A method and system for testing the chewing ability of the elderly based on texture parameters

Abstract

The application relates to the technical field of oral function test, and particularly discloses a method and system for testing chewing ability of the elderly based on texture parameters, which comprises the following steps: texture detection of multiple types of food, obtaining hardness, elasticity and resilience, calculating a chewing coefficient according to a preset weight relationship, dividing chewing difficulty levels according to the chewing coefficient and texture parameter distribution, forming standard texture parameters, selecting and preprocessing test samples according to the standard texture parameters, providing the test samples to subjects in an order of increasing difficulty, collecting chewing force signals and chewing action time sequences, screening effective chewing segments, detecting particle size information of chewing particles, and determining a chewing ability level in combination with the effective chewing segments and the particle detection results. The application continuously cooperates texture grading, process screening and particle detection, so that the test sample level, the chewing process and the post-chewing state are kept corresponding, and the chewing ability test result has traceable basis.

Description

Technical Field

[0001] This invention relates to the field of oral function testing technology, specifically to a method and system for testing the chewing ability of elderly people based on texture parameters. Background Technology

[0002] The field of oral function testing technology typically focuses on testing oral activities such as occlusion, tongue movement, chewing process, and swallowing coordination. It utilizes sensors, testing instruments, terminal programs, and storage media to collect data on oral movement states, force changes, and sample handling, and completes data transmission, recording, and retrieval between the testing end, terminal, and server. Traditional methods and systems for testing the chewing ability of the elderly refer to technical approaches for functional testing of the oral chewing process in older adults. Typically, the subject chews a standard sample according to a prescribed method, and the chewing process and sample state are acquired through occlusion testing instruments, image acquisition devices, or texture testing devices. The terminal program reads, compares, and records data based on the subject's information, testing procedures, and preset judgment conditions, and the test process and results are stored locally or on a server.

[0003] Current tests on chewing ability in the elderly are mainly based on natural foods and artificial observation. The test samples are affected by variety, maturity, processing method and storage conditions. There is no unified correspondence between chewing difficulty and texture parameters. The recording standards are inconsistent between different test batches. When the same subject is retested, it is difficult to keep the sample state and chewing process consistent. There is no continuous verification between the subject's subjective feelings, the state of chewed particles and the test stopping conditions. The matching basis between test results and the appropriate food level is not stable enough. The dietary recommendations are scattered. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for testing the chewing ability of the elderly based on texture parameters. By coordinating food texture parameter grading, test sample pretreatment, chewing process signal screening, and chewing particle detection, a corresponding relationship is established between the chewing difficulty level, the subject's chewing process, and the particle state after chewing, providing a relatively stable test basis for determining the chewing ability level of the elderly.

[0005] To achieve the above objectives, the present invention provides a method for testing the chewing ability of elderly people based on texture parameters, comprising the following steps:

[0006] Texture testing is performed on various types of food to obtain hardness, elasticity, and resilience. The chewing coefficient is calculated according to a preset weighting relationship. Based on the chewing coefficient and the distribution relationship of hardness, elasticity, and resilience, chewing difficulty levels are divided to form standard texture parameters corresponding to each chewing difficulty level.

[0007] Test samples were selected according to the standard texture parameters. After pretreatment with consistent temperature and placement time, the test samples were provided to the subjects for chewing in order of increasing chewing difficulty.

[0008] During the chewing test sample, sensors synchronously collect chewing force signals and chewing action sequences in real time, setting peak force thresholds and action interval thresholds. When multiple peaks of the chewing force signal within a continuous time period meet the peak force threshold, and the intervals between adjacent actions in the chewing action sequence are all within the action interval threshold range, the continuous time period is recorded as a valid chewing segment. When the peak value of the chewing force signal does not reach the peak force threshold, or the intervals between adjacent actions in the chewing action sequence exceed the action interval threshold range, the continuous time period is recorded as an invalid chewing segment and removed from subsequent analysis.

[0009] Collect the test samples after chewing, detect the particle size distribution, average particle size, and proportion of particles within a preset particle size range, and determine the subject's corresponding chewing ability level by combining the total duration and / or number of multiple effective chewing segments.

