Pillow comfort evaluation method and system based on force line balance system

Abstract

The present application relates to the field of bedding comfort test and evaluation. The pillow comfort evaluation method based on force line balance system comprises the following steps: step S1, obtaining subjective sleep quality score; step S2, collecting cervical vertebra shape maintenance degree, pressure distribution performance and muscle relaxation degree; step S3, establishing BP neural network evaluation model; step S4, for other pillow to be evaluated, repeating step S2, inputting it into the trained BP neural network evaluation model, the model outputs the corresponding sleep quality score, and the sleep quality score is used for realizing quantitative evaluation of pillow comfort.

Description

Technical Field

[0001] This invention relates to the field of bedding comfort testing and evaluation, specifically to the testing and evaluation of pillow core comfort. Background Technology

[0002] Human force lines refer to the biomechanical transmission paths formed by the coordinated action of bones, joints, and muscles during static or dynamic activities. Their core function is to maintain postural stability and movement efficiency, specifically involving three key aspects: gravity distribution, muscle tension balance, and skeletal joint alignment. These directly impact human athletic performance, cervical spine health, and overall physical health. Force line balance, as a core indicator of human biomechanical health, requires the coordinated action of bones, joints, and muscles to ensure the body is in a proper biomechanical state, reducing chronic damage to bones, joints, and muscles.

[0003] Sleep is an important daily physiological activity for the human body. During sleep, the body is in a static and relaxed state. At this time, the force state of the bones, joints and muscles directly affects the balance of the body's force line. As the most important item for sleep, the design of the pillow core directly determines whether the body's force line can maintain balance during sleep.

[0004] Based on the core requirements of the force line balance system, the pillow core design needs to take into account the two mainstream sleeping postures of supine and side sleeping, and focus on four key support heights: the height of the head fossa and the height of the neck support area when supine, and the height of the head support and the height of the neck support when side sleeping. Through the coordinated adaptation of the four heights, it is ensured that the cervical spine is in a state of force line balance in both postures.

[0005] Currently, there is a lack of a scientific and systematic verification method to test whether pillow cores can effectively maintain the body's force line balance during sleep. Summary of the Invention

[0006] The purpose of this invention is to provide a method for evaluating pillow core comfort based on a force line balance system, so as to achieve a scientific, quantitative, and accurate evaluation of pillow core comfort and provide a reliable basis for product optimization and consumer choice.

[0007] Another objective of this invention is to provide a pillow core comfort evaluation system based on a force line balance system.

[0008] The method for evaluating pillow core comfort based on a force line balance system is characterized by the following steps: Step S1: Obtain the user's subjective sleep quality score when using the pillow core to be tested; Step S2: Collect three types of objective characteristic parameters related to the pillow core and force line balance. The three types of objective characteristic parameters include cervical spine shape maintenance, pressure distribution performance, and muscle relaxation. Step S3: Establish a BP neural network evaluation model: Using the lateral cervical spine shape maintenance degree, supine cervical spine shape maintenance degree, maximum pressure, average pressure, contact area, root mean square value of electromyography, and average power frequency of electromyography collected in step S2 as input feature parameters, and the sleep quality score obtained in step S1 as output parameters, construct a BP neural network model. Step S4, Pillow Core Comfort Evaluation: For other pillow cores to be evaluated, repeat step S2 to collect seven input feature parameters: lateral cervical spine shape maintenance, supine cervical spine shape maintenance, maximum pressure, average pressure, contact area, root mean square value of electromyography, and average power frequency of electromyography. Input these parameters into the trained BP neural network evaluation model to obtain the sleep quality score for each tester. Take the average score as the final comfort score for the pillow core. The model outputs the corresponding sleep quality score, and the pillow core comfort is quantitatively evaluated based on this sleep quality score.

[0009] Preferably, the Pittsburgh Sleep Quality Index questionnaire is used, which allows users to fill out the questionnaire after using the pillow core to be evaluated for a preset period of time. The subjective sleep score of the pillow core to be tested is calculated based on the questionnaire results.

