index includes: Obtaining a motion monitoring effect evaluation index according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index; The motion monitoring effect evaluation index is compared with a preset motion monitoring effect evaluation index threshold. If the threshold comparison result does not meet the preset threshold comparison result requirement, a poor motion monitoring effect determination is performed.

[0030] It should be noted that the calculation formula of the exercise monitoring effect evaluation index is: ; in, It is the exercise monitoring effect evaluation index. and is a preset weight coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0031] According to an embodiment of the present invention, it also includes: Comparing the motion monitoring effect evaluation index with a preset motion monitoring effect evaluation index threshold, and taking the range level to which the threshold comparison result belongs as the motion monitoring effect evaluation level; Inputting the motion monitoring effect evaluation level into a preset wearable device performance optimization solution library for matching and identification, and obtaining a wearable device performance optimization solution; The smart wearable device is optimized and adjusted according to the wearable device performance optimization solution.

[0032] It should be noted that the wearable device performance optimization solution is obtained according to the motion monitoring effect evaluation level.

[0033] The present invention also discloses a smart wearable device motion monitoring effect evaluation system, comprising a memory and a processor, wherein the memory stores a smart wearable device motion monitoring effect evaluation method program, and when the smart wearable device motion monitoring effect evaluation method program is executed by the processor, the following steps are implemented: Test smart wearable devices to obtain motion parameter monitoring data and motion data quality monitoring data; Obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing; Obtaining a motion parameter measurement deviation index under different motion scenes, and combining the motion parameter measurement deviation index with a motion pattern recognition accuracy assessment factor to obtain a motion monitoring accuracy assessment index; Obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing; The motion monitoring effect of the wearable device is evaluated according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index.

[0034] It should be noted that the present application achieves the purpose of evaluating the motion monitoring effect of wearable devices by evaluating the motion parameter measurement deviation, multi-scene recognition capability, motion pattern recognition accuracy and motion monitoring efficiency.

[0035] According to an embodiment of the present invention, the step of testing the smart wearable device to obtain motion parameter monitoring data and motion data quality monitoring data includes: The sports parameter monitoring data includes step error data, sports distance error data, sports speed error data, sports intensity recognition accuracy, intelligent prompt accuracy and sports type recognition accuracy; The motion data quality monitoring data includes key data recording completeness rate, number of interruptions, percentage of missing segment duration, data update frequency and response delay data.

[0036] It should be noted that the accuracy of exercise intensity recognition can be expressed by the ratio of the number of accurate exercise intensity recognitions to the total number of tests, the accuracy of smart prompts can be expressed by the ratio of the number of accurate smart prompts to the total number of tests, the accuracy of exercise type recognition can be expressed by the ratio of the number of accurate exercise type recognitions to the total number of tests, and the completeness rate of key data records can be expressed by the ratio of the number of complete records to the total number of tests.

[0037] According to an embodiment of the present invention, the step of obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing includes: Obtaining a motion parameter measurement deviation index according to the step number error data, the motion distance error data and the motion speed error data; The exercise pattern recognition accuracy evaluation factor is obtained according to the exercise intensity recognition accuracy, intelligent prompt accuracy and exercise type recognition accuracy.

[0038] It should be noted that the calculation formula of the motion parameter measurement deviation index is: ; in, Measure the deviation index for motion parameters, , and They are step error data, motion distance error data and motion speed error data respectively. , and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database); The calculation formula of the motion pattern recognition accuracy evaluation factor is: ; in, is the evaluation factor for motion pattern recognition accuracy, , and They are exercise intensity recognition accuracy, smart prompt accuracy, and exercise type recognition accuracy. , and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0039] According to an embodiment of the present invention, the step of obtaining the motion parameter measurement deviation index under different motion scenes and combining the motion parameter measurement deviation index and the motion pattern recognition accuracy evaluation factor to obtain the motion monitoring accuracy evaluation index includes: Obtaining motion parameter measurement deviation indexes under different motion scenes, and obtaining multi-scene recognition capability evaluation factors according to the motion parameter measurement deviation indexes; The motion monitoring accuracy evaluation index is obtained according to the multi-scene recognition capability evaluation factor, the motion pattern recognition accuracy evaluation factor and the motion parameter measurement deviation index.