[0010] When the subject gives a stop signal that they can no longer chew, the subsequent test at a higher level of chewing difficulty is stopped, and the highest level of chewing difficulty corresponding to the effective chewing segment completed before the stop signal is taken as the final chewing ability level.

[0011] Furthermore, the process of conducting texture testing on multiple types of food includes: establishing test batches for multiple types of food according to food category; obtaining the hardness, elasticity, and resilience of candidate foods within the same test batch; conducting at least two texture tests on the same candidate food and calculating the average values ​​of hardness, elasticity, and resilience; when the difference between each test result of the same candidate food and the average value falls within the allowable deviation range, the average value is used as the texture parameter of the candidate food; when the difference exceeds the allowable deviation range, the texture test is repeated on the candidate food.

[0012] Furthermore, the process of calculating the chewing coefficient includes: assigning hardness weight, elasticity weight, and resilience weight according to the correspondence between hardness, elasticity, and resilience in chewing difficulty; multiplying the hardness, elasticity, and resilience of the same candidate food by the hardness weight, elasticity weight, and resilience weight respectively, and then summing them to obtain the chewing coefficient of the candidate food; arranging the candidate foods from low to high according to the chewing coefficient, and dividing the chewing difficulty level according to the distribution range of hardness, elasticity, and resilience corresponding to the arranged candidate foods, and obtaining the median value of hardness, elasticity, and resilience within each chewing difficulty level as the standard texture parameter.

[0013] Furthermore, the process of classifying test samples according to the chewing coefficient and standard textural parameters includes: comparing the hardness, elasticity, and resilience of the same candidate food with the standard textural parameters corresponding to each chewing difficulty level; when the hardness, elasticity, and resilience all fall within the parameter range of the same chewing difficulty level, the candidate food is determined as the test sample of that chewing difficulty level; when the hardness, elasticity, and resilience do not fall within the parameter range of the same chewing difficulty level, the test level of the candidate food is determined according to the chewing difficulty level corresponding to the chewing coefficient, and the textural parameters that do not fall within the parameter range are recorded.

[0014] Furthermore, the pretreatment process of the test samples includes: placing test samples of the same chewing difficulty level under the same temperature conditions for a set time; after the storage is completed, removing the test samples and recording the removal time; when the interval between the removal time and the start time of the chewing test does not exceed the set placement time, the test sample is used for this chewing test; when the interval between the removal time and the start time of the chewing test exceeds the set placement time, the test sample is removed from this chewing test.

[0015] Furthermore, when providing chewing samples to subjects in order of increasing chewing difficulty, the test samples used in this test and their corresponding chewing difficulty levels are first determined. Then, chewing tests are conducted in order of increasing chewing difficulty levels. Before each chewing difficulty level test begins, the subject number, test sample number, and test start time are recorded. After each chewing difficulty level test is completed, the test end time is recorded, and the test sample number, chewing force signal, and chewing action sequence are included in the same test record.

[0016] Furthermore, when screening valid chewing segments, the chewing force signal and chewing action timing of the same test record are read to obtain the peak value of the chewing force signal and the time interval between adjacent chewing actions. When the peak value of the chewing force signal reaches the peak force condition and the time interval between adjacent chewing actions falls into the action interval condition, the corresponding time period is determined as a valid chewing segment. When the peak value of the chewing force signal does not reach the peak force condition, or the time interval between adjacent chewing actions does not fall into the action interval condition, the corresponding time period is determined as an invalid chewing segment.

[0017] Furthermore, when detecting the particle size distribution, average particle size, and proportion of particles within a preset particle size range of chewable particles, all test samples after chewing are collected, and unchewed residues are removed to obtain chewable particles. The chewable particles are then spread evenly in the detection area, and the particle size distribution and average particle size are obtained using an image acquisition device or a laser particle size analyzer. The proportion of particle number or particle area is calculated according to the preset particle size range, and the particle size distribution, average particle size, proportion of particle number or particle area are included in the same particle detection record along with the test sample number and effective chewing fragment.