[0010] Preferred method for collecting data on lateral decubitus cervical spine morphology maintenance: The angle between the cervical spine centerline and the horizontal plane when the subject lies on their side with the pillow being tested, as measured by a three-dimensional optical motion capture system. included angle The smaller the size, the better the cervical spine posture is maintained when using this pillow core; Preferably, marker points of the three-dimensional optical motion capture system are affixed to the occipital protuberance, the spinous processes of the first, third, fifth, and seventh cervical vertebrae of the subject's cervical spine, and designated as M1-M5 respectively. The subject lies supine on a horizontally placed bed in the laboratory, with the subject's body direction parallel to the zOy plane. The angle between the center line of the cervical spine and the horizontal plane when the subject is supine is... .

[0011] Preferred method for collecting data on cervical spine morphology maintenance while supine: The forward tilt angle of the neck when the subject is lying supine with the pillow being tested was measured using a three-dimensional optical motion capture system. The forward tilt angle of the neck when the subject is upright Using eigenvalues Compare and Differences between them, eigenvalues The smaller the value, the better the cervical spine posture is maintained when using the pillow core while lying supine.

[0012] Preferably, marker points of the three-dimensional optical motion capture system are affixed to the subject's chin and cervical fossa, denoted as m1 and m2 respectively. The subject lies supine on a bed placed horizontally in the laboratory, with the subject's body direction parallel to the zOy plane. The forward tilt angle of the subject's neck when supine is [value missing]. Simultaneously, with the coronal plane of the subject parallel to the zOy plane when standing upright, the forward tilt angle of the neck when the subject is standing is... Using eigenvalues Compare and Differences between them, eigenvalues The smaller the value, the better the cervical spine posture is maintained when using the pillow core while lying supine. Preferably, the method for collecting pressure distribution performance parameters includes the following steps: Step (1) Place the pressure distribution testing system on the pillow core to be tested and test the pressure distribution value of the subject on the pillow core to be tested; Step (2) performs mathematical processing on the measured pressure distribution values ​​to calculate the maximum pressure. Average pressure Contact area Among them, the maximum pressure The average pressure is the maximum value among the measured pressure values. The average value of the measured pressure, and the contact area. It is the contact area between the test subject and the pillow core.

[0013] Preferably, the method for collecting muscle relaxation parameters is as follows: a surface electromyography (EMG) sensor is used to collect EMG signals from the user's sternocleidomastoid, trapezius, splenius cervicis, and / or levator scapulae muscles. After preprocessing the EMG signals, the evaluation indicators are time-domain correlation indicators and frequency-domain correlation indicators. The time-domain correlation indicator is the root mean square (RMS) value or integrated electromyography (iEMG), and the frequency-domain correlation indicator is the average power frequency (MPF) or median frequency (MF).

[0014] Preferably, the BP neural network model includes an input layer, a hidden layer, and an output layer. The input layer has 7 neurons, corresponding to 7 input feature parameters: lateral cervical spine shape maintenance, supine cervical spine shape maintenance, maximum pressure, average pressure, contact area, electromyography (RMS), and electromyography (MPF). The output layer has 1 neuron, corresponding to the sleep quality score, and uses a linear activation function. The number of neurons in the hidden layer is determined by trial and error, ranging from 10 to 20. During model training, gradient descent is used to optimize the network weights and thresholds, with a learning rate of 0.01-0.05 and 1000-5000 iterations, until the model error is less than the preset threshold, completing the model training and obtaining the trained BP neural network evaluation model.

[0015] The pillow core comfort evaluation system based on the force line balance system is characterized by including a data acquisition module, a data preprocessing module, a model training module, and an evaluation module. The data acquisition module is used to collect the user's subjective sleep quality score, cervical spine morphology detection unit, pressure distribution detection unit and electromyography signal acquisition unit when using the pillow core; The data preprocessing module is used to process the raw data collected by the data acquisition module, including cervical spine morphology maintenance data and pressure distribution data, to obtain the angle α between the cervical spine centerline and the horizontal plane when lying on the side and the characteristic values ​​of the cervical spine forward tilt angle when lying on the back. Maximum pressure, average pressure, and contact area; filter, denoise, and normalize the electromyographic signals to extract the RMS and MPF parameters; after preprocessing, transmit the data to the model training module. The model training module is used to construct a BP neural network model, receive the cervical spine morphology maintenance degree, maximum pressure, average pressure, contact area, electromyography RMS, and electromyography MPF output by the data preprocessing module, output sleep quality score, train and optimize the BP neural network model, and obtain a trained BP neural network evaluation model. The evaluation module is used to receive the preprocessed input feature parameters corresponding to the pillow core to be evaluated, input them into the trained BP neural network evaluation model, obtain the sleep quality score output by the model, output the comfort evaluation result according to the scoring criteria, and store and display the evaluation result.

