A method and system for controlling baby crib sleep based on environmental simulation

Abstract

The present application relates to the technical field of environment simulation control, in particular to a crib lulling control method and system based on environment simulation, comprising the following steps: collecting a baby's crying signal, setting a fixed time window, calculating the short-time energy change rate between adjacent frames and the interval time between continuous syllables, analyzing the change trend of the interval time sequence of the syllables, and obtaining the crying syllable rhythm change analysis result. In the present application, the crying signal is processed by short-time framing, the short-time energy change rate is calculated, the syllable boundary is detected, the syllable interval time change trend is extracted, the emotion fluctuation recognition is more real-time, the soothing demand is classified according to the syllable rhythm change rate and the energy fluctuation characteristics, the baby's state is accurately matched, the movement rhythm is synchronized with the crying mode by dynamically adjusting the shaking frequency according to the phase shift, the shaking frequency is adjusted, the whistling sound is played, and the breathing signal is analyzed, the environment simulation is further optimized, and the stability and reliability of the lulling process are improved.

Description

Technical Field

[0001] This invention relates to the field of environmental simulation control technology, and in particular to a method and system for controlling a baby crib to fall asleep based on environmental simulation. Background Technology

[0002] The field of environmental simulation and control technology encompasses control methods and systems for adjusting and simulating environmental parameters. It primarily involves the automated regulation of environmental factors such as temperature, humidity, light, and sound to meet the needs of specific application scenarios. The core concept is to use microphone arrays to collect environmental data and then adjust environmental parameters through control algorithms and actuators to achieve preset conditions. This field is mainly applied in smart homes, automated greenhouses, immersive experience systems, and industrial production environments, typically combining real-time monitoring, data analysis, and feedback adjustment mechanisms to construct accurate environmental simulation systems.

[0003] Among them, the crib soothing control method based on environmental simulation refers to a control method that adjusts the environmental parameters around the crib to simulate a specific natural or artificial environment in order to achieve the purpose of soothing the baby to sleep. It covers the regulation of environmental factors such as sound, light, temperature and air flow. Specifically, a microphone array is used to collect the baby's activity status and environmental data, and the current status of the baby is analyzed in combination with an environmental simulation model. Then, a sound of a specific frequency or rhythm is played through a speaker, the brightness and color temperature of the light are adjusted by an intelligent lighting control system, and the ambient temperature is adjusted by a temperature control device. In conjunction with an air circulation device, a natural wind is simulated. The process relies on environmental data analysis and combined with preset environmental change strategies to control the relevant equipment to adjust synchronously, so as to create a stable soothing environment for the baby to sleep.

[0004] Existing technologies for controlling infant sleep in cribs have shortcomings. Sound, light, temperature, and humidity adjustments are primarily static, failing to consider the real-time emotional changes in the infant's cries. This leads to a mismatch between environmental regulation and soothing needs, making it difficult to match emotional fluctuations. Fixed or preset rocking patterns lack dynamic adjustment capabilities, and the lack of a matching mechanism between rocking frequency and crying rhythm causes rhythm conflict, resulting in a counterproductive effect on soothing and exacerbating crying. Environmental simulation systems lack adaptive feedback on soothing effects, relying solely on unidirectional adjustment and failing to establish multi-channel interactive control. This limits the infant's sleep process to a single soothing method, reducing overall soothing efficiency. The lack of in-depth analysis of the infant's physiological state and the failure to integrate breathing and emotional rhythms in comprehensive regulation cause environmental control to lag behind the infant's actual state changes, reducing the success rate of soothing to sleep. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a baby crib sleep control method based on environmental simulation.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a baby crib sleep-inducing control method based on environmental simulation, comprising the following steps:

[0007] S1: Collect infant crying signals, set a fixed time window, calculate the short-term energy change rate and continuous syllable interval time between adjacent frames, analyze the changing trend of syllable interval time sequence, and obtain the analysis results of crying syllable rhythm change.

[0008] S2: Based on the analysis results of the rhythm changes of the crying syllables, determine the stability of the infant's crying rhythm, calculate the amplitude of the change in energy change rate, determine the need for comfort, and obtain the classification results of the type of comfort need;

[0009] S3: Based on the classification results of the soothing needs type, obtain the current rocking frequency of the crib, calculate the phase offset value between the crying rhythm and the rocking frequency, determine the matching degree of the current rocking mode and adjust the rocking frequency, and obtain the adaptive rocking frequency adjustment result.

[0010] S4: Based on the adaptive rocking frequency adjustment results, calculate the increase or decrease of the current rocking frequency, dynamically control the rocking rhythm of the crib, and obtain the rocking rhythm data of the crib after dynamic adjustment.

[0011] S5: Based on the dynamically adjusted crib rocking rhythm data, a hissing sound is emitted synchronously, the rate of change of the baby's breathing rhythm is calculated, the baby's sleep status is determined, and the baby's sleep-inducing process is completed.

[0012] As a further aspect of the present invention, the analysis results of the crying syllable rhythm change include the mean square error of syllable interval time, the amplitude of syllable rhythm fluctuation, and the short-term energy change rate; the classification results of the soothing need type include the soothing need, the strong soothing need, and the energy fluctuation status record; the adaptive rocking frequency adjustment results include the current rocking frequency, the rocking frequency adjustment amplitude, and the phase offset correction amount; and the dynamically adjusted crib rocking rhythm data includes the rocking acceleration adjustment value, the rocking frequency stability, and the rhythm synchronization status.

[0013] As a further aspect of the present invention, the specific steps for acquiring infant cry signals, setting a fixed time window, calculating the short-term energy change rate and continuous syllable interval time between adjacent frames, analyzing the variation trend of the syllable interval time sequence, and obtaining the analysis results of the cry syllable rhythm change are as follows:

[0014] S111: Acquire the baby's crying signal, perform short-time framing processing on the signal, set a fixed time window, calculate the short-time energy value of each frame, calculate the short-time energy change rate of adjacent frames based on the short-time energy of adjacent frames, call the short-time energy value and the short-time energy change rate, and obtain the energy fluctuation characteristics.

[0015] S112: Based on the energy fluctuation characteristics, determine the syllable boundary positions, calculate the interval time between consecutive syllables, analyze the changing trend based on the syllable interval time sequence, and use the formula:

[0016]

[0017] Calculate the rate of change R of syllable interval time to obtain syllable rhythmic features, where T i T represents the interval time of the i-th syllable, N represents the total number of syllables, and |T i -T i-1 | represents the change in the time interval between adjacent syllables. This represents the sum of squares of the intervals between all syllables;

[0018] S113: Based on the rhythmic characteristics of the syllables, analyze the changing trend of the syllable interval time sequence, and combine the rate of change of the syllable interval time to obtain the analysis results of the rhythmic change of the crying syllables.

