Partitioned visual display method for sleep health report

Abstract

The invention relates to the technical field of sleep data processing, in particular to a partitioned visual display method for sleep health reports. The method comprises the following steps: acquiring a preset human body three-dimensional model, and dividing the human body three-dimensional model into a front view and a side view; determining the parts of the head, the neck and the shoulders in the human body three-dimensional model; setting a head-shoulder-neck measuring and calculating area in the human body three-dimensional model according to the head, the neck and the shoulders; and collecting size data of the head, the neck and the shoulders based on the head-shoulder-neck measurement and calculation area. According to the method, the sleep health monitoring area is subdivided, and the sleep health report is presented in a subarea visualization form, so that the sleep health associated data of each part is quickly positioned, the sleep health report style is intuitively displayed, and a visual data basis is provided for customized adaptation of a pillow and a mattress.

Description

Technical Field

[0001] This invention relates to the field of sleep data processing technology, and in particular to a method for visualizing and displaying sleep health reports in a partitioned manner. Background Technology

[0002] Current sleep health reports have significant shortcomings and fail to meet practical application needs. Most reports focus only on basic indicators such as sleep duration and deep sleep ratio, or rely on CT and MRI images for guided analysis. The data dimensions are limited and the presentation is obscure, making it difficult for ordinary users to understand intuitively, let alone directly apply to the design and customization of health products such as pillows and mattresses. Furthermore, existing reports often focus on assessing the body's static support structure, analyzing static parameters only for a single sleeping position, lacking dynamic adaptation research for diverse sleeping positions such as side-lying and prone positions. This results in related product solutions failing to match the user's postural changes during sleep, making it difficult to meet personalized support needs. In addition, existing reports do not accurately quantify and visualize the dimensions of the head, shoulders, and neck. They neither subdivide and identify key dimensions of the head, neck, and shoulders, nor establish a logical connection between these data and spinal physiological parameters and sleeping posture characteristics. The data is fragmented and weakly correlated, failing to support multi-dimensional sleep health assessments or effectively guide the customization and adaptation of sleep health products, severely limiting the practical value of sleep health reports. Summary of the Invention

[0003] Therefore, it is necessary to provide a method for visualizing sleep health reports by region to solve at least one of the aforementioned technical problems.

[0004] To achieve the above objectives, a method for visually displaying a sleep health report by region is provided, the method comprising the following steps: Step S1: Obtain a preset 3D human body model, and divide the 3D human body model into a front view and a side view; determine the head, neck and shoulder parts in the 3D human body model; Step S2: Set the head, neck, and shoulder measurement area in the 3D human body model according to the head, neck, and shoulder parts; collect the dimensional data of the head, neck, and shoulders based on the head, neck, and shoulder measurement area; Step S3: Based on the front and side views, as well as the size data of the head, neck, and shoulders, divide the sleep health monitoring area and display it in sections; mark the size data of the head, neck, and shoulders in the corresponding sleep health monitoring area to build a sleep health report and present it in a visual form; Step S4: Collect the user's actual sleeping posture data, and perform mattress sleep health analysis based on the data corresponding to the sleep health monitoring area in the sleep health report to determine the mattress firmness customization plan.

[0005] The beneficial effects of this invention are: On the one hand, by subdividing the sleep health monitoring area into modules such as neck and shoulder dimensions, spinal health, and pillow height, the scattered head, shoulder and neck dimension data, spinal physiological parameters, pillow height configuration and other information are classified and displayed accordingly. At the same time, the associated views and data annotations allow users to quickly locate the sleep health related data of each part.

[0006] On the other hand, in the zoning display, head, shoulder and neck size data are directly linked to customized solutions such as pillow height zoning and mattress firmness level. At the same time, the contour curves of actual sleeping posture and recommended sleeping posture are superimposed to intuitively present the correspondence between data and product solutions in a visual form.

[0007] On the other hand, the sleep health report integrates objective size / physiological data, subjective sleep preference questionnaires, dynamic differences in sleeping posture contours, and other multi-dimensional information in a partitioned and visualized manner. This not only achieves the classification and presentation of data but also preserves the logical connections between different areas, allowing the sleep health report to serve as a basis for sleep health assessment and to directly guide the customization and adaptation of pillows and mattresses. Attached Figure Description

[0008] Figure 1 A flowchart illustrating the steps of a method for visually displaying a sleep health report in a partitioned format; Figure 2 This refers to the neck and shoulder measurement area in the sleep health report of this embodiment; Figure 3 This is the pillow-themed display area in the sleep health report of this embodiment; Figure 4 This is the customer questionnaire area in the sleep health report of this embodiment; Figure 5 This is a customized area for mattress firmness in the sleep health report of this embodiment; Figure 6 This refers to the recommended pillow height area in the sleep health report of this embodiment; Figure 7 This is an overall view of the sleep health report in this embodiment; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0009] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0010] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0011] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0012] It should be noted that the human body-related data collected or obtained was done with the user's knowledge and consent, and all of it is legal and compliant.

[0013] To achieve the above objectives, please refer to Figures 1 to 7 A method for visually displaying a sleep health report by region, the method comprising the following steps: Preferably, step S1: Obtain a preset three-dimensional human body model, divide the three-dimensional human body model into a front view and a side view; determine the head, neck and shoulder parts in the three-dimensional human body model; In this embodiment, a 3D human body scanning device is used to acquire 3D human body model data. During the acquisition process, the laser scanning frequency of the device is set to 500 points / second, the scanning accuracy is controlled within ±0.1cm, and the scanning range covers an area from the top of the head to 10cm below the buttocks to completely acquire the morphological data of the head, neck, and shoulders. The acquired 3D human body model is divided into views, decomposing it into a frontal view according to the coronal plane and a side view according to the sagittal plane. The view resolution is uniformly set to 1920×1080 pixels, and the view scaling ratio is fixed at 1:20 to ensure the accuracy of subsequent size measurements. Based on human... The physiological structural features of the body are used to locate the head, neck, and shoulders. The head region is referenced by the arc-shaped contour from the brow ridge to the base of the mandible, with the boundary set from the highest point of the top of the head to the lowest point of the base of the mandible. The neck region is referenced by the linear contour from the spinous process of the seventh cervical vertebra to the angle of the mandible, with the boundary set from the lowest point of the base of the mandible to the highest point of the spinous process of the seventh cervical vertebra. The shoulder region is referenced by the oblique contour from the acromion to the medial end of the clavicle, with the boundary set from the highest point of the spinous process of the seventh cervical vertebra to the outermost point of the acromion on both sides. During the localization process, points with a contour curvature change rate ≥0.8 are used as feature boundary points to ensure the accuracy of the division of the head, neck, and shoulders.

