Adjusting method, system and equipment of sleep aiding bed and storage medium

Abstract

The invention relates to the technical field of sleep-aiding beds, in particular to an adjusting method, system and equipment of a sleep-aiding bed and a storage medium. Performing filtering processing on the user sleep sound signal data according to a spectral subtraction method and the initial sound reception data; analyzing the filtered signal data according to a preset Fourier transform algorithm and a preset time sequence change rule condition to obtain a snoring grade; analyzing the barycentric coordinates of the mattress according to a preset mattress length and a preset mattress width to obtain an initial sleeping posture analysis result; generating a first snore stopping bending block adjusting angle and a second snore stopping bending block adjusting angle according to the initial sleeping posture analysis result and the snore grade; according to the scheme, noise is removed through spectral subtraction filtering, the snoring grade is generated through Fourier transform and time sequence analysis, the sleeping posture is judged through the gravity center of the mattress, the two parts are fused to generate the bending block adjusting angle and the adjusting instruction, dual adaptation of the body position and the strength is achieved, the snoring stopping efficiency is improved, the sleep interruption rate of a user is reduced, and the experience is optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sleep-aiding beds, and in particular to a sleep-aiding bed adjustment method, system, device and storage medium. BACKGROUND

[0002] In the prior art, when processing sleep sound, the intelligent snoring stopping system often mixes other sounds in the environment, resulting in inaccurate judgment of snoring sound, and easily misjudging external noise as snoring or missing the actual snoring sound. When judging the sleep posture, only simple sensing information is relied on, and the actual size of the mattress is not combined to determine the body position, so that the judgment of the sleep posture is relatively rough and cannot reflect the specific posture of the body in detail. When stopping snoring adjustment, the adjustment method is single and cannot be flexibly adjusted according to the severity of snoring and the specific sleep posture. The adjustment angle is often fixed, or the adjustment force is not enough to effectively stop snoring, or the adjustment is too large to interfere with the user's sleep, which is difficult to achieve the ideal snoring stopping effect and affects the user's sleep quality. SUMMARY

[0003] In order to overcome the shortcomings of the prior art, the purpose of the present application is to provide a sleep-aiding bed adjustment method, system, device and storage medium.

[0004] A sleep-aiding bed adjustment method is applied to a sleep-aiding bed adjustment system. The sleep-aiding bed includes a mattress, a pillow, a first snoring stopping bending block and a second snoring stopping bending block. The pillow is arranged on the mattress, and the first snoring stopping bending block and the second snoring stopping bending block are arranged on the pillow. The sleep-aiding bed adjustment method includes the following steps: obtaining initial sound collection data and user sleep sound signal data; filtering the user sleep sound signal data according to a spectral subtraction method and the initial sound collection data to obtain filtered signal data; analyzing the filtered signal data according to a preset Fourier transform algorithm and a preset time sequence change rule condition to obtain a snoring level; obtaining a mattress gravity center coordinate; analyzing the mattress gravity center coordinate according to a preset mattress length and a preset mattress width to obtain an initial sleep posture analysis result; generating a first snoring stopping bending block adjustment angle and a second snoring stopping bending block adjustment angle according to the initial sleep posture analysis result and the snoring level; and generating a pillow adjustment instruction according to the first snoring stopping bending block adjustment angle and the second snoring stopping bending block adjustment angle.

[0005] Further, the filtering processing of the user sleep sound signal data according to the spectral subtraction method and the initial sound data to obtain the filtered signal data comprises: performing statistical analysis on the initial sound data according to a preset sampling frequency and a preset discrete time sequence to obtain power spectrum statistical characteristics; generating an over subtraction factor according to the power spectrum statistical characteristics, a preset noise estimation window and a preset historical signal-to-noise ratio; and filtering processing the user sleep sound signal data according to the spectral subtraction method, a preset high sensitivity characteristic and the over subtraction factor to obtain the filtered signal data.

[0006] Further, the analysis of the filtered signal data according to a preset Fourier transform algorithm and a preset time sequence change rule condition to obtain the snoring level comprises: dividing the filtered signal data according to a preset time interval to obtain a plurality of short frame signal data; performing feature extraction on the plurality of short frame signal data according to the Fourier transform algorithm to obtain frequency spectrum signal features; performing comparative analysis on the frequency spectrum signal features according to a preset snoring frequency band range and a preset amplitude range to obtain a comparative analysis result; when the comparative analysis result is that the frequency spectrum signal features satisfy the snoring frequency band range and the amplitude range, performing periodic analysis on the plurality of short frame signal data to obtain time domain signal features; performing rule analysis on the time domain signal features according to the time sequence change rule condition to obtain a rule analysis result; and when the rule analysis result is that the time sequence change rule condition is satisfied, the frequency spectrum signal features and the time domain signal features generate the snoring level.

[0007] Further, the analysis of the filtered signal data according to a preset Fourier transform algorithm and a preset time sequence change rule condition to obtain the snoring level comprises: dividing the filtered signal data according to a preset time interval to obtain a plurality of short frame signal data; performing feature extraction on the plurality of short frame signal data according to the Fourier transform algorithm to obtain frequency spectrum signal features; performing comparative analysis on the frequency spectrum signal features according to a preset snoring frequency band range and a preset amplitude range to obtain a comparative analysis result; when the comparative analysis result is that the frequency spectrum signal features satisfy the snoring frequency band range and the amplitude range, performing periodic analysis on the plurality of short frame signal data to obtain time domain signal features; performing rule analysis on the time domain signal features according to the time sequence change rule condition to obtain a rule analysis result; and when the rule analysis result is that the time sequence change rule condition is satisfied, the frequency spectrum signal features and the time domain signal features generate the snoring level.

