Method, device and equipment for intelligently adjusting crawler belt speed of treadmill and medium

Abstract

The invention discloses a method, a device, equipment and a medium for intelligently adjusting the track speed of a treadmill, and relates to the technical field of treadmill speed regulation, and the method comprises the following steps: receiving position data sent by a laser radar sensor, and determining the stride frequency and stride difference of a runner according to the position data; determining a target speed according to the stride frequency and the stride difference; and adjusting the speed of the treadmill track to the target speed. The stride frequency and stride difference of a runner are captured in real time through the laser radar, and direct dynamic association between the human body motion intention and the track speed is established. The step change trend is accurately quantified through the step difference, so that the system prejudges the speed regulation requirement before the gravity center of a runner shifts, and near-real-time response is achieved; and meanwhile, the traditional fixed partition constraint is eliminated, and the risk of response lag and deceleration region falling caused by partition switching is avoided. On the basis of closed-loop control of motion intrinsic parameters, full-time-domain active safety protection is constructed while speed regulation precision is improved, and motion safety and self-adaptive experience are remarkably optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of treadmill speed regulation, and in particular to a method and device for intelligently adjusting the speed of a treadmill belt, as well as a device and medium. BACKGROUND

[0002] In the field of intelligent speed regulation for treadmills, the current mainstream technology uses a speed control strategy based on belt partitioning. This method divides the belt into multiple fixed functional zones along the length direction. Typical implementations include an acceleration zone at the front of the belt, a constant speed zone in the middle, and a deceleration zone at the back. By installing position sensors (such as pressure sensors or infrared sensors) on the treadmill, the real-time position of the user on the belt is detected. When the user enters the acceleration zone, the control system drives the belt to accelerate. When the user is in the constant speed zone, the current speed of the belt is maintained. If the user moves to the deceleration zone, the belt deceleration instruction is triggered.

[0003] Although this technical solution achieves basic speed regulation functions, it has the following inherent defects:

[0004] Insufficient speed regulation accuracy and response speed: Because the acceleration, constant speed, and deceleration zones need to reserve a large physical space to ensure detection reliability, the user must move a significant distance to trigger speed switching. This absolute position-triggered mechanism causes a significant lag in speed adjustment, which cannot respond to the user's instantaneous gait changes in a timely manner. Especially when switching between acceleration and deceleration states, the user needs to cross the entire constant speed zone, further exacerbating the response delay problem, causing a mismatch between the exercise rhythm and the belt speed.

[0005] Safety risks are prominent: The setting of the deceleration zone fundamentally conflicts with human movement patterns. When the user's physical strength decreases, their pace naturally shifts backward to reduce exercise intensity. At this time, if they are in the deceleration zone, the belt deceleration action and the user's backward movement trend overlap, which can easily cause a loss of balance. More seriously, the deceleration zone is usually close to the end of the belt, and the user has a risk of falling in an unbalanced state, posing a substantial threat to exercise safety.

[0006] The root cause of the above defects lies in the fact that existing technologies bind speed control to the absolute physical position of the belt. The partitioned speed regulation is essentially a discrete and phased control, which is difficult to accurately adapt to continuous human movement behavior. SUMMARY

[0007] The embodiments of the present application provide a method, device, equipment and medium for intelligently adjusting the speed of a treadmill belt, aiming to solve the problems of low accuracy and safety of existing treadmill speed regulation methods.

[0008] In a first aspect, the embodiments of the present application provide a method for intelligently adjusting the speed of a treadmill belt, wherein a laser radar sensor is installed in front of the treadmill belt, the laser radar sensor collects position data of the most forward point of the runner's foot in real time, and the method comprises:

[0009] receiving the position data sent by the laser radar sensor, determining the step frequency and the stride difference of the runner according to the position data;

[0010] determining a target speed according to the step frequency and the stride difference;

[0011] adjusting the speed of the treadmill belt to the target speed.