[0014] Preferably, step S2: set the head, neck, and shoulder measurement area in the human body 3D model according to the head, neck, and shoulder parts; collect the size data of the head, neck, and shoulders based on the head, neck, and shoulder measurement area; Please see Figure 2 In step S2, the head, shoulder, and neck measurement area in the 3D human body model is specifically set as follows: In the front view, the first front measurement segment A1 and the second front measurement segment A2 are set at the symmetrical contour edges on both sides of the head of the human three-dimensional model, the third front measurement segment A3 and the fourth front measurement segment A4 are set at the contour edges corresponding to the cervical vertebrae on both sides of the neck of the human three-dimensional model, and the fifth front measurement segment A5 is set at the contour endpoints corresponding to the acromion on both sides of the shoulder of the human three-dimensional model. In the side view, a first side measurement segment B1 is set at the top of the head of the human 3D model, a second side measurement segment B2 is set at the contour area corresponding to the lower jaw on the side of the head of the human 3D model, a third side measurement segment B3 is set at the contour area corresponding to the cervical spine on the side of the neck of the human 3D model, and a fourth side measurement segment B4 is set at the contour area corresponding to the scapula on the side of the shoulder of the human 3D model.

[0015] In this embodiment, Figure 2In the frontal view, with the midline of the human head as the symmetry reference, the first frontal measurement segment A1 and the second frontal measurement segment A2 are set at positions where the horizontal distance from the midline of the contour edges on both sides of the head is equal. The horizontal deviation of the center point of the two regions from the midline is controlled within ±0.2cm. The third frontal measurement segment A3 and the fourth frontal measurement segment A4 are set at the contour edges of the outer edges of the cervical vertebrae on both sides of the neck. The third frontal measurement segment A3 corresponds to the contour point of the outer edge of the third cervical vertebra on the left, and the fourth frontal measurement segment A4 corresponds to the contour point of the outer edge of the third cervical vertebra on the right. The vertical height difference between the center points of the two regions is controlled within ±0.3cm. The fifth frontal measurement segment A5 is set at the outermost contour endpoint of the acromion on both sides of the shoulder. The overlap deviation between the center point of the fifth frontal measurement segment A5 and the acromion endpoint does not exceed ±0.1cm, and the coverage area of ​​the fifth frontal measurement segment A5 extends inward along the shoulder contour by 0.5cm.

[0016] exist Figure 2 In the side view, the first side measurement segment B1 is set at the most prominent contour apex of the top of the head, and the vertical deviation between the center point of the first side measurement segment B1 and the apex does not exceed ±0.1cm; the second side measurement segment B2 is set in the contour area of ​​the foremost side of the lower edge of the mandible on the side of the head, and the coverage area of ​​the second side measurement segment B2 extends upward and downward by 0.3cm with the lower edge contour point of the mandible as the center; the third side measurement segment B3 is set in the contour area of ​​the neck corresponding to the anterior edge of the fourth cervical vertebra, and the horizontal deviation between the center point of the third side measurement segment B3 and the anterior edge contour point of the vertebra is controlled within ±0.2cm; the fourth side measurement segment B4 is set in the contour area of ​​the most prominent medial edge of the scapula on the side of the shoulder, and the coverage area of ​​the fourth side measurement segment B4 extends forward and backward by 0.4cm with the medial edge contour point of the scapula as the center.

[0017] Optionally, step S2, which involves collecting dimensional data of the head, neck, and shoulders based on the head-shoulder-neck measurement region, includes: In the front view, obtain the lateral length of the opposing contour coverage of the first front measurement segment A1 and the second front measurement segment A2, the lateral length of the opposing contour coverage of the third front measurement segment A3 and the fourth front measurement segment A4, and the overall length of the coverage between the acromion contour endpoints of the fifth front measurement segment A5. In the side view, obtain the longitudinal length of the vertical contour coverage of the first side measurement segment B1 to the fourth side measurement segment B4, and the lateral length of the horizontal contour coverage of the second side measurement segment B2 to the third side measurement segment B3. Use the length data corresponding to each region in the front and side views as the size data for the head, neck, and shoulders.

[0018] In one embodiment, in the front view, using a preset horizontal baseline as a measurement reference, a three-dimensional dimensional measuring device is used to collect the lateral length of the opposing contour coverage of the first front measurement segment A1 and the second front measurement segment A2. The device's contour edge recognition function is used to lock the outermost contour points of the two regions, and the distance data between the two points is read along the horizontal baseline. After collecting 5 sets of data, the average value is taken as the lateral length of the opposing contour coverage of the first front measurement segment A1 and the second front measurement segment A2. Based on the same horizontal baseline, the device is used to locate the cervical spine contour edge points corresponding to the third front measurement segment A3 and the fourth front measurement segment A4 on both sides of the neck. The distance between the two contour edge points is measured along the horizontal direction. Similarly, 5 sets of data are collected continuously and the average value is taken to obtain the lateral length of the opposing contour coverage of the third front measurement segment A3 and the fourth front measurement segment A4. For the fifth front measurement segment A5, the device's feature point recognition function is used to determine the acromion contour endpoints on both sides. The straight-line distance between the two points is measured along the horizontal baseline. 5 sets of data are collected and the average value is taken as the overall length of the coverage area between the acromion contour endpoints of the fifth front measurement segment A5.

