A post-exercise breath guidance method, apparatus, and device and medium
Patent Information
- Application Number
- CN202611308390.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-27
- Publication Date
- 2026-09-25
AI Technical Summary
[0004]为解决上述技术问题，本发明提供了一种运动后呼吸引导方法、装置和设备及介质，解决了现有的呼吸引导方式降低适配性问题
[0015]有益效果：本发明首先计算运动后呼吸数据与静息呼吸数据之间的呼吸偏差数据，再基于呼吸偏差数据制定用于过渡到静息呼吸数据的目标呼吸数据，之后引导用户跟踪目标呼吸数据的节律进行呼吸，在引导的过程中，实时监测用户受呼吸影响的反馈数据，以根据用户的实时反馈数据判断目标呼吸数据是否适用于用户，并根据判断结果优化目标呼吸数据继续引导用户呼吸至静息呼吸数据。从上述分析可知，本发明在引导的过程基于用户实时反馈数据优化目标呼吸数据，从而使得用户能够跟随目标呼吸数据的节律，进而提供本发明呼吸引导的适配性。
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Figure CN122806048A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of non-contact breathing guidance technology, specifically to a method, device, equipment, and medium for post-exercise breathing guidance. Background Technology
[0002] After exercise, the body is typically in a recovery phase characterized by increased respiratory rate, unstable inhalation and exhalation rhythms, and a strong subjective feeling of shortness of breath. Without effective rhythm guidance and intervention, users often have to rely on experience to adjust their breathing, which can easily lead to slow recovery, prolonged rhythm disturbances, insufficient comfort, and significant individual differences in recovery outcomes. To guide users to resume normal breathing after exercise, current technologies directly instruct users to breathe according to a fixed rhythm. However, this guidance process does not consider whether the fixed breathing rhythm is suitable for the individual user, resulting in reduced adaptability of existing breathing guidance methods.
[0003] Therefore, existing technologies still need to be improved and enhanced. Summary of the Invention
[0004] To address the aforementioned technical problems, this invention provides a method, apparatus, device, and medium for guiding breathing after exercise, which solves the problem of reduced adaptability in existing breathing guidance methods.
[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for guiding breathing after exercise, comprising: Acquire the user's breathing data after exercise and the user's resting breathing data when at rest, and determine the breathing deviation data between the breathing data after exercise and the resting breathing data; Based on the breathing deviation data, target breathing data is determined; wherein, the target breathing data is used to guide and transition from the post-exercise breathing data to the resting breathing data; The user is given breathing guidance based on the target breathing data; during the guidance process, the user's real-time feedback data is monitored; and the target breathing data is updated based on the real-time feedback data, and the user continues to receive breathing guidance based on the updated target breathing data.
[0006] In one implementation, determining target respiratory data based on the respiratory deviation data includes: Respiratory rate deviation data is obtained from the respiratory deviation data; The user's exercise intensity is obtained, and a transition coefficient is determined based on the exercise intensity and the respiratory rate deviation data; The resting respiratory rate is obtained from the resting respiratory data, and the target respiratory rate is determined based on the resting respiratory rate, the transition coefficient, and the respiratory rate deviation data. Based on the target respiratory rate, the target inhalation duration and target exhalation duration are determined, and the target respiratory rate, the target inhalation duration, and the target exhalation duration are used as target respiratory data.
[0007] In one implementation, optimizing the target respiratory data based on the real-time feedback data includes: Determine the real-time respiratory data in the real-time feedback data; Determine the guidance deviation data between the real-time respiratory data and the target respiratory data; Based on the guidance deviation data, the target breathing data are optimized.
[0008] In one implementation, determining the guidance deviation data between the real-time respiratory data and the target respiratory data includes: Determine the target respiratory rate, target inspiratory duration, and target expiratory duration from the target respiratory data, and determine the target inspiratory-expiratory ratio based on the target inspiratory duration and the target expiratory duration; Obtain the user's real-time inspiratory-to-expiratory ratio (IPR) during the guided process, and determine the IPR deviation between the real-time IPR and the target IPR; Determine the real-time respiratory rate in the real-time respiratory data, and determine the respiratory rate deviation between the real-time respiratory rate and the target respiratory rate; Based on the respiratory rate deviation and the inspiratory-to-expiratory ratio deviation, the guidance deviation data is determined.