[0012] Further technical solutions are that the position data includes distance information of the most forward point of the runner's foot from the laser radar sensor at a plurality of consecutive sampling points, and determining the step frequency of the runner according to the position data comprises:

[0013] determining the step cycle of the runner based on the time interval between the sampling points;

[0014] determining the step frequency of the runner according to the step cycle.

[0015] Further technical solutions are that determining the step cycle of the runner based on the time interval between the sampling points comprises:

[0016] obtaining the average time interval between a plurality of sampling points before the preset detection time as the step cycle of the runner.

[0017] Further technical solutions are that determining the stride difference of the runner according to the position data comprises:

[0018] calculating the stride difference of the runner through the formula dA=L n -L (n-1) .

[0019] Wherein, dA is the stride difference; L n is the distance between the most forward point of the runner's foot and the laser radar sensor at the nth sampling point, and L (n-1) is the distance between the most forward point of the runner's foot and the laser radar sensor at the (n-1)th sampling point, wherein the nth sampling point is the sampling point corresponding to the detection time.

[0020] Further technical solutions are that determining a target speed according to the step frequency and the stride difference comprises:

[0021] determining the target speed through the formula Vd=Vc+0.5*Fs*dA.

[0022] wherein Vd is the target speed, Vc is the speed of the treadmill belt corresponding to the detection time, Fs is the step frequency, and dA is the step difference.

[0023] Further, the method further comprises, before receiving the position data sent by the laser radar sensor and determining the step frequency and the step difference of the runner according to the position data:

[0024] If the start instruction is received, the speed of the treadmill belt is adjusted to a preset initial speed.

[0025] Further, the method further comprises:

[0026] If the target speed is lower than the initial speed, the treadmill belt is controlled to run at the initial speed.

[0027] In a second aspect, the embodiments of the present application further provide an apparatus for intelligently adjusting the speed of a treadmill belt, which comprises units for executing the above method.

[0028] In a third aspect, the embodiments of the present application further provide a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the above method.

[0029] In a fourth aspect, the embodiments of the present application further provide a computer readable storage medium, which stores a computer program, and the computer program is executable by a processor to implement the above method.

[0030] The embodiment of the present application provides a method, device, equipment and medium for intelligently adjusting the speed of a treadmill belt. The method comprises the following steps: receiving the position data sent by the laser radar sensor, determining the step frequency and step length difference of the runner according to the position data, determining the target speed according to the step frequency and the step length difference, and adjusting the speed of the treadmill belt to the target speed. The present application can improve the accuracy and safety of the speed adjustment of the treadmill. The present application captures the position data of the most forward point of the runner's foot in real time through the laser radar sensor, dynamically calculates the step frequency and step length difference according to the position data, and then generates a target speed control signal to drive the speed adjustment of the belt. This technical solution fundamentally changes the mechanical control logic of the traditional treadmill which relies on fixed partition triggering speed adjustment, and instead establishes a closed-loop response mechanism based on the intrinsic parameters of human motion. Since the step frequency directly reflects the speed of the running rhythm, the step length difference accurately quantifies the trend of the pace change (such as the forward movement of the toes to accelerate or the backward movement to decelerate), and the fusion of the two makes the determination of the target speed and the real-time motion intention of the runner form a strong correlation. For example, when the runner actively accelerates, the step frequency naturally increases and the step length difference is continuously positive, and the system increases the target speed in real time. Conversely, when the pace is reduced due to physical decline, the negative step length difference triggers an early deceleration, thereby compressing the speed adjustment response to a near real-time level, completely solving the significant lag problem caused by partition displacement detection in the traditional solution. At the same time, the step length difference as a predictive indicator can identify potential imbalance. When a continuous negative step length difference is detected, the system actively reduces the speed before the runner's center of gravity is significantly offset, thereby avoiding the risk of falling caused by the superposition of belt deceleration and human backward movement at the end of the traditional deceleration zone from a physical level. More importantly, this dynamic speed adjustment mechanism is free from the physical constraints of fixed functional zones, allowing the runner to freely adjust the speed according to the natural gait at any position on the belt, eliminating the speed step mutation at the partition boundary, and avoiding the motion interference caused by deliberately adjusting the running position to trigger speed adjustment. This adaptive feature is particularly critical in complex motion scenarios: such as frequent speed changes in interval training, the system continuously tracks the coordinated changes of the step frequency and step length difference, achieving millimeter-level precision matching between the belt speed and the human motion rhythm, and significantly improving the motion comfort and training efficiency. Ultimately, the control strategy based on the essential characteristics of human kinematics not only breaks through the traditional speed adjustment precision bottleneck, but also establishes a full-time active safety protection system. BRIEF DESCRIPTION OF DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creating any inventive labor.