[0019] In another embodiment, in the side view, with a preset vertical baseline as a reference, the top contour point of the first side measurement segment B1 and the bottom contour point of the fourth side measurement segment B4 are located using a three-dimensional dimension measuring device. The distance between the two points is measured along the vertical baseline, and five sets of data are collected and averaged to obtain the longitudinal length of the vertical contour coverage area from the first side measurement segment B1 to the fourth side measurement segment B4. With a horizontal baseline in the side view as a reference, the front point of the mandibular contour of the second side measurement segment B2 and the front point of the cervical contour of the third side measurement segment B3 are located. The distance between the two points is measured along the horizontal direction, and five sets of data are collected and averaged to obtain the lateral length of the horizontal contour coverage area from the second side measurement segment B2 to the third side measurement segment B3. The lateral lengths of the opposing contour coverage areas of the first and second frontal measurement segments A1 and A2, the lateral lengths of the opposing contour coverage areas of the third and fourth frontal measurement segments A3 and A4, and the overall length of the coverage area between the acromion contour endpoints of the fifth frontal measurement segment A5, as well as the longitudinal lengths of the vertical contour coverage areas from the first to the fourth side measurement segments B1 and the lateral lengths of the horizontal contour coverage areas from the second to the third side measurement segments B2, as measured in the side view, are uniformly used as the dimensional data for the head, neck, and shoulders. All measurement data are retained to one decimal place, and the measurement error is controlled within ±0.1cm.

[0020] Preferably, step S3: Based on the front view and side view, and the size data of the head, neck and shoulders, divide the sleep health monitoring area and display it in sections; mark the size data of the head, neck and shoulders in the corresponding sleep health monitoring area to construct a sleep health report; Optionally, the sleep health monitoring area in step S3 includes a shoulder and neck size area, a spinal health area, a pillow height and zone display area, a customer questionnaire area, and a mattress firmness customization area. The sleep health monitoring area is specifically divided as follows: Assign the dimensions of the front view, side view, head, neck, and shoulders to the shoulder and neck dimension area; Based on the dimensional data of the head, neck, and shoulders and the three-dimensional human body model, the spinal data is determined, and the spinal data, as well as the front and side views, are assigned to the healthy area of ​​the spine. Based on spinal location data and human 3D model, determine pillow height configuration data, and assign pillow height configuration data, front view and side view to pillow height and zoned display area; The collected user sleep information will be mapped to the customer questionnaire area; The upright model in the human body 3D model is converted into a lying model. The lying support data is determined based on the size data of the head, neck and shoulders and the human body 3D model. The lying support data and the lying model are then mapped to the mattress firmness customization area.

[0021] In one embodiment, the front view, side view, and collected head, neck, and shoulder dimension data (including the lateral length of the opposing contour coverage of the first front measurement segment A1 and the second front measurement segment A2 in the front view, the lateral length of the opposing contour coverage of the third front measurement segment A3 and the fourth front measurement segment A4 in the front view, the overall length of the coverage between the acromion contour endpoints of the fifth front measurement segment A5, the longitudinal length of the vertical contour coverage of the side first measurement segment B1 to the side fourth measurement segment B4 in the side view, and the lateral length of the horizontal contour coverage of the side second measurement segment B2 to the side third measurement segment B3) are imported into the shoulder and neck dimension area of ​​the sleep health report. During the import process, by matching the view coordinates with the data labels, each dimension data is labeled next to the corresponding measurement area in the view. The distance between the label position and the edge of the measurement area is controlled within 0.5cm to ensure that the correspondence between the data and the view is clearly distinguishable. In another embodiment, based on the dimensional data of the head, neck, and shoulders, and combined with the normal parameter ranges of the human spinal physiological structure (normal range of cervical spine offset -2cm~2cm, normal range of cervical spine curvature 18°~27°, normal range of shoulder balance -2°~2°, normal range of thoracic spine curvature 20°~40°, normal range of scapular protrusion 0~2cm, normal range of lumbar spine curvature 30°~45°), the spinal region data (including cervical spine offset, cervical spine curvature, shoulder balance, thoracic spine curvature, scapular protrusion, and lumbar spine curvature) are obtained through the conversion between dimensional data and spinal parameters. Then, the spinal region data, along with the front and side views, are imported into the spinal health area. During import, the spinal region data are arranged in the format of "parameter name-measurement value-normal range", and the corresponding position of the spine is marked with a dashed line in the view. The deviation between the dashed line and the actual spinal contour does not exceed 0.3cm. In another embodiment, based on the cervical curvature and shoulder balance in the spinal data, combined with the support requirements of the human head and neck when lying down, the pillow height configuration data (including pillow height values ​​for different zones) is obtained by converting the ratio of cervical curvature to pillow height and the adaptation calculation of shoulder balance to pillow height zones. The pillow height configuration data, front view, and side view are imported into the pillow height and zone display area. After importing, the display area is divided into several sub-zones according to the differences in pillow height values. The corresponding pillow height value is marked in each sub-zone. The width of the sub-zone is set to 2cm, and the height is presented in a 1:1 ratio with the corresponding pillow height value. In another embodiment, the collected user sleep information (including sleep onset time, sleep duration, whether to get up at night, sleep posture, sleep symptoms, wakefulness, mattress quality preference, mattress firmness preference, special function requirements, mattress replacement frequency, expected mattress price, and mattress size requirements) is organized according to the classification dimension of "sleep characteristics-preference-requirements" and filled into the preset fields in the customer questionnaire area. When filling in, the associated head, shoulder and neck size data label is marked next to each field (such as "mattress firmness preference - associated with the fifth measurement segment A5 acromion length from the front"), and the spacing between the label and the field is controlled at 0.3cm. In another embodiment, based on the head, neck, and shoulder dimensions of the human body in an upright state, combined with the physiological curvature characteristics of each part of the body when lying down (such as the forward convexity of the neck and the downward sag of the shoulders), the lying posture data is obtained by converting the dimension data with the lying posture. Then, based on the lying posture data and the pressure tolerance range of each part of the body when lying down (lower leg pressure tolerance range 20-30kPa, thigh pressure tolerance range 30-40kPa, buttock pressure tolerance range 40-50kPa, waist pressure tolerance range 15-25kPa, back pressure tolerance range 25-35kPa, shoulder pressure tolerance range 20-30kPa, head pressure tolerance range 10-20kPa), the lying posture support data (including the support strength and support angle of each part) is calculated. The lying posture support data and lying posture data are imported into the mattress firmness customization area. After import, the lying posture support data is arranged by part, and the support parameters of the corresponding parts are marked next to the lying posture data, with a marking deviation of no more than 0.2cm.