[0009] In one implementation, optimizing the target respiratory data based on the guidance deviation data includes: The first consecutive respiratory cycle corresponding to when the guidance deviation data is less than the first threshold is monitored; When the first continuous respiratory cycle is greater than the set cycle, the target respiratory rate in the target respiratory data is reduced. Alternatively, monitor the second consecutive respiratory cycle corresponding to the guidance deviation data being greater than the second threshold; When the second continuous respiratory cycle is greater than the set cycle, the target respiratory rate in the target respiratory data is increased.
[0010] In one implementation, optimizing the target respiratory data based on the real-time feedback data includes: Real-time chest movement video data and real-time abdominal movement video data are obtained from the real-time feedback data; The degree of chest-abdominal coordination is determined based on the real-time chest movement video data and the real-time abdominal movement video data. The target respiratory data is optimized based on the degree of chest-abdominal coordination.
[0011] One implementation also includes: The system monitors the trend of the guidance deviation data and controls the expansion and contraction speed of the prompting ball based on the trend. The prompting ball is used to prompt the user to adjust their breathing to follow the target breathing data.
[0012] Secondly, embodiments of the present invention also provide a post-exercise breathing guidance device, wherein the device comprises the following components: The deviation calculation module is used to acquire the user's breathing data after exercise and the user's resting breathing data when at rest, and to determine the breathing deviation data between the breathing data after exercise and the resting breathing data; A target setting module is used to determine target breathing data based on the breathing deviation data; wherein the target breathing data is used to guide and transition from the post-exercise breathing data to the resting breathing data; An optimized guidance module is used to provide breathing guidance to the user based on the target breathing data; during the guidance process, the module monitors the user's real-time feedback data; and updates the target breathing data based on the real-time feedback data, and continues to provide breathing guidance to the user based on the updated target breathing data.
[0013] Thirdly, embodiments of the present invention also provide a terminal device, wherein the terminal device includes a memory, a processor, and a post-exercise breathing guidance program stored in the memory and executable on the processor, wherein when the processor executes the post-exercise breathing guidance program, it implements the steps of the post-exercise breathing guidance method described above.
[0014] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a post-exercise breathing guidance program, which, when executed by a processor, implements the steps of the post-exercise breathing guidance method described above.
[0015] Beneficial Effects: This invention first calculates the respiratory deviation data between post-exercise breathing data and resting breathing data. Then, based on this deviation data, it formulates target breathing data for transitioning to resting breathing data. Next, it guides the user to follow the rhythm of the target breathing data. During this guidance process, it monitors the user's feedback data on the impact of breathing in real time. Based on this real-time feedback, it determines whether the target breathing data is suitable for the user and optimizes the target breathing data accordingly to continue guiding the user to resting breathing data. From the above analysis, it can be seen that this invention optimizes the target breathing data based on real-time user feedback during the guidance process, enabling the user to follow the rhythm of the target breathing data, thereby providing adaptability for the breathing guidance of this invention. Attached Figure Description
[0016] Figure 1 This is an overall flowchart of the present invention; Figure 2 This is a structural diagram of the post-exercise breathing guidance device provided by the present invention; Figure 3 This is a block diagram illustrating the internal structure of a terminal device provided in an embodiment of the present invention. Detailed Implementation
[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments and accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.
[0018] Research has found that after exercise, the body is typically in a recovery phase characterized by increased respiratory rate, unstable inhalation and exhalation rhythms, and a strong subjective feeling of shortness of breath. Without effective rhythm guidance and intervention, users often have to rely on experience to adjust their breathing, which can easily lead to slow recovery, prolonged rhythm disturbances, insufficient comfort, and significant individual differences in recovery outcomes. To guide users to resume normal breathing after exercise, current technologies directly instruct users to breathe according to a fixed rhythm. However, this guidance process does not consider whether the fixed breathing rhythm is suitable for the individual user, resulting in reduced adaptability of existing breathing guidance methods.
[0019] To address the aforementioned technical problems, this invention provides a method, apparatus, device, and medium for guiding breathing after exercise, which solves the problem of reduced adaptability in existing breathing guidance methods.
[0020] The post-exercise breathing guidance method of this embodiment can be applied to a terminal device, which can be a terminal product with image processing capabilities, such as a computer. In this embodiment, as... Figure 1 As shown, the post-exercise breathing guidance method specifically includes the following steps: S100, acquire the user's breathing data after exercise and the user's resting breathing data when at rest, and determine the breathing deviation data between the breathing data after exercise and the resting breathing data; S200, Based on the breathing deviation data, determine the target breathing data; wherein, the target breathing data is used to guide and transition from the post-exercise breathing data to the resting breathing data; S300, based on the target breathing data, provide breathing guidance to the user; during the guidance process, monitor the user's real-time feedback data; and based on the real-time feedback data, update the target breathing data, and based on the updated target breathing data, continue to provide breathing guidance to the user.