[0016] Preferably, the cervical spine morphology detection unit uses a three-dimensional optical motion capture system to detect the three-dimensional spatial coordinates of the marker points pasted on the cervical spine in the user's supine and lateral states; The pressure distribution detection unit adopts an array-type pressure distribution testing system to detect the pressure distribution data when the user uses the pillow core; The electromyography (EMG) signal acquisition unit uses a surface electromyography (SEMG) sensor to acquire EMG signals from the user's neck muscles and output raw EMG signal data.

[0017] Beneficial Effects: 1. Comprehensive Evaluation Dimensions, Balancing Subjective Experience and Objective Data: This invention focuses on the force line balance system, combining three objective characteristic parameters—cervical spine shape maintenance, pressure distribution, and muscle relaxation—with the subjective sleep score of the Pittsburgh Sleep Quality Index questionnaire. This avoids the one-sidedness of relying solely on subjective or objective parameter evaluations, and can truly and comprehensively reflect the actual comfort of the pillow core. 2. Scientific, Quantitative, and Highly Precise Evaluation Method: By extracting the root mean square (RMS) and mean power frequency (MPF) of electromyography signals to quantify muscle relaxation, and combining this with cervical spine shape maintenance and pressure distribution parameters, a BP neural network is used to establish a correlation model between these features and the sleep quality score, achieving a quantitative evaluation of comfort and solving the problem of... The evaluation system overcomes the problems of subjectivity and low accuracy in existing evaluation methods, making the evaluation results more scientific and reliable; 3. The system has a reasonable structure, is easy to operate, and has strong versatility: The evaluation system of this invention integrates data acquisition, preprocessing, model training, and evaluation functions, forming a complete closed loop. It is simple to operate and applicable to different types and specifications of pillow core products. It can provide data support for product optimization for enterprises and provide consumers with objective product comfort references; 4. It is highly practical and has a wide range of application scenarios: The feature parameters collected by the evaluation method and system of this invention are easy to obtain. After the model is trained, the comfort evaluation of pillow cores can be quickly realized. It is applicable to various scenarios such as pillow core product research and development, quality inspection, market supervision, and consumer selection. Attached Figure Description

[0018] Figure 1 Image showing the pressure distribution of an ergonomic pillow when lying supine; Figure 2 Image showing the pressure distribution of an ergonomic pillow when lying on your side; Figure 3 Image of pressure distribution when prone using an ergonomic pillow Figure 4 This is an image showing the pressure distribution when lying supine with a standard pillow. Figure 5 This is an image showing the pressure distribution when lying on your side with a normal pillow. Figure 6 Image showing the pressure distribution when lying prone with a standard pillow; Figure 7 Schematic diagram of electromyography (EMG) test sites; Figure 8 MPF values ​​for four types of muscles at different stages. Detailed Implementation

[0019] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below with reference to specific illustrations.

[0020] The method for evaluating pillow core comfort based on a force line balance system includes the following steps: Step S1: Obtain the user's subjective sleep quality score while using the pillow to be tested: The Pittsburgh Sleep Quality Index (PSQI) questionnaire is used. Users complete the questionnaire after using the pillow to be evaluated for a preset period of time. The user's sleep quality score is calculated based on the questionnaire results and serves as a subjective reference benchmark for comfort evaluation. The preset period of 7-14 days ensures that the user adapts to the pillow to be tested and guarantees the authenticity and reliability of the subjective score. Example: 50 subjects are recruited, and each subject uses the pillow to be tested for 10 consecutive days. After 10 days, the subjects complete the Pittsburgh Sleep Quality Index (PSQI) questionnaire to obtain the subjective sleep score of the pillow to be tested. The questionnaire includes 7 dimensions: sleep quality, sleep onset time, sleep duration, sleep efficiency, sleep disorders, hypnotic drugs, and daytime functioning. Each dimension is scored from 0 to 3 points, with a total score range of 0-21 points. The relationship between PSQI total score and sleep quality is as follows: PSQI 0–5: very good sleep quality; PSQI 6–10: fair sleep quality; PSQI 11–15: average sleep quality; PSQI 16–21: very poor sleep quality.