[0032] Figure 1 The flowchart of the method for intelligently adjusting the speed of a treadmill belt provided by the embodiment of the present application;

[0033] Figure 2 The schematic block diagram of the computer device provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of the present application.

[0035] It should be understood that the terms “comprising” and “including” as used in the specification and the appended claims indicate the presence of the described features, integers, steps, operations, elements, and / or components but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0036] It should also be understood that the terms used in the present application specification are only for the purpose of describing particular embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0037] It should be further understood that the term “and / or” as used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations thereof, and includes these combinations.

[0038] As used in the present application specification and the appended claims, the term “if’ can be interpreted as “when” or “upon” or “in response to a determination” or “in response to detecting” depending on the context. Similarly, the phrase “if determined” or “if detected [the described condition or event]” can be interpreted as meaning “upon determining” or “in response to determining” or “upon detecting [the described condition or event]” or “in response to detecting [the described condition or event]” depending on the context.

[0039] Referring to Figure 1 The embodiment of the present application provides a method for intelligently adjusting the speed of a treadmill belt, which comprises the following steps:

[0040] S1, receiving the position data sent by the laser radar sensor, and determining the step frequency and stride difference of the runner according to the position data.

[0041] In specific implementation, a laser radar sensor is installed in front of the treadmill belt, which collects position data of the frontmost point of the runner's foot in real time. Specifically, the installation specification of the laser radar sensor and the measurement principle of the frontmost point of the foot are as follows:

[0042] Installation specification: The laser radar sensor is fixed in front of the treadmill belt, with the detection main axis parallel to the running direction of the treadmill belt, and the installation height is adapted to the swing range of the typical runner's foot (10-30 cm away from the belt surface), to ensure that the scanning beam can cover the foot movement track of the runner and accurately capture the position of the frontmost point of the toe.

[0043] Measurement principle of the frontmost point of the foot:

[0044] The distance point cloud sequence of the laser radar is collected in real time, each data point contains a timestamp and a distance value of the frontmost point of the foot; by calculating the slope value (Δd / Δt) of the distance change rate of adjacent data points, when the absolute value of the slope exceeds a preset threshold (such as |slope|≥5m / s), it is determined that the foot touches the ground; record the distance value L n and the occurrence time Tn, where n is the step number.

[0045] Further, after collecting the position data, the step frequency and stride difference of the runner are determined according to the position data.

[0046] For example, in some preferred embodiments, the position data includes distance information of the frontmost point of the runner's foot from the laser radar sensor at multiple consecutive sampling points, and the step "determining the step frequency of the runner according to the position data" includes: determining the step cycle of the runner based on the time interval between the sampling points; determining the step frequency of the runner according to the step cycle.

[0047] In specific implementation, in order to improve the accuracy of calculation, the average time interval between multiple sampling points before the preset detection time is obtained as the step cycle of the runner. The reciprocal of the step cycle can obtain the step frequency of the runner. The detection time can be set by those skilled in the art, for example, measuring the step frequency and stride difference once every preset time (10S), which is not specifically limited in the present application.

