Self-adaptive running rhythm excitation and control method and device
The adaptive beat control solution is constructed through pressure sensors and smart watches, which solves the problem of step frequency mismatch in the traditional running beat system, realizes real-time adjustment of dynamic beats and physiological adaptability, and improves the user's movement efficiency and experience.
Patent Information
- Application Number
- CN202510466897.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-15
- Publication Date
- 2025-08-08
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Traditional running beat systems cannot perceive changes in the user's dynamic physiological state in real time, resulting in mismatch between the pace frequency and the terrain, increasing the probability of sports injury, and lacking physiological adaptability and single interaction methods.
Through the pressure sensor, the smart watch builds a dynamic beat control scheme to generate adaptive vibration and audio beat excitation signals, and adjusts in real time to match the user's pace frequency.
Accurately reflect the user's movement status, improve exercise efficiency, reduce fatigue risks, enhance interaction methods, and improve user experience.
Smart Images
Figure CN120437568A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of fitness equipment, and in particular to an adaptive running rhythm motivation and control method and device. Background Art
[0002] Traditional running rhythm systems generally adopt a preset fixed rhythm mode, guiding users to maintain a constant cadence through audio or vibration signals. Its static rhythm output mode cannot adapt to the user's dynamically changing physiological state during running. When the user needs to adjust the cadence due to muscle fatigue, changes in cardiopulmonary load, sudden physical fluctuations or terrain changes, the system lacks real-time perception and dynamic adjustment mechanisms, which may lead to reduced exercise efficiency or excessive fatigue risk, resulting in a mismatch between cadence and terrain, and an increased probability of sports injuries; moreover, traditional equipment generally adopts a one-way signal output mode and lacks closed-loop monitoring of the user's cadence, resulting in a lack of physiological adaptability of the rhythm; in addition, existing technologies mostly use simple beat sound prompts, and there are problems such as a single interaction method and attention interference in complex sports scenes. Summary of the Invention
[0003] This application provides an adaptive running rhythm excitation and control method and device, which can collect plantar pressure data in real time through a pressure sensor. The smart watch time unit constructs a dynamic rhythm control scheme based on the change of pace, which more accurately reflects the user's exercise state, thereby adjusting the vibration rhythm excitation signal and the audio rhythm excitation signal to match the user's step frequency in real time, effectively solving the problem of mismatch between the rhythm setting of the traditional metronome and the user's exercise state.
[0004] In a first aspect, an embodiment of the present application provides an adaptive running rhythm motivation and control method, the method comprising:
[0005] The pressure sensor collects left heel contact pressure data, left forefoot contact pressure data, right heel contact pressure data, and right forefoot contact pressure data, and sends the data to the smart watch time unit via Bluetooth;
[0006] The smartwatch timing unit generates a first contact time location based on the received left heel contact pressure data; generates a second contact time location based on the received left forefoot contact pressure data; generates a third contact time location based on the received right heel contact pressure data; and generates a fourth contact time location based on the received right forefoot contact pressure data; and transmits the first contact time location, the second contact time location, the third contact time location, and the fourth contact time location to the smartwatch controller unit.
[0007] The smartwatch controller unit determines the motion state based on the coincidence relationship and interval duration of the first, second, third, and fourth contact time points, and generates a determination result; generates a vibration beat excitation signal and an audio beat excitation signal for the next motion cycle based on the determination result, and sends the vibration beat excitation signal to the vibration unit of the smartwatch and the audio beat excitation signal to the audio unit of the smartwatch;
[0008] The vibration unit of the smart watch plays a vibration beat excitation signal;
[0009] The smart watch audio unit plays the audio beat stimulus signal.
[0010] Furthermore, the motion state is determined based on the coincidence relationship and interval durations of the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point, and a determination result is generated, including:
[0011] The smartwatch controller unit receives the ground contact time interval data of the user within 1 minute of the walking speed, and calculates the average value of the ground contact time interval data as a reference baseline;
[0012] A sprint is determined when the first, second, third, and fourth contact points do not overlap, and the duration between the second and third contact points is between 40% and 60% of the reference baseline.
[0013] Furthermore, the method further comprises:
[0014] When the smart watch controller unit only receives the left forefoot contact pressure data and the right forefoot contact pressure data, and the interval between the second contact time point and the fourth contact time point exceeds 60% of the reference baseline, the result is determined to be toe running.