[0019] As a further aspect of the present invention, based on the analysis results of the rhythmic changes in the infant's crying syllables, the specific steps for determining the stability of the infant's crying rhythm, calculating the amplitude of the change in energy rate, determining the need for comfort, and obtaining the classification results of the type of comfort need are as follows:

[0020] S211: Based on the analysis results of the rhythm change of the crying sound syllables, calculate the mean square error of the syllable interval time, determine the syllable stability, and obtain syllable rhythm stability data.

[0021] S212: Based on the rhythmic stability of the syllables, the following formula is used:

[0022]

[0023] Calculate the magnitude of the energy change rate M to obtain energy fluctuation amplitude data, where E i Let |E| represent the energy value of the i-th frame, and n represent the total number of energy frames. i -E i-1 | represents the energy change between adjacent frames. Represents the sum of squares of all energy values. represents the sum of squares of the intervals between all syllables, and z represents the total number of syllables;

[0024] S213: Based on the energy fluctuation amplitude data and the syllable rhythm stability data, classify the energy fluctuation amplitude according to whether it is in a stable range. If it is in a stable range, it is classified as a soothing and calming need. If the energy fluctuation amplitude is large and the syllable rhythm stability fluctuates violently, it is classified as a strong calming need. Obtain the classification result of the calming need type.

[0025] As a further aspect of the present invention, based on the classification results of the soothing needs type, the specific steps for obtaining the current rocking frequency of the crib, calculating the phase offset value between the crying rhythm and the rocking frequency, determining the matching degree of the current rocking mode, adjusting the rocking frequency, and obtaining the adaptive rocking frequency adjustment result are as follows:

[0026] S311: Based on the classification results of the soothing needs type, obtain the current rocking frequency of the crib through the microphone array, call the rocking frequency, and obtain the current rocking mode parameters;

[0027] S312: Based on the current shaking mode parameters, calculate the phase shift value between the crying rhythm and the shaking frequency using the formula:

[0028]

[0029] Calculate the phase offset value Φ to obtain the sway pattern matching degree, where f c,i f represents the frequency of the crying rhythm detected for the i-th time. s,i J represents the frequency of the shaking detected in the i-th instance, and J represents the number of detections.

[0030] S313: Based on the matching degree of the shaking mode, classify according to whether the phase offset value is within the set threshold. If it is within the set threshold, maintain the current shaking mode. If the phase offset value exceeds the threshold range, adjust the shaking frequency so that the crying rhythm and the shaking mode are gradually synchronized, and obtain the adaptive shaking frequency adjustment result.

[0031] As a further aspect of the present invention, based on the adaptive rocking frequency adjustment result, the increase or decrease of the current rocking frequency is calculated, and the rocking rhythm of the crib is dynamically controlled. The specific steps for obtaining the dynamically adjusted crib rocking rhythm data are as follows:

[0032] S411: Based on the adaptive shaking frequency adjustment result, calculate the increase or decrease of the current shaking frequency, analyze the change amplitude, and obtain shaking frequency adjustment amplitude data;

[0033] S412: Based on the shaking frequency adjustment amplitude data, determine whether it is necessary to reduce the shaking frequency, using the following formula:

[0034]

[0035] Calculate the short-time energy change rate ΔG, analyze the short-time energy change trend, and output the short-time energy change trend record, where G... i G represents the short-time energy value of the i-th frame, g represents the total number of short-time energy frames, and G i-1 F represents the short-time energy value of the previous frame. i F0 represents the current shaking frequency, and F0 represents the initial shaking frequency. Represents the normalization factor for the shaking frequency;

[0036] S413: Based on the recorded short-term energy change trend, if the short-term energy shows a decreasing trend, reduce the shaking acceleration; if the short-term energy remains stable, maintain the current adjustment result and obtain the dynamic adjustment data of the crib's shaking rhythm.

[0037] As a further aspect of the present invention, based on the dynamically adjusted baby crib rocking rhythm data, a hissing sound is emitted synchronously, the rate of change in the baby's breathing rhythm is calculated, and the baby's sleep status is determined. The specific steps for completing the baby's sleep-inducing process are as follows:

[0038] S511: Based on the dynamically adjusted crib rocking rhythm data, a hissing sound is emitted synchronously, the latest infant breathing signal is collected, and the latest infant breathing syllable data is obtained.

[0039] S512: Based on the latest infant respiratory syllable data, the following formula is used:

[0040]

[0041] Calculate the rate of change V of respiratory syllable rhythm to obtain the results of respiratory rhythm fluctuation trend analysis, where u i |u| represents the interval between the i-th detected respiratory syllables, and U represents the number of detections. i -u i-1 | represents the absolute change in the interval between adjacent respiratory syllables, u i-1 This represents the interval between the previously detected respiratory syllables;

[0042] S513: Based on the analysis results of the breathing rhythm fluctuation trend, if the interval between breathing syllables is stable, it indicates that the mood is stabilizing and the baby is falling asleep, thus completing the process of putting the baby to sleep.

[0043] A crib sleep-inducing control system based on environmental simulation includes:

[0044] The crying feature extraction module acquires the crying signal, performs short-time framing processing, calculates the short-time energy value and the short-time energy change rate, extracts energy fluctuation features, determines the syllable boundary position, calculates the syllable interval time, extracts syllable rhythm features, analyzes the changing trend of the syllable interval time sequence, and obtains the crying syllable rhythm change analysis results.

[0045] The comfort needs classification module calculates the mean square error of syllable interval time and the amplitude of short-term energy change rate based on the analysis results of the crying syllable rhythm change, judges the comfort needs, and obtains the comfort needs type classification results;

[0046] The shaking frequency matching module obtains the shaking frequency based on the classification results of the soothing needs type, calculates the phase offset value, determines the degree of matching of the shaking mode, adjusts the shaking frequency, and obtains the adaptive shaking frequency adjustment result.

[0047] Based on the adaptive rocking frequency adjustment results, the rocking rhythm adjustment module calculates the increase or decrease in rocking frequency, judges the short-term energy trend, adjusts the rocking acceleration, and obtains the dynamically adjusted baby crib rocking rhythm data.