[0018] Furthermore, when determining the chewing ability level, firstly, based on the particle detection record, it is determined whether the chewing particles under the same chewing difficulty level meet the particle determination condition. Then, based on the effective chewing segments in the particle detection record, it is determined whether the chewing process meets the test completion condition. When both the particle determination condition and the test completion condition are met, the corresponding chewing difficulty level is taken as the candidate chewing ability level. When multiple candidate chewing ability levels are consecutively established, the candidate chewing ability level with the highest level is taken as the chewing ability level. When the subject issues a stop signal, the highest candidate chewing ability level that was established before the stop signal is taken as the chewing ability level.

[0019] The present invention also provides a chewing ability testing system for the elderly based on texture parameters, including a texture detection device, a chewing process sensor, a particle detection device, a testing terminal, and a storage unit.

[0020] The texture testing equipment is used to obtain the hardness, elasticity, and resilience of food. The testing terminal is used to calculate the chewing coefficient according to a preset weighting relationship, and classify the chewing difficulty level according to the chewing coefficient and the distribution relationship of hardness, elasticity, and resilience, forming standard texture parameters corresponding to each chewing difficulty level.

[0021] The testing terminal is also used to determine the test sample and test sequence according to the standard texture parameters, and to control the chewing process sensor to synchronously collect chewing force signals and chewing action timing during the subject's chewing of the test sample.

[0022] The test terminal is also used to set a peak force threshold and an action interval threshold, and in response to the chewing force signal satisfying the peak force threshold and the chewing action sequence satisfying the action interval threshold, to record the corresponding continuous time period as a valid chewing segment, and in response to the condition not being met, to record the corresponding continuous time period as an invalid chewing segment and remove it.

[0023] The particle detection device is used to detect the particle size distribution, average particle size, and proportion of particles within a preset particle size range of the test sample after chewing. The testing terminal is also used to determine the chewing ability level by combining multiple effective chewing segments and particle detection results, and when it receives a stop signal from the subject, it takes the highest chewing difficulty level corresponding to the effective chewing segment completed before the stop signal as the final chewing ability level and stops subsequent tests.

[0024] The storage unit is used to associate and save standard texture parameters, chewing process data, particle detection results, and chewing ability levels.

[0025] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following:

[0026] In this invention, by obtaining hardness, elasticity, and resilience during the food texture testing stage and calculating the chewing coefficient, a unified quantitative basis for chewing difficulty levels is established, and the correspondence between test sample selection and level is clear. Pre-treatment with consistent temperature and placement time reduces sample state differences. Effective chewing segments are screened using chewing force signals and chewing action timing, excluding chewing processes that do not meet the peak force conditions or action interval conditions from level judgment. This, combined with particle detection results, forms a chewing ability level, ensuring that the test conclusion is simultaneously constrained by sample texture, chewing process, and post-chewing particle state. A stop signal terminates higher-level tests, ensuring the test process corresponds to the actual state experienced by the test subject. Attached Figure Description

[0027] Figure 1 This is the main flowchart of the chewing ability test for the elderly according to the present invention;

[0028] Figure 2 This is a schematic diagram illustrating the detection of food texture parameters according to the present invention;

[0029] Figure 3 This is a data flow diagram illustrating the chewing difficulty level classification of this invention;

[0030] Figure 4 This is a schematic diagram illustrating the effective chewing fragment screening and particle detection record formation of the present invention;

[0031] Figure 5 This is a schematic diagram illustrating the determination of chewing ability levels according to the present invention;

[0032] Figure 6 This is a schematic diagram of the chewing ability testing system for the elderly according to the present invention. Detailed Implementation

[0033] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0034] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0035] Example 1, please refer to Figures 1 to 5This embodiment provides a method for testing the chewing ability of elderly people based on texture parameters. This method is used in oral function testing scenarios to test the chewing ability of elderly subjects. The testing process is based on the texture parameters of various types of food. First, food chewing difficulty levels and standard texture parameters are established. Then, test samples are selected according to the standard texture parameters. Signal acquisition and effective fragment screening of the subject's chewing process are performed, and the chewing ability level is determined by combining the chewing particle detection results. In this embodiment, the subjects are elderly people aged 60 years and above. Before the test, the subject's number, age group, denture wearing status, and self-reported chewing discomfort are recorded. The above information is only stored as basic information for the same test record and is not used as a substitute for the determination of chewing ability level.