[0040] It should be noted that the calculation formula of the multi-scenario recognition capability evaluation factor is: ; in, is the multi-scenario recognition capability evaluation factor, i=1,...n, is the motion parameter measurement deviation index corresponding to the i-th motion scene, The average value of the deviation index of the motion parameter measurement for n motion scenes; The calculation formula of the motion monitoring accuracy evaluation index is: ; in, is the motion monitoring accuracy evaluation index, and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0041] According to an embodiment of the present invention, the step of obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing includes: Obtaining a data integrity assessment factor based on the completeness rate of key data records, the number of interruptions, and the proportion of missing segment duration; A motion monitoring efficiency evaluation index is obtained according to the data integrity evaluation factor and the data update frequency and response delay data processing.

[0042] It should be noted that the calculation formula of the data integrity assessment factor is: ; in, is the data integrity assessment factor, , and They are the completeness rate of key data records, the number of interruptions, and the proportion of missing fragment duration. , and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database); The calculation formula of the motion monitoring efficiency evaluation index is: ; in, is the motion monitoring efficiency evaluation index, is the data update frequency, In response to delayed data, and is a preset characteristic coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0043] According to an embodiment of the present invention, the step of evaluating the motion monitoring effect of the wearable device according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index includes: Obtaining a motion monitoring effect evaluation index according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index; The motion monitoring effect evaluation index is compared with a preset motion monitoring effect evaluation index threshold. If the threshold comparison result does not meet the preset threshold comparison result requirement, a poor motion monitoring effect determination is performed.

[0044] It should be noted that the calculation formula of the exercise monitoring effect evaluation index is: ; in, It is the exercise monitoring effect evaluation index. and is a preset weight coefficient (which can be obtained by querying the preset smart wearable device motion monitoring platform database).

[0045] According to an embodiment of the present invention, it also includes: Comparing the motion monitoring effect evaluation index with a preset motion monitoring effect evaluation index threshold, and taking the range level to which the threshold comparison result belongs as the motion monitoring effect evaluation level; Inputting the motion monitoring effect evaluation level into a preset wearable device performance optimization solution library for matching and identification, and obtaining a wearable device performance optimization solution; The smart wearable device is optimized and adjusted according to the wearable device performance optimization solution.

[0046] It should be noted that the wearable device performance optimization solution is obtained according to the motion monitoring effect evaluation level.

[0047] The third aspect of the present invention provides a readable storage medium, which stores a program for a method for evaluating the effect of motion monitoring of a smart wearable device. When the program for evaluating the effect of motion monitoring of a smart wearable device is executed by a processor, the steps of the method for evaluating the effect of motion monitoring of a smart wearable device as described in any one of the above items are implemented.

[0048] The present invention discloses a method, system and medium for evaluating the motion monitoring effect of a smart wearable device, which achieves the purpose of evaluating the motion monitoring effect of a wearable device by evaluating motion parameter measurement deviation, multi-scene recognition capability, motion pattern recognition accuracy and motion monitoring efficiency.

[0049] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0050] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0051] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0052] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0053] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for evaluating the effect of motion monitoring of a smart wearable device, characterized in that: The following steps are involved: Test smart wearable devices to obtain motion parameter monitoring data and motion data quality monitoring data; Obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing; Obtaining motion parameter measurement deviation indexes under different motion scenes, and combining the motion parameter measurement deviation indexes with motion pattern recognition accuracy assessment factors to obtain motion monitoring accuracy assessment indexes; Obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing; The motion monitoring effect of the wearable device is evaluated according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index.

2. The method for evaluating the motion monitoring effect of a smart wearable device according to claim 1, characterized in that: The testing of the smart wearable device to obtain motion parameter monitoring data and motion data quality monitoring data includes: The sports parameter monitoring data includes step error data, sports distance error data, sports speed error data, sports intensity recognition accuracy, intelligent prompt accuracy and sports type recognition accuracy; The motion data quality monitoring data includes key data recording completeness rate, number of interruptions, percentage of missing segment duration, data update frequency and response delay data.