[0048] In the embodiment of the present application, based on the distance information of the continuous sampling points of the laser radar, the step cycle is accurately captured through the time interval. The average time interval of a plurality of sampling points before the preset detection time is taken to calculate the step cycle, and the essence is to introduce a data smoothing mechanism. For example, when the runner occasionally steps abnormally (such as avoiding obstacles) to cause distortion of a single step cycle, through the moving average of N cycles (such as N = 4), the accidental interference can be filtered out, and the stable step frequency trend can be extracted. This significantly improves the anti-interference ability: if the average processing is not used, a single abnormal step may trigger an incorrect acceleration instruction; and after the averaging, the system only responds to the persistent step frequency change, ensuring that the speed adjustment decision is consistent with the true movement intention Figure 1 .

[0049] Further, in some preferred embodiments, the above step "determining the step length difference of the runner according to the position data" comprises: calculating the step length difference of the runner through the formula dA = L n -L (n-1) .

[0050] Wherein, dA is the step length difference; L n is the distance between the frontmost point of the runner's foot and the laser radar sensor at the nth sampling point, L (n-1) is the distance between the frontmost point of the runner's foot and the laser radar sensor at the (n-1)th sampling point, wherein the nth sampling point is the sampling point corresponding to the detection time, i.e. the sampling point closest to the detection time.

[0051] In specific implementation, the calculation of the step length difference dA = L n -L (n-1) is essentially to quantify the spatial change trend of consecutive steps. When L n >L (n-1) , dA > 0 indicates that the runner is actively moving the center of gravity forward and needs to accelerate to maintain balance; otherwise dA < 0 indicates that the runner is physically declining or slowing down.

[0052] For example, in marathon training, when the athlete is tired, the step naturally shortens (L n <L (n-1) ), and the negative value of dA triggers deceleration in time, which is 1-2 steps earlier than the traditional scheme. More importantly, this calculation only requires adjacent two-step data, and the operation complexity is low, which can realize microsecond-level real-time decision-making and eliminate response delay from the physical layer.

[0053] S2, determining the target speed according to the step frequency and the step length difference.

[0054] In specific implementation, the target speed is determined according to the step frequency and the step length difference, which realizes predicting the target speed based on the actual running behavior of the user, thereby improving the accuracy.

[0055] For example, in some preferred embodiments, the above step of "determining a target speed according to the step frequency and the step length difference" specifically comprises the step of determining the target speed by the formula Vd = Vc + 0.5*Fs*dA; wherein Vd is the target speed, Vc is the speed of the treadmill belt at the detection time, Fs is the step frequency, and dA is the step length difference.

[0056] In specific implementations, the incremental design of the formula Vd = Vc + 0.5*Fs*dA creatively establishes a speed differential control mechanism.

[0057] The term Fs*dA: the step frequency Fs amplifies the speed adjustment weight of the step length difference dA (for example, under the same dA, a high step frequency requires a larger speed adjustment amount);

[0058] The coefficient 0.5: calibrates the contribution of the double-foot step length (because Vd corresponds to the single-foot moving speed, and the running speed is twice the product of the step length and the step frequency);

[0059] Superimposing the current speed Vc: to achieve smooth transition and avoid stepwise speed change.

[0060] For example, when dA = +0.1 m and Fs = 2 Hz, the target speed is increased by 0.1 m / s (0.5*2*0.1), which accurately matches the step length expansion requirement. The physical meaning of this formula is that the displacement of the human body center of gravity (dA) and the motion energy (Fs) are converted into the speed increment that the belt needs to compensate, realizing the coupling of human-machine motion.

[0061] S3, adjusting the speed of the treadmill belt to the target speed.

[0062] In specific implementations, the control treadmill adjusts the speed of the treadmill belt to the target speed, so that the data of the treadmill matches the motion posture of the user.

[0063] Further, in some preferred embodiments, before the step of "receiving the position data sent by the laser radar sensor, and determining the step frequency and the step length difference of the runner according to the position data", the method further comprises the step of: if a start instruction is received, adjusting the speed of the treadmill belt to a preset initial speed.