[0022] Optionally, the determination of spinal region data based on the dimensional data of the head, neck, and shoulders and the three-dimensional human body model specifically involves: The difference in lateral length between the third measurement segment A3 and the fourth measurement segment A4 in the front view corresponds to the cervical spine offset in the spinal data. The deviation between the longitudinal length of the first measurement segment B1 to the third measurement segment B3 in the side view and the physiological curvature range is used as the cervical curvature in the spinal data. The length of the fifth measurement segment A5 in the frontal view corresponds to the shoulder balance in the spinal region data. The longitudinal length from the third measurement segment B3 to the fourth measurement segment B4 in the side view corresponds to the thoracic curvature in the spinal data. The outward expansion length of the fifth measurement segment A5 in the frontal view corresponds to the scapular protrusion in the spinal data. The vertical extension data of the fourth measurement segment B4 in the side view is used to correspond to the lumbar curvature in the spinal data.

[0023] In one embodiment, the lateral length data of the opposing contour coverage areas of the third and fourth measurement segments A3 and A4 in the frontal view are retrieved. The difference between the two lengths is calculated using a length measurement tool. This difference is the cervical spine offset in the spinal region data. The measurement accuracy is controlled within ±0.1cm, and the result is retained to one decimal place. The longitudinal length segment data of the first to third measurement segments B1 to B3 in the side view are retrieved. The standard longitudinal length corresponding to the midpoint of the physiological range of cervical curvature 18°~27° is determined. The deviation value between the segment data and the standard longitudinal length is calculated. The angle is converted into an angle value according to the formula: angle = arcsin(longitudinal length deviation value / standard longitudinal length) × (180 / π). This angle is used as the cervical spine curvature in the spinal region data. The angle is retained to one decimal place, and the deviation value calculation accuracy is ±0.2cm. In another embodiment, the overall length between the endpoints of the acromion contour of the fifth measurement segment A5 in the frontal view is divided into left and right segments, with the projection of the midline of the human head in the frontal view as the boundary. The difference between the lengths of the two segments is calculated and converted into an angle value at 1 cm corresponding to 1°. This value is used as the shoulder balance in the spinal data. The length measurement accuracy is ±0.1 cm, and the angle is kept to one decimal place. The result matches the physiological range of -2° to 2°. Specifically, retrieve the longitudinal length segment data from the third measurement segment B3 to the fourth measurement segment B4 in the side view, set the standard thoracic spine length corresponding to the midpoint of the physiological range of thoracic spine curvature 20°~40° 30°, convert the angle to an angle value according to angle = arcsin(longitudinal length segment data / standard thoracic spine length) × (180 / π), and use it as the thoracic spine curvature in the spinal data. The angle is retained to one decimal place, and the conversion accuracy is ±0.5°. In another embodiment, the acromion standard coordinates in the frontal view with the shoulder in a natural drooping state are used as a reference. The horizontal outward expansion distance of the acromion contour endpoint of the fifth measurement segment A5 in the frontal view beyond the standard coordinates is calculated as the scapular protrusion in the spinal data. The coordinate measurement accuracy is ±0.1cm, and the result is retained to one decimal place and matched with the physiological range of 0~2cm. Specifically, retrieve the vertical coordinates of the fourth measurement segment B4 in the side view and calculate the difference between them and the standard vertical coordinates under the natural physiological curvature of the lumbar spine (i.e., the vertical extension data of the fourth measurement segment B4 in the side view). Set a standard lumbar spine length corresponding to the midpoint of the physiological range of lumbar curvature 30°~45°, which is 37.5°. Convert the angle to an angle value using the formula: angle = arcsin(vertical extension data / standard lumbar spine length) × (180 / π). Use this angle value as the lumbar curvature in the spinal data. The angle is kept to one decimal place, and the conversion accuracy is ±0.5°.

[0024] It should be noted that in this embodiment, the conversion relationship between dimensional data and spinal location data is based on relevant research published in the *Journal of Spinal Surgery* and GB / T39223-2020 *Methods for Measuring the Physiological Curvature of the Human Spine*. Verification was performed using simultaneous three-dimensional spinal scans and two-dimensional image measurements on 50 subjects (experimental data shown in Table 1). The conversion errors were ≤0.5cm (length parameter) and ≤1.5° (angle parameter), meeting the accuracy requirements for ergonomic measurements.

[0025] Table 1. Verification Experimental Data on Spinal Region Conversion Please see Figure 3 This is a schematic diagram of the pillow's zoning display area in this sleep health report; the pillow zoning scheme is preset by the manufacturer, such as... Figure 3 The diagram shown illustrates the seven-zone and nine-zone layouts preset by the merchant. The pillow zoning scheme includes, but is not limited to, these. Figure 3 The seven-zone and nine-zone layouts shown can be preset by the merchant according to the actual situation of the pillow product. They can also be set to five-zone, three-zone, or other pillow zoning schemes. It should be noted that the different pillow zoning schemes set by the merchant will be displayed in the corresponding pillow zoning display area of ​​this sleep health report.

[0026] Optionally, mapping the collected user sleep information to the customer questionnaire area includes: Collect users' sleep latency, sleep duration, sleeping position type, mattress firmness preference, functional needs, replacement frequency and other personalized sleep characteristics and preferences, and integrate them into user sleep information; The user's sleep information is arranged in a structured manner according to the preset classification dimensions and then filled into the preset fields in the customer questionnaire area. The user's sleep information fields are associated with the head, shoulder and neck size data.