[0048] The sleep state determination module, based on the dynamically adjusted crib rocking rhythm data, synchronously emits a hissing sound, acquires the baby's breathing signal, calculates the rate of change of breathing syllable rhythm, determines the baby's sleep state, and completes the baby's soothing process.

[0049] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0050] In this invention, the crying signal is processed through short-time framing to calculate the short-time energy change rate. Combined with syllable boundary detection, the trend of syllable interval time change is extracted, making emotional fluctuation recognition more real-time. Soothing needs are categorized based on syllable rhythm change rate and energy fluctuation characteristics, allowing gentle and strong soothing strategies to accurately match the infant's state. The rocking frequency is dynamically adjusted by calculating phase offset, synchronizing the movement rhythm with the crying pattern and reducing maladaptation to external stimuli. After adjusting the rocking frequency, combined with shushing sound playback and respiratory signal analysis, the environmental simulation is further optimized. This makes the soothing method no longer dependent on preset parameters but adaptively changes based on the infant's state, reducing the problem of a single environmental intervention method and improving the stability and reliability of the soothing process. Attached Figure Description

[0051] Figure 1 This is a flowchart of the main steps of the present invention;

[0052] Figure 2 This is a flowchart of step S1 of the present invention;

[0053] Figure 3 This is a flowchart of step S2 of the present invention;

[0054] Figure 4 This is a flowchart of step S3 of the present invention;

[0055] Figure 5 This is a flowchart of step S4 of the present invention;

[0056] Figure 6 This is a flowchart of step S5 of the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0058] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0059] Please see Figure 1 A crib sleep control method based on environmental simulation includes the following steps:

[0060] S1: Acquire infant crying signals through a microphone array, perform short-time frame processing, set a fixed time window, calculate the short-time energy value of each frame, calculate the rate of change of short-time energy between adjacent frames, extract energy fluctuation features, determine syllable boundary positions, calculate the interval time of consecutive syllables, extract syllable rhythm features, analyze the changing trend of syllable interval time sequence, and obtain the analysis results of crying syllable rhythm changes.

[0061] S2: Based on the analysis results of the rhythm changes of crying syllables, calculate the mean square error of the syllable interval time, determine the stability of the infant's crying rhythm, calculate the variation range of the energy change rate, if the variation range is within the stable range, it is classified as a soothing need; if the variation range is large and the syllable interval time fluctuates violently, it is classified as a strong soothing need, and obtain the classification results of soothing need type.

[0062] S3: Based on the classification results of soothing needs, the current rocking frequency of the crib is obtained through the microphone array, the phase offset value between the crying rhythm and the rocking frequency is calculated, and the matching degree of the current rocking mode is determined. If the phase offset value is within the set threshold, the current rocking mode is maintained. If the phase offset value exceeds the threshold range, the rocking frequency is adjusted so that the crying rhythm and the rocking mode are gradually synchronized, and the adaptive rocking frequency adjustment result is obtained.

[0063] S4: Based on the adaptive rocking frequency adjustment results, calculate the increase or decrease of the current rocking frequency and determine whether it is necessary to further reduce the rocking frequency. If the short-term energy shows a downward trend, the rocking acceleration is slowly reduced. If the short-term energy remains stable, the current adjustment result is maintained, and the dynamic adjustment data of the crib rocking rhythm is obtained.

[0064] S5: Based on the dynamically adjusted crib rocking rhythm data, it synchronously emits a hissing sound, collects the latest infant breathing signals, calculates the current rate of change of infant breathing syllable rhythm and judges the fluctuation trend. If the interval between breathing syllables is stable, it indicates that the baby's emotions are stabilizing and the baby has entered sleep, thus completing the process of putting the baby to sleep.

[0065] The analysis results of crying syllable rhythm changes include the mean square error of syllable interval time, the amplitude of syllable rhythm fluctuation, and the short-term energy change rate. The classification results of soothing needs include soothing needs, strong soothing needs, and energy fluctuation status records. The results of adaptive rocking frequency adjustment include the current rocking frequency, the rocking frequency adjustment amplitude, and the phase offset correction amount. The data of the crib rocking rhythm after dynamic adjustment include the rocking acceleration adjustment value, rocking frequency stability, and rhythm synchronization status.

[0066] Please see Figure 2 Step S1 is as follows:

[0067] S111: Acquire the baby's crying signal, perform short-time framing processing on the signal, set a fixed time window, calculate the short-time energy value of each frame, calculate the short-time energy change rate of adjacent frames based on the short-time energy of adjacent frames, call the short-time energy value and the short-time energy change rate, and obtain the energy fluctuation characteristics.

[0068] Acquiring a baby's cry signal typically relies on a microphone array installed around the crib. The microphones collect ambient sound data in real time and filter out background noise, such as appliance noise and family conversations, to obtain a relatively pure baby cry signal. This signal is then processed through short-time framing, with a fixed time window (e.g., 20ms) to ensure signal continuity. For each time window, a short-time energy value is calculated, representing the signal's energy level within that frame. This short-time energy value is obtained by accumulating the squared signal amplitude within that frame, using the following formula:

[0069]

[0070] Among them, E n Let x(m) be the short-time energy value of the nth frame, x(m) represent the signal amplitude of the mth sampling point, and e be the number of sampling points per frame. Taking a common 16kHz sampling rate as an example, each frame typically contains 320 sampling points. Next, the rate of change of short-time energy between adjacent frames is calculated using the following formula:

[0071] ΔE n =|E n -E n-1 |

[0072] Where, ΔE n This represents the short-term energy change rate between the nth frame and the previous frame. Ultimately, energy fluctuation characteristics can be obtained based on the short-term energy value and the short-term energy change rate.

[0073] Table 1.1 shows examples of short-time energy values ​​and short-time energy change rates collected over a certain period of time:

[0074] Table 1.1 Short-time energy and rate of change

[0075]

[0076] As shown in Table 1.1, the short-term energy change rate reached 0.0032 in the third frame, indicating a larger fluctuation in signal energy at this time, which may mean that the baby was crying at a higher intensity. Compared with the change rate of 0.0005 in the fourth frame, the energy fluctuation was smaller, indicating that the crying intensity was reduced. The energy fluctuation characteristics were finally obtained.

