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Universal gait autocorrelation pedometer for IOS and android platforms

An autocorrelation and pedometer technology, which is applied in instruments, measuring devices, surveying and navigation, etc., can solve the problems of low step counting accuracy of the module, low willingness of users to use it for a long time, and the inability of the module to be directly transplanted to android devices, etc. , to achieve the effect of accurate step counting and practicality

Inactive Publication Date: 2017-10-20
浙江斑智科技有限公司
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AI Technical Summary

Problems solved by technology

[0003] At present, IOS devices have built-in pedometers, but the step counting accuracy of this module is not high, and at the same time, this module cannot be directly transplanted to android devices
In addition to mobile phones, there are many wearable devices that can count steps, but these devices need to be worn on a certain part of the body, and users are not willing to use them for a long time

Method used

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  • Universal gait autocorrelation pedometer for IOS and android platforms
  • Universal gait autocorrelation pedometer for IOS and android platforms
  • Universal gait autocorrelation pedometer for IOS and android platforms

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Embodiment Construction

[0031] Attached below figure 1 Introduce the specific implementation manner of the present invention, each frame in the figure represents a functional module or a section of executable code, and these modules are to occur in the order marked in the figure, in addition, all modules in the figure can pass code on IOS and android platforms accomplish.

[0032] First determine the frequency of mobile phone data. The IOS platform can directly set the required sensor data frequency. The sensor frequency of the android platform is divided into four levels: Normal, UI, Game, and Fast. The corresponding frequencies are about 5HZ, 15HZ, 50HZ, and 100HZ. For IOS devices, set the system sampling frequency to 30HZ; for Android devices, set the system sampling frequency to Game;

[0033] Secondly, recursive sampling is performed on the data obtained by mobile phone sampling to stabilize the data frequency at 15HZ. The so-called recursive sampling refers to recursive decomposition of the sa...

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Abstract

The invention provides a universal gait autocorrelation pedometer for IOS and android platforms and relates to an implementation method of the universal pedometer for the IOS and android platforms and the pedometer. According to the method, a high-precision step calculation function is realized on the basis of data of an acceleration sensor of a mobile phone, and the mobile phone can be carried by a user in any postures, for example, the mobile phone can be held in hands and placed in a pocket of a coat / trousers or a backpack and the like. The method comprises steps as follows: determining sampling frequency of the acceleration sensor, performing low-pass filtering treatment on original data to eliminate noise, calculating fluctuation degree and gait autocorrelation coefficient with a dynamic autocorrelation algorithm, and counting the number of steps. The universal gait autocorrelation pedometer can be used for counting the number of daily walking steps for the mobile phones provided with the acceleration sensor and IOS / android operating systems, the method is provided for various APPs for determining walking behavior of the user, a tool is provided for the user for recording daily activities, and the universal gait autocorrelation pedometer has the characteristics that user behaviors are not required to be preset for training, the statistical accuracy is high, cross-platform use can be realized and the like.

Description

technical field [0001] The invention relates to a common pedometer implementation method on IOS and android platforms, in particular to the technology of collecting acceleration sensor data, stabilizing frequency, filtering and denoising, and calculating to achieve the pedometer effect. Background technique [0002] With the popularity of smart phones and the advancement of sensor technology, more and more mobile phones have built-in various sensors. The big data contained in these sensors can help users / third-party APPs to monitor users' daily behavior more conveniently, which is convenient for users. Statistics of daily exercise and consumption, for third-party APPs, can understand the current status of users, and make scene-based recommendations for users / avoid disturbing users. [0003] Currently, IOS devices have a built-in pedometer, but the accuracy of this module is not high. At the same time, this module cannot be directly transplanted to android devices. In addi...

Claims

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Application Information

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IPC IPC(8): G01C22/00
CPCG01C22/006
Inventor 胡晓伟任娟叶宽余
Owner 浙江斑智科技有限公司
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