[0015] Furthermore, the method further comprises:
[0016] When the smart watch controller unit receives only the left heel contact pressure data and the right heel contact pressure data, and the interval between the first contact time point and the third contact time point exceeds 60% of the reference baseline, the result is determined to be heel running.
[0017] Furthermore, the method further comprises:
[0018] If the first, second, third, and fourth contact points do not overlap, and the duration between the second and third contact points is between 20% and 40% of the reference baseline, the result is considered jogging.
[0019] Furthermore, the method further comprises:
[0020] If the second contact time point coincides with the third contact time point, and the fourth contact time point coincides with the second contact time point of the next cycle, and the overlap duration is less than a preset threshold, and the interval duration from the first contact time point to the second contact time point and the interval duration from the third contact time point to the fourth contact time point both exceed 60% of the reference baseline, the result is determined to be a race walking.
[0021] If the second contact time point coincides with the third contact time point, and the fourth contact time point coincides with the second contact time point of the next cycle, and the overlap duration is less than a preset threshold, and the interval duration from the first contact time point to the second contact time point and the interval duration from the third contact time point to the fourth contact time point are both less than a reference baseline, the result is determined to be slow walking.
[0022] Furthermore, the method further comprises:
[0023] The smart watch controller unit adjusts the audio beat excitation signal or the vibration beat excitation signal according to a comparison result between the received current contact time position data and the audio beat excitation signal or the vibration beat excitation signal predicted in the previous exercise cycle.
[0024] In a second aspect, an embodiment of the present application provides an adaptive running rhythm incentive and control device, which includes:
[0025] The pressure sensor module is used to collect left heel contact pressure data, left forefoot contact pressure data, right heel contact pressure data, and right forefoot contact pressure data, and send the data to the smart watch time unit via Bluetooth;
[0026] a smartwatch timing unit configured to generate a first contact time location based on the received left heel contact pressure data; generate a second contact time location based on the received left forefoot contact pressure data; generate a third contact time location based on the received right heel contact pressure data; and generate a fourth contact time location based on the received right forefoot contact pressure data; and transmit the first contact time location, the second contact time location, the third contact time location, and the fourth contact time location to a smartwatch controller unit;
[0027] The smartwatch controller unit is configured to determine the motion state based on the coincidence relationship and interval duration of the first, second, third, and fourth contact time points, and generate a determination result; generate a vibration beat excitation signal and an audio beat excitation signal for the next motion cycle based on the determination result, and transmit the vibration beat excitation signal to the vibration unit of the smartwatch and the audio beat excitation signal to the audio unit of the smartwatch;
[0028] Smart watch vibration unit, used to play vibration beat excitation signal;
[0029] Smart watch audio unit, used to play audio beat excitation signals.
[0030] Furthermore, the smart watch controller unit is also used to receive the user's contact time interval data within 1 minute of the walking speed, and calculate the average value of the contact time interval data as a reference baseline; when the first contact time point, the second contact time point, the third contact time point and the fourth contact time point do not overlap, and the interval length from the second contact time point to the third contact time point is between 40% and 60% of the reference baseline, the result is judged to be fast running.
[0031] Furthermore, the smart watch controller unit is also used to adjust the audio beat excitation signal or the vibration beat excitation signal based on the comparison result between the received current contact time location data and the audio beat excitation signal or the vibration beat excitation signal predicted in the previous movement cycle.
[0032] In summary, compared with the prior art, the technical solutions provided by the embodiments of the present application have at least the following beneficial effects:
[0033] An embodiment of the present application provides an adaptive running rhythm excitation and control method. The above method can collect plantar pressure data in real time through a pressure sensor. The smart watch time unit constructs a dynamic rhythm control scheme based on the change in pace, which more accurately reflects the user's exercise state, thereby adjusting the vibration rhythm excitation signal and the audio rhythm excitation signal to match the user's step frequency in real time, effectively solving the problem of mismatch between the rhythm setting of the traditional metronome and the user's exercise state. BRIEF DESCRIPTION OF THE DRAWINGS
[0034] Figure 1 A flowchart of an adaptive running tempo incentive and control method provided as an exemplary embodiment of the present application.
[0035] Figure 2 A structural diagram of an adaptive running rhythm incentive and control device provided as an exemplary embodiment of the present application. DETAILED DESCRIPTION
[0036] 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 part of the embodiments of the present application, rather than all the embodiments.
[0037] Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of this application.
[0038] See Figure 1The embodiment of the present application provides an adaptive running rhythm incentive and control method, which specifically includes the following steps:
[0039] Step S1: The pressure sensor collects left heel contact pressure data, left forefoot contact pressure data, right heel contact pressure data, and right forefoot contact pressure data, and sends the data to the smart watch time unit via Bluetooth.