[0021] The user's breathing data after exercise and resting breathing data used in this embodiment are all obtained through non-contact methods. Non-contact means that there is no contact with the user's body. The breathing guidance method in this embodiment is not used for the diagnosis and treatment of respiratory diseases.
[0022] The post-exercise breathing data in step S100 refers to the breathing data of the user after completing running, cycling, strength training, aerobic training, rehabilitation training or other exercises.
[0023] The breathing guidance method in this embodiment can be applied not only to post-exercise recovery, but also to scenarios such as lung function training, rehabilitation training, anxiety relaxation training, postoperative breathing training, pre-sleep relaxation training, and home health management.
[0024] The acquisition of post-exercise respiratory data includes: capturing videos of breathing-related areas of the user's body using a camera after exercise and before the start of guided exercise; analyzing the videos to obtain changes in the user's torso displacement, contour changes, temporal changes in pixel intensity, local area motion patterns, and chest and abdominal zone changes, thus obtaining post-exercise respiratory data. Calculating post-exercise respiratory data is a prior art technique. This data includes respiratory rate, respiratory amplitude metrics (such as chest and abdominal displacement distance within a respiratory cycle), rhythm stability, inspiratory duration, expiratory duration, inspiratory-to-expiratory ratio (the ratio of inspiratory to expiratory duration within a respiratory cycle), and a recovery trend parameter, which indicates whether the user's breathing becomes increasingly smooth or increasingly rapid.
[0025] The aforementioned cameras include RGB cameras, near-infrared cameras, and depth cameras. RGB cameras are red, green, and blue color cameras, where R represents red, G represents green, and B represents blue.
[0026] The respiratory deviation data in step S100 is the respiratory rate deviation data, using... This represents respiratory rate deviation data, which is the difference between a user's respiratory rate after exercise and before guidance, and the user's own resting respiratory rate. The calculation formula is as follows: ; In the formula, This represents the user's breathing frequency after exercise (the breathing frequency of the user after exercise and before guidance). This represents the resting respiratory rate, which is the user's breathing rate at rest before exercise. The value can be the respiratory rate during the last resting period before exercise. It can also be the average of the user's resting breathing rate over multiple periods.
[0027] Step S200, which determines the target respiratory data based on the respiratory deviation data, includes the following specific steps S201, S202, S203, and S204: S201, Obtain respiratory rate deviation data from the respiratory deviation data; The respiratory rate deviation data is as described above. .
[0028] S202, acquire the user's exercise intensity, and based on the exercise intensity and the respiratory rate deviation data... Determine the transition coefficient .
[0029] use Exercise intensity can be obtained by normalizing any one of the following indicators: heart rate reserve percentage, oxygen uptake reserve percentage, subjective exertion score (RPE), or other exercise load indicators. Among them, there is a linear relationship between heart rate and exercise intensity during exercise, so the user's exercise intensity can be calculated by monitoring heart rate.
[0030] ; Represents the amplitude limiting function, when The value is located at and In between, The value is equal to The value; when The value is less than hour, The value is equal to ;when The value is greater than hour, The value is 0.85.
[0031] S203, Obtain the resting respiratory rate from the resting respiratory data, and determine the target respiratory rate based on the resting respiratory rate, the transition coefficient, and the respiratory rate deviation data. .
[0032] ; In the formula, The value is equal to the respiratory rate deviation data. Multiply by resting breathing rate .
[0033] When exercise intensity Larger or greater deviation in respiratory rate data When the respiratory rate is higher, set a target respiratory rate. The transition coefficient used The larger the value, the higher the target respiratory rate. The larger the target respiratory rate The larger the value, the closer it is to the high-frequency breathing after exercise. This allows users to breathe at a rate close to their post-exercise breathing frequency rather than directly reducing it to their resting breathing frequency. This avoids the breathing rate dropping too quickly during the initial recovery period after exercise, as a rapid drop from rapid breathing to slow breathing is detrimental to health. This embodiment sets a transition coefficient to correlate the target breathing frequency with the exercise intensity, thus matching the target breathing frequency to the exercise intensity and preventing the breathing rate from dropping too quickly during the initial recovery period after exercise, thereby protecting health.
[0034] S204, Based on the target respiratory rate, determine the target inspiratory duration. Exhalation duration with the target The target respiratory rate, the target inhalation duration, and the target exhalation duration are used as target respiratory data.