[0064] In specific implementations, the start instruction can be the user clicking the start button or selecting a video, which is not specifically limited by the present application. In the embodiments of the present application, the initial speed preset mechanism is used to solve the cold start safety problem. Specifically, the initial speed of the belt is set to a safety value (such as a walking speed of 0.5 m / s), and the belt runs at a low speed when the user steps on the treadmill, so that even if the user does not step in time, he or she will not fall backward and fall down, thereby ensuring safety.

[0065] In some preferred embodiments, the method further comprises the step of controlling the treadmill belt to run at the initial speed if the target speed is lower than the initial speed.

[0066] In some embodiments, the lower limit of the target speed is set to be the initial speed (e.g., 0.5 m / s) to provide a safety margin for the motion termination phase. When the runner is exhausted, the step frequency Fs drops sharply and dA is negative, and if the calculation is strictly followed, Vd can approach zero, causing the belt to stop abruptly and resulting in a risk of falling. By setting the lower limit of the target speed to be the initial speed, the system can respond to the demand for deceleration while still providing a safety margin. For example, in an emergency stop scenario, the system can maintain a safe low speed instead of stopping immediately, embodying the core design philosophy of "gradual safety".

[0067] Further, upon receiving a stop instruction (e.g., the user clicks the stop button or the video playback is complete), the treadmill belt is controlled to stop moving slowly.

[0068] The embodiment of the present application provides a method for intelligently adjusting the speed of a treadmill belt, comprising: receiving the position data sent by the laser radar sensor, determining the step frequency and the step length difference of the runner according to the position data; determining the target speed according to the step frequency and the step length difference; and adjusting the speed of the treadmill belt to the target speed. The present application can improve the accuracy and safety of the speed adjustment of the treadmill. The present application captures the position data of the most forward point of the runner's foot in real time through the laser radar sensor, dynamically calculates the step frequency and the step length difference according to the position data, and then generates a target speed control signal to drive the speed adjustment of the belt. This technical solution fundamentally changes the mechanical control logic of the traditional treadmill which relies on fixed partition triggering speed adjustment, and instead establishes a closed-loop response mechanism based on the intrinsic parameters of human motion. Since the step frequency directly reflects the speed of the running rhythm, the step length difference accurately quantifies the trend of the pace change (such as the forward movement of the toes to accelerate or the backward movement to decelerate), and the fusion of the two makes the determination of the target speed and the real-time motion intention of the runner form a strong correlation. For example, when the runner actively accelerates, the step frequency naturally increases and the step length difference is continuously positive, and the system increases the target speed in real time; on the contrary, when the body strength decreases and the pace is reduced, the negative step length difference triggers the speed reduction in advance, thereby compressing the speed adjustment response to a near real-time level, completely solving the significant lag problem caused by partition displacement detection in the traditional solution. At the same time, the step length difference as a predictive indicator can identify the potential imbalance state - when a continuous negative step length difference is detected, the system actively reduces the speed before the runner's center of gravity is significantly offset, thereby avoiding the falling risk caused by the superposition of belt speed reduction and human backward movement at the end of the traditional deceleration zone from the physical level. More importantly, this dynamic speed adjustment mechanism breaks free from the physical constraints of fixed functional areas, allowing the runner to freely adjust the speed according to the natural gait at any position of the belt, eliminating the speed step mutation at the partition boundary and avoiding the motion disturbance caused by deliberately adjusting the running position to trigger speed adjustment. This adaptive feature is particularly critical in complex motion scenarios: such as frequent speed changes in interval training, the system continuously tracks the coordinated changes of the step frequency and the step length difference, realizes the millimeter-level precision matching between the belt speed and the human motion rhythm, and significantly improves the motion comfort and training efficiency. Finally, the control strategy based on the essential characteristics of human kinematics not only breaks through the traditional speed adjustment precision bottleneck, but also builds a full-time active safety protection system.