[0077] S112: Based on energy fluctuation characteristics, determine the syllable boundary positions, calculate the interval time between consecutive syllables, analyze the changing trend based on the syllable interval time series, and use the following formula:

[0078]

[0079] Calculate the rate of change R of syllable interval time to obtain syllable rhythmic features, where T i T represents the interval time of the i-th syllable, N represents the total number of syllables, and |T i -T i-1 | represents the change in the time interval between adjacent syllables. This represents the sum of squares of the intervals between all syllables;

[0080] Based on energy fluctuation characteristics, the location of syllable boundaries can be further determined, that is, the start and end times of different syllables in the cry can be detected, usually by setting a short-time energy threshold E. th The system makes a judgment: if the short-term energy value is higher than a threshold, it is determined that a syllable exists; if it is lower than the threshold, it is determined that a syllable has ended. For example, if E is set... th =0.005. When the short-term energy value changes from below the threshold to above the threshold, the start time of the syllable is determined. Conversely, when the short-term energy value changes from above the threshold to below the threshold, the end time of the syllable is determined. The interval T between consecutive syllables is then calculated. i This is obtained by calculating the difference in the start time of adjacent syllables:

[0081] Ti =t start,i+1 -t start,i

[0082] Among them, t start,i This represents the start time of the i-th syllable. Next, we analyze the trend of the syllable interval time series, using the rate of change R of the syllable interval time as a metric.

[0083] Now, suppose the syllable intervals of a certain segment of an infant's cry are shown in Table 1.2 below:

[0084] Table 1.2 Syllable Interval Time Data Table

[0085]

[0086] Substitute into the formula to calculate:

[0087]

[0088] The results showed that the rate of change of syllable interval time was 0.231. The larger the value, the greater the change in crying rhythm, and finally the syllable rhythm characteristics were obtained.

[0089] S113: Based on the rhythmic characteristics of syllables, analyze the changing trend of the syllable interval time sequence, and combine the rate of change of syllable interval time to obtain the analysis results of the rhythmic changes of crying syllables.

[0090] Based on the rhythmic characteristics of syllables, the changing trend of the syllable interval time series can be further analyzed, that is, its range of change and stability can be calculated. This can be achieved by setting a threshold R for the rate of change of syllable interval time. th Make a judgment if R > R th This indicates a drastic change in the rhythm of the crying. If R <R th This indicates that the crying rhythm is relatively stable, and the threshold R... th The settings are based on the rhythmic variation range of normal infant cries, specifically referring to a large number of infant cry data samples. The distribution of the rate of change of syllable interval time was statistically analyzed. Assuming that 2000 infant cry samples were collected, each containing at least 10 consecutive syllable interval time data, the rate of change was calculated and the distribution was analyzed. The data distribution is shown in Table 1.3 below:

[0091] Table 1.3 Statistical Table of Syllable Interval Time Variation Rate

[0092]

[0093]

[0094] According to statistical data, among the 2000 samples, the rate of change R mainly concentrated between 0.15 and 0.25, accounting for 57.5% cumulatively. 0.25 is already close to the range of relatively high rates of change; therefore, R is set as... th =0.25 is used as the stability threshold for the change in crying rhythm. Exceeding this value indicates a drastic change in crying rhythm, while below this value indicates a relatively stable crying rhythm. The calculated R = 0.231 is below the threshold, so it can be judged that the change in the rhythm of the crying is relatively stable, and the final result of the analysis of the change in the rhythm of the crying syllables is obtained.

[0095] Please see Figure 3 Step S2 is as follows:

[0096] S211: Based on the analysis results of the rhythm changes of crying syllables, calculate the mean square error of syllable interval time, determine syllable stability, and obtain syllable rhythm stability data.

[0097] Based on the analysis of the rhythmic changes of crying syllables, the collected syllable interval time data were first processed to calculate the mean square error of the syllable interval time. In practical applications, for a dataset, such as a syllable interval time of t = [0.8s, 1.2s, 1.0s, 0.9s, 1.3s], the formula for calculating the mean square error is as follows:

[0098]

[0099] in, Let Nt be the mean of the syllable interval time, and Nt represent the total number of data points. Calculate the mean based on the dataset:

[0100]

[0101] Then calculate the mean squared error:

[0102]

[0103] The stable threshold range is set based on the natural fluctuation range of infant cry syllables. Analysis of cry syllable data from different infants in various states revealed that when the mean square error (MSE) is below 0.05, the infant's cry rhythm is relatively regular and fluctuates little, while exceeding 0.05 indicates unstable cry rhythm with significant changes. This value is affected by the infant's emotional state, sleep quality, and the degree of external interference; as the infant's emotional excitement increases, the MSE may rise rapidly.

[0104] The calculated syllable rhythm stability can be used to determine the degree of change in the crying rhythm. The smaller the value, the more stable the crying rhythm. If the stability threshold range is set to [0, 0.05], then the mean square error MSE = 0.0352 in the current dataset is in the stable range. Therefore, it can be determined that the crying rhythm is relatively stable, and syllable rhythm stability data can be obtained.

[0105] S212: Based on the rhythmic stability of syllables, the following formula is used:

[0106]

[0107] Calculate the magnitude of the energy change rate M to obtain energy fluctuation amplitude data, where E i Let |E| represent the energy value of the i-th frame, and n represent the total number of energy frames. i -E i-1 | represents the energy change between adjacent frames. Represents the sum of squares of all energy values. represents the sum of squares of the intervals between all syllables, and z represents the total number of syllables;

[0108] Based on the syllable rhythm stability data, the variation amplitude of the energy change rate is calculated. The collected energy change rate dataset is set as E = [3.2, 3.8, 4.1, 3.5, 4.0], and the calculation is performed using a formula.

[0109] First, calculate the absolute value of the energy change between adjacent frames:

[0110] |E2-E1|=|3.8-3.2|=0.6;

[0111] |E3-E2|=|4.1-3.8|=0.3;

[0112] |E4-E3|=|3.5-4.1|=0.6;

[0113] |E5-E4|=|4.0-3.5|=0.5;

[0114] Summing yields:

[0115]

[0116] Then calculate the sum of squares:

[0117]

[0118] Substitute into the formula to calculate:

[0119]

[0120] Obtain energy fluctuation amplitude data and determine the energy change of the crying sound based on this value.

[0121] S213: Based on energy fluctuation amplitude data and syllable rhythm stability data, classify according to whether the energy fluctuation amplitude is in a stable range. If it is in a stable range, it is classified as a need for soothing and calming. If the energy fluctuation amplitude is large and the syllable rhythm stability fluctuates violently, it is classified as a need for strong calming and calming. Obtain the classification results of calming and calming need types.