[0036] S1 performs texture testing on multiple types of food to obtain hardness, elasticity, and resilience, and calculates the chewing coefficient according to a preset weighting relationship. Based on the chewing coefficient and the distribution relationship of hardness, elasticity, and resilience, it classifies the chewing difficulty level and forms standard texture parameters corresponding to each chewing difficulty level.

[0037] S101, food is categorized into testing batches for staple foods, vegetable dishes, meat, egg and soy products, fruits, and snacks. Representative foods are selected from each testing batch as candidate foods. The original disclosure materials state that each food category has at least 15 candidate foods, totaling 100 candidate foods. Testing batches are used to record the category to which the candidate foods belong, the testing order, and the attribution of texture testing results, enabling subsequent chewing difficulty level classification to be traced back to the candidate food category and testing source. In this embodiment, the total number of candidate foods is 100, including 20 staple foods, 20 vegetable dishes, 20 meat, egg and soy products, 20 fruits, and 20 snacks. Testing batches are established for each food category, and the testing batch number is stored corresponding to the candidate food number. The candidate food number is formed by combining the food category code and the sequence number: staple foods correspond to Z01 to Z20, vegetable dishes to V01 to V20, meat, egg and soy products to M01 to M20, fruits to F01 to F20, and snacks to S01 to S20.

[0038] S102, a texture analysis device is used to perform a compression test on the candidate food in TPA mode. The test speed is 1 mm / s, and the compression ratio is 50%. During the compression test, the texture analysis device obtains the hardness, elasticity, and resilience of the candidate food. Hardness characterizes the resistance state of the candidate food under pressure, elasticity characterizes the ability of the candidate food to recover its shape after compression, and resilience characterizes the degree of recovery of the candidate food after continuous compression. The hardness, elasticity, and resilience obtained by the texture analysis device are stored corresponding to the candidate food name, food category, and test batch. In this embodiment, the test speed in TPA mode is 1 mm / s, the compression ratio is 50%, and the trigger force and probe type are set according to the conventional TPA test conditions of the texture analysis device. The same candidate food is prepared with the same thickness or the same single-piece state before testing and placed at the center of the test platform of the texture analysis device. Hardness is recorded as the maximum force value during the first compression process, elasticity is recorded as the time history or displacement response corresponding to the sample's shape recovery after the first compression, and resilience is recorded as the recovery state of the second compression response relative to the first compression response during two consecutive compression processes.

[0039] S103, set up 3 parallel tests for the same candidate food and calculate the mean values ​​of hardness, elasticity, and resilience. When the difference between each test result of the same candidate food and the mean value falls within the allowable deviation range, the mean value is used as the texture parameter of the candidate food; when the difference exceeds the allowable deviation range, the texture test of the candidate food is repeated. When repeating the texture test, the candidate food remains from the original test batch, and the newly obtained test results are used again to determine the mean value and allowable deviation range. The mean value is expressed using the arithmetic mean formula: ,in, The mean value for the same texture parameter of the same candidate food. , , These are the test values ​​of the same texture parameter obtained from three sets of parallel tests. The allowable deviation range is determined using relative deviation, expressed by the formula: ,in, denoted as the relative deviation of the i-th group's detection result from the detection mean. For the i-th group of detection results, The mean value is used as the detection mean. When the relative deviation of the three parallel tests does not exceed 10%, the mean value is used as the texture parameter of the candidate food. When the relative deviation of any parallel test exceeds 10%, the texture test is repeated on the candidate food.

[0040] In a set of test records, the three sets of hardness test values ​​for candidate food Z01 in the staple food category were 8.6N, 8.9N, and 8.8N, respectively, with a mean hardness of 8.77N. The relative deviations of the three test results from the mean hardness did not exceed 10%, therefore 8.77N was taken as the hardness of Z01. The mean elasticity test value for the same candidate food Z01 was recorded as 0.82, and the mean resilience test value was recorded as 0.45. The above test data are only used as the textural parameters of this candidate food in this test batch and are saved in correspondence with Z01, staple food category, and test batch number.