[0021] S2. Collect three types of objective characteristic parameters related to the balance of the pillow core and the force line. These three objective characteristic parameters include cervical spine morphology maintenance, pressure distribution, and muscle relaxation. The specific collection method is as follows: S21. Collect cervical spine morphology maintenance parameters: Method for collecting data on lateral cervical spine morphology maintenance: The angle between the cervical spine centerline and the horizontal plane when the subject lies on their side with the pillow being tested, as measured by a three-dimensional optical motion capture system. included angle The smaller the value, the better the cervical spine shape is maintained when using this pillow.

[0022] Marker points of a three-dimensional optical motion capture system were affixed to the occipital protuberance, the spinous processes of the first, third, fifth, and seventh cervical vertebrae of the subject's cervical spine, and designated M1-M5 respectively. The subject was placed supine on a horizontally positioned bed in the laboratory, with their body parallel to the zOy plane. The angle between the cervical spine centerline and the horizontal plane was determined when the subject was supine. .

[0023] The table below shows the test results of 8 test subjects (numbered 1-8) lying on their sides on ergonomic pillow cores and ordinary pillows (the actual number of participants was 50; due to the large amount of data and the fact that the test results of 8 test subjects are sufficient to reflect the situation, only the test results of 8 test subjects (numbered 1-8) will be shown below): Method for collecting data on cervical spine morphology maintenance while supine: The forward tilt angle of the neck when the subject is lying supine with the pillow being tested was measured using a three-dimensional optical motion capture system. The forward tilt angle of the neck when the subject is upright Using eigenvalues Compare and Differences between them, eigenvalues The smaller the value, the better the cervical spine posture is maintained when using the pillow core while lying supine.

[0024] Marker points for the 3D optical motion capture system were affixed to the subject's chin and cervical fossa, denoted as m1 and m2, respectively. The subject was placed supine on a horizontally positioned bed in the laboratory, with their body parallel to the zOy plane. The forward tilt angle of the subject's neck while supine was [value missing]. Simultaneously, with the coronal plane of the subject parallel to the zOy plane when standing upright, the forward tilt angle of the neck when the subject is standing is... Using eigenvalues Compare and Differences between them, eigenvalues The smaller the value, the better the cervical spine posture is maintained when using the pillow core while lying supine. The table below shows the characteristic values ​​of eight test subjects (numbered 1-8) lying supine on ergonomic pillow cores and ordinary pillows. Test results: < ,and A value closer to 0 indicates that the ergonomic pillow is better able to maintain the normal curvature of the cervical spine when lying on your back.

[0025] The present invention uses different evaluation methods for side sleeping and back sleeping, so that the test results are closer to the real feeling.

[0026] S22. Acquisition of pressure distribution performance parameters: The specific steps are as follows: (1) Place a pressure distribution testing system on the pillow core to be tested and test the pressure distribution value of the subject on the pillow core. The testers here are the same testers recruited in step S1. Note that three sleeping positions are required: supine, lateral, and prone. The data for the three sleeping positions will be measured later.

[0027] (2) The measured pressure distribution values ​​are mathematically processed to calculate characteristic values ​​such as maximum pressure, average pressure, and contact area. Among them, the maximum pressure... , represents the maximum value among the measured pressure values. Average pressure This represents the average of the measured pressure values. Contact area It is the contact area between the test subject and the pillow core. ; The number of pressure distribution test points, This represents the resolution of the pressure distribution testing system. Maximum pressure indicates whether there is pressure concentration in certain areas. Some experts suggest that the pressure threshold on the human skin surface should not exceed 30 mmHg (4 kPa), otherwise blood circulation in the subcutaneous muscles and soft tissues cannot be guaranteed, leading to pressure sores. If abnormally high pressure points appear in certain areas, it indicates that the pillow core provides too much support to some parts of the body while providing too little support to areas that need it, resulting in an unbalanced pressure distribution. In this case, the pillow core design does not meet the requirements of a force line balance system. Excessive average pressure indicates that the pillow core is too hard overall and has poor pressure distribution.

[0028] Some test results are shown in the figure below. Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 As shown, the test statistics are as follows: As shown in the table above, the ergonomic pillow has lower maximum pressure, average pressure, and the difference between maximum and average pressure than the ordinary pillow. This indicates that the ergonomic pillow provides better support for the head, neck, and shoulders, resulting in a more even distribution of pressure.