[0122] Based on energy fluctuation amplitude data and syllable rhythm stability data, and according to the set stability range, if the energy fluctuation amplitude is within the stability range [0, 0.25] and the syllable rhythm stability meets the stability threshold [0, 0.05], it is classified as a soothing and calming need. If the energy fluctuation amplitude exceeds 0.25 and the syllable rhythm stability exceeds 0.05, it is classified as a strong calming need. The current data calculation results show:

[0123] Syllable rhythm stability = 0.0352 (0 ≤ 0.0352 ≤ 0.05);

[0124] Energy fluctuation amplitude = 0.241 (0 ≤ 0.241 ≤ 0.25);

[0125] The energy fluctuation amplitude threshold was set based on statistical analysis of the energy change rate. Monitoring a large amount of infant crying data revealed that when the energy fluctuation amplitude was below 0.25, the crying energy changes were relatively gentle and stable, typically corresponding to mild discomfort or mild emotional fluctuations in the infant. However, when the energy fluctuation amplitude exceeded 0.25, the energy change increased significantly, indicating more intense crying, usually related to severe discomfort, hunger, or pain in the infant. This threshold is affected by the volume, frequency amplitude, and duration of the cry. An energy change rate exceeding 0.25 usually indicates severe emotional fluctuations in the infant, requiring stronger soothing interventions.

[0126] Therefore, the crying rhythm is stable and the energy fluctuation is low under this data, which is classified as a need for soothing and comforting, and the classification result of the type of soothing need is obtained.

[0127] Please see Figure 4 Step S3 is as follows:

[0128] S311: Based on the classification results of soothing needs, obtain the current rocking frequency of the crib through the microphone array, call the rocking frequency, and obtain the current rocking mode parameters;

[0129] Based on the classification of soothing needs, the current rocking frequency of the crib is acquired using a microphone array. The microphone array consists of multiple high-sensitivity sensors, each capable of detecting ambient sound signals. To ensure data accuracy, ambient noise needs to be filtered, for example, using a time-domain weighted average to remove background noise. In practice, if the ambient noise amplitude acquired by the microphone array is below 20dB, the noise impact is considered relatively small; otherwise, a bandpass filter is used to suppress high-frequency or low-frequency noise. The acquired rocking frequency can be analyzed using a short-time Fourier transform (STFT) to determine the main frequency components of the signal. For example, the rocking motion data of a crib over 5 seconds is as follows:

[0130] 0.5, 0.52, 0.49, 0.51, 0.50Hz

[0131] The average value is then taken as the initial estimate, which is 0.504Hz, to obtain the parameters of the current shaking mode.

[0132] S312: Based on the current shaking mode parameters, calculate the phase shift value between the crying rhythm and the shaking frequency using the formula:

[0133]

[0134] Calculate the phase offset value Φ to obtain the sway pattern matching degree, where f c,i f represents the frequency of the crying rhythm detected for the i-th time. s,i J represents the frequency of the shaking detected in the i-th instance, and J represents the number of detections.

[0135] Based on the current shaking mode parameters, the phase shift value between the crying rhythm and the shaking frequency is calculated. The phase shift value measures the degree of synchronization between the two rhythms and is calculated using a formula.

[0136] Among them, the frequency of crying rhythm f c,i The dominant frequency can be obtained by performing a Fourier transform on the continuous crying signal of an infant. For example, the frequency change of an infant's cry within a 5-second time window is as follows:

[0137] 0.48, 0.47, 0.49, 0.50, 0.46Hz

[0138] Then calculate the mean f c =0.48Hz, similarly, the rocking frequency f of the crib. s,i f is calculated from the aforementioned shaking mode parameters s =0.504Hz, substitute into the formula to calculate the phase shift value:

[0139]

[0140] Table 3.1 lists the calculation results of phase offset values ​​under different scenarios.

[0141] Table 3.1 Calculation Table of Shaking Pattern and Crying Rhythm Phase Shift

[0142]

[0143] As shown in Table 3.1, a smaller phase offset value (such as in scenario C) indicates better rhythm synchronization, thus obtaining the shaking pattern matching degree.

[0144] S313: Based on the matching degree of the shaking pattern, classify according to whether the phase offset value is within the set threshold. If it is within the set threshold, maintain the current shaking pattern. If the phase offset value exceeds the threshold range, adjust the shaking frequency so that the crying rhythm and the shaking pattern are gradually synchronized to obtain the adaptive shaking frequency adjustment result.

[0145] Based on the matching degree of the rocking pattern, and categorized according to whether the phase offset value is within a set threshold, the synchronization threshold is set at 20°. This value is set based on the matching relationship between the infant's crying rhythm and soothing movements. According to the response characteristics of the infant's nervous system to periodic movements, research shows that when the phase offset value is between 15° and 25°, the infant's heart rate and respiratory rate fluctuate less, and the movement rhythm tends to be consistent with the physiological rhythm. Therefore, the median value of 20° is taken as the adjustment benchmark. The change in this value is mainly affected by the degree of deviation between the rocking frequency and the crying rhythm frequency. That is, when the rocking frequency deviates significantly from the crying rhythm, the phase offset value increases; when the two are close to synchronization, the phase offset value tends to zero. If the phase offset value is less than this threshold, then... Maintain the current rocking pattern. If the threshold is exceeded, adjust the rocking frequency to gradually synchronize the crying rhythm with the rocking pattern. Set the adjustment step size of the rocking frequency to 0.01Hz. If the phase offset value is higher than 20°, adjust the rocking frequency according to the phase offset direction to make it closer to the crying rhythm. For example, if the current rocking frequency is 0.504Hz, the crying frequency is 0.48Hz, and the phase offset value is 17.14°, which is lower than the threshold, the rocking pattern remains unchanged. However, if the rocking frequency is 0.55Hz, the crying frequency is 0.48Hz, and the phase offset value reaches 30°, adjust the rocking frequency to 0.54Hz, recalculate the phase offset value, and repeat this adjustment process to obtain the adaptive rocking frequency adjustment result.

[0146] Please see Figure 5 Step S4 is as follows:

[0147] S411: Based on the adaptive shaking frequency adjustment results, calculate the increase or decrease of the current shaking frequency, analyze the change amplitude, and obtain shaking frequency adjustment amplitude data;

[0148] Based on the adaptive rocking frequency adjustment results, the specific value of the current rocking frequency needs to be obtained first. Assuming the initial rocking frequency of the crib is 0.8Hz, sensors can be used to detect the current rocking state in real time. Combined with data from the gyroscope and accelerometer, the current rocking frequency is calculated. The data acquisition window is set to 10 seconds, with 100 samples per second, for a total of 1000 sets of rocking frequency data. Then, the average value is calculated as the current rocking frequency. The calculation formula is as follows:

[0149]

[0150] Among them, f current This represents the current shaking frequency, K represents the corresponding number of sampled data points, and f i This represents the shaking frequency of the i-th sample.