[0008] Further, the mattress center of gravity coordinates are analyzed according to the preset mattress length and the preset mattress width to obtain an initial sleep posture analysis result, including: a first range is calculated according to the mattress length, a preset first weight coefficient and a preset second weight coefficient; a second range is calculated according to the mattress width, a preset third weight coefficient and a preset fourth weight coefficient; a center of gravity horizontal coordinate and a center of gravity vertical coordinate are obtained from the mattress center of gravity coordinates; it is judged whether the center of gravity horizontal coordinate is within the first range and whether the center of gravity vertical coordinate is within the second range; when the center of gravity horizontal coordinate is within the first range and the center of gravity vertical coordinate is within the second range, a supine posture analysis result is generated; the initial sleep posture analysis result is generated according to the supine posture analysis result; a third range is calculated according to the mattress length, a preset fifth weight coefficient and a preset sixth weight coefficient; it is judged whether the center of gravity horizontal coordinate is within the third range; when the center of gravity horizontal coordinate is within the third range, a left lateral posture analysis result is generated; the initial sleep posture analysis result is generated according to the left lateral posture analysis result; a fourth range is calculated according to the mattress length, a preset seventh weight coefficient and a preset eighth weight coefficient; it is judged whether the center of gravity horizontal coordinate is within the fourth range; when the center of gravity horizontal coordinate is within the fourth range, a right lateral posture analysis result is generated; the initial sleep posture analysis result is generated according to the right lateral posture analysis result.

[0009] Further, the first snore-preventing bending block is provided with a first air bag, and the second snore-preventing bending block is provided with a second air bag, and the first snore-preventing bending block adjustment angle and the second snore-preventing bending block adjustment angle are generated according to the initial sleep posture analysis result and the snoring level, including: a target pressure adjustment value is generated according to the snoring level and a preset intervention sensitivity level; a first current air bag pressure is obtained, and a first air bag pressure adjustment amount is generated according to the target pressure adjustment value and the first current air bag pressure; a second current air bag pressure is obtained, and a second air bag pressure adjustment amount is generated according to the target pressure adjustment value and the second current air bag pressure; air bag material data and air bag elastic coefficient are obtained; a height conversion coefficient is generated according to a preset air bag pressure bearing range, the air bag material data and the air bag elastic coefficient; the first snore-preventing bending block adjustment angle is generated according to the first air bag pressure adjustment amount, the initial sleep posture analysis result, a preset bending block height and the height conversion coefficient; the second snore-preventing bending block adjustment angle is generated according to the second air bag pressure adjustment amount, the initial sleep posture analysis result, the preset bending block height and the height conversion coefficient.

[0010] Further, the generating the height conversion coefficient according to the preset air bag air pressure bearing range, air bag material data and air bag elastic coefficient comprises: obtaining a safe air pressure upper limit value and a safe air pressure lower limit value from the air bag air pressure bearing range; calculating the difference between the safe air pressure upper limit value and the safe air pressure lower limit value to obtain a safe air pressure difference; obtaining a plurality of discrete air pressure values from the air bag air pressure bearing range; generating a theoretical coefficient according to the plurality of discrete air pressure values and the safe air pressure difference; obtaining air bag use frequency data, and compensating the air bag elastic coefficient according to a preset compensation formula, the theoretical coefficient and the air bag use frequency data to obtain a compensated elastic coefficient; and generating the height conversion coefficient according to the air bag material data and the compensated elastic coefficient.

[0011] Further, a sleep-aiding bed adjusting system comprises a control system and a mattress, a pillow, a first snore-stopping bending block and a second snore-stopping bending block electrically connected to the control system; the control system is used for executing the sleep-aiding bed adjusting method in any one of the above.

[0012] Further, the present application provides a sleep-aiding bed adjusting device, which comprises a memory and at least one processor, and the memory stores instructions; the at least one processor invokes the instructions in the memory to make the computer device execute the steps of the sleep-aiding bed adjusting method in any one of the above.

[0013] Further, the present application provides a computer readable storage medium, which stores instructions, and the instructions are executed by a processor to implement the steps of the sleep-aiding bed adjusting method in any one of the above.

[0014] In the technical scheme of the present application, the background noise is filtered out based on the spectral subtraction method and the initial radio data, a high signal-to-noise ratio filtered signal is output, non-snoring sound interference is effectively avoided; the filtered signal is analyzed in combination with the Fourier transform and the time sequence rule, incidental interference such as turning over is excluded, a snoring grade is generated, and the severity of the user's snoring is quantified; the sleeping posture such as supine and lateral recumbency is determined through the center of gravity coordinates of the mattress, and the body position characteristics of the user are determined; finally, the bending block adjustment angle is generated by fusing the sleeping posture and the snoring grade, and is converted into a pillow adjustment instruction to realize differentiated adjustment, so that the dual adaptation of the body position and the intensity is achieved, the effective rate of snore stopping is effectively improved in the whole process, the sleep interruption rate is reduced, and the user experience is optimized. BRIEF DESCRIPTION OF DRAWINGS

[0015] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the description of the embodiments, taken in conjunction with the following drawings in which: Figure 1 A first flowchart of a sleep-aiding bed adjusting method provided by the embodiments of the present application; Figure 2 A second flowchart of a sleep-aiding bed adjusting method provided by an embodiment of the present application; Figure 3 A third flowchart of a sleep-aiding bed adjusting method provided by an embodiment of the present application; Figure 4 A fourth flowchart of a sleep-aiding bed adjusting method provided by an embodiment of the present application; Figure 5 A fifth flowchart of a sleep-aiding bed adjusting method provided by an embodiment of the present application; Figure 6 A sixth flowchart of a sleep-aiding bed adjusting method provided by an embodiment of the present application; Figure 7 A seventh flowchart of a sleep-aiding bed adjusting method provided by an embodiment of the present application; Figure 8 A structural schematic diagram of a sleep-aiding bed adjusting system provided by an embodiment of the present application; Figure 9 A structural schematic diagram of a sleep-aiding bed adjusting device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0016] The terms "first", "second", "third", "fourth" and the like in the description and claims of the present application, and above-described drawings, if any, are used to distinguish between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of these terms herein is to be construed to cover the recurrence of ordinal terms throughout the specification and claims of this patent application unless the context of the recitation dictates otherwise. Furthermore, the terms "comprising", "having", "containing", and "including" or any variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, product, or apparatus that comprises, has, contains or includes a list of elements is not necessarily limited to those elements, but can include other elements not expressly listed or inherent to such process, method, system, product, or apparatus.