[0027] Please see Figure 4Through a pre-set customer questionnaire information collection interface, users are asked to select one of the following options: sleep onset time (less than 15 minutes), sleep duration (15-30 minutes), sleep position (30-60 minutes), or sleep firmness preference (very soft), sleep duration (less than 4 hours), sleep position (4-6 hours), sleep position (sleeping), sleep position (sleeping), or sleep position (prone); mattress firmness preference (very soft), mattress firmness preference (moderate), mattress firmness preference (very firm); functional needs (at least one of the following: mite removal), antibacterial), anti-mold and moisture-proof, zoned support, or environmentally friendly materials); and replacement frequency (1-3 years), mattress firmness preference (3-5 years), mattress firmness preference (more than 5 years), or mattress firmness preference (never replaced). This personalized sleep characteristic and preference information, including sleep onset time, sleep duration, sleep position, mattress firmness preference, functional needs, and replacement frequency, is then integrated into the user's sleep information. During integration, the information field integrity check must cover all collected items to ensure no omissions. The preset classification dimensions are set as "Sleep Characteristics" and "Mattress Preferences." "Sleep Characteristics" includes fields for sleep onset time, sleep duration, and sleeping position type, while "Mattress Preferences" includes fields for mattress firmness preference, functional needs, and replacement frequency. Information processing tools are used to structure user sleep information according to these classification dimensions, presenting each field in the format of "Classification Dimension - Field Name - User Selection Result." The structured user sleep information is then filled into the preset fields in the customer questionnaire area. The matching accuracy between the fields "Sleep Onset Time," "Sleep Duration," "Sleep Position," "Mattress Firmness Preference," "Special Functions," and "Mattress Replacement Frequency" in the customer questionnaire area and their corresponding fields in the user sleep information is set to 100% to ensure accurate and complete data entry. After the data is filled in, the association markers between each field and the head, shoulder and neck size data are established using the marker tool: the sleep duration field is associated with the horizontal length of the horizontal contour coverage area from the second measurement segment B2 to the third measurement segment B3 in the side view; the sleep duration field is associated with the horizontal length of the opposing contour coverage area from the first measurement segment A1 to the second measurement segment A2 in the front view; the sleeping posture type field is associated with the overall length of the coverage area between the acromion contour endpoints in the fifth measurement segment A5 in the front view; the mattress firmness preference field is associated with the horizontal length of the opposing contour coverage area from the third measurement segment A3 to the fourth measurement segment A4 in the front view; the functional requirements field is associated with the vertical length of the vertical contour coverage area from the first measurement segment B1 to the fourth measurement segment B4 in the side view; and the replacement frequency field is associated with the segmented data of the vertical length from the third measurement segment B3 to the fourth measurement segment B4 in the side view. The accuracy of the association markers is controlled to 100%.

[0028] Please see Figure 5 The specific construction of the mattress firmness customization area is as follows: The upright model in the 3D human body model is converted into a lying model. The corresponding points of the lower leg, thigh, buttock, waist, back, shoulder and head in the lying model are determined, and the body features of the corresponding points in the lying position are marked. Based on the size data of the head, neck, and shoulders, lying support data is determined for the corresponding points in the lying position, and corresponding support performance evaluation parameters are matched based on the lying support data. The mattress firmness support level is determined based on the support performance evaluation parameters, and the firmness support level parameters are specified.

[0029] In this embodiment, Figure 5 As shown, the upright posture data is converted into lying posture data according to the proportions of human physiological structure, and the corresponding lying posture points are determined for the lower leg (center of the cross-section at the thickest part of the calf), thigh (center of the cross-section at the middle of the thigh), buttock (center of the pelvic region), waist (center of the lumbar region), back (center of the thoracic region), shoulder (center of the region below the acromion), and head (intersection of the line extending from the top of the skull to the cervical spine). The posture characteristics of each point are marked with a posture feature annotation tool, such as "lower leg shape: standard", thigh "knee shape: standard XO-shaped legs", buttock "pelvic tilt: posterior pelvic tilt, pelvic tilt to the left", waist "waist and abdomen shape: slightly protruding belly, lumbar curvature: curvature too straight", back "thoracic curvature: standard", shoulder "shoulder balance: good shoulder balance, back opening shape: standard", and head "head and neck standard: standard, cervical curvature: curvature too large++".

[0030] In another embodiment, the dimensional data of the head, neck, and shoulders are retrieved (lateral lengths of the first frontal measurement segment A1 and the second frontal measurement segment A2, the third frontal measurement segment A3 and the fourth frontal measurement segment A4, and the fifth frontal measurement segment A5; and lateral lengths of the first side measurement segment B1 to the fourth side measurement segment B4, and the second side measurement segment B2 to the third side measurement segment B3). A support data calculation tool is used to determine the lying support data for each point (calf length × 0.3 of the fifth frontal measurement segment A5, thigh length × 0.4 of the fifth frontal measurement segment A5, and hip length × 0.4 of the fifth frontal measurement segment A5). The following measurements are calculated: length × 0.6; lumbar region (lateral length from side measurement segment B2 to side measurement segment B3) × 0.8; back region (vertical length from side measurement segment B1 to side measurement segment B4) × 0.5; shoulder region (lateral length from front measurement segment A3 to front measurement segment A4) × 0.7; head region (lateral length from front measurement segment A1 to front measurement segment A2) × 0.6. The results are rounded to one decimal place with an error of ±0.1cm. Support performance evaluation parameters are matched from the parameter library based on the support data (the firmness level increases by 1 level for every 1cm increase in support data). The mattress firmness support level is matched according to the support performance level (levels 1-2 correspond to firmness 2, 3-4 to 3, 5-6 to 4, 7-8 to 5, 9-10 to 6), resulting in the following firmness levels for each point: calf 4, thigh 3, hip 6, lumbar region 3, back 2, shoulder 2, head 4. These level parameters are marked below the corresponding zones in the mattress firmness customization area, with a positional deviation ≤0.2cm.

[0031] In this embodiment, it is important to note that the mapping relationship of "every 1cm increase in support data → 1 level increase in firmness" is verified through a pressure sensor experiment involving 40 subjects, referencing the QB / T2670-2013 standard for "Upholstered Furniture Mattresses" (experimental data are shown in Table 2). "Support data" is defined as the vertical support displacement during lying posture. The firmness level shows a 90% goodness of fit with the human body pressure distribution, avoiding localized pressure concentration.

[0032] Table 2. Experimental data for mattress firmness conversion verification. Of particular importance is that the sleep health monitoring area in step S3 also includes a pillow selection area. The specific data collection operations for cervical lordosis and unilateral shoulder width in the pillow selection area are as follows: In the side view, taking the third side measurement segment B3 as the reference, the vertical distance from the third side measurement segment B3 to the apex of the front contour of the neck is collected as the cervical lordosis measurement data, and the cervical lordosis measurement data is correlated with the neck size data corresponding to the third side measurement segment B3. In the frontal view, using the fourth measurement segment A4 as the midline reference of the human body, the horizontal distance from the fifth measurement segment A5 to the fourth measurement segment A4 is collected as the shoulder width data on one side. The shoulder width data on one side is then correlated with the neck and shoulder size data corresponding to the fourth measurement segment A4 and the fifth measurement segment A5. The data on cervical lordosis and unilateral shoulder width were added to the dimensional data of the head, neck, and shoulders.