[0151] The initial shaking frequency f0 was set to 0.8 Hz, and the sampled shaking frequency data are shown in Table 4.1:

[0152] Table 4.1 Current shaking frequency sampling data (partial)

[0153]

[0154] As shown in Table 4.1, the current shaking frequency f is calculated. current It is approximately 0.805 Hz. Next, calculate the increase or decrease in the shaking frequency:

[0155] Δf=f current -f0

[0156] Substituting the values, we get:

[0157] Δf = 0.805 - 0.8 = 0.005 Hz

[0158] Obtain the shaking frequency adjustment range.

[0159] S412: Based on the shaking frequency adjustment amplitude data, determine whether it is necessary to reduce the shaking frequency using the following formula:

[0160]

[0161] Calculate the short-time energy change rate ΔG, analyze the short-time energy change trend, and output the short-time energy change trend record, where G... i G represents the short-time energy value of the i-th frame, g represents the total number of short-time energy frames, and G i-1 F represents the short-time energy value of the previous frame. i F0 represents the current shaking frequency, and F0 represents the initial shaking frequency. Represents the normalization factor for the shaking frequency;

[0162] Based on the adjustment range of the shaking frequency, it is determined whether the shaking frequency needs to be further reduced. This requires analyzing the short-term energy variation trend. Short-term energy calculation is based on audio signal processing. The acquired crying signal is processed in short-time frames, with each frame set to 25ms, and a 50% overlap sliding window is used to calculate the energy value of each frame.

[0163]

[0164] Among them, E i Let x be the short-time energy of the i-th frame. i (n) represents the amplitude value of the nth data point in the frame, and Z represents the number of data points contained in each frame.

[0165] Collect 100 frames of data, use formulas to calculate short-term energy change trends.

[0166] The average short-time energy over 100 frames is as follows (partial data):

[0167] Table 4.2 Short-time energy calculation results (partial)

[0168]

[0169]

[0170] Calculate the short-time energy change rate:

[0171]

[0172] The calculation yielded:

[0173] ΔG = -0.0012

[0174] Since ΔG is negative, it indicates that the short-term energy is decreasing, so the shaking acceleration needs to be reduced slowly. Obtain the short-term energy change trend.

[0175] S413: Based on the short-term energy change trend record, if the short-term energy shows a downward trend, reduce the shaking acceleration; if the short-term energy remains stable, maintain the current adjustment result and obtain the crib shaking rhythm data after dynamic adjustment.

[0176] Based on short-term energy change trend records, if the short-term energy decreases, the shaking acceleration is gradually reduced, and the adjustment formula is as follows:

[0177]

[0178] Among them, a new For the adjusted shaking acceleration, a current Let G be the current shaking acceleration, |ΔG| be the absolute value of the short-time rate of change of energy, and G be the current shaking acceleration. max This represents the maximum value of the short-time energy.

[0179] Set the current acceleration a current 0.15m / s 2 Short-time energy maximum value G max =0.02, substitute into the calculation:

[0180]

[0181] The calculation yields:

[0182] a new =0.141

[0183] Due to the short-term energy drop, the shaking acceleration decreased from 0.15 m / s². 2 Reduced to 0.141 m / s 2 To obtain data on the rocking rhythm of the crib after dynamic adjustment.

[0184] Please see Figure 6 The S5 steps are as follows:

[0185] S511: Based on the dynamically adjusted crib rocking rhythm data, it synchronously emits a hissing sound, collects the latest infant breathing signals, and obtains the latest infant breathing syllable data.

[0186] Based on the dynamically adjusted crib rocking rhythm data, a synchronous hissing sound is emitted to collect the latest infant breathing signals. These signals are detected using a miniature microphone array installed around the crib. Real-time signal processing is used to calculate the periodic characteristics of the breathing syllables; for example, the time interval of breathing syllables is typically between 0.8s and 1.5s. Assuming a collected breathing signal interval time sequence is [0.85s, 0.88s, 0.92s, 0.91s], the collected signals need to undergo a short-time Fourier transform (STFT) to decompose the spectral information and remove environmental noise. In practical applications, the amplitude variation of the filtered signal should match the infant's breathing pattern. A reference breathing cycle range T is set. ref =[0.8s, 1.5s] is based on the normal respiratory rhythm distribution of infants at different ages. Typically, the respiratory rate of newborns ranges from 30-50 breaths per minute, and the corresponding single respiratory cycle is... to The normal respiratory rate for infants aged 1-6 months is 25-40 breaths per minute, with a corresponding single respiratory cycle of... to After eliminating environmental factors and individual differences, a reference range of 0.8s to 1.5s was taken as the stable respiratory cycle to ensure that it can cover the respiratory fluctuations of infants in the main age groups. The current cycle T was then calculated. curWhether it is within the range, if the current period is within the range, the data is considered valid; if the deviation is large, the signal needs to be re-acquired and error correction needs to be performed, as shown in Table 5.1.

[0187] Table 5.1 Results of Infant Respiratory Signal Acquisition

[0188]

[0189]

[0190] As shown in Table 5.1, data number 3 exceeded the threshold and needed to be re-collected and filtered for correction. After error correction, the latest infant respiratory syllable data was obtained.

[0191] S512: Based on the latest infant respiratory syllable data, the following formula is used:

[0192]

[0193] Calculate the rate of change V of respiratory syllable rhythm to obtain the results of respiratory rhythm fluctuation trend analysis, where u i |u| represents the interval between the i-th detected respiratory syllables, and U represents the number of detections. i -u i-1 | represents the absolute change in the interval between adjacent respiratory syllables, u i-1 This represents the interval between the previously detected respiratory syllables;

[0194] Based on the latest infant respiratory syllable data, the rate of change in infant respiratory syllable rhythm is calculated. This rate of change reflects the stability of the respiratory rhythm. The calculation requires analyzing each syllable individually. i The changes are as follows: the currently collected respiratory interval data are [0.85s, 0.88s, 0.92s, 0.91s], where:

[0195] u1 = 0.85s;

[0196] u2 = 0.88s;

[0197] u3 = 0.92s;

[0198] u4 = 0.91s;

[0199] Calculate the rate of change for each pair of adjacent time intervals:

[0200]

[0201] Calculate the average rate of change of rhythm:

[0202]

[0203] Assuming that when V is less than 5%, the breathing rhythm is considered stable; otherwise, it is considered to fluctuate significantly, as shown in Table 2.