[0069] Corresponding to the above method for intelligently adjusting the speed of a treadmill belt, the present application also provides an apparatus for intelligently adjusting the speed of a treadmill belt. The apparatus for intelligently adjusting the speed of a treadmill belt comprises units for executing the above method for intelligently adjusting the speed of a treadmill belt, and the apparatus for intelligently adjusting the speed of a treadmill belt can be configured in a desktop computer, a tablet computer, a laptop computer, or the like terminal. Specifically, the apparatus for intelligently adjusting the speed of a treadmill belt comprises:

[0070] A receiving unit is configured to receive the position data sent by the laser radar sensor, and determine the step frequency and the step length difference of the runner according to the position data.

[0071] a determining unit configured to determine a target speed according to the step frequency and the step length difference;

[0072] a first adjusting unit configured to adjust the speed of the treadmill belt to the target speed.

[0073] In some preferred embodiments, the position data comprises distance information of the most forward point of the runner's foot from the lidar sensor at a plurality of consecutive sampling points, and the step frequency of the runner is determined according to the position data, comprising:

[0074] determining the step cycle of the runner based on the time interval between the sampling points;

[0075] determining the step frequency of the runner according to the step cycle.

[0076] In some preferred embodiments, the determining the step cycle of the runner based on the time interval between the sampling points comprises:

[0077] obtaining the average time interval between a plurality of the sampling points before the preset detection time as the step cycle of the runner.

[0078] In some preferred embodiments, the step length difference of the runner is determined according to the position data, comprising:

[0079] calculating the step length difference of the runner by the formula dA = L n -L (n-1) n

[0080] wherein dA is the step length difference; L n is the distance between the most forward point of the runner's foot and the lidar sensor at the nth sampling point, and L (n-1) is the distance between the most forward point of the runner's foot and the lidar sensor at the (n-1)th sampling point, wherein the nth sampling point is the sampling point corresponding to the detection time.

[0081] In some preferred embodiments, the target speed is determined according to the step frequency and the step length difference, comprising:

[0082] determining the target speed by the formula Vd = Vc + 0.5 * Fs * dA;

[0083] wherein Vd is the target speed, Vc is the speed of the treadmill belt corresponding to the detection time, Fs is the step frequency, and dA is the step length difference.

[0084] In some preferred embodiments, the device for intelligently adjusting the speed of the treadmill belt further comprises:

[0085] a second adjusting unit, configured to adjust the speed of the treadmill belt to a preset initial speed if the start instruction is received.

[0086] In some preferred embodiments, the device for intelligently adjusting the speed of the treadmill belt further comprises:

[0087] a third adjusting unit, configured to control the treadmill belt to run at the initial speed if the target speed is lower than the initial speed.

[0088] It should be noted that the specific implementation process of the device for intelligently adjusting the speed of the treadmill belt and each unit can be clearly understood by those skilled in the art, which can be referred to the corresponding description in the foregoing method embodiments. For the convenience and brevity of description, it will not be repeated here.

[0089] The device for intelligently adjusting the speed of the treadmill belt can be implemented in the form of a computer program, which can run on a computer device as shown in the specification. Figure 2

[0090] Please refer to Figure 2 , Figure 2 is a schematic block diagram of a computer device provided by an embodiment of the present application. The computer device 500 can be a terminal or a server.

[0091] The computer device 500 includes a processor 502, a memory and a network interface 505 connected through a system bus 501, wherein the memory can include a non-volatile storage medium 503 and an internal memory 504.

[0092] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, can make the processor 502 execute a method for intelligently adjusting the speed of the treadmill belt.

[0093] The processor 502 is configured to provide computing and control capabilities to support the operation of the entire computer device 500.

[0094] The internal memory 504 provides an environment for the running of the computer program 5032 in the non-volatile storage medium 503. The computer program 5032, when executed by the processor 502, can make the processor 502 execute a method for intelligently adjusting the speed of the treadmill belt.