[0040] Pressure sensors are located on the left heel, left forefoot, right heel, and right forefoot of the insole. The comprehensive collection of pressure data from each contact point by the pressure sensors enables the smartwatch's time unit to more accurately generate each contact point, enabling the smartwatch controller to more accurately determine the user's exercise status and provide a better user experience. The pressure sensors serve as the foundation for data collection, and their comprehensive setup ensures smooth subsequent generation of the stimulus beat.
[0041] In step S2, the smart watch timing unit generates a first contact time location based on the received left heel contact pressure data; generates a second contact time location based on the received left forefoot contact pressure data; generates a third contact time location based on the received right heel contact pressure data, and generates a fourth contact time location based on the received right forefoot contact pressure data; and transmits the first contact time location, the second contact time location, the third contact time location, and the fourth contact time location to the smart watch controller unit.
[0042] The contact time location can be a point in time or a time period. When the contact time location is a time period, the pressure recorded when the pressure sensor first contacts the ground corresponds to the first moment, and the pressure recorded after the pressure disappears, i.e., when the force on the pressure sensor becomes zero, corresponds to the second moment. The time period between the first and second moments is the contact time location time period.
[0043] In step S3, the smart watch controller unit determines the motion state based on the coincidence relationship and interval duration of the first touchdown time point, the second touchdown time point, the third touchdown time point, and the fourth touchdown time point, and generates a determination result; based on the determination result, a vibration beat excitation signal and an audio beat excitation signal for the next motion cycle are generated, and the vibration beat excitation signal is sent to the vibration unit of the smart watch, and the audio beat excitation signal is sent to the audio unit of the smart watch.
[0044] Among them, it also includes the heart rate variability monitoring unit's preset warning range and safety range rules; when the heart rate variability monitoring unit receives heart rate variability data in the running state that is within the warning range, the smart watch controller unit will give a speed reduction rhythm; when it is outside the safety range, the smart watch controller unit will give a continuous danger prompt, slow down the rhythm and trigger a mobile phone contact communication dialogue prompt.
[0045] Step S4: the vibration unit of the smart watch plays a vibration rhythm excitation signal.
[0046] Step S5: the smart watch audio unit plays the audio beat excitation signal.
[0047] The synchronous triggering of the audio beat excitation signal and the vibration beat excitation signal allows users to focus more on the running rhythm, avoiding the problem of a single beat excitation being too weak. At the same time, it greatly reduces the interference of environmental factors on the user's running rhythm, allowing users to be more immersed in running, which is conducive to improving the user's cardiopulmonary function and running skills.
[0048] The adaptive running rhythm excitation and control method provided in the above embodiment can collect plantar pressure data in real time through a pressure sensor. The smart watch time unit constructs a dynamic rhythm control scheme based on the change in pace, which more accurately reflects the user's exercise state, thereby adjusting the vibration rhythm excitation signal and the audio rhythm excitation signal to match the user's step frequency in real time, effectively solving the problem of mismatch between the rhythm setting of the traditional metronome and the user's exercise state.
[0049] In some embodiments, determining the motion state based on the coincidence relationship and interval durations of the first, second, third, and fourth contact time points and generating a determination result includes:
[0050] The smartwatch controller unit receives the ground contact time interval data of the user within 1 minute of the walking speed and calculates the average value of the ground contact time interval data as a reference baseline.
[0051] The interval duration is the interval duration from the end of the previous time period to the beginning of the next time period.
[0052] A sprint is determined when the first, second, third, and fourth contact points do not overlap, and the duration between the second and third contact points is between 40% and 60% of the reference baseline.
[0053] When the smart watch controller unit only receives the left forefoot contact pressure data and the right forefoot contact pressure data, and the interval between the second contact time point and the fourth contact time point exceeds 60% of the reference baseline, the result is determined to be toe running.
[0054] When the smart watch controller unit receives only the left heel contact pressure data and the right heel contact pressure data, and the interval between the first contact time point and the third contact time point exceeds 60% of the reference baseline, the result is determined to be heel running.
[0055] If the first, second, third, and fourth contact points do not overlap, and the duration between the second and third contact points is between 20% and 40% of the reference baseline, the result is considered jogging.