[0029] Meanwhile, from the pressure distribution diagram ( Figures 1-6 As can be seen from the data, when using an ergonomic pillow, the pressure on the head is lower, the pressure distribution on the head, neck and shoulders is more even, and the neck can be effectively supported. In contrast, when using an ordinary pillow, there is a concentration of pressure on the head, and the neck is not supported.

[0030] S23. Acquiring muscle relaxation parameters: Using a surface electromyography (EMG) sensor, the EMG signals of the sternocleidomastoid, trapezius, splenius cervicis, and / or levator scapulae muscles are acquired when the user is supine. After preprocessing the EMG signals (filtering, denoising, and normalization), the evaluation indicators are time-domain correlation indicators (such as root mean square value RMS and integrated EMG iEMG) and frequency-domain correlation indicators (such as average power frequency MPF and median frequency MF).

[0031] During the test, the electromyographic (EMG) activity levels of the main relevant muscles were measured before the subject used the pillow and after lying still on the pillow for a period of time (e.g., 20 minutes). The root mean square (RMS) and mean power frequency (MPF) of the EMG signals were extracted as core characteristic parameters of muscle relaxation. The RMS reflects the amplitude of the EMG signal; a smaller value indicates lower muscle contraction and better relaxation. The MPF reflects the frequency distribution of the EMG signal; a higher value indicates better muscle relaxation. The specific calculation formula is as follows: These are electromyography (EMG) signal sample values; Indicates the total number of values; It refers to the frequency on the frequency axis; It is the power spectral density of the electromyographic signal.

[0032] An ideal state of force line balance should significantly reduce the resting tension of these muscles, manifested as a decrease in the level of electromyographic activity; at the same time, an ideal state of force line balance should increase the rate of change of electrical potential in muscle activity, manifested as an increase in electromyographic frequency.

[0033] This validation used the MPF (Mean Frequency Detection) value of electromyography (EMG) signals, which represents the average value of the frequency range with the highest power density in the spectrum, reflecting the main distribution frequency of EMG signal energy. MPF is an important indicator for assessing muscle fatigue. During muscle fatigue, the value usually decreases, which is closely related to physiological changes during muscle activity. Therefore, by monitoring changes in MPF, the degree of muscle fatigue can be determined. In an environment of 21±1℃ and 50±5%RH, the trapezius, splenius cervicis, and sternocleidomastoid muscles (e.g., [missing information]) were monitored in 8 subjects before sleep, 20 minutes after sleep onset, and throughout the night. Figure 7 Changes in electromyographic signals of muscle groups (as shown in the image), with some test results as follows: Figure 8 As shown, the test results are statistically summarized below: Based on the table above, the following conclusions can be drawn: Compared to ordinary pillows, ergonomic pillows showed higher MPF values ​​for the trapezius, splenius cervicis, and sternocleidomastoid muscles at all test points, indicating superior muscle relaxation performance. Furthermore, as sleep time increased, the MPF values ​​of both types of samples fluctuated or slightly increased in most muscles, but the ergonomic pillow consistently maintained a higher MPF level. This suggests that the ergonomic pillow better meets the requirements of the pillow core's force line balance system in terms of muscle relaxation.

[0034] S3. Establish a BP neural network evaluation model: Using the lateral cervical spine shape maintenance degree, supine cervical spine shape maintenance degree, maximum pressure, average pressure, contact area, root mean square value of electromyography (RMS), and average power frequency of electromyography (MPF) collected in step S2 as input feature parameters, and the sleep quality score obtained in step S1 as output parameter, construct a BP neural network model.

[0035] The BP neural network model includes an input layer, a hidden layer, and an output layer. The input layer has 7 neurons (corresponding to 7 input feature parameters: supine cervical spine shape maintenance, supine cervical spine shape maintenance, maximum pressure, average pressure, contact area, electromyography RMS, and electromyography MPF). The output layer has 1 neuron (corresponding to the sleep quality score, using a linear activation function). The number of neurons in the hidden layer is determined by trial and error, ranging from 10 to 20. During model training, gradient descent is used to optimize network weights and thresholds, with a learning rate of 0.01-0.05 and 1000-5000 iterations, until the model error is less than a preset threshold (0.001). This completes the model training, resulting in a trained BP neural network evaluation model. Example: 50 sets of data (7 input feature parameters + 1 output parameter) were divided into a training set (40 sets) and a test set (10 sets). Gradient descent was used to optimize the network weights and thresholds. The learning rate was set to 0.03, and the number of iterations was 3000 until the model error was less than 0.001, completing the model training. After training, the model was validated using the test set data. The validation results showed that the error between the sleep quality score output by the model and the actual score was less than 0.5 points, and the model accuracy met the evaluation requirements.