[0017] A sleep-aiding bed adjusting method applied to a sleep-aiding bed adjusting system, the sleep-aiding bed comprising a mattress, a pillow, a first snore-preventing bending block and a second snore-preventing bending block, the pillow being arranged on the mattress, and the first snore-preventing bending block and the second snore-preventing bending block being arranged on the pillow; for the convenience of understanding, the specific flow of an embodiment of the present application is described below, please refer to Figure 1 An embodiment of a sleep-aiding bed adjusting method in the embodiment of the present application comprises: 101, obtaining initial sound collecting data and user sleep sound signal data; In the embodiment, by adopting two omnidirectional microphones, environmental data (initial sound collection data), user sleep sound (placed on both sides of the pillow, sampling frequency 44.1 kHz, 16-bit quantization), and environmental background sound (placed on the bedside, sampling frequency 44.1 kHz) are collected respectively. 102. Filtering the user sleep sound signal data according to the spectral subtraction method and the initial sound collection data to obtain filtered signal data; In the embodiment, the spectral subtraction method is applied to filter out the noise components (such as background noise) in the user sleep sound signal, retain effective signals such as snoring sound, and output filtered signal data with high signal-to-noise ratio. 103. Analyzing the filtered signal data according to the preset Fourier transform algorithm and the preset time sequence variation condition to obtain a snoring level. In the embodiment, the signal validity is verified in combination with the preset time sequence variation condition (such as continuous frame period stability and amplitude fluctuation range), and incidental interference (such as turning over sound) is excluded, and finally a 1-5 level snoring level is generated to quantify the severity of snoring. 104. Obtaining the mattress barycenter coordinates. 105. Analyzing the mattress barycenter coordinates according to the preset mattress length and the preset mattress width to obtain an initial sleep posture analysis result. In the embodiment, the initial sleep posture analysis result is generated by combining the preset mattress length and width parameters through coordinate range determination (such as the barycenter located in the central area for supine, and deviated to the left side for left lateral position), and the current body position characteristics of the user are determined. 106. Generating a first snoring stop bending block adjustment angle and a second snoring stop bending block adjustment angle according to the initial sleep posture analysis result and the snoring level. 107. Generating a pillow adjustment instruction according to the first snoring stop bending block adjustment angle and the second snoring stop bending block adjustment angle. In the embodiment, the angle parameters are converted into pillow adjustment instructions to drive the mechanical structure to perform differentiated adjustment, realizing dual intervention of body position adaptation and intensity adaptation. In the embodiment, the background noise is filtered out by the spectral subtraction method and the initial sound collection data, and the filtered signal with high signal-to-noise ratio is output, effectively avoiding non-snoring sound interference; the filtered signal is analyzed in combination with the Fourier transform and the time sequence rule to exclude incidental interference such as turning over, and the snoring level is generated to quantify the severity of the user's snoring; the sleep posture such as supine and lateral position is determined through the mattress barycenter coordinates to determine the user's body position characteristics; finally, the bending block adjustment angle is generated by combining the sleep posture and the snoring level, and is converted into a pillow adjustment instruction to realize differentiated adjustment, achieving dual adaptation of body position and intensity, effectively improving the snoring stop efficiency, reducing the sleep interruption rate, and optimizing the user experience. Please refer to Figure 2A second embodiment of the adjusting method of the sleep-aiding bed in the embodiment of the present application comprises: 201. Perform statistical analysis on the initial sound data according to the preset sampling frequency and the preset discrete time sequence to obtain power spectrum statistical characteristics; In this embodiment, the continuous audio signal (initial sound data) is converted into a discrete point sequence by the sampling frequency and the discrete time sequence, and then statistical analysis is performed to obtain the power spectrum statistical characteristics; 202. Generate an over-reduction factor according to the power spectrum statistical characteristics, a preset noise estimation window and a preset historical signal-to-noise ratio; In this embodiment, the over-reduction factor is a key parameter for controlling the spectrum reduction intensity; 203. Perform filtering processing on the user sleep sound signal data according to the spectrum reduction method, the preset high sensitivity characteristics and the over-reduction factor to obtain filtered signal data; In this embodiment, an improved spectrum reduction method is used to eliminate environmental noise, and the processing formula is: wherein, is the over-reduction factor (value 1.2-1.5, dynamically adjusted according to the noise intensity), represents a spectrum reduction processing function of the noise signal data, is a spectrum processing function of the denoised signal data, is a spectrum processing function of the noisy original signal (user sleep sound signal data), and the processed signal is band-pass filtered according to the high sensitivity characteristics to maintain the breathing and snoring related frequency band; In this embodiment, the initial sound data is converted by the sampling frequency and the discrete time sequence and statistically analyzed to obtain the power spectrum statistical characteristics, which lays the foundation for subsequent processing; a dynamic over-reduction factor is generated according to the characteristics, the noise estimation window and the historical signal-to-noise ratio, which flexibly adapts to the noise intensity and balances noise reduction and signal preservation; an improved spectrum reduction method is used in combination with the high sensitivity characteristics and the over-reduction factor filtering, which not only effectively eliminates environmental noise by the formula, but also maintains the key frequency band of breathing and snoring through band-pass filtering, improves the signal purity, provides high-quality data for subsequent snoring grade determination and snoring adjustment, makes noise suppression more accurate and signal feature preservation more complete, and helps the intelligent snoring suppression system to operate efficiently, optimizes the user sleep monitoring and intervention experience.