[0056] The result is race walking if the second contact time point coincides with the third contact time point and the fourth contact time point coincides with the second contact time point of the next cycle, and the overlap duration is less than a preset threshold, and the interval duration from the first contact time point to the second contact time point and the interval duration from the third contact time point to the fourth contact time point both exceed 60% of the reference baseline.
[0057] The overlap duration is the first point where the second contact time point coincides with the third contact time point, and the second point where the fourth contact time point coincides with the second contact time point of the next cycle, that is, the overlap duration between the first point and the second point.
[0058] Specifically, when the overlapping duration is 10% to 20% of the preset threshold, the result is determined to be race walking.
[0059] If the second contact time point coincides with the third contact time point, and the fourth contact time point coincides with the second contact time point of the next cycle, and the overlap duration is less than a preset threshold, and the interval duration from the first contact time point to the second contact time point and the interval duration from the third contact time point to the fourth contact time point are both less than a reference baseline, the result is determined to be slow walking.
[0060] Specifically, when the overlap duration is 30% to 40% of the preset threshold, the determination result is slow walking.
[0061] The above reference baseline settings and the multiple judgment results generated by the smart watch controller unit through machine learning enable users to have appropriate incentive beats to match their pace during running exercises at various paces. The applicable paces and scenarios are more numerous and comprehensive, avoiding the discomfort caused by the user having to receive a single incentive beat when the pace changes.
[0062] Among them, the pressure sensor also sends each contact pressure data to the smart watch controller unit; the smart watch controller unit extracts the characteristics of each contact pressure data; and inputs the characteristics and judgment results of each contact pressure data into the machine learning model, wherein the characteristics of each contact pressure data include pressure, time series data and other characteristics.
[0063] Specifically, the machine learning model also includes:
[0064] First, the data processing step: First, data collection is performed: during exercise, each sensor collects pressure changes in real time during the heel strike, toe lift-off, single-leg support phase, and body launch phase during running, forming a time series; then data preprocessing is performed to remove outliers and noise; finally, feature extraction is performed to extract valuable features from the preprocessed motion data. In addition to the raw pressure and time series data, derived features can also be calculated, such as cadence (calculated by analyzing the periodic peaks of pressure data to calculate the number of steps per minute), stride length (estimated by combining cadence and movement speed), and footstep impact force (measured based on pressure peaks). These features can better describe the rhythm of exercise.
[0065] Second, the TCN model construction steps begin with network architecture design: Causal Convolution Layer: The core of TCN is causal convolution, which ensures that convolution operations depend only on the current time step and the previous time step, meeting the causal requirements of time series prediction. When constructing the first causal convolution layer, the convolution kernel size can be set to 3, and the padding mode to "valid" (no padding). This way, the convolution operation only processes the data of the current time step and the previous two time steps, without introducing future information.
[0066] Next, dilated convolution is performed: To increase the receptive field and enable the network to capture changes in motion rhythm over a longer timeframe, TCNs typically employ dilated convolution. In the second convolutional layer, the dilation rate is set to 2. This creates a one-time-step gap between each element of the convolution kernel, enabling coverage of a wider range of time series while keeping the number of parameters relatively stable.
[0067] To avoid the vanishing gradient problem and improve network training efficiency, TCN uses residual connections. Adding a residual connection after each convolutional block directly adds the input to the output of the convolutional block, making it easier for the network to learn the identity mapping, thereby better training deep networks.
[0068] Finally, determine the model parameters: the number of input channels is determined by the number of features in the input data; the number of output channels is determined by the prediction target; parameters such as the number of convolutional layers, kernel size, and dilation rate are determined through experimentation and cross-validation. Generally speaking, more convolutional layers increase the receptive field of the network, but may also lead to overfitting. Start with a simpler architecture, such as 3-5 convolutional layers, a kernel size between 3 and 5, and an exponentially increasing dilation rate (e.g., 1, 2, 4, 8, etc.). Observe the model's performance on the validation set and adjust the parameters accordingly.
[0069] The third step is model training and optimization. The collected and preprocessed motion data is divided into training, validation, and test sets. 70% of the data is used for training, 20% for verifying model performance and adjusting hyperparameters, and the remaining 10% for final testing. For predicting motion rhythm changes, the mean squared error loss function is used. The Adam and RMSProp optimizers are selected, and a learning rate of 0.001 is set to update the model weights.
[0070] Training data is fed into the TCN model in time series order. At each time step, the model uses causal convolution and dilated convolution to calculate the predicted change in motion rhythm based on the current input and information from previous time steps. The predicted results are compared with the actual results to calculate the loss function, and then the optimizer is used to update the model weights to minimize the loss. This process continues for multiple training cycles until the model's performance on the validation set stops improving or the preset number of training cycles is reached.