[0036] S4. Pillow Core Comfort Evaluation: For other pillow cores to be evaluated, repeat step S2 to collect seven input feature parameters: lateral cervical spine shape maintenance, supine cervical spine shape maintenance, maximum pressure, average pressure, contact area, root mean square value of electromyography (RMS), and average power frequency of electromyography (MPF). Input these parameters into the trained BP neural network evaluation model to obtain the sleep quality score for each tester. Take the average score as the final comfort score for the pillow core. The model outputs the corresponding sleep quality score, and the pillow core comfort is quantitatively evaluated based on this sleep quality score.

[0037] The comfort evaluation rules are as follows: Predicted PSQI 0–5 points: excellent comfort; predicted PSQI 6–10 points: good comfort; predicted PSQI 11–15 points: average comfort; predicted PSQI 16–21 points: poor comfort.

[0038] A pillow core comfort evaluation system based on a force line balance system is used to implement the aforementioned pillow core comfort evaluation method based on a force line balance system. The system includes a data acquisition module, a data preprocessing module, a model training module, and an evaluation module. The modules are connected through a data interface to realize data transmission and interaction.

[0039] The data acquisition module is used to collect the user's subjective sleep quality score and three types of objective characteristic parameters when using the pillow core, including a questionnaire acquisition unit, a cervical spine morphology detection unit, a pressure distribution detection unit, and an electromyography signal acquisition unit.

[0040] The questionnaire collection unit is used to present the Pittsburgh Sleep Quality Index (PSQI) questionnaire, receive questionnaire data filled out by users, and calculate a sleep quality score based on the questionnaire data. The questionnaire collection unit uses a tablet computer terminal with a built-in Pittsburgh Sleep Quality Index (PSQI) questionnaire program. Testers fill out the questionnaire through the terminal, and the program automatically calculates and outputs the sleep quality score, while storing the score data in a database.

[0041] The cervical spine morphology detection unit uses a three-dimensional optical motion capture system to detect the three-dimensional spatial coordinates of marker points pasted on the cervical spine in supine and lateral positions. Preferably, a Qualisys three-dimensional motion capture system with a sampling frequency of 2000Hz is used.

[0042] The pressure distribution detection unit employs an array-type pressure distribution testing system to detect pressure distribution data when the user uses the pillow core. Preferably, the sensor array density is 32×42, the pressure detection range is 0-120 mmHg, the accuracy is ±10%FS, and the sampling frequency is 20Hz, enabling real-time acquisition of pressure distribution data.

[0043] The electromyography (EMG) signal acquisition unit uses a surface electromyography (SEMG) sensor to acquire EMG signals from the user's neck muscles and output raw EMG signal data. Preferably, the sampling frequency is 2000Hz and the input impedance is ≥10MΩ.

[0044] The data preprocessing module is used to process the raw data collected by the data acquisition module, including 1) the angle between the cervical spine centerline and the horizontal plane. The calculation includes: 1) calculating the maximum pressure, average pressure, and contact area of ​​the pressure distribution parameters; 2) filtering, denoising, and normalizing the electromyographic signals to extract the root mean square (RMS) and average power frequency (MPF) of the electromyographic signals. Preferably, the data preprocessing module uses a microcontroller with a built-in signal processing program, which can process the cervical spine morphology maintenance data and pressure distribution data to obtain the angle α between the cervical spine centerline and the horizontal plane when lying on the side and the characteristic value of the cervical forward tilt angle when lying on the back. The maximum pressure, average pressure, and contact area are measured. The electromyographic (EMG) signals are filtered, denoised, and normalized to extract the RMS and MPF parameters. After preprocessing, the data is transmitted to the model training module.