[0204] Table 5.2 Calculation results of respiratory rhythm change rate

[0205]

[0206] As shown in Table 5.2, the rate of change of respiratory rhythm in this set of data is within a stable range, thus yielding the results of the respiratory rhythm fluctuation trend analysis.

[0207] S513: According to the analysis results of the respiratory rhythm fluctuation trend, if the interval between respiratory syllables is stable, it indicates that the mood is stabilizing and the baby is falling asleep, thus completing the process of putting the baby to sleep.

[0208] Based on the analysis of respiratory rhythm fluctuation trends, if the interval between respiratory syllables is stable, it indicates that the infant's mood is stabilizing and they have entered sleep. In practical applications, this process typically lasts 5-10 minutes. This is combined with other physiological signals of the infant (such as heart rate and body temperature) for comprehensive analysis. Assuming the infant's current heart rate is between 120-140 beats / min and body temperature is between 36.5-37.5℃, the state is considered stable; otherwise, monitoring continues. Based on this, referring to the aforementioned respiratory cycle range [0.8s, 1.5s], further multi-dimensional analysis is performed using physiological indicators. For example, the average sleep respiratory cycle of infants aged 1-6 months is between 0.9s and 1.3s. If a respiratory interval of approximately 1.0s is detected for 5 consecutive minutes, it can be determined that the infant has entered deep sleep. Conversely, if the respiratory interval fluctuates by more than 10%, the monitoring time needs to be extended. In actual calculations, when the infant's respiratory rhythm maintains a change rate of less than 5% within 5 minutes, and the heart rate and body temperature are within the normal range, the infant is considered to have entered sleep, as shown below:

[0209] Monitoring period of 1 minute: respiratory rhythm change rate 3.2%, heart rate 125 beats / min, body temperature 36.8℃ → Continue monitoring;

[0210] Monitoring period of 3 minutes: respiratory rate change rate 3.0%, heart rate 130 beats / min, body temperature 36.7℃ → Continue monitoring;

[0211] Monitoring period of 5 minutes: respiratory rhythm change rate 2.9%, heart rate 128 beats / min, body temperature 36.6℃ → enters sleep state;

[0212] In this situation, the system will stop shaking and confirm that the baby has been put to sleep, thus completing the process of putting the baby to sleep.

[0213] A crib sleep-inducing control system based on environmental simulation includes:

[0214] The crying feature extraction module acquires the crying signal, performs short-time framing processing, calculates the short-time energy value and the short-time energy change rate, extracts energy fluctuation features, determines the syllable boundary position, calculates the syllable interval time, extracts syllable rhythm features, analyzes the changing trend of the syllable interval time sequence, and obtains the crying syllable rhythm change analysis results.

[0215] The comfort needs classification module calculates the mean square error of syllable interval time and the amplitude of short-term energy change rate based on the analysis results of crying syllable rhythm changes, determines the comfort needs, and obtains the comfort needs type classification results;

[0216] The shaking frequency matching module obtains the shaking frequency based on the classification results of the soothing needs type, calculates the phase offset value, judges the degree of matching of the shaking mode, adjusts the shaking frequency, and obtains the adaptive shaking frequency adjustment result.

[0217] The rocking rhythm adjustment module calculates the increase or decrease in rocking frequency based on the adaptive rocking frequency adjustment results, judges the short-term energy trend, adjusts the rocking acceleration, and obtains the dynamically adjusted baby crib rocking rhythm data.

[0218] The sleep state determination module uses dynamically adjusted crib rocking rhythm data to simultaneously emit a hissing sound, acquire the baby's breathing signal, calculate the rate of change of breathing syllable rhythm, determine the baby's sleep state, and complete the baby's sleep-inducing process.

[0219] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A crib soothmg control method based on environmental simulation, characterized in that, The method comprises the following steps: S1: collecting infant crying signal, setting fixed time window, calculating short-time energy change rate between adjacent frames and continuous syllable interval time, analyzing variation trend of syllable interval time sequence, and obtaining crying syllable rhythm change analysis result; S2: based on the crying syllable rhythm change analysis result, judging the stability degree of infant crying rhythm, calculating the variation amplitude of energy change rate, judging the pacification demand, and obtaining pacification demand type classification result; S3: based on the pacification demand type classification result, obtaining the shaking frequency of the current infant bed, calculating the phase offset value between the crying rhythm and the shaking frequency, judging the matching degree of the current shaking mode and adjusting the shaking frequency, and obtaining adaptive shaking frequency adjustment result; S4: based on the adaptive shaking frequency adjustment result, calculating the increment or decrement of the current shaking frequency, dynamically controlling the shaking rhythm of the infant bed, and obtaining the shaking rhythm data of the infant bed after dynamic adjustment; S5: based on the shaking rhythm data of the infant bed after dynamic adjustment, calculating the current infant breathing syllable rhythm change rate and judging the infant sleep condition, and completing the infant lullaby process.

2. The environmental simulation based crib soothmg control method of claim 1, wherein, The crying syllable rhythm change analysis result includes syllable interval time mean square error, syllable rhythm fluctuation amplitude and short-time energy change rate, the pacification demand type classification result includes soothing pacification demand, strong pacification demand and energy fluctuation state record, the adaptive shaking frequency adjustment result includes current shaking frequency, shaking frequency adjustment amplitude and phase offset correction amount, and the shaking rhythm data of the infant bed after dynamic adjustment includes shaking acceleration adjustment value, shaking frequency stability and rhythm synchronization state.

3. The environmental simulation based crib soothmg control method of claim 1, wherein, The specific steps of collecting infant crying signal, setting fixed time window, calculating short-time energy change rate between adjacent frames and continuous syllable interval time, and analyzing variation trend of syllable interval time sequence to obtain crying syllable rhythm change analysis result are as follows: S111: obtaining infant crying signal, performing short-time framing processing on the signal, setting fixed time window, calculating short-time energy value of each frame, calculating short-time energy change rate of adjacent frames according to short-time energy of adjacent frames, calling energy fluctuation characteristics of short-time energy value and short-time energy change rate, and obtaining energy fluctuation characteristics; S112: based on the energy fluctuation characteristics, determining syllable boundary position, calculating continuous syllable interval time, analyzing variation trend according to syllable interval time sequence, and using formula: The syllable interval time variation rate R is calculated to obtain the syllable rhythm feature, wherein T i represents the interval time of the i-th syllable, and N represents the total number of syllables i -T i-1 represents the variation amount of the interval time between adjacent syllables, represents the square sum of the interval times of all syllables S113: based on the syllable rhythm characteristics, analyzing variation trend of syllable interval time sequence, combining syllable interval time variation rate, and obtaining crying syllable rhythm change analysis result.