[0071] When the rhythm change is a single-step prediction, after the athlete starts exercising, the real-time collected motion data is input into the trained TCN model, and the model can predict the motion rhythm change in the next time step.
[0072] Specifically, the smart watch controller unit adjusts the audio beat excitation signal or the vibration beat excitation signal according to the comparison result between the received current contact time position data and the audio beat excitation signal or the vibration beat excitation signal predicted in the previous exercise cycle. When the smart watch controller unit receives that the actual occurrence time of the next time cycle is slower than the predicted rhythm, the pace slows down, and the audio beat excitation signal and the vibration beat excitation signal given in the next time cycle are also delayed; when the smart watch controller unit receives that the actual occurrence time of the next time cycle is faster than the predicted rhythm, the pace increases, and the audio beat excitation signal and the vibration beat excitation signal given in the next time cycle are also advanced; when the smart watch controller unit receives that the actual occurrence time of the next time cycle is consistent with the predicted rhythm, it indicates a uniform speed state, and the beat of the audio beat excitation signal and the vibration beat excitation signal given in the next time cycle remains unchanged.
[0073] See Figure 2 Another embodiment of the present application provides an adaptive running rhythm incentive and control device, the device comprising:
[0074] The pressure sensor module 101 is used to collect left heel contact pressure data, left forefoot contact pressure data, right heel contact pressure data, and right forefoot contact pressure data, and send them to the smart watch time unit via Bluetooth.
[0075] The smart watch timing unit 102 is configured to generate a first contact time location based on the received left heel contact pressure data; generate a second contact time location based on the received left forefoot contact pressure data; generate a third contact time location based on the received right heel contact pressure data; and generate a fourth contact time location based on the received right forefoot contact pressure data; and transmit the first contact time location, the second contact time location, the third contact time location, and the fourth contact time location to the smart watch controller unit.
[0076] The smart watch controller unit 103 is used to determine the motion state based on the coincidence relationship and interval length of the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point, and generate a determination result; generate a vibration beat excitation signal and an audio beat excitation signal for the next motion cycle based on the determination result, and send the vibration beat excitation signal to the vibration unit of the smart watch and send the audio beat excitation signal to the audio unit of the smart watch.
[0077] The smart watch vibration unit 104 is used to play the vibration rhythm excitation signal.
[0078] The smart watch audio unit 105 is used to play the audio beat excitation signal.
[0079] In some embodiments, the smart watch controller unit is further used to receive the user's contact time interval data within 1 minute of the walking speed, and calculate the average value of the contact time interval data as a reference baseline; when the first contact time point, the second contact time point, the third contact time point and the fourth contact time point do not overlap, and the interval length from the second contact time point to the third contact time point is between 40% and 60% of the reference baseline, the result is determined to be fast running.
[0080] In some embodiments, the smart watch controller unit is further used to adjust the audio beat excitation signal or the vibration beat excitation signal based on a comparison result between the received current contact time location data and the audio beat excitation signal or the vibration beat excitation signal predicted in the previous motion cycle.
[0081] The specific limitations of the adaptive running tempo excitation and control device provided in this embodiment can be found in the embodiments of the adaptive running tempo excitation and control method described above and will not be repeated here. Each module in the adaptive running tempo excitation and control device described above can be implemented in whole or in part via software, hardware, or a combination thereof. Each of the modules can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in the computer device in software form, so that the processor can call and execute the corresponding operations of each module.
[0082] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0083] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.
Claims
1. An adaptive running rhythm incentive and control method, characterized in that: The method comprises: The pressure sensor collects left heel contact pressure data, left forefoot contact pressure data, right heel contact pressure data, and right forefoot contact pressure data, and sends the data to the smart watch time unit via Bluetooth; The smartwatch timing unit generates a first contact time location based on the received left heel contact pressure data; generates a second contact time location based on the received left forefoot contact pressure data; generates a third contact time location based on the received right heel contact pressure data; and generates a fourth contact time location based on the received right forefoot contact pressure data; and transmits the first contact time location, the second contact time location, the third contact time location, and the fourth contact time location to a smartwatch controller unit. The smartwatch controller unit determines the motion state based on the coincidence relationship and interval duration between the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point, and generates a determination result; generates a vibration beat excitation signal and an audio beat excitation signal for the next motion cycle based on the determination result, and sends the vibration beat excitation signal to the vibration unit of the smartwatch and the audio beat excitation signal to the audio unit of the smartwatch; The smart watch vibration unit plays the vibration beat excitation signal; The smart watch audio unit plays the audio beat excitation signal.