[0035] Inhalation duration and exhalation duration are the duration of inhalation and exhalation within one respiratory cycle, respectively. Represents one respiratory cycle: ; In the formula, This represents the unit of time used to count respiratory rate, in this embodiment. The value is 60 seconds.
[0036] use Represents the target exhalation duration Target inhalation duration Breathing ratio: ; when ≥ 0.7 or When ≥ 0.5, let = 1.0~1.2; When 0.4 ≤ <0.7 or 0.2 ≤ When <0.5, let = 1.2~1.4; when <0.4 and When <0.2, let = 1.4~1.6.
[0037] In determining After obtaining the value, calculate the target expiratory duration using the following formula. Values and target inhalation duration Value: ; ; This embodiment is based on exercise intensity. and respiratory rate deviation data set up And then according to Setting target exhalation and inhalation durations helps avoid forcing users to breathe too slowly in the early stages of recovery after exercise, while gradually guiding users to extend exhalation appropriately in the later stages of recovery, thereby improving comfort and stability during the recovery process.
[0038] In this embodiment, the optimization of the target respiratory data based on the real-time feedback data in step S300 includes the following specific steps S301a, S302a, S303a, S304a, S305a, and S306a: S301a, determine the real-time respiratory data in the real-time feedback data.
[0039] Real-time breathing data includes the user's real-time breathing rate. In this embodiment, the user's real-time breathing rate during the guidance process is used as feedback on whether the user is suitable for the target breathing rate. This feedback indicates whether the user can follow the rhythm of the target breathing rate. If the user can follow the rhythm of the target breathing rate, the target breathing rate can be further reduced to gradually transition to the resting breathing rate, thereby gradually guiding the user from high-frequency breathing after exercise to low-frequency resting breathing.
[0040] If the user's real-time breathing during the guidance process cannot keep up with the rhythm of the target breathing rate, then temporarily reduce the target breathing rate or slightly increase the target breathing rate so that the user can keep up with the guidance rhythm.
[0041] S302a, determine the target respiratory rate, target inspiratory duration, and target expiratory duration in the target respiratory data, and determine the target inspiratory-expiratory ratio based on the target inspiratory duration and the target expiratory duration.
[0042] Target inspiratory-to-expiratory ratio It is equal to the ratio of the target inhalation duration to the target exhalation duration within one respiratory cycle.
[0043] S303a, obtain the user's real-time inspiratory-to-expiratory ratio during the guidance process, and determine the inspiratory-to-expiratory ratio deviation between the real-time inspiratory-to-expiratory ratio and the target inspiratory-to-expiratory ratio.
[0044] During the guided breathing process, the user's real-time inspiratory duration and real-time expiratory duration within one respiratory cycle are monitored. The ratio of real-time inspiratory duration to real-time expiratory duration is defined as the real-time inspiratory-expiratory ratio (IRR). ,in Representing the first in the guidance process One respiratory cycle. (Use) This represents the deviation in the inspiratory-to-expiratory ratio.
[0045] S304a, Determine the real-time respiratory rate in the real-time respiratory data. And determine the respiratory rate deviation between the real-time respiratory rate and the target respiratory rate.
[0046] use This represents a deviation in respiratory rate.
[0047] S305a, Based on the respiratory rate deviation and the inspiratory-expiratory ratio deviation, determine the guidance deviation data. : ; and These are two weighting coefficients, and .
[0048] S306a, Based on the guidance deviation data, optimize the target breathing data.
[0049] When guiding deviation data If the first continuous respiratory cycle lasting less than the first threshold is greater than the set cycle, then the target respiratory rate in the target respiratory data is reduced.
[0050] That is, when several consecutive respiratory cycles meet the requirements If the value is less than 0.1 (the first threshold), the target respiratory rate is reduced to allow the patient to move from the initial guidance phase to the next guidance phase, until resting breathing is achieved.
[0051] The set cycle in this embodiment can be five breathing cycles.
[0052] When guiding deviation data If the second consecutive respiratory cycle exceeding the second threshold is longer than the set cycle, then the target respiratory rate is increased.
[0053] That is, when several consecutive respiratory cycles meet the requirements If the value is greater than 0.3 (the second threshold), the target breathing rate is increased to slow down the guidance process, allowing the user to keep up with the breathing rate used in the guidance and return to the previous stage from the current guidance phase. In this embodiment, the frequency of the expansion and contraction of the prompt ball on the display interface represents the target breathing rate, guiding the user to breathe according to the expansion and contraction frequency of the prompt ball. Increasing the expansion and contraction frequency of the prompt ball represents increasing the target breathing rate.
