Treadmill landing mode analysis method, treadmill and storage medium

Abstract

The invention relates to the technical field of treadmills, in particular to a treadmill landing mode analysis method, a treadmill and a storage medium. The treadmill landing mode analysis method comprises the following steps: acquiring real-time air pressure data of a left air bag and a right air bag, and respectively generating air pressure time sequence curves; distinguishing a plurality of left foot landing data segments and a plurality of right foot landing data segments based on the air pressure time sequence curve; intercepting a left foot landing data segment and / or a right foot landing data segment for gait analysis; identifying and judging whether double peaks exist in the left foot landing data segment and / or the right foot landing data segment by adopting a peak searching algorithm; if the two peaks exist, the landing mode of the foot is heel landing; if the two peaks do not exist, whether the waveform is smooth or not is judged, if the waveform is smooth, the landing mode of the foot is tiptoe landing, and otherwise, the landing mode of the foot is sole landing. According to the method, the landing mode of the user can be visually reflected, wearing is not needed, and the daily running habit of the user is not affected.

Description

Technical Field

[0001] The present invention relates to the technical field of treadmills, and particularly to a method for analyzing the landing mode of a treadmill, a treadmill, and a storage medium. Background Art

[0002] As an aerobic fitness equipment that is not affected by the weather and can conveniently control the exercise intensity by adjusting the speed and slope, electric treadmills are increasingly entering families to meet the needs of home fitness exercises. Due to the lack of professional guidance for runners, incorrect running postures often occur, resulting in poor exercise effects or exercise injuries. For this reason, various treadmills with running posture analysis functions have also emerged in the prior art. For example, the running posture analysis method based on running video images disclosed in the Chinese patent publication (CN115188063A), the running posture detection method based on intelligent wearable devices disclosed in the Chinese patent publication (CN113457106A), and the quantitative evaluation method of lower limb motor ability based on thin film pressure sensors on insoles disclosed in the Chinese patent publication (CN109331406A).

[0003] Although shock-absorbing airbags have been provided between the treadmill chassis and the running board in the prior art, the current application of shock-absorbing airbags is limited to using their compression deformation to achieve the functions of buffering, shock absorption, and adjusting softness and hardness, but no analysis method for running postures including landing modes using the pressure change of shock-absorbing airbags has been disclosed. The landing mode refers to the way of contacting the ground at the moment of single-foot landing, which is divided into forefoot landing, full-foot landing, and heel landing, and is affected by running shoes, the runner's own habits, lower limb muscle strength level, pace, terrain, etc.; detecting the landing mode is beneficial to assisting in analyzing the reason for the user's excessive impact load rate and giving improvement suggestions to the user based on the landing mode. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for analyzing the landing mode of a treadmill, a treadmill, and a storage medium, which can intuitively reflect the user's landing mode, does not require wearing, and does not affect the user's daily running habits.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is: A method for analyzing the landing mode of a treadmill includes the following steps: S1. Obtain the real-time air pressure data of the left airbag and the right airbag and generate air pressure time series curves respectively; S2. Based on the air pressure time series curves, distinguish multiple left-foot landing data segments and multiple right-foot landing data segments; S3. Intercept the left-foot landing data segment and / or the right-foot landing data segment for gait analysis; S4. Use a peak-seeking algorithm to identify and determine whether there are double peaks in the left-foot landing data segment and / or the right-foot landing data segment; S5. If there are two peaks, the landing mode of this foot is heel landing; S6. If there are no two peaks, then combine with judging whether the waveform is smooth. If the waveform is smooth, the landing mode of this foot is toe landing; otherwise, the landing mode of this foot is sole landing.

[0006] Preferably, the distinguishing method in step S2 is specifically as follows: Call the air pressure time series curves on the left and right sides and obtain the difference waveform at the same moment based on the following difference formula. If the difference is positive, it means the left foot lands; if the difference is negative, it means the right foot lands; the difference formula is: .

[0007] Preferably, the distinguishing method in step S2 is specifically as follows: Call the air pressure time series curves on the left and right sides; calculate the peak-valley ratios of the peak air pressure data and the valley air pressure data on the left and right sides respectively within the same time period; if the peak-valley ratio on the left side is greater than the peak-valley ratio on the right side, it means the left foot lands; if the peak-valley ratio on the right side is greater than the peak-valley ratio on the left side, it means the right foot lands.

[0008] Preferably, the method for judging whether the waveform is smooth is as follows: Obtain the waveform starting point, peak point, and the amount of data between the waveform starting point and the peak point; Calculate the average change value from the waveform starting point to the peak point; Calculate the change value between every two data points between the waveform starting point and the peak point; Compare the size between the average change value and the change value between every two data points. When there is an obvious difference between the change value between every two data points and the average change value, it is non-smooth; otherwise, it is smooth.

[0009] Preferably, every two data points are real-time air pressure data collected adjacent to each other before and after.

[0010] Preferably, the collection frequency is once every 8 milliseconds to 50 milliseconds, and more preferably the collection frequency is once every 10 milliseconds to 25 milliseconds.