2. The adaptive running rhythm motivation and control method according to claim 1, characterized in that: The determining of the motion state based on the coincidence relationship and interval durations of the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point, and generating a determination result includes: The smartwatch controller unit receives ground contact time interval data of the user within a 1-minute walking speed, and calculates an average value of the ground contact time interval data as a reference baseline; When the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point do not overlap, and the duration of the interval from the second contact time point to the third contact time point is between 40% and 60% of the reference baseline, the determination result is sprinting.
3. The adaptive running rhythm motivation and control method according to claim 2, characterized in that: Also includes: When the smartwatch controller unit receives only the left forefoot contact pressure data and the right forefoot contact pressure data, and the interval between the second contact time point and the fourth contact time point exceeds 60% of the reference baseline, the determination result is toe running.
4. The adaptive running rhythm motivation and control method according to claim 2, characterized in that: Also includes: When the smart watch controller unit only receives the left heel contact pressure data and the right heel contact pressure data, and the interval between the first contact time point and the third contact time point exceeds 60% of the reference baseline, the determination result is heel running.
5. The adaptive running rhythm motivation and control method according to claim 2, characterized in that: Also includes: When the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point do not overlap, and the duration of the interval from the second contact time point to the third contact time point is between 20% and 40% of the reference baseline, the determination result is jogging.
6. The adaptive running rhythm motivation and control method according to claim 2, characterized in that: Also includes: The determination result is race walking when the second contact time point coincides with the third contact time point and the fourth contact time point coincides with the second contact time point of the next cycle, and the overlap duration is less than a preset threshold, and the interval duration from the first contact time point to the second contact time point and the interval duration from the third contact time point to the fourth contact time point both exceed 60% of the reference baseline. When the second contact time point coincides with the third contact time point, and the fourth contact time point coincides with the second contact time point of the next cycle, and the overlap duration is less than a preset threshold, and the interval duration from the first contact time point to the second contact time point and the interval duration from the third contact time point to the fourth contact time point are both less than the reference baseline, the determination result is slow walking.
7. The adaptive running rhythm motivation and control method according to claim 1, characterized in that: Also includes: The smart watch controller unit adjusts the audio beat excitation signal or the vibration beat excitation signal according to a comparison result between the received current contact time position data and the audio beat excitation signal or the vibration beat excitation signal predicted in the previous exercise cycle.
8. An adaptive running rhythm incentive and control device, characterized in that: The device comprises: The pressure sensor module is used to collect left heel contact pressure data, left forefoot contact pressure data, right heel contact pressure data, and right forefoot contact pressure data, and send the data to the smart watch time unit via Bluetooth; a smartwatch timing unit, configured to generate a first contact time location based on the received left heel contact pressure data; generate a second contact time location based on the received left forefoot contact pressure data; generate a third contact time location based on the received right heel contact pressure data; and generate a fourth contact time location based on the received right forefoot contact pressure data; and transmit the first contact time location, the second contact time location, the third contact time location, and the fourth contact time location to a smartwatch controller unit; The smartwatch controller unit is configured to determine an exercise state based on the coincidence relationship and interval duration between the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point, and generate a determination result; generate a vibration beat excitation signal and an audio beat excitation signal for a next exercise cycle based on the determination result, and transmit the vibration beat excitation signal to the vibration unit of the smartwatch and the audio beat excitation signal to the audio unit of the smartwatch; The smart watch vibration unit is used to play the vibration beat excitation signal; The smart watch audio unit is used to play the audio beat excitation signal.
9. The adaptive running rhythm incentive and control device according to claim 8, characterized in that: The smartwatch controller unit is further configured to receive contact time interval data of the user within a 1-minute walking speed, and calculate an average value of the contact time interval data as a reference baseline; when the first contact time point, the second contact time point, the third contact time point, and the fourth contact time point do not overlap, and the interval length from the second contact time point to the third contact time point is between 40% and 60% of the reference baseline, the determination result is fast sprinting.
10. The adaptive running rhythm incentive and control device according to claim 9, characterized in that: The smart watch controller unit is also used to adjust the audio beat excitation signal or the vibration beat excitation signal according to the comparison result between the received current contact time location data and the audio beat excitation signal or the vibration beat excitation signal predicted in the previous movement cycle.