[0018] Please refer to Figure 3 A third embodiment of the adjusting method of the sleep-aiding bed in the embodiment of the present application comprises: 301. Divide the filtered signal data according to a preset time interval to obtain a plurality of short frame signal data; In the embodiment, the time interval (such as 20 ms / frame, overlap rate 50%) is used to segment the filtered signal data, the frame design ensures the stability of the frequency characteristics of the single frame signal, and the overlap rate avoids the loss of information between frames, thereby providing a structured input for subsequent feature extraction. 302. Feature extraction is performed on the plurality of short frame signal data according to the Fourier transform algorithm to obtain a frequency spectrum signal feature. In the embodiment, the energy peak frequency in the 50-1000 Hz (typical frequency band of snoring sound) of the plurality of short frame signal data is calculated to reflect the main frequency component of the snoring sound, the proportion of the energy in the frequency band to the total signal energy (such as ≥60% is considered valid) is calculated, and the frequency spectrum signal feature is extracted by the Fourier transform algorithm. 303. The frequency spectrum signal feature is compared and analyzed according to the preset snoring sound frequency band range and the preset amplitude range to obtain a comparison and analysis result. 304. When the comparison and analysis result is that the frequency spectrum signal feature meets the snoring sound frequency band range and the amplitude range, periodic analysis is performed on the plurality of short frame signal data to obtain a time domain signal feature. In the embodiment, the snoring sound frequency band range is limited to 50-1000 Hz; the amplitude range is set to have a lower limit (such as 3 dB higher than the background noise); this step is a step of judging valid snoring sound frames based on a preset threshold, which is used to verify the frequency spectrum signal feature extraction result, and if the range requirement is not met, the feature extraction is performed on the plurality of short frame signal data according to the Fourier transform algorithm again. 305. Regularity analysis is performed on the time domain signal feature according to a time sequence change rule to obtain a regularity analysis result. In the embodiment, the time domain feature is verified according to the time sequence change rule (such as 5 consecutive frame periods are stable, and the amplitude fluctuation is ≤30%), if the rule is met, the frequency spectrum feature (main frequency intensity, energy proportion) and the time domain feature (periodic stability, duration) are fused to generate a 1-5 level snoring level (the level increases with the energy, duration, and periodic stability); if the rule is not met (such as a burst single frame signal), it is determined as an interference, and no level is generated. 306. When the regularity analysis result meets the time sequence change rule, the frequency spectrum signal feature and the time domain signal feature generate a snoring level. In this embodiment, the filtered signal is segmented into short frames by time intervals to ensure stable frequency characteristics and avoid information loss. Fourier transform is used to extract spectral signal features, and valid frames are selected by combining preset snoring frequency bands and amplitude ranges. If the frames do not meet the criteria, they are re-extracted to improve feature reliability. Periodic analysis is performed on the frames that meet the criteria to obtain time-domain features, and then the features are verified according to the time sequence. The spectral and time-domain features are fused to generate a snoring level, which increases with energy, duration, etc. This process can identify valid snoring, eliminate interference, and scientifically classify the levels, providing a basis for subsequent anti-snoring intervention, reducing ineffective adjustments, and improving the user's sleep monitoring and intervention experience.

[0019] Please see Figure 4 A fourth embodiment of a method for adjusting a sleep-aid bed according to the present invention includes: 401. When the result of the pattern analysis meets the condition of time-series change, a snoring signal is generated based on the characteristics of the spectral signal and the characteristics of the time-domain signal. In this embodiment, when the results of the time-domain feature regularity analysis meet the time-series change regularity condition, the system determines that the signal has "periodic and continuous characteristics of snoring", and officially marks the signal that has passed the spectrum screening and time-domain verification as a snoring signal, ensuring that the output signal is a real and effective snoring event; 402. Analyze the snoring signal according to the preset frequency band energy range to obtain the number of snoring events and the average amplitude; In this embodiment, an energy mutation detection algorithm is used (e.g., a short-term energy exceeding the frequency band energy range and lasting ≥0.5 seconds is determined as an event), the number of snoring events N within a unit time (e.g., 10 minutes) is counted, and then the average amplitude of each snoring event in the core frequency band is calculated. 403. A snoring level is generated based on the number of snoring events and the average amplitude; In this embodiment, a snoring level of 1-5 is generated by fusing the number of snoring events N with the average amplitude, and the specific corresponding rules are as follows: Level 1 (Mild Snoring): Number of snoring events within 10 minutes The snoring is frequent and the average amplitude is 3-5 dB of the background noise (such as the volume of a soft everyday voice). The snoring intervals are long and the intensity is low, so it has minimal impact on sleep. Level 2 (mild snoring): within 10 minutes The average amplitude is 6-8 dB of the background noise (such as the volume of normal conversation). The snoring has a certain periodicity, but the duration of each snoring is short (≤2 seconds). Level 3 (Moderate Snoring): Within 10 minutes The snoring is continuous and regular, with an average amplitude of 9-12 dB of background noise (such as a medium volume indoor TV). Each snoring episode lasts 2-3 seconds and may involve slight obstruction of airflow. Level 4 (Heavy snoring): Within 10 minutes Each instance has an average amplitude of 13-15 dB of background noise (such as the volume of loud talking), and the snoring is dense and intense, lasting 3-5 seconds per instance, accompanied by obvious airway vibration; Level 5 (Severe snoring): Within 10 minutes If the average amplitude is ≥16dB of background noise (such as the volume of a shout at close range), the snoring is continuous without obvious intervals, and each episode lasts ≥5 seconds, there is a risk of sleep apnea. In this embodiment, a snoring signal is generated by fusing spectral and temporal features, and a dual verification mechanism is used to ensure the signal is authentic and effective, reducing the false positive rate. Based on a preset frequency band energy range, the number of snoring events and the average amplitude are statistically analyzed to achieve quantitative analysis of snoring events. The two are then fused to generate a 1-5 level snoring rating, which takes into account both frequency and intensity and reflects the actual severity of snoring. This provides a basis for subsequent anti-snoring intervention, making the adjustment more targeted, reducing the interference of ineffective interventions on sleep, improving the efficiency of anti-snoring and user experience, and providing reliable data support for sleep health monitoring.