[0054] In another embodiment, optimizing the target respiratory data based on the real-time feedback data in step S300 includes the following specific steps S301b, S302b, and S303b: S301b, Obtain real-time chest movement video data and real-time abdominal movement video data from the real-time feedback data.
[0055] S302b, Based on the real-time chest movement video data and the real-time abdominal movement video data, determine the degree of chest-abdominal coordination.
[0056] In other words, during the process of guiding users to recover from fast-rhythmic breathing after exercise to slow-rhythmic resting breathing using a target respiratory rate, real-time video data of chest movement and abdominal movement reflecting the user's respiratory rhythm is collected. The chest pixel displacement change data is extracted from the chest movement video data, and the abdominal pixel displacement change data is extracted from the abdominal movement video data. The respective motion time-series signals are constructed using the chest pixel displacement change data and the abdominal pixel displacement change data, and the degree of chest-abdominal coordination is calculated based on the two motion time-series signals.
[0057] S303b, Optimize the target respiratory data based on the degree of chest-abdomen coordination.
[0058] If the degree of chest-abdominal coordination is very high, it means that the target respiratory rate contained in the target respiratory data is suitable for guiding the user's breathing to resting breathing. Therefore, continue to reduce the target respiratory rate to further guide the user to reduce their respiratory rate.
[0059] If the chest-abdominal coordination is low, maintain the current target breathing rate and let the user continue to practice breathing at the target breathing rate.
[0060] In addition to optimizing the target respiratory rate using the degree of coordination between the chest and abdomen, this embodiment can also optimize the target respiratory rate using parameters such as the phase difference between the motion timing signals of the abdomen and chest, synchronous or asynchronous indicators, and chest-dominant or abdominal-dominant modes.
[0061] use Representing the timing signal of chest movement, using Represents the timing signal of abdominal movement, for and The instantaneous phase of the chest was obtained by employing Hilbert transform, peak-valley detection, zero-crossing analysis, or phase fitting methods, respectively. and abdominal instantaneous phase Calculate the chest-abdomen phase difference Within a sliding time window of one or more consecutive respiratory cycles, the average phase difference, the range of phase difference fluctuations, or a coordination index constructed based on the phase difference are calculated to characterize the degree of coordination of chest and abdominal movements.
[0062] Among them, the synergy index , The closer the value is to 1, the more synchronized the chest and abdominal movements are. The lower the value, the worse the chest-abdominal coordination.
[0063] In another embodiment, the target respiratory data is optimized using a deep learning model, and the specific optimization process is as follows: The user's real-time respiratory rate, respiratory rate within a historical time window, whether it is in the initial recovery phase, exercise intensity, user's resting respiratory rate, whether the user can follow the current target respiratory rate, and the user's subjective shortness of breath score are input into the deep learning model. The deep learning model outputs the optimized target respiratory rate, target inspiratory duration, target expiratory duration, target inspiratory-expiratory ratio, and target respiratory rate.
[0064] The deep learning model in this embodiment comprises two parts: an encoder and a decision model. The encoder encodes the user's current respiratory signal and its state parameters to obtain a feature vector representing the current recovery state. The respiratory signal and state parameters include at least one or more of the following: respiratory rate, respiratory amplitude representation, rhythm stability, inspiratory duration, expiratory duration, inspiratory-expiratory ratio, recovery trend, and degree of follow-through. Subsequently, the feature vector, along with the user's basic information, recovery stage information, and the current intervention target, is input into the decision model, which then outputs the corresponding target rhythm and feedback intervention suggestions.
[0065] The decision model in this embodiment is a pre-trained large language model. The training of the large language model includes: collecting historical recovery samples from multiple users under different exercise types, intensities, and recovery stages; for each sample, recording the corresponding video breathing state parameter sequence, user basic information, user follow-up results, and corresponding target breathing frequency adjustment results. Then, using an encoder, the above breathing state sequence and auxiliary information are mapped into low-dimensional semantic representations, and converted into input representations that can be processed by the large language model through a linear projection layer or cue templates; then, using expert annotations from historical samples, suggestions given by doctors / coaches based on their experience, or intervention plans generated by established rules and verified to be effective as supervision labels, the pre-trained large language model is fine-tuned under supervision, enabling it to learn the mapping relationship between "user's current breathing frequency - target breathing frequency - update rhythm".