[0033] Please see Figure 6 To provide a recommended pillow height area map, in this embodiment, a side view is retrieved, and the center point of the third measurement segment B3 (the contour area corresponding to the cervical spine on the side of the neck) is locked using a coordinate positioning tool. A vertical measurement line is established based on this point, and a length measurement tool is used to collect the vertical distance from the third measurement segment B3 to the apex of the front contour of the neck along this line, obtaining a cervical lordosis measurement of 7.8cm. The sampling interval is set to 0.05cm, and three sets of data are collected consecutively and the average value is taken. The result is retained to one decimal place, and the error is controlled within ±0.1cm. The data is then associated with the neck size data corresponding to the third measurement segment B3 (the lateral length from the third measurement segment B3 to the second measurement segment B2 and the longitudinal length from the third measurement segment B3 to the fourth measurement segment B4) using a data association tool.

[0034] In another embodiment, a frontal view is retrieved, and the center point of the fourth measurement segment A4 (the contour area corresponding to the right cervical vertebrae of the neck) is locked using a coordinate positioning tool. A horizontal measurement line is established with this point as the midline reference of the human body. A length measurement tool is used to collect the horizontal distance from the fifth measurement segment A5 (the endpoint of the right acromion contour) to the fourth measurement segment A4 along this line, obtaining a single-sided shoulder width data of 13.4cm. The measurement sampling interval is set to 0.05cm, and three sets of data are collected consecutively and the average value is taken. The result is retained to one decimal place, and the error is controlled within ±0.1cm. The data is then associated with the neck size data corresponding to the fourth measurement segment A4 (the horizontal length of the third measurement segment A3 and the fourth measurement segment A4) and the shoulder size data corresponding to the fifth measurement segment A5 (the overall length of the fifth measurement segment A5) using a data association tool.

[0035] like Figure 6 As shown, the cervical lordosis measurement of 7.8cm and the unilateral shoulder width of 13.4cm were added to the existing head, neck, and shoulder size data (lateral lengths of the first and second frontal measurement segments A1 and A2, lateral lengths of the third and fourth frontal measurement segments A3 and A4, overall length of the fifth frontal measurement segment A5; longitudinal lengths of the first and fourth side measurement segments B1 and B4, and lateral lengths of the second and third side measurement segments B2 and B3). The data format was kept consistent during the addition, and the data was classified and labeled in the same dataset as the original data.

[0036] Most importantly, the recommended pillow height matching method in the pillow selection section is as follows: The cervical lordosis data associated with the third lateral measurement segment B3 is divided into multiple continuous numerical intervals, and the unilateral shoulder width data associated with the fourth frontal measurement segment A4 and the fifth frontal measurement segment A5 is divided into corresponding numerical intervals, establishing a cross-mapping relationship between the two sets of intervals. Based on the interval combination of the collected cervical lordosis and unilateral shoulder width data, the recommended pillow height range corresponding to the interval combination is retrieved; The interval combinations are associated with the corresponding head, shoulder and neck size data and displayed synchronously in the pillow height and zone display areas to achieve the association and adaptation between size data and pillow height recommendations.

[0037] Please see Figure 6 In this embodiment, the cervical lordosis data associated with the third lateral measurement segment B3 is divided into multiple continuous numerical intervals such as <7cm, 7cm, 8cm, 9cm, 10cm, 11cm, 12cm, 13cm, 14cm, 15cm, and >15cm. The unilateral shoulder width data associated with the fourth frontal measurement segment A4 and the fifth frontal measurement segment A5 is divided into corresponding numerical intervals such as <10cm, 10cm, 11cm, 12cm, 13cm, 14cm, 15cm, 16cm, 17cm, 18cm, and >18cm. A cross-mapping relationship between two sets of intervals was established using an interval mapping tool. For example, a cervical lordosis of 7cm and a unilateral shoulder width of 10cm correspond to a recommended pillow height of 10cm, while a cervical lordosis of 9-10cm and a unilateral shoulder width of 12-13cm correspond to a recommended pillow height of 10-12cm. The accuracy of the mapping relationship was controlled at 100%. Based on the collected data of cervical lordosis of 7.8cm and unilateral shoulder width of 13.4cm, the interval combination was determined to be the cervical lordosis interval of 8cm and the unilateral shoulder width interval of 13cm. The recommended pillow height range of 10-12cm corresponding to the combination is retrieved from the preset range combination-recommended pillow height mapping library using a data retrieval tool, with the data matching accuracy set to 100% during retrieval; Specifically, the interval combination is associated with the corresponding head, shoulder and neck size data (cervical lordosis 7.8cm, unilateral shoulder width 13.4cm, the horizontal length of the opposing contour coverage of the first measurement segment A1 and the second measurement segment A2 in the front view, the horizontal length of the opposing contour coverage of the third measurement segment A3 and the fourth measurement segment A4 in the front view, the overall length of the coverage between the acromion contour endpoints of the fifth measurement segment A5 in the front view, the vertical length of the vertical contour coverage of the first measurement segment B1 to the fourth measurement segment B4 in the side view, and the horizontal length of the horizontal contour coverage of the side view of the second measurement segment B2 to the third measurement segment B3) using the association and binding tool, and marked 0.2cm to the right of the recommended pillow height interval; finally, the associated and bound content is synchronously presented in the pillow height and zone display area.

[0038] It should be noted that in this embodiment, the mapping between cervical lordosis, unilateral shoulder width and pillow height is based on the conclusion of the personalized pillow height study in the Journal of Sleep Medicine and verified through a sleep experiment of 60 subjects (experimental data are shown in Table 3). This mapping relationship can maintain cervical lordosis within the normal range of 18°-27°, with a suitability rate of over 92%.

[0039] Table 3. Experimental data verifying the pillow height mapping relationship. Preferably, step S4: collect the user's actual sleeping posture data, and perform mattress sleep health analysis based on the data corresponding to the sleep health monitoring area in the sleep health report to determine the mattress firmness customization plan.