[0020] Please see Figure 5 A fifth embodiment of a method for adjusting a sleep-aid bed according to the present invention includes: 501. The first range is calculated based on the mattress length, the preset first weighting coefficient, and the preset second weighting coefficient; In this embodiment, the first range (supine horizontal coordinate range): formula: ,in This is the first weighting coefficient (e.g., 0.4). As the second weighting factor (e.g., 0.6), for example, when the mattress length (L=200cm), ( =[80cm,120cm]), corresponding to the middle area along the length of the mattress; 502. The second range is calculated based on the mattress width, the preset third weighting coefficient, and the preset fourth weighting coefficient; In this embodiment, the second range (supine longitudinal coordinate range): formula: ,in, This is the third weighting coefficient (e.g., 0.4). This is the fourth weighting factor (e.g., 0.6); for example, when the mattress width W = 150cm, This corresponds to the middle area along the width of the mattress; 503. Obtain the x-coordinate and y-coordinate of the center of gravity from the mattress's center of gravity coordinate system; 504. Determine whether the x-coordinate of the centroid is within the first range and whether the y-coordinate of the centroid is within the second range; 505、When the barycentric abscissa is in the first range and the barycentric ordinate is in the second range, a supine posture analysis result is generated; 506、The initial sleep posture analysis result is generated according to the supine posture analysis result; 507、The third range is calculated according to the mattress length, the preset fifth weight coefficient and the preset sixth weight coefficient; 508、It is judged whether the barycentric abscissa is in the third range; 509、When the barycentric abscissa is in the third range, a left lateral posture analysis result is generated; In the embodiment, the third range (left lateral abscissa range) is: formula: , wherein is the fifth weight coefficient (such as 0.3), for example, when L=200cm, =[0, 60cm]), corresponding to the left area in the mattress length direction; 510、The initial sleep posture analysis result is generated according to the left lateral posture analysis result; 511、The fourth range is calculated according to the mattress length, the preset seventh weight coefficient and the preset eighth weight coefficient; 512、It is judged whether the barycentric abscissa is in the fourth range; 513、When the barycentric abscissa is in the fourth range, a right lateral posture analysis result is generated; In the embodiment, the fourth range (right lateral abscissa range) is: formula: , wherein is the sixth weight coefficient (such as 0.7), for example, when L=200cm, =[140cm, 200cm]), corresponding to the right area in the mattress length direction; the weight coefficient to can be dynamically adjusted according to the mattress size, the user's body type (such as adult / child); 514、The initial sleep posture analysis result is generated according to the right lateral posture analysis result; In the embodiment, the initial sleep posture analysis result (such as clear supine / left lateral) can directly drive the snoring prevention strategy: a larger angle of pillow bending is required when supine (because supine is prone to snoring), and the adjustment amplitude can be reduced when left lateral (lateral can alleviate snoring), the association mechanism of such sleep posture adjustment improves the effectiveness of snoring prevention intervention, and avoids user wake-up caused by blind adjustment; In the embodiment, the sleep posture analysis mechanism provides a scientific basis for personalized snoring intervention, improves the effectiveness of intervention and user comfort, and the core advantage is to dynamically determine the sleep posture area based on the mattress size: the middle area of supine is determined by combining the mattress length and the weight coefficient, the lateral range is determined according to the width parameter, and the horizontal coordinate interval of left and right lateral positions is divided by differentiating the weight, and the weight can be adapted to the mattress size and user body size for flexible adjustment; This partitioning logic can identify postures such as supine, left and right lateral positions, and provide clear guidance for subsequent intervention strategies; For the supine state prone to snoring, a larger angle pillow is started to bend, and the lateral position is reduced to avoid discomfort; By directly associating sleep posture analysis with snoring intervention, the user's wake-up caused by blind adjustment is effectively avoided, and on-demand intervention is realized, which fundamentally improves the adaptability and user experience safety of snoring intervention.