[0045] The model training module is used to construct a BP neural network model. It receives input feature parameters (lateral cervical spine shape maintenance, supine cervical spine shape maintenance, maximum pressure, average pressure, contact area, RMS electromyography, MPF electromyography) and output parameters (sleep quality score) from the data preprocessing module. It then trains and optimizes the BP neural network model to obtain a trained BP neural network evaluation model. Preferably, the model training module uses an industrial computer with a built-in BP neural network training program. It can receive data transmitted from the data preprocessing module, construct the BP neural network model, complete the training, optimization, and validation of the model, store the trained model in a model database, and iteratively update the model based on new test data to improve model accuracy.

[0046] The evaluation module receives preprocessed input feature parameters of the pillow core to be evaluated, inputs them into a trained BP neural network evaluation model, obtains the sleep quality score output by the model, outputs a comfort evaluation result according to the scoring criteria, and stores and displays the evaluation result. Preferably, the evaluation module includes a data input unit, a model calling unit, and a result display unit; the data input unit receives feature parameter data of the pillow core to be evaluated; the model calling unit calls the trained BP neural network evaluation model in the model training module to process the input data and output a sleep quality score; the result display unit uses an LCD screen to display the sleep quality score and the corresponding comfort level, and can also export the evaluation result to an Excel file for easy data statistics and analysis.

[0047] The evaluation system of this invention is simple to operate and highly automated, and can quickly complete data collection, preprocessing, model training and comfort evaluation. It is suitable for scenarios such as pillow core product development, quality testing and market supervision.

[0048] The foregoing has shown and described the basic principles and main features of the present invention, as well as its advantages. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for evaluating the comfort of a pillow core based on a force line balance system, characterized in that, Includes the following steps: Step S1: Obtain the user's subjective sleep quality score when using the pillow core to be tested; Step S2: Collect three types of objective characteristic parameters related to the balance of the pillow core and the force line. The three types of objective characteristic parameters include the cervical spine shape maintenance degree, pressure distribution performance, and muscle relaxation degree. Step S3: Establish a BP neural network evaluation model: Using the lateral cervical spine shape maintenance degree, supine cervical spine shape maintenance degree, maximum pressure, average pressure, contact area, root mean square value of electromyography, and average power frequency of electromyography collected in step S2 as input feature parameters, and the sleep quality score obtained in step S1 as output parameters, construct a BP neural network model. Step S4, Pillow Core Comfort Evaluation: For other pillow cores to be evaluated, repeat step S2 to collect seven input feature parameters: lateral cervical spine shape maintenance, supine cervical spine maintenance, maximum pressure, average pressure, contact area, root mean square value of electromyography, and average power frequency of electromyography. Input these parameters into the trained BP neural network evaluation model to obtain the sleep quality score for each tester. Take the average score as the final comfort score for the pillow core. The model outputs the corresponding sleep quality score, and the pillow core comfort is quantitatively evaluated based on this sleep quality score.

2. The pillow core comfort evaluation method based on a force line balance system according to claim 1, characterized in that, The Pittsburgh Sleep Quality Index questionnaire was used, allowing users to complete the questionnaire after using the pillow core to be evaluated for a preset period of time. The subjective sleep score of the pillow core to be tested was calculated based on the questionnaire results.

3. The pillow core comfort evaluation method based on a force line balance system according to claim 1, characterized in that, Method for collecting data on lateral cervical spine morphology maintenance: The angle between the cervical spine centerline and the horizontal plane when the subject lies on their side with the pillow being tested, as measured by a three-dimensional optical motion capture system. included angle The smaller the size, the better the cervical spine posture is maintained when using this pillow core; Method for collecting data on cervical spine morphology maintenance while supine: The forward tilt angle of the neck when the subject is lying supine with the pillow being tested was measured using a three-dimensional optical motion capture system. The forward tilt angle of the neck when the subject is upright Using eigenvalues Compare and Differences between them, eigenvalues The smaller the value, the better the cervical spine posture is maintained when using the pillow core while lying supine.

4. The pillow core comfort evaluation method based on a force line balance system according to claim 3, characterized in that, Marker points of a three-dimensional optical motion capture system were attached to the occipital protuberance (M1) and the spinous process (M5) of the seventh cervical vertebra on the subject's cervical spine. The subject was then placed on a horizontally positioned bed in the laboratory. The angle between the cervical spine centerline and the horizontal plane was measured when the subject was lying on their side. .