[0040] Optionally, step S4 includes: Collect users' actual sleeping posture data and generate human body actual sleeping posture contour curves based on the user's actual sleeping posture data; Generate suggested healthy sleeping posture contour curves based on lying posture support data; The actual sleeping posture contour curve and the suggested healthy sleeping posture contour curve are superimposed and displayed in the mattress firmness customization area. The difference in sleeping posture adaptation is characterized by the coordinate deviation value between the actual sleeping posture contour curve and the suggested healthy sleeping posture contour curve, so as to determine the mattress firmness customization plan.

[0041] Please see Figure 5 In this embodiment, the user's actual sleeping posture data (including real-time coordinates of the calves, thighs, buttocks, waist, back, shoulders, and head) is acquired. Based on this coordinate data, a contour curve of the actual sleeping posture is generated, with a curve sampling interval of 0.5cm and a coordinate error controlled within ±0.2cm. Pre-determined lying posture support data (support strength and angle at points such as the calves, thighs, and buttocks) is retrieved, and a suggested healthy sleeping posture contour curve is generated based on this data using a curve generation tool. The matching accuracy between the coordinates of each point on the curve and the corresponding support data is set to 100%. The actual sleeping posture contour curve of the human body (in) Figure 5 (Presented in red), and suggested healthy sleeping posture contour curves (in...) Figure 5 (Presented in blue) It is superimposed and displayed below the lying posture in the mattress firmness customization area. When displayed, the starting point of the curve is aligned with the corresponding point of the human head and the ending point is aligned with the corresponding point of the lower leg. Using a coordinate deviation calculation tool, the coordinate deviation values ​​(vertical differences) of the two curves at corresponding points on the calf, thigh, hip, waist, back, shoulder, and head are calculated. The deviation value is rounded to one decimal place, and the calculation error is ≤0.1cm. This deviation value represents the difference in sleeping posture adaptation. Areas with deviation values ​​>1cm are marked as adaptation difference zones. Based on the distribution of adaptation difference zones and deviation values, the lying posture support data and firmness level parameters of the corresponding zones are adjusted to finally determine the mattress firmness customization plan (e.g., maintaining a firmness level of 6 in the hip area and a firmness level of 3 in the waist area).

[0042] It should be noted that in this embodiment, the healthy sleeping posture contour curve is recommended to refer to the 2023 version of the "Guidelines of the Chinese Sleep Research Society". The experiment was verified by 30 healthy subjects (experimental data are shown in Table 4). The consistency with the recognized healthy sleeping posture reached 93%. The deviation value calculation incorporates weight coefficients such as scoliosis and excessive cervical flexion to ensure that the hardness adjustment solves the actual sleep health problem.

[0043] Table 4 shows the experimental data for the recommended sleeping posture curve. Of particular importance, step S4, in determining the mattress firmness customization plan, also includes configuring the firmness level in the mattress firmness customization area: Based on the coordinate deviation values ​​of the head, neck, and shoulder size data and the actual human sleeping posture contour curve and the suggested healthy sleeping posture contour curve; Retrieve the softness and hardness support level parameters of each lying position corresponding to the location, and mark the softness and hardness support level parameters as gradient labels at the corresponding location of the lying position in the lying position model.

[0044] In this embodiment, the dimensional data of the head, neck, and shoulders are first retrieved (the lateral length of the coverage area of ​​the opposing contours of the first and second measurement segments A1 and A2 in the front view, the lateral length of the coverage area of ​​the opposing contours of the third and fourth measurement segments A3 and A4 in the front view, the overall length of the coverage area between the endpoints of the acromion contour of the fifth measurement segment A5 in the front view, the longitudinal length of the vertical contour coverage area from the first measurement segment B1 to the fourth measurement segment B4 in the side view, and the lateral length of the horizontal contour coverage area from the second measurement segment B2 to the third measurement segment B3 in the side view). At the same time, the coordinate deviation values ​​(vertical difference, rounded to one decimal place, calculation error ≤ 0.1cm) of the user's actual sleeping posture contour curve and the suggested healthy sleeping posture contour curve at the corresponding points of the calf, thigh, buttock, waist, back, shoulder, and head are obtained. Based on the above size data and coordinate deviation values, retrieve the softness and hardness support level parameters (e.g., calf hardness level 4, thigh hardness level 3, hip hardness level 6, waist hardness level 3, back hardness level 2, shoulder hardness level 2, head hardness level 4) for each lying position (lower leg, thigh hardness level 4, hip hardness level 3, back hardness level 2, shoulder hardness level 2, head hardness level 4) for each corresponding point in the lying position model using a gradient labeling tool. The labeling position is located 0.3cm below each point area, ensuring that the positional deviation between the level parameter and the corresponding point area does not exceed 0.2cm.

[0045] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0046] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for visually displaying a sleep health report by region, characterized in that, Includes the following steps: Step S1: Obtain a preset 3D human body model and divide the 3D human body model into a front view and a side view; Identify the head, neck, and shoulder areas in the 3D human body model; Step S2: Set the head, neck, and shoulder measurement area in the 3D human body model according to the head, neck, and shoulder parts; collect the dimensional data of the head, neck, and shoulders based on the head, neck, and shoulder measurement area; Step S3: Based on the front and side views, as well as the dimensional data of the head, neck, and shoulders, divide the sleep health monitoring area and display it in sections; mark the dimensional data of the head, neck, and shoulders in the corresponding sleep health monitoring area to construct a sleep health report; Step S4: Collect the user's actual sleeping posture data, and perform mattress sleep health analysis based on the data corresponding to the sleep health monitoring area in the sleep health report to determine the mattress firmness customization plan.

2. The method for partitioned visualization display of sleep health reports according to claim 1, characterized in that, In step S2, the head, shoulder, and neck measurement area in the 3D human body model is specifically set as follows: In the front view, the first front measurement segment (A1) and the second front measurement segment (A2) are set at the symmetrical contour edges on both sides of the head of the human three-dimensional model, the third front measurement segment (A3) and the fourth front measurement segment (A4) are set at the contour edges corresponding to the cervical vertebrae on both sides of the neck of the human three-dimensional model, and the fifth front measurement segment (A5) is set at the contour endpoints corresponding to the acromion on both sides of the shoulder of the human three-dimensional model. In the side view, a first side measurement segment (B1) is set at the top of the head of the human three-dimensional model, a second side measurement segment (B2) is set at the contour area corresponding to the lower jaw of the head of the human three-dimensional model, a third side measurement segment (B3) is set at the contour area corresponding to the cervical spine of the neck of the human three-dimensional model, and a fourth side measurement segment (B4) is set at the contour area corresponding to the scapula of the shoulder of the human three-dimensional model.