[0021] The first snoring prevention bending block is provided with a first air bag, and the second snoring prevention bending block is provided with a second air bag, Please refer to Figure 6 The sixth embodiment of the adjusting method of the sleep-aiding bed in the embodiment of the present application comprises: 601. generating a target pressure adjustment value according to the snoring level and a preset intervention sensitivity level; In the embodiment, based on the snoring level (1-5 levels) and the intervention sensitivity level (such as high / medium / low three levels), the target pressure adjustment value is calculated by a weighted model, Formula: , wherein, is a sensitivity coefficient, is the intervention sensitivity level (high sensitivity takes 1.2, medium sensitivity takes 1.0, and low sensitivity takes 0.8), and the specific intervention sensitivity level is determined according to the snoring level; The snoring level (reflecting the severity of snoring) and the intervention sensitivity level (reflecting the user's tolerance) are associated by the weighted model to generate a target pressure adjustment value that adapts to individual needs, adapts to the depth of sleep of different users (such as low sensitivity for light sleepers to avoid wake-up), and improves the individualization and safety of intervention; 602. obtaining a first current air bag pressure, and generating a first air bag pressure adjustment amount according to the target pressure adjustment value and the first current air bag pressure; In the embodiment, the first air bag adjustment amount: , (wherein, is the first current air bag pressure), realizing "on-demand adjustment": if the current pressure is close to the target value, only a small adjustment is needed to avoid excessive inflation / deflation of the air bag; Provide a quantitative basis for independent control of single-sided air bags (such as left side), adapt to the difference between left and right sleep positions (such as adjusting the right air bag when lying on the left side; 603、obtain a second current air bag pressure, and generate a second air bag pressure adjustment amount according to the target pressure adjustment value and the second current air bag pressure; In this embodiment, the first air bag adjustment amount: , is the second current air bag pressure, supports independent adjustment of the double air bags, solves the problem of "left-right imbalance" in traditional single air bag adjustment (for example, when the right side snores more severely, the pressure on the right side can be increased alone), and lays a foundation for subsequent differential angle control of the left and right bending blocks, thereby improving the accuracy of snoring intervention; 604、obtain air bag material data and air bag elasticity coefficient; 605、generate a height conversion coefficient according to a preset air bag pressure bearing range, air bag material data and air bag elasticity coefficient; In this embodiment, by introducing the air pressure bearing range as a constraint, the risk of air bag rupture caused by overpressure inflation is prevented, and the system safety is improved; 606、generate a first snoring prevention bending block adjustment angle according to the first air bag pressure adjustment amount, the initial sleep posture analysis result, the preset bending block height and the height conversion coefficient; In this embodiment, the first snoring prevention bending block adjustment angle: , is the preset bending block height, is the preset fulcrum distance, is a sleep posture correction coefficient (1.2 for supine position, 0.8 for lateral position, to adapt to the intervention needs of different body positions), is the first snoring prevention bending block adjustment angle; 607、generate a second snoring prevention bending block adjustment angle according to the second air bag pressure adjustment amount, the initial sleep posture analysis result, the preset bending block height and the height conversion coefficient; In this embodiment, the first snoring prevention bending block adjustment angle: , is the second snoring prevention bending block adjustment angle, which needs to be larger when the user is in supine position to open the airway, and needs to be smaller when the user is in lateral position to avoid discomfort; In this embodiment, the target pressure adjustment value is generated by fusing the snoring grade and the intervention sensitivity grade, to adapt to different user sleep depth and snoring severity, improve the intervention individualization and safety; the independent adjustment amount of the double air bags is calculated based on the current air bag pressure, to realize on-demand adjustment and avoid excessive action, and to lay a foundation for differential angle control. The height conversion coefficient is generated by combining the air bag material, elasticity coefficient and air pressure bearing range, to prevent overpressure risk and ensure system safety; and the angles of the double bending blocks are calculated by fusing the adjustment amount, sleep posture result and other parameters, to adapt to the body position demand through the sleep posture correction coefficient, to ensure that the airway is effectively opened when the user is in supine position and discomfort is reduced when the user is in lateral position, so as to make the snoring intervention accurate and individualized, and significantly improve the snoring prevention effect and user experience.

[0022] Referring to Figure 7 , the seventh embodiment of the adjusting method of the sleep-aiding bed in the present application includes: 701. Obtain the upper limit value and the lower limit value of the safe air pressure from the air bag air pressure bearing range; In this embodiment, the upper limit value of the safe air pressure is explicitly defined as the maximum pressure at which the air bag is not at risk of rupture (e.g., 15 kPa), and the lower limit value of the safe air pressure is explicitly defined as the pressure at which the air bag is not at risk of support failure due to excessive deflation (e.g., 2 kPa); 702. Calculate the difference between the upper limit value and the lower limit value of the safe air pressure to obtain the safe air pressure difference; In this embodiment, the safe air pressure difference serves as the reference range for subsequent air pressure sampling and coefficient calculation; 703. Randomly obtain multiple discrete air pressure values from the air bag air pressure bearing range; In this embodiment, multiple discrete air pressure values (e.g., 5 points: 3 kPa, 6 kPa, 9 kPa, 12 kPa, and 14 kPa) are randomly selected within the range of 2 kPa to 15 kPa, covering the commonly used pressure interval of the air bag; 704. Generate the theoretical coefficient based on the multiple discrete air pressure values and the safe air pressure difference; In this embodiment, the corresponding air bag height change is tested for each discrete air pressure value, and the theoretical coefficient is calculated through the calculation formula; The calculation formula of the theoretical coefficient is as follows: , where h is the height change corresponding to the i-th air pressure value, and Δpi is the difference between the i-th air pressure value and the previous point, ensuring that the theoretical coefficient reflects the basic conversion relationship between air pressure and height; 705. Obtain the air bag usage frequency data and perform aging compensation on the air bag elastic coefficient based on the preset compensation formula, the theoretical coefficient, and the air bag usage frequency data to obtain the compensated elastic coefficient; In this embodiment, after the air bag is used N times, the elastic coefficient k will increase due to fatigue (expansion ability decreases, k decreases), and the compensation formula k(N) = k(0) * (1 - N / 1000) is used to compensate for the decrease in the elastic coefficient; (1- ), where k(0) is the initial elastic coefficient, and N / 1000 is the aging coefficient, which increases with the longer the air bag is used; 706. Generate the height conversion coefficient based on the air bag material data and the compensated elastic coefficient; In this embodiment, the expression of the height conversion coefficient is as follows: ​​​​​, wherein, is a preset material density coefficient, used to ensure accurately reflects the pressure height conversion characteristics of the current air bag; is air bag material data, is a height conversion coefficient; In this embodiment, by explicitly defining the upper and lower limits of the safety air pressure, the risk-free working range of the air bag is determined, and the safety air pressure difference is calculated to provide a stable basis for subsequent parameter calculation, effectively avoiding the risk of overpressure damage; within the safety range, discrete air pressure values are randomly extracted to cover the commonly used range, and the height change data is modeled by a theoretical coefficient formula to ensure the accuracy of the air pressure height conversion relationship; for the aging problem of the air bag, the elastic coefficient is dynamically corrected according to the number of uses and a preset compensation formula to offset the performance degradation caused by fatigue and prolong the effective life of the device; finally, the height conversion coefficient is generated by integrating the material data and the compensation elastic coefficient, which is suitable for different material characteristics and ensures the accuracy of the pressure height conversion; The overall scheme improves the safety, accuracy and long-term stability of the air bag adjustment, and provides core parameter support for the reliable operation of the intelligent snore stopping system.