5. The pillow core comfort evaluation method based on a force line balance system according to claim 3, characterized in that, Marker points of the 3D optical motion capture system were affixed to the subject's chin and cervical fossa, denoted as m1 and m2 respectively. The subject was then laid supine on a horizontally placed bed in the laboratory, with the subject's neck tilted forward at a certain angle. At the same time, the subject was asked to stand upright, and the forward tilt angle of the subject's neck when standing upright was [value missing]. Using eigenvalues Compare and Differences between them, eigenvalues The smaller the size, the better the cervical spine posture is maintained when lying supine using this pillow. .

6. The pillow core comfort evaluation method based on a force line balance system according to claim 1, characterized in that, The method for collecting pressure distribution parameters includes the following steps: Step (1) Place the pressure distribution testing system on the pillow core to be tested and test the pressure distribution value of the subject on the pillow core to be tested; Step (2) performs mathematical processing on the measured pressure distribution values ​​to calculate the maximum pressure. Average pressure Contact area Among them, the maximum pressure The average pressure is the maximum value among the measured pressure values. The average value of the measured pressure, and the contact area. It is the contact area between the test subject and the pillow core.

7. The pillow core comfort evaluation method based on a force line balance system according to claim 1, characterized in that, Methods for collecting muscle relaxation parameters: Surface electromyography (EMG) sensors were used to collect EMG signals from the user's sternocleidomastoid, trapezius, splenius cervicis, and / or levator scapulae muscles. After preprocessing the EMG signals, the evaluation indicators were time-domain and frequency-domain correlation indicators. The time-domain correlation indicator was the root mean square (RMS) value or integrated electromyography (iEMG), and the frequency-domain correlation indicator was the average power frequency (MPF) or median frequency (MF).

8. The method for evaluating pillow core comfort based on a force line balance system according to claim 1, characterized in that, The BP neural network model includes an input layer, a hidden layer, and an output layer. The input layer has 7 neurons, corresponding to 7 input feature parameters: lateral cervical spine shape maintenance, supine cervical spine shape maintenance, maximum pressure, average pressure, contact area, electromyography (RMS), and electromyography (MPF). The output layer has 1 neuron, corresponding to the sleep quality score, and uses a linear activation function. The number of neurons in the hidden layer is determined by trial and error, ranging from 10 to 20. During model training, gradient descent is used to optimize network weights and thresholds, with a learning rate of 0.01-0.05 and 1000-5000 iterations, until the model error is less than the preset threshold, completing the model training and obtaining the trained BP neural network evaluation model.

9. A pillow core comfort evaluation system based on a force line balance system, characterized in that, It includes a data acquisition module, a data preprocessing module, a model training module, and an evaluation module; The data acquisition module is used to collect the user's subjective sleep quality score, cervical spine morphology detection unit, pressure distribution detection unit and electromyography signal acquisition unit when using the pillow core; The data preprocessing module is used to process the raw data collected by the data acquisition module, including cervical spine morphology maintenance data and pressure distribution data, to obtain the angle α between the cervical spine centerline and the horizontal plane when lying on the side and the characteristic values ​​of the cervical spine forward tilt angle when lying on the back. Maximum pressure, average pressure, contact area; The electromyography (EMG) signals were filtered, denoised, and normalized to extract the EMG RMS and MPF parameters. After preprocessing, the data is transferred to the model training module; The model training module is used to construct a BP neural network model, receive the lateral cervical spine shape maintenance degree, supine cervical spine shape maintenance degree, maximum pressure, average pressure, contact area, electromyography RMS, and electromyography MPF output by the data preprocessing module, output sleep quality score, train and optimize the BP neural network model, and obtain a trained BP neural network evaluation model. The evaluation module is used to receive the preprocessed input feature parameters corresponding to the pillow core to be evaluated, input them into the trained BP neural network evaluation model, obtain the sleep quality score output by the model, output the comfort evaluation result according to the scoring criteria, and store and display the evaluation result.

10. The pillow core comfort evaluation system based on a force line balance system according to claim 9, characterized in that, The cervical spine morphology detection unit uses a three-dimensional optical motion capture system to detect the three-dimensional spatial coordinates of the marker points pasted on the cervical spine in the user's supine and lateral states. The pressure distribution detection unit adopts an array-type pressure distribution testing system to detect the pressure distribution data when the user uses the pillow core; The electromyography (EMG) signal acquisition unit uses a surface electromyography (SEMG) sensor to acquire EMG signals from the user's neck muscles and output raw EMG signal data.

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