3. The method for partitioned visualization display of sleep health reports according to claim 2, characterized in that, Step S2 involves collecting dimensional data of the head, neck, and shoulders based on the head-shoulder-neck measurement region, including: In the front view, obtain the lateral length of the opposing contour coverage of the first front measurement segment (A1) and the second front measurement segment (A2), the lateral length of the opposing contour coverage of the third front measurement segment (A3) and the fourth front measurement segment (A4), and the overall length of the coverage between the acromion contour endpoints of the fifth front measurement segment (A5). In the side view, obtain the longitudinal length of the vertical profile coverage of the first side measurement segment (B1) to the fourth side measurement segment (B4) and the lateral length of the horizontal profile coverage of the second side measurement segment (B2) to the third side measurement segment (B3). Use the length data corresponding to each region in the front and side views as the size data for the head, neck, and shoulders.

4. The method for partitioned visualization display of sleep health reports according to claim 1, characterized in that, Step S3, the sleep health monitoring area includes a shoulder and neck size area, a spinal health area, a pillow height and zone display area, a customer questionnaire area, and a mattress firmness customization area. The sleep health monitoring area is specifically divided as follows: Assign the dimensions of the front view, side view, head, neck, and shoulders to the shoulder and neck dimension area; Based on the dimensional data of the head, neck, and shoulders and the three-dimensional human body model, the spinal data is determined, and the spinal data, as well as the front and side views, are assigned to the healthy area of ​​the spine. Based on spinal location data and human 3D model, determine pillow height configuration data, and assign pillow height configuration data, front view and side view to pillow height and zoned display area; The collected user sleep information will be mapped to the customer questionnaire area; The upright model in the human body 3D model is converted into a lying model. The lying support data is determined based on the size data of the head, neck and shoulders and the human body 3D model. The lying support data and the lying model are then mapped to the mattress firmness customization area.

5. The method for partitioned visualization display of sleep health reports according to claim 4, characterized in that, The specific steps for determining the spinal region data based on the dimensional data of the head, neck, and shoulders, and the three-dimensional human body model are as follows: The difference in lateral length between the third measurement segment (A3) and the fourth measurement segment (A4) in the frontal view is used as the cervical spine offset in the spinal data. The deviation between the longitudinal length of the first measurement segment (B1) to the third measurement segment (B3) on the side view and the physiological curvature range is used as the cervical curvature in the spinal data. The length value of the fifth measurement segment (A5) in the front view corresponds to the shoulder balance in the spinal data. The longitudinal lengths from the third measurement segment (B3) to the fourth measurement segment (B4) in the side view correspond to the thoracic curvature in the spinal data. The outward extension length of the endpoint of the fifth measurement segment (A5) in the frontal view corresponds to the scapular protrusion in the spinal data; The vertical extension data of the fourth measurement segment (B4) in the side view is used to correspond to the lumbar curvature in the spinal data.

6. The method for partitioned visualization display of sleep health reports according to claim 4, characterized in that, Step S3, the sleep health monitoring area also includes a pillow selection area. The specific steps for collecting data on cervical lordosis and unilateral shoulder width in the pillow selection area are as follows: In the side view, taking the third side measurement segment (B3) as the reference, the vertical distance from the third side measurement segment (B3) to the apex of the front contour of the neck is collected as the cervical lordosis data, and the cervical lordosis data is correlated with the neck size data corresponding to the third side measurement segment (B3). In the frontal view, the fourth measurement segment (A4) is used as the midline reference of the human body. The horizontal distance from the fifth measurement segment (A5) to the fourth measurement segment (A4) is collected as the shoulder width data of one side. The shoulder width data of one side is then correlated with the neck and shoulder size data corresponding to the fourth measurement segment (A4) and the fifth measurement segment (A5). The data on cervical lordosis and unilateral shoulder width were added to the dimensional data of the head, neck, and shoulders.

7. The method for partitioned visualization display of sleep health reports according to claim 4, characterized in that, The step of mapping the collected user sleep information to the customer questionnaire area includes: Collect users' sleep latency, sleep duration, sleeping position type, mattress firmness preference, functional needs, replacement frequency and other personalized sleep characteristics and preferences, and integrate them into user sleep information; The user's sleep information is arranged in a structured manner according to the preset classification dimensions and then filled into the preset fields in the customer questionnaire area. The user's sleep information fields are associated with the head, shoulder and neck size data.

8. The method for partitioned visualization display of a sleep health report according to claim 4, characterized in that, The specific construction of the mattress firmness customization area is as follows: The upright model in the 3D human body model is converted into a lying model. The corresponding points of the lower leg, thigh, buttock, waist, back, shoulder and head in the lying model are determined, and the body features of the corresponding points in the lying position are marked. Based on the size data of the head, neck, and shoulders, lying support data is determined for the corresponding points in the lying position, and corresponding support performance evaluation parameters are matched based on the lying support data. The mattress firmness support level is determined based on the support performance evaluation parameters, and the firmness support level parameters are specified.

9. The method for partitioned visualization display of a sleep health report according to claim 4, characterized in that, Step S4 includes: Collect users' actual sleeping posture data and generate human body actual sleeping posture contour curves based on the user's actual sleeping posture data; Generate suggested healthy sleeping posture contour curves based on lying posture support data; The actual sleeping posture contour curve and the suggested healthy sleeping posture contour curve are superimposed and displayed in the mattress firmness customization area. The difference in sleeping posture adaptation is characterized by the coordinate deviation value between the actual sleeping posture contour curve and the suggested healthy sleeping posture contour curve, so as to determine the mattress firmness customization plan.

10. The method for partitioned visualization display of a sleep health report according to claim 4, characterized in that, Step S4, determining the mattress firmness customization plan, also includes configuring the firmness level in the mattress firmness customization area: Based on the coordinate deviation values ​​of the head, neck, and shoulder size data and the actual human sleeping posture contour curve and the suggested healthy sleeping posture contour curve; Retrieve the softness and hardness support level parameters of each lying position corresponding to the location, and mark the softness and hardness support level parameters as gradient labels at the corresponding location of the lying position in the lying position model.

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