[0011] Preferably, the judgment index for there being an obvious difference between the change value between every two data points and the average change value is that the absolute value of the accumulated value of 5 - 20 difference results is greater than or equal to the threshold value, and more preferably it is the absolute value of the accumulated value of 10 - 15 difference results.

[0012] Preferably, the threshold value is a point value between 20 and 30.

[0013] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0014] The present invention further provides a treadmill, comprising a treadmill body and a controller, wherein the controller comprises a memory, a processor and a computer program stored in the memory and running on the processor, and the steps of the above method are implemented when the processor executes the computer program; an air pressure sensor for monitoring the air pressure inside the airbag is respectively connected to the left airbag and the right airbag, and the air pressure sensor is electrically connected to the controller through an air pressure acquisition circuit to input real-time air pressure data to the controller.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention utilizes the left airbag and the right airbag that directly act on the left and right sides of the running board, collects in real time the internal air pressure data changes caused by the squeezing degree of the left airbag and the right airbag by the running board during running, and adopts the left and right air pressure difference or the left and right peak-to-valley ratio difference from the left air pressure timing curve and the right air pressure timing curve to analyze and distinguish the different data segments of the left foot landing, the right foot landing and both feet vacant in the air pressure timing curve of each airbag, thereby realizing the landing mode from the corresponding band analysis.

[0016] The data source of the present invention is the contact between the sole of the foot and the running board, which is a direct reflection of the force exerted by the running board, and can intuitively reflect the user's landing method. This method does not require wearing and does not affect the user's daily running habits. Although the running posture data collected by this method is not as accurate as that of pressure insoles, because the data source is relatively direct, the accuracy is greatly improved compared to the three-axis acceleration sensor on the instep. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a principle block diagram of the air pressure sensor and controller of the present invention.

[0018] Figure 2 The figure is a flow chart for analyzing the landing mode of the treadmill of the present invention.

[0019] Figure 3 This is a schematic diagram of the principle of differentiating left and right feet by difference in the present invention.

[0020] Figure 4 This is a waveform diagram of the present invention for distinguishing left and right feet by difference.

[0021] Figure 5 It is a schematic diagram of the band curves corresponding to the three landing modes of the present invention. DETAILED DESCRIPTION

[0022] In order to make the above features and advantages of the present invention more obvious and easy to understand, embodiments are given below with reference to the accompanying drawings for detailed description as follows.

[0023] The present embodiment provides a treadmill, including a treadmill body and a controller, wherein the controller includes a memory, a processor, and a computer program stored in the memory and running on the processor. The treadmill body of the present embodiment includes a chassis, a running board, and a left airbag and a right airbag located on the left and right sides between the chassis and the running board. The installation structure of the left airbag and the right airbag between the chassis and the running board is not limited. During running, the left airbag and the right airbag respectively support and withstand the impact of the running board to produce a shock-absorbing effect. The left airbag and the right airbag of the present embodiment are respectively connected to an air pressure sensor for monitoring the air pressure inside the airbag. The air pressure sensor is electrically connected to the controller through a conventional air pressure acquisition circuit to input real-time air pressure data to the controller. The principle block diagram is shown in FIG. Figure 1 .

[0024] like Figure 2 As shown, when the processor executes the computer program, the steps of analyzing the landing mode are implemented, specifically: S1. Obtain the real-time air pressure data of the left and right air bags and generate air pressure timing curves respectively. Every two data points are real-time air pressure data collected adjacent to each other. The air pressure sensor collects data every 8 to 50 milliseconds, and the more preferred collection frequency is every 10 to 25 milliseconds. Perform conventional IIR filtering and denoising on the real-time air pressure data before generating the air pressure timing curve. It should be noted that since the left and right air bags are installed below the left and right sides of the running board, when the left foot is supported, the left air bag will be compressed to produce pressure changes, and the right air bag will also be compressed to produce different degrees of pressure changes. Similarly, when the right foot is supported, the left and right air bags will also produce pressure changes. This also results in the need to perform step S2 to distinguish which section of the air pressure timing curves on the left and right sides belongs to the left foot landing, the right foot landing, and both feet in the air.

[0025] S2. Distinguish a plurality of left foot landing data segments and a plurality of right foot landing data segments based on the air pressure timing curve.

[0026] One of the distinguishing methods in step S2 is: Figures 3 to 4 As shown, the air pressure timing curves on the left and right sides are called and the difference waveform at the same time is obtained based on the following difference formula. If the difference is positive, the left foot is on the ground, and if the difference is negative, the right foot is on the ground; the difference formula is: .

[0027] The second distinguishing method in step S2 is: calling the air pressure time series curves on the left and right sides; respectively calculating the peak-to-valley ratios of the peak air pressure data and the trough air pressure data on the left and right sides in the same time period; if the peak-to-valley ratio on the left side is greater than the peak-to-valley ratio on the right side, it means the left foot has touched the ground, and if the peak-to-valley ratio on the right side is greater than the peak-to-valley ratio on the left side, it means the right foot has touched the ground.