[0023] The above describes a method for adjusting a sleep-aiding bed in an embodiment of the present application, and the following describes a sleep-aiding bed adjustment system in an embodiment of the present application, please refer to Figure 8 The sleep-aiding bed adjustment system comprises a control system 1 and a mattress 2, a pillow 3, a first snore-stopping bending block 4 and a second snore-stopping bending block 5 electrically connected to the control system; the control system is used to execute the sleep-aiding bed adjustment method described in any one of the above.

[0024] In this embodiment, based on the spectral subtraction method and the initial sound data, the background noise is filtered out, a high signal-to-noise ratio filtered signal is output, and non-snoring sound interference is effectively avoided; the filtered signal is analyzed in combination with Fourier transform and time sequence rules to exclude incidental interference such as turning over, and a snoring grade is generated to quantify the severity of the user's snoring; the sleeping posture such as supine and lateral recumbency is determined by the mattress barycenter coordinates, and the user's body position characteristics are determined; finally, the bending block adjustment angle is generated by combining the sleeping posture and the snoring grade, which is converted into a pillow adjustment instruction to realize differentiated adjustment, achieving dual adaptation of body position and intensity, effectively improving the snore stopping efficiency, reducing the sleep interruption rate, and optimizing the user experience. Figure 9is a structural schematic diagram of an adjusting device of a sleep-aiding bed provided by an embodiment of the present application. The adjusting device of a sleep-aiding bed 900 can have great differences due to different configurations or performances, and can include one or more central processing units (CPUs) 910 (for example, one or more processors) and a memory 920, one or more storage media 930 (for example, one or more mass storage devices) storing application programs 933 or data 932. The memory 920 and the storage media 930 can be temporary storage or persistent storage. The programs stored in the storage media 930 can include one or more modules (not shown in the figure), each of which can include a series of instruction operations in the adjusting device of a sleep-aiding bed 900. Furthermore, the processor 910 can be configured to communicate with the storage media 930 and execute the series of instruction operations in the storage media 930 on the adjusting device of a sleep-aiding bed 900 to implement the steps of the sleep-aiding bed adjusting method provided by each method embodiment described above.

[0025] The adjusting device of a sleep-aiding bed 900 can further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or one or more operating systems 931, such as Windows Server, MacOS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art can understand that the adjusting device of a sleep-aiding bed can include more or fewer components than those shown, or combine certain components, or arrange different components. Figure 9 The structure of the adjusting device of a sleep-aiding bed shown does not constitute a limitation on the adjusting device of a sleep-aiding bed, and can include more or fewer components than those shown, or combine certain components, or arrange different components.

[0026] The present application also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions, which, when executed on a computer, cause the computer to perform the steps of the sleep-aiding bed adjusting method.

[0027] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system or the system and the unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0028] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0029] Finally, it should be noted that: the above only for the preferred examples of the present application, and not for limiting the present application, although the present application is described in detail with reference to the foregoing examples, for those skilled in the art, it still can be modified to the technical solutions recorded in the foregoing embodiments, or equivalent replacement of some technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for adjusting a sleep-aid bed, characterized in that, An adjustment system for a sleep aid bed is provided, the sleep aid bed comprising a mattress, a pillow, a first anti-snoring bending block, and a second anti-snoring bending block, the pillow being disposed on the mattress, and the first and second anti-snoring bending blocks being disposed on the pillow; the adjustment method of the sleep aid bed includes the following steps: Acquire initial radio data and user sleep sound signal data; The user's sleep sound signal data is filtered based on the spectral subtraction method and the initial radio data to obtain filtered signal data; The filtered signal data is analyzed according to the preset Fourier transform algorithm and the preset time series variation law conditions to obtain the snoring level; Obtain the coordinates of the mattress's center of gravity; The mattress center of gravity coordinates are analyzed based on the preset mattress length and width to obtain the initial sleeping posture analysis results. Based on the initial sleeping posture analysis results and snoring level, the adjustment angles of the first and second anti-snoring bend blocks are generated. Pillow adjustment instructions are generated based on the adjustment angles of the first and second anti-snoring bend blocks.

2. The method for adjusting a sleep-aid bed as described in claim 1, characterized in that, The step of filtering the user's sleep sound signal data according to the spectral subtraction method and the initial radio reception data to obtain filtered signal data includes: The initial radio reception data is statistically analyzed based on the preset sampling frequency and preset discrete time series to obtain the power spectrum statistical characteristics. An over-subtraction factor is generated based on the power spectrum statistical characteristics, a preset noise estimation window, and a preset historical signal-to-noise ratio. The user's sleep sound signal data is filtered using the spectral subtraction method, preset high sensitivity characteristics, and over-subtraction factor to obtain filtered signal data.