4. The environmental simulation based crib soothmg control method of claim 1, wherein, The specific steps of judging the stability degree of infant crying rhythm based on the crying syllable rhythm change analysis result, calculating the variation amplitude of energy change rate, judging the pacification demand, and obtaining the pacification demand type classification result are as follows: S211: based on the crying syllable rhythm change analysis result, calculating the mean square error of syllable interval time, judging the syllable stability, and obtaining syllable rhythm stability data; S212: according to the syllable rhythm stability, using formula: The energy change rate variation range M is calculated to obtain energy fluctuation range data, wherein E i Ei represents the energy value of the i-th frame, and n represents the total number of energy frames. i Ei represents the energy value of the i-th frame, and n represents the total number of energy frames. i-1 | represents the energy change amount of adjacent frames, Ei represents the energy value of the i-th frame, and n represents the total number of energy frames. Ei represents the energy value of the i-th frame, and n represents the total number of energy frames. S213: Based on the energy fluctuation amplitude data and the syllable rhythm stability data, classify according to whether the energy fluctuation amplitude is in the stable interval. If it is in the stable interval, it is classified as a soothing demand. If the energy fluctuation amplitude is large and the syllable rhythm stability fluctuates sharply, it is classified as a strong soothing demand. Obtain the soothing demand type classification result.

5. The environmental simulation based crib soothmg control method of claim 1, wherein, Based on the soothing demand type classification result, obtain the rocking frequency of the current baby bed, calculate the phase offset value between the crying rhythm and the rocking frequency, judge the matching degree of the current rocking mode and adjust the rocking frequency, and obtain the specific steps of the adaptive rocking frequency adjustment result: S311: Based on the soothing demand type classification result, obtain the rocking frequency of the current baby bed through the microphone array, call the rocking frequency, and obtain the current rocking mode parameter; S312: Based on the current rocking mode parameter, calculate the phase offset value between the crying rhythm and the rocking frequency, and use the formula: Calculate the phase offset value Φ, obtain the shaking mode matching degree, wherein, f c,i represents the i-th detected crying rhythm frequency, f s,i represents the i-th detected shaking frequency, and J represents the number of detections; S313: According to the rocking mode matching degree, classify according to whether the phase offset value is within the set threshold. If it is within the set threshold, maintain the current rocking mode. If the phase offset value exceeds the threshold range, adjust the rocking frequency to make the crying rhythm and the rocking mode gradually synchronized, and obtain the adaptive rocking frequency adjustment result.

6. The environmental simulation based crib soothmg control method of claim 1, wherein, Based on the adaptive rocking frequency adjustment result, calculate the increase or decrease amount of the current rocking frequency, dynamically control the rocking rhythm of the baby bed, and obtain the dynamic adjustment of the baby bed rocking rhythm data: S411: Based on the adaptive rocking frequency adjustment result, calculate the increase or decrease amount of the current rocking frequency, analyze the change amplitude, and obtain the rocking frequency adjustment amplitude data; S412: Based on the rocking frequency adjustment amplitude data, judge whether the rocking frequency needs to be reduced, and use the formula: calculating short-time energy variation rate AG, analyzing the variation trend of short-time energy, and outputting a short-time energy variation trend record, wherein, G i representing the short-time energy value of the i-th frame, g representing the total number of short-time energy frames, G i-1 representing the short-time energy value of the previous frame, F i representing the current shaking frequency, F0 representing the initial shaking frequency, representing the shaking frequency normalization factor; S413: According to the short-time energy change trend record, if the short-time energy shows a downward trend, reduce the rocking acceleration. If the short-time energy remains stable, maintain the current adjustment result, and obtain the dynamic adjustment of the baby bed rocking rhythm data.

7. The environmental simulation based crib soothmg control method of claim 1, wherein, Based on the dynamic adjustment of the baby bed rocking rhythm data, synchronize the sound of blowing, calculate the current baby breathing syllable rhythm change rate and judge the baby sleep situation, and complete the baby lullaby process: S511: Based on the dynamic adjustment of the baby bed rocking rhythm data, collect the latest baby breathing signal and obtain the latest baby breathing syllable data; S512: According to the latest baby breathing syllable data, use the formula: A respiratory sound interval variation rate V is calculated, and a respiratory rhythm fluctuation trend analysis result is obtained, wherein u i represents the interval time of the i-th detected respiratory sound, u represents the number of detections, and |u i -u i-1 represents the absolute variation amount of the interval time of adjacent respiratory sounds, u i-1 represents the interval time of the respiratory sound detected last time; S513: According to the breathing rhythm fluctuation trend analysis result, if the breathing syllable interval time is stable, it indicates that the mood tends to be stable and enters sleep, and the baby lullaby process is completed.

8. A crib soothmg control system based on environmental simulation, characterized in that, The system is used to execute the method of any one of claims 1-7, comprising: The crying feature extraction module obtains the crying signal, performs short-time framing processing, calculates the short-time energy value and the short-time energy change rate, extracts the energy fluctuation feature, judges the syllable boundary position, calculates the syllable interval time, extracts the syllable rhythm feature, analyzes the change trend of the syllable interval time sequence, and obtains the crying syllable rhythm change analysis result; The soothing demand classification module calculates the syllable interval time mean square error and the short-time energy change rate variation amplitude based on the syllable rhythm change analysis result, judges the soothing demand, and obtains a soothing demand type classification result; The shaking frequency matching module obtains a shaking frequency based on the soothing demand type classification result, calculates a phase offset value, judges a shaking mode matching degree, adjusts the shaking frequency, and obtains an adaptive shaking frequency adjustment result; The shaking rhythm adjustment module calculates a shaking frequency increase / decrease amount based on the adaptive shaking frequency adjustment result, judges a short-time energy trend, adjusts a shaking acceleration, and obtains dynamic adjustment after the baby bed shaking rhythm data; The sleep state judgment module synchronously issues a hushing sound based on the dynamic adjustment after the baby bed shaking rhythm data, obtains a baby breathing signal, calculates a breathing syllable rhythm change rate, judges a baby sleep state, and completes a baby lulling process.

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