[0095] ​The network interface 505 is configured to communicate with other devices via a network. Those skilled in the art can understand that the above structure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device 500 to which the scheme of the present application is applied. Specifically, the computer device 500 can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0096] The processor 502 is configured to run the computer program 5032 stored in the memory to implement the following steps:

[0097] receiving the position data sent by the laser radar sensor, determining the step frequency and the stride difference of the runner according to the position data;

[0098] determining a target speed according to the step frequency and the stride difference;

[0099] adjusting the speed of the treadmill belt to the target speed.

[0100] In some preferred embodiments, the position data includes distance information of the most forward point of the runner's foot from the laser radar sensor at a plurality of consecutive sampling points, and determining the step frequency of the runner according to the position data includes:

[0101] determining the step cycle of the runner based on the time interval between the sampling points;

[0102] determining the step frequency of the runner according to the step cycle.

[0103] In some preferred embodiments, determining the step cycle of the runner based on the time interval between the sampling points includes:

[0104] obtaining the average time interval between a plurality of sampling points before the preset detection time as the step cycle of the runner.

[0105] In some preferred embodiments, determining the stride difference of the runner according to the position data includes:

[0106] calculating the stride difference of the runner by the formula dA=L n -L (n-1)

[0107] wherein dA is the stride difference; L n is the distance between the most forward point of the runner's foot and the laser radar sensor at the nth sampling point, and L (n-1) is the distance between the most forward point of the runner's foot and the laser radar sensor at the (n-1)th sampling point, wherein the nth sampling point is the sampling point corresponding to the detection time.​

[0108] In some preferred embodiments, the determining the target speed according to the step frequency and the step length difference comprises:

[0109] The target speed is determined by the formula Vd = Vc + 0.5 * Fs * dA.

[0110] Wherein, Vd is the target speed, Vc is the speed of the treadmill belt corresponding to the detection time, Fs is the step frequency, and dA is the step length difference.

[0111] In some preferred embodiments, before the receiving the position data sent by the laser radar sensor and the determining the step frequency and the step length difference of the runner according to the position data, the method further comprises:

[0112] If a start instruction is received, the speed of the treadmill belt is adjusted to a preset initial speed.

[0113] In some preferred embodiments, the method further comprises: if the target speed is lower than the initial speed, controlling the treadmill belt to run at the initial speed.

[0114] It should be understood that, in the embodiments of the present application, the processor 502 can be a central processing unit (CPU), and the processor 502 can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0115] It can be understood by those skilled in the art that all or part of the processes in the method of the above embodiments can be completed by a computer program instructing related hardware. The computer program can be stored in a storage medium, which is a computer readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the above-mentioned embodiments of the method.

[0116] Therefore, the present application also provides a storage medium. The storage medium can be a computer readable storage medium. The storage medium stores a computer program. The computer program is executed by a processor to make the processor perform the following steps:

[0117] receiving the position data sent by the lidar sensor, determining a step frequency and a stride difference of the runner according to the position data;

[0118] determining a target speed according to the step frequency and the stride difference;

[0119] adjusting a speed of the treadmill belt to the target speed.

[0120] In some preferred embodiments, the position data comprises distance information of a foot foremost point of the runner from the lidar sensor at a plurality of consecutive sampling points, and determining the step frequency of the runner according to the position data comprises:

[0121] determining a step cycle of the runner based on time intervals between the sampling points;

[0122] determining the step frequency of the runner according to the step cycle.

[0123] In some preferred embodiments, the determining the step cycle of the runner based on time intervals between the sampling points comprises:

[0124] obtaining an average time interval between a plurality of the sampling points before a preset detection time as the step cycle of the runner.