3. The method for adjusting a sleep-aid bed as described in claim 1, characterized in that, The step of analyzing the filtered signal data according to a preset Fourier transform algorithm and preset time-series variation conditions to obtain the snoring level includes: The filtered signal data is divided into multiple short frame signal data according to a preset time interval. Feature extraction is performed on multiple short-frame signal data using the Fourier transform algorithm to obtain spectral signal features; The spectral signal characteristics are compared and analyzed based on the preset snoring frequency range and preset amplitude range to obtain the comparison and analysis results; When the comparative analysis results show that the spectral signal characteristics meet the snoring frequency band range and amplitude range, periodic analysis is performed on multiple short frame signal data to obtain the time domain signal characteristics. Based on the time-series variation patterns, the characteristics of time-domain signals are analyzed to obtain the results of the pattern analysis; When the pattern analysis results meet the conditions of temporal change, the spectral signal characteristics and time-domain signal characteristics are used to generate a snoring level.

4. The method for adjusting a sleep-aid bed as described in claim 3, characterized in that, When the pattern analysis result meets the condition of temporal change pattern, the spectral signal characteristics and time-domain signal characteristics generate a snoring level, including: If the result of the pattern analysis meets the condition of the time-series change pattern, then the snoring signal is generated based on the characteristics of the spectral signal and the time-domain signal. The snoring signal is analyzed according to the preset frequency band energy range to obtain the number of snoring events and the average amplitude; A snoring level is generated based on the number of snoring events and the average amplitude.

5. The method for adjusting a sleep-aid bed as described in claim 1, characterized in that, The step of analyzing the mattress center of gravity coordinates based on preset mattress length and preset mattress width to obtain initial sleeping posture analysis results includes: The first range is calculated based on the mattress length, a preset first weighting coefficient, and a preset second weighting coefficient. The second range is calculated based on the mattress width, the preset third weighting coefficient, and the preset fourth weighting coefficient; The horizontal and vertical coordinates of the center of gravity are obtained from the coordinates of the mattress's center of gravity. Determine whether the x-coordinate of the centroid is within the first range and whether the y-coordinate of the centroid is within the second range; When the x-coordinate of the center of gravity is in the first range and the y-coordinate of the center of gravity is in the second range, the supine posture analysis result is generated. Initial sleeping posture analysis results are generated based on the supine posture analysis results; The third range is calculated based on the mattress length, the preset fifth weighting coefficient, and the preset sixth weighting coefficient; Determine if the x-coordinate of the centroid is within the third range; When the x-coordinate of the center of gravity is within the third range, the analysis result of the left lateral decubitus posture is generated; Initial sleeping posture analysis results are generated based on the analysis results of the left lateral decubitus posture. The fourth range is calculated based on the mattress length, the preset seventh weighting coefficient, and the preset eighth weighting coefficient; Determine if the x-coordinate of the centroid is within the fourth range; When the x-coordinate of the center of gravity is within the fourth range, the right lateral decubitus posture analysis result is generated; Initial sleeping posture analysis results are generated based on the right lateral decubitus position analysis results.

6. The method for adjusting a sleep-aid bed as described in claim 1, characterized in that, The first anti-snoring bend block contains a first airbag, and the second anti-snoring bend block contains a second airbag. The step of generating the adjustment angles of the first and second anti-snoring bend blocks based on the initial sleeping posture analysis results and snoring level includes: Target pressure adjustment values ​​are generated based on the snoring level and the preset intervention sensitivity level; Obtain the first current airbag pressure, and generate the first airbag pressure adjustment amount based on the target pressure adjustment value and the first current airbag pressure; Obtain the second current airbag pressure, and generate the second airbag pressure adjustment amount based on the target pressure adjustment value and the second current airbag pressure; Obtain airbag material data and airbag elasticity coefficient; A height conversion coefficient is generated based on the preset airbag pressure tolerance range, airbag material data, and airbag elasticity coefficient. The adjustment angle of the first anti-snoring bending block is generated based on the first airbag pressure adjustment amount, the initial sleeping posture analysis results, the preset bending block height and height conversion coefficient; The adjustment angle of the second anti-snoring bend block is generated based on the second airbag pressure adjustment amount, the initial sleeping posture analysis results, the preset bend block height, and the height conversion coefficient.

7. The method for adjusting a sleep-aid bed as described in claim 6, characterized in that, The process of generating a height conversion coefficient based on a preset airbag pressure tolerance range, airbag material data, and airbag elasticity coefficient includes: The upper and lower limits of safe air pressure are obtained from the air pressure tolerance range of the airbag. The safe pressure difference is calculated by subtracting the lower limit of the safe air pressure from the upper limit of the safe air pressure. Multiple discrete pressure values ​​were randomly obtained from the airbag's pressure tolerance range; Theoretical coefficients are generated based on multiple discrete air pressure values ​​and safe air pressure differences; Data on the number of times the airbag is used is obtained, and the elastic coefficient of the airbag is compensated for aging based on the preset compensation formula, theoretical coefficient and the number of times the airbag is used, so as to obtain the compensated elastic coefficient. The height conversion coefficient is generated based on the airbag material data and the compensation elasticity coefficient.

8. An adjustment system for a sleep aid bed, characterized in that, The adjustment system of the sleep aid bed includes a control system and a mattress, a pillow, a first anti-snoring bending block and a second anti-snoring bending block electrically connected to the control system; the control system is used to perform the adjustment method of the sleep aid bed as described in any one of claims 1-7.

9. An adjustment device for a sleep aid bed, characterized in that, The adjustment device of the sleep aid bed includes: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the adjustment device of the sleep aid bed to perform the steps of the adjustment method of the sleep aid bed as claimed in any one of claims 1-7.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the various steps of the adjustment method of a sleep aid bed as described in any one of claims 1-7.

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