[0066] The aforementioned supervised fine-tuning employs a parameter-efficient fine-tuning approach. Low-rank adaptation parameters are inserted into the attention layer and / or feedforward layer of the pre-trained large language model. The LoRA method (LoRA stands for Low-Rank Adaptation) is used to update only the low-rank adaptation parameters, while freezing or essentially freezing the main parameters of the pre-trained model. This reduces training costs and improves adaptability to specific respiratory recovery scenarios. The training loss function includes regression losses for continuous variables such as target respiratory rate, target inspiratory duration, and target expiratory duration, and may also include classification losses for discrete variables such as update rhythm. A weighted average of the classification and regression losses yields the total loss function required for training the large language model.
[0067] In another embodiment, the cue ball not only serves to indicate the target respiratory rate through its contraction and expansion frequency, but also prompts the user whether they need to keep up with the target respiratory rate. The cue ball's contraction and expansion are controlled within one cue cycle; that is, the expansion and contraction speed of the cue ball is controlled by controlling the cue cycle. When the user sees the cue ball's expansion and contraction speed slowing down, it prompts the user to slow down their breathing rhythm to keep up with the target respiratory rate.
[0068] In this embodiment, different colored cue balls inform the user whether the cue ball indicates the target breathing rate or suggests that the user needs to slow down their breathing rhythm; that is, different colors are used to distinguish the different functions of the cue balls.
[0069] Notification period : .
[0070] When guiding deviation data When the trend of the indicator increases, it means that the user's real-time breathing rate is deviating more and more from the target breathing rate. In this case, the function of the indicator ball needs to be switched to prompt the user to reduce the breathing rate.
[0071] If the guiding deviation data The trend of change is that it decreases, and gradually decreases to below 0.1. Then, the function of the cue ball will be restored to the target breathing rate, that is, the collision contraction cycle of the cue ball will be restored to... .
[0072] In another embodiment, the display interface shows a feedback ball while displaying the prompt ball. The expansion of the feedback ball is synchronized with the user's inhalation, and the contraction of the feedback ball is synchronized with the user's exhalation. The user can intuitively see the speed of their breathing through the feedback ball.
[0073] In another embodiment, the degree of matching between the user's real-time respiratory rate and the target respiratory rate (the degree of matching is expressed using guide deviation data) is considered. (Representations) are mapped to control variables in the game. Control variables include one or more of the following: character position, movement speed, rise or fall rate, target hit rate, score increase rate, level progress, or reward feedback. For example, when the user inhales at the target breathing rate, the character moves upward, the energy bar rises, or the target trajectory advances; when the user exhales at the target breathing rate, the character slides forward, passes through obstacles, remains hovered, or locks onto the target; when the deviation between the user's real-time breathing rate and the target breathing rate decreases, the system increases the score, increases rewards, or speeds up level progress; when the deviation increases, the scoring speed is reduced, a deceleration prompt is triggered, or the user is required to re-follow the rhythm.
[0074] In another embodiment, gamified feedback can be constructed as a "breathing ball following game." The system displays a cue ball that expands and contracts with the target breathing rate, and a feedback ball that changes synchronously with the user's real-time breathing rate. The user adjusts their inhalation and exhalation to make the feedback ball as consistent as possible with the target breathing ball in terms of size, rhythm, and phase changes. When the two are highly matched, the system determines it as effective following and accumulates points, increases completion rate, or unlocks the next stage; when the two deviate significantly, the system reminds the user to adjust their breathing through color changes, border flashing, vibration prompts, or voice prompts.
[0075] In another embodiment, gamified feedback can be constructed as a "target tracking game." The system generates a reference trajectory on the display interface that changes with the target's breathing frequency. The user's current breathing frequency corresponds to the movement of a moving cursor, flying object, swimming character, or floating object. Inhalation and exhalation control the object's ascent, descent, forward movement, or stillness, respectively. By adjusting their breathing, the user keeps the object close to or following the reference trajectory. When the object remains near the target trajectory within a preset time window, the system determines that the current stage has passed and proceeds to the next recovery stage; if the object continues to deviate from the trajectory, the system reduces the propulsion speed, increases the intensity of prompts, or switches to a simpler guidance interface.