[0125] In some preferred embodiments, determining the stride difference of the runner according to the position data comprises:

[0126] calculating the stride difference of the runner by a formula dA = L n -L (n-1) n n n-1 (n-1) n

[0127] wherein dA is the stride difference; L n n (n-1) n-1

[0128] In some preferred embodiments, the determining the target speed according to the step frequency and the stride difference comprises:

[0129] determining the target speed by a formula Vd = Vc + 0.5 * Fs * dA;

[0130] wherein Vd is the target speed, Vc is a speed of the treadmill belt corresponding to the detection time, Fs is the step frequency, and dA is the stride difference.

[0131] In some preferred embodiments, before the receiving the position data transmitted by the laser radar sensor, determining the step frequency of the runner according to the position data, and determining the step length difference, the method further comprises:

[0132] If the start instruction is received, the speed of the treadmill belt is adjusted to a preset initial speed.

[0133] In some preferred embodiments, the method further comprises: if the target speed is lower than the initial speed, controlling the treadmill belt to run at the initial speed.

[0134] The storage medium is a physical, non-transient storage medium, which can be a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk, and various physical storage media that can store program codes. The computer readable storage medium can be non-volatile or volatile.

[0135] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the above description in general terms. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0136] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and actual implementation can have another division manner. For example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not executed.

[0137] The steps in the method of the embodiments of the present application can be adjusted, combined and deleted in sequence according to actual needs. The units in the device of the embodiments of the present application can be combined, divided and deleted according to actual needs. In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0138] The integrated unit, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part of the prior art that contributes to the present application, or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application.

[0139] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0140] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, these modifications and variations of the present application also belong to the scope of the claims of the present application and its equivalent technologies, and the present application also intends to include these modifications and variations.

[0141] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for intelligently adjusting the speed of a treadmill belt, characterized in that, A lidar sensor is installed at the front of the treadmill belt. The lidar sensor collects real-time position data of the foremost point of the runner's foot. The method includes: Receive the location data sent by the lidar sensor, and determine the runner's cadence and stride difference based on the location data; The target speed is determined based on the step frequency and the step size difference; Adjust the speed of the treadmill belt to the target speed.

2. The method for intelligently adjusting the speed of a treadmill belt according to claim 1, characterized in that, The location data includes distance information of the runner's foremost foot point from the lidar sensor at multiple consecutive sampling points. Determining the runner's stride frequency based on the location data includes: The runner's stride period is determined based on the time interval between the sampling points; The runner's cadence is determined based on the gait cycle.

3. The method for intelligently adjusting the speed of a treadmill belt according to claim 2, characterized in that, Determining the runner's stride period based on the time interval between the sampling points includes: The average time interval between multiple sampling points prior to a preset detection time is obtained as the runner's stride cycle.

4. The method for intelligently adjusting the speed of a treadmill belt according to claim 3, characterized in that, Determining the runner's stride difference based on the location data includes: Using the formula dA=L n -L (n-1) Calculate the stride difference of the runners; Where dA is the stride difference; L n Let L be the distance between the runner's foremost foot and the lidar sensor at the nth sampling point. (n-1) Let n be the distance between the foremost point of the runner's foot and the lidar sensor at the (n-1)th sampling point, where the nth sampling point is the sampling point corresponding to the detection time.

5. The method for intelligently adjusting the speed of a treadmill belt according to claim 4, characterized in that, Determining the target speed based on the step frequency and the step size difference includes: The target velocity is determined using the formula Vd = Vc + 0.5 * Fs * dA; Wherein, Vd is the target speed, Vc is the speed of the treadmill belt at the detection time, Fs is the step frequency, and dA is the stride difference.

6. The method according to claim 1, characterized in that, Before receiving the location data sent by the lidar sensor and determining the runner's cadence and stride difference based on the location data, the method further includes: If a start command is received, the speed of the treadmill belt is adjusted to the preset initial speed.

7. The method according to claim 6, characterized in that, The method further includes: If the target speed is lower than the initial speed, control the treadmill belt to run at the initial speed.

8. A device for intelligently adjusting the speed of a treadmill belt, characterized in that, Includes a unit for performing the method as described in any one of claims 1-7.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the method as described in any one of claims 1-7.

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