3. The method for evaluating the motion monitoring effect of a smart wearable device according to claim 2, characterized in that: The step of obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing includes: Obtaining a motion parameter measurement deviation index according to the step number error data, the motion distance error data and the motion speed error data; The exercise pattern recognition accuracy evaluation factor is obtained according to the exercise intensity recognition accuracy, intelligent prompt accuracy and exercise type recognition accuracy.

4. The method for evaluating the motion monitoring effect of a smart wearable device according to claim 3, characterized in that: The step of obtaining the motion parameter measurement deviation index under different motion scenes and combining the motion parameter measurement deviation index and the motion pattern recognition accuracy evaluation factor to obtain the motion monitoring accuracy evaluation index includes: Obtaining motion parameter measurement deviation indexes under different motion scenes, and obtaining multi-scene recognition capability evaluation factors according to the motion parameter measurement deviation indexes; The motion monitoring accuracy evaluation index is obtained according to the multi-scene recognition capability evaluation factor, the motion pattern recognition accuracy evaluation factor and the motion parameter measurement deviation index.

5. The method for evaluating the effect of motion monitoring of a smart wearable device according to claim 4, characterized in that: The step of obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing includes: Obtaining a data integrity assessment factor based on the completeness rate of key data records, the number of interruptions, and the proportion of missing segment duration; A motion monitoring efficiency evaluation index is obtained according to the data integrity evaluation factor and the data update frequency and response delay data processing.

6. The method for evaluating the effect of motion monitoring of a smart wearable device according to claim 5, characterized in that: The step of evaluating the motion monitoring effect of the wearable device according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index includes: Obtaining a motion monitoring effect evaluation index according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index; The motion monitoring effect evaluation index is compared with a preset motion monitoring effect evaluation index threshold. If the threshold comparison result does not meet the preset threshold comparison result requirement, a poor motion monitoring effect determination is performed.

7. A smart wearable device motion monitoring effect evaluation system, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a program of a method for evaluating the effect of motion monitoring of a smart wearable device, and when the program of the method for evaluating the effect of motion monitoring of a smart wearable device is executed by the processor, the following steps are implemented: Test smart wearable devices to obtain motion parameter monitoring data and motion data quality monitoring data; Obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing; Obtaining motion parameter measurement deviation indexes under different motion scenes, and combining the motion parameter measurement deviation indexes with motion pattern recognition accuracy assessment factors to obtain motion monitoring accuracy assessment indexes; Obtaining a motion monitoring efficiency evaluation index according to the motion data quality monitoring data processing; The motion monitoring effect of the wearable device is evaluated according to the motion monitoring accuracy evaluation index and the motion monitoring efficiency evaluation index.

8. The smart wearable device motion monitoring effect evaluation system according to claim 7, characterized in that: The testing of the smart wearable device to obtain motion parameter monitoring data and motion data quality monitoring data includes: The sports parameter monitoring data includes step error data, sports distance error data, sports speed error data, sports intensity recognition accuracy, intelligent prompt accuracy and sports type recognition accuracy; The motion data quality monitoring data includes key data recording completeness rate, number of interruptions, percentage of missing segment duration, data update frequency and response delay data.

9. The smart wearable device motion monitoring effect evaluation system according to claim 8, characterized in that: The step of obtaining a motion parameter measurement deviation index and a motion pattern recognition accuracy evaluation factor according to the motion parameter monitoring data processing includes: Obtaining a motion parameter measurement deviation index according to the step number error data, the motion distance error data and the motion speed error data; The exercise pattern recognition accuracy evaluation factor is obtained according to the exercise intensity recognition accuracy, intelligent prompt accuracy and exercise type recognition accuracy.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a smart wearable device motion monitoring effect evaluation program. When the smart wearable device motion monitoring effect evaluation program is executed by the processor, the steps of the smart wearable device motion monitoring effect evaluation method as described in any one of claims 1 to 6 are implemented.

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