[0076] In summary, this invention utilizes a camera to collect video information of the user after movement and obtains the user's current respiratory state parameters through a non-contact respiratory state perception module. These respiratory state parameters include at least one or more of the following: respiratory rate, respiratory amplitude representation, rhythm stability, inspiratory duration, expiratory duration, inspiratory-expiratory ratio, and recovery trend. Based on this, the system generates an individualized target respiratory rhythm and feedback intervention strategy according to the deviation between the current state and the preset recovery target, and outputs guidance information to the user through visual animation, light rhythm, sound cues, voice prompts, or a gamified interface. Simultaneously, the system continuously evaluates the user's adherence to the guidance and dynamically adjusts the target rhythm, feedback intensity, feedback form, or stage progression speed based on the adherence results, thereby forming a closed-loop recovery chain of "state perception—target generation—feedback intervention—response evaluation—strategy update." This invention transforms the original fixed-rhythm open-loop guidance into adaptive intervention based on real-time state differences, providing more targeted guidance solutions for different users and different recovery stages.
[0077] In another embodiment, a post-exercise breathing guidance device is provided, such as Figure 2 As shown, the device comprises the following components: Deviation calculation module 01 is used to acquire the user's breathing data after exercise and the user's resting breathing data when at rest, and to determine the breathing deviation data between the breathing data after exercise and the resting breathing data; The target setting module 02 is used to determine target breathing data based on the breathing deviation data; wherein, the target breathing data is used to guide and transition from the post-exercise breathing data to the resting breathing data; The optimized guidance module 03 is used to guide the user's breathing based on the target breathing data; during the guidance process, it monitors the user's real-time feedback data; and updates the target breathing data based on the real-time feedback data, and continues to guide the user's breathing based on the updated target breathing data.
[0078] The target setting module 02 includes: A respiratory rate deviation calculation unit is used to obtain respiratory rate deviation data from the respiratory deviation data; The transition coefficient calculation unit is used to acquire the user's exercise intensity and determine the transition coefficient based on the exercise intensity and the respiratory rate deviation data; The target respiratory rate calculation unit is used to obtain the resting respiratory rate from the resting respiratory data, and determine the target respiratory rate based on the resting respiratory rate, the transition coefficient, and the respiratory rate deviation data; The target respiratory data formulation unit is used to determine the target inhalation duration and the target exhalation duration based on the target respiratory rate, and to use the target respiratory rate, the target inhalation duration, and the target exhalation duration as target respiratory data.
[0079] Optimize boot module 03, including: The data decomposition unit is used to determine the target respiratory rate, target inspiratory duration, and target expiratory duration in the real-time feedback data, and to determine the target inspiratory-expiratory ratio based on the target inspiratory duration and the target expiratory duration. The inspiratory-to-expiratory ratio deviation calculation unit is used to obtain the user's real-time inspiratory-to-expiratory ratio during the guidance process and determine the inspiratory-to-expiratory ratio deviation between the real-time inspiratory-to-expiratory ratio and the target inspiratory-to-expiratory ratio; A respiratory rate deviation calculation unit is used to determine the real-time respiratory rate in the real-time respiratory data and to determine the respiratory rate deviation between the real-time respiratory rate and the target respiratory rate. The guidance deviation data calculation unit is used to determine guidance deviation data based on the respiratory rate deviation and the inspiratory-expiratory ratio deviation. An optimization unit is used to optimize the target breathing data based on the guidance deviation data.
[0080] Based on the above embodiments, the present invention also provides a terminal device, the principle block diagram of which can be as follows: Figure 3 As shown, the terminal device includes a processor, memory, network interface, and display screen connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a post-exercise breathing guidance method. The display screen can be a liquid crystal display (LCD) or an e-ink display.
[0081] Those skilled in the art will understand that Figure 3The schematic diagram shown is only a partial structural diagram related to the present invention and does not constitute a limitation on the terminal device to which the present invention is applied. The specific terminal device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.
[0082] In one embodiment, a terminal device is provided, the terminal device including a memory, a processor, and a post-exercise breathing guidance program stored in the memory and executable on the processor. When the processor executes the post-exercise breathing guidance program, it implements the following operation instructions: Acquire the user's breathing data after exercise and the user's resting breathing data when at rest, and determine the breathing deviation data between the breathing data after exercise and the resting breathing data; Based on the breathing deviation data, target breathing data is determined; wherein, the target breathing data is used to guide and transition from the post-exercise breathing data to the resting breathing data; The user is given breathing guidance based on the target breathing data; during the guidance process, the user's real-time feedback data is monitored; and the target breathing data is updated based on the real-time feedback data, and the user continues to receive breathing guidance based on the updated target breathing data.