[0028] S3, intercepting the left foot landing data segment and / or the right foot landing data segment for gait analysis. When the left foot landing mode is to be analyzed, the left foot landing data segment is intercepted; when the right foot landing mode is to be analyzed, the right foot landing data segment is intercepted.

[0029] S4, using a peak-finding algorithm to identify and determine whether there are double peaks in the left foot landing data segment and / or the right foot landing data segment. The peak-finding algorithm is already very common and will not be described in detail here.

[0030] S5. If there are double peaks, the foot lands on the heel.

[0031] S6. If there are no double peaks, determine whether the waveform is smooth. If the waveform is smooth, the foot lands on the tiptoe. Otherwise, the foot lands on the sole.

[0032] The method to judge whether the waveform is smooth is: Get the starting point of the waveform , peak point , the amount of data between the waveform start point and the peak point ; Calculate the average change value from the waveform starting point to the peak point ; Calculate the change value of every two data points between the waveform starting point and the peak point ; Compare the average change values The change between every two data points If there is a significant difference between the change value of each two data points and the average change value, it is non-smooth, otherwise it is smooth (such as Figure 5 as shown).

[0033] The judgment indicator that there is a clear difference between the change value of each two data points and the average change value is that the absolute value of the cumulative value of 5-20 consecutive, more preferably 10-15, difference results is greater than or equal to a threshold, and the threshold is a point value between 20-30, for example, the threshold is 25.

[0034] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0035] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the running status monitoring device.

[0036] The processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the treadmill and connects all parts of the entire treadmill through various interfaces and circuits.

[0037] The memory can be used to store the computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory, and by calling the data stored in the memory, the processor realizes various functions of the treadmill. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital card (SD), a flash card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0038] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. Analysis method for the landing mode of a treadmill, characterized in that, It includes the following steps: S1. Obtain the real-time air pressure data of the left airbag and the right airbag, and respectively generate air pressure time series curves; S2. Based on the air pressure time series curves, distinguish multiple left-foot landing data segments and multiple right-foot landing data segments; S3. Intercept the left-foot landing data segment and / or right-foot landing data segment for gait analysis; S4. Use a peak-finding algorithm to identify and determine whether there are double peaks in the left-foot landing data segment and / or right-foot landing data segment; S5. If there are double peaks, the landing mode of this foot is heel landing; S6. If there are no double peaks, then combine to judge whether the waveform is smooth. If the waveform is smooth, the landing mode of this foot is toe landing, otherwise the landing mode of this foot is sole landing.

2. The method for analyzing the landing mode of a treadmill according to claim 1, characterized in that: The specific method for distinguishing in step S2 is as follows: Call the air pressure time sequence curves on the left and right sides and obtain the difference waveform at the same moment based on the following subtraction formula. If the difference is positive, it means the left foot touches the ground; if the difference is negative, it means the right foot touches the ground. The subtraction formula is: .

3. The method for analyzing the landing mode of a treadmill according to claim 1, characterized in that: The specific method for distinguishing in step S2 is: call the air pressure time series curves on the left and right sides; respectively calculate the peak-valley ratios of the peak air pressure data and the valley air pressure data on the left and right sides within the same time period; if the peak-valley ratio on the left is greater than the peak-valley ratio on the right, it is left-foot landing, and if the peak-valley ratio on the right is greater than the peak-valley ratio on the left, it is right-foot landing.

4. The method for analyzing the landing mode of a treadmill according to any one of claims 1 to 3, characterized in that: The method for judging whether the waveform is smooth is: Obtain the waveform starting point, the peak point, and the data volume between the waveform starting point and the peak point; Calculate the average change value from the waveform starting point to the peak point; Calculate the change value between every two data points between the waveform starting point and the peak point; Compare the magnitudes between the average change value and the change value between every two data points. When there is an obvious difference between the change value between every two data points and the average change value, it is non-smooth, otherwise it is smooth.

5. The method for analyzing the landing mode of a treadmill according to claim 4, characterized in that: Every two data points are real-time air pressure data collected adjacent to each other before and after.

6. The method for analyzing the landing mode of a treadmill according to claim 5, characterized in that: The acquisition frequency is once every 8 milliseconds to 50 milliseconds.

7. The method for analyzing the landing mode of a treadmill according to claim 4, characterized in that: The judgment index for there being an obvious difference between the change value between every two data points and the average change value is that the absolute value of the cumulative value of 5-20 difference results is greater than or equal to the threshold.

8. The method for analyzing the landing mode of a treadmill according to claim 7, characterized in that: The threshold is a point value between 20 and 30.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

10. A treadmill, comprising a treadmill body and a controller, characterized in that, The controller includes a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8; air pressure sensors for monitoring the internal air pressure of the airbags are respectively connected and arranged on the left airbag and the right airbag, and the air pressure sensors are electrically connected to the controller through an air pressure acquisition circuit to input real-time air pressure data to the controller.

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