[0083] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for guiding breathing after exercise, characterized in that, include: Acquire the user's breathing data after exercise and the user's resting breathing data when at rest, and determine the breathing deviation data between the breathing data after exercise and the resting breathing data; Based on the breathing deviation data, target breathing data is determined; wherein, the target breathing data is used to guide and transition from the post-exercise breathing data to the resting breathing data; The user is given breathing guidance based on the target breathing data; during the guidance process, the user's real-time feedback data is monitored; and the target breathing data is updated based on the real-time feedback data, and the user continues to receive breathing guidance based on the updated target breathing data.
2. The method for guiding breathing after exercise as described in claim 1, characterized in that, Based on the respiratory deviation data, target respiratory data are determined, including: Respiratory rate deviation data is obtained from the respiratory deviation data; The user's exercise intensity is obtained, and a transition coefficient is determined based on the exercise intensity and the respiratory rate deviation data; The resting respiratory rate is obtained from the resting respiratory data, and the target respiratory rate is determined based on the resting respiratory rate, the transition coefficient, and the respiratory rate deviation data. Based on the target respiratory rate, the target inhalation duration and the target exhalation duration are determined, and the target respiratory rate, the target inhalation duration, and the target exhalation duration are used as target respiratory data.
3. The method for guiding breathing after exercise as described in claim 1, characterized in that, Based on the real-time feedback data, the target respiratory data is updated, including: Obtain real-time respiratory data from the real-time feedback data; Determine the guidance deviation data between the real-time respiratory data and the target respiratory data; The target breathing data is updated based on the guidance deviation data.
4. The method for guiding breathing after exercise as described in claim 3, characterized in that, Determining the guidance deviation data between the real-time respiratory data and the target respiratory data includes: The target respiratory rate, target inspiratory duration, and target expiratory duration are obtained from the target respiratory data, and the target inspiratory-expiratory ratio is determined based on the target inspiratory duration and the target expiratory duration. Obtain the user's real-time inspiratory-to-expiratory ratio (IPR) during the guidance process, and determine the IPR deviation between the real-time IPR and the target IPR. The real-time respiratory rate is obtained from the real-time respiratory data, and the respiratory rate deviation between the real-time respiratory rate and the target respiratory rate is determined. Based on the respiratory rate deviation and the inspiratory-to-expiratory ratio deviation, the guidance deviation data is determined.
5. The method for guiding breathing after exercise as described in claim 3, characterized in that, Based on the guidance deviation data, the target breathing data is updated, including: The first continuous respiratory cycle corresponding to the guidance deviation data being less than a first threshold is monitored; when the first continuous respiratory cycle is greater than a set cycle, the target respiratory rate in the target respiratory data is reduced. Alternatively, monitor the second consecutive respiratory cycle corresponding to the guidance deviation data being greater than the second threshold; when the second consecutive respiratory cycle is greater than the set cycle, increase the target respiratory rate in the target respiratory data.
6. The method for guiding breathing after exercise as described in claim 1, characterized in that, Based on the real-time feedback data, the target respiratory data is updated, including: Real-time chest movement video data and real-time abdominal movement video data are obtained from the real-time feedback data; The degree of chest-abdominal coordination is determined based on the real-time chest movement video data and the real-time abdominal movement video data. The target respiratory data is updated based on the degree of chest-abdominal coordination.
7. The method for guiding breathing after exercise as described in claim 3, characterized in that, After determining the guidance deviation data between the real-time respiratory data and the target respiratory data, the method further includes: The system monitors the trend of the guidance deviation data and controls the expansion and contraction speed of the prompting ball based on the trend. The prompting ball is used to prompt the user to adjust their breathing to follow the target breathing data.
8. A post-exercise breathing guidance device, characterized in that, The device comprises the following components: The deviation calculation module is used to acquire the user's breathing data after exercise and the user's resting breathing data when at rest, and to determine the breathing deviation data between the breathing data after exercise and the resting breathing data; A target setting module is used to determine target breathing data based on the breathing deviation data; wherein the target breathing data is used to guide and transition from the post-exercise breathing data to the resting breathing data; An optimized guidance module is used to provide breathing guidance to the user based on the target breathing data; during the guidance process, the module monitors the user's real-time feedback data; and updates the target breathing data based on the real-time feedback data, and continues to provide breathing guidance to the user based on the updated target breathing data.
9. A terminal device, characterized in that, The terminal device includes a memory, a processor, and a post-exercise breathing guidance program stored in the memory and executable on the processor. When the processor executes the post-exercise breathing guidance program, it implements the steps of the post-exercise breathing guidance method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a post-exercise breathing guidance program, which, when executed by a processor, implements the steps of the post-exercise breathing guidance method as described in any one of claims 1-7.