[0041] S104, according to the correspondence between hardness, elasticity, and resilience in chewing difficulty, hardness weight, elasticity weight, and resilience weight are respectively configured. The hardness weight is 0.4 to 0.6, the elasticity weight is 0.2 to 0.3, and the resilience weight is 0.2 to 0.3. The sum of the hardness weight, elasticity weight, and resilience weight is 1. The testing terminal multiplies the hardness of the same candidate food by its hardness weight, the elasticity by its elasticity weight, and the resilience by its resilience weight, and then adds the three products to obtain the chewing coefficient of the candidate food. The hardness weight, elasticity weight, and resilience weight can be determined based on the results of multiple linear regression analysis. After the weights are determined, they are used to calculate the chewing coefficient of the same batch of candidate foods. The chewing coefficient is expressed by the weighted summation formula as follows: ,in, The chewing coefficient, Hardness For elasticity, For responsiveness, As the hardness weight, For elastic weights, As a response weight, and In this embodiment, Take a value between 0.4 and 0.6. Take a value of 0.2 to 0.3. The values ​​are taken as 0.2 to 0.3; in a set of chewing coefficient calculation data, the hardness weight is taken as 0.50, the elasticity weight as 0.25, the resilience weight as 0.25, and the sum of the weights is 1.

[0042] For candidate food Z01, the hardness (H) was recorded as 8.77 N, elasticity (E) as 0.82, and resilience (R) as 0.45. With weights of 0.50, 0.25, and 0.25, the testing terminal recorded these values ​​in the same calculation record and obtained the corresponding chewing coefficient. For candidate food M08 (meat, egg, and soy products), the hardness (H) was recorded as 18.40 N, elasticity (E) as 0.61, and resilience (R) as 0.33. The testing terminal generated the chewing coefficient for M08 using the same weighting caliber. The chewing coefficients of the different candidate foods are arranged under the same weighting caliber for classification into chewing difficulty levels.

[0043] S105, the testing terminal arranges candidate foods according to their chewing coefficient from low to high, and uses the distribution range of hardness, elasticity, and resilience of the candidate foods as clustering input. K-means clustering is used to divide the candidate foods into five chewing difficulty levels. These five levels correspond to easy chewing (Level 1) to difficult chewing (Level 5). After classifying the levels, the testing terminal extracts the median values ​​of hardness, elasticity, and resilience within each chewing difficulty level as standard textural parameters corresponding to each level. These standard textural parameters include hardness benchmarks, elasticity benchmarks, and resilience benchmarks, and serve as the basis for subsequent sample adaptation. K-means clustering uses the hardness, elasticity, and resilience of the candidate foods as input fields, and the five chewing difficulty levels as the number of clusters. After clustering, the food is classified according to its chewing coefficient from low to high as easy chewing (Level 1), relatively easy chewing (Level 2), moderately chewing (Level 3), relatively difficult chewing (Level 4), and difficult chewing (Level 5). The median value of the standard texture parameter is determined using the median rule. If the number of candidate foods within the same chewing difficulty level is odd, the middle texture parameter value after sorting is taken; if the number of candidate foods is even, the average of the two middle texture parameter values ​​after sorting is taken.

[0044] In a set of standard texture parameter records, Grade 1 (easy to chew) corresponds to a median hardness of 4.5 N to 6.5 N, a median elasticity of 0.78 to 0.90, and a median resilience of 0.46 to 0.58; Grade 2 (relatively easy to chew) corresponds to a median hardness of 6.6 N to 10.0 N, a median elasticity of 0.70 to 0.82, and a median resilience of 0.40 to 0.50; and Grade 3 (medium chew) corresponds to a median hardness of 10.1 N to 16.0 N. The median values ​​for N, elasticity, and resilience are 0.60 to 0.72 and 0.32 to 0.43, respectively. For grade four (difficult to chew), the median values ​​for hardness are 16.1 N to 24.0 N, elasticity, and resilience are 0.48 to 0.62 and 0.24 to 0.34. For grade five (difficult to chew), the median values ​​for hardness are 24.1 N to 36.0 N, elasticity, and resilience are 0.35 to 0.50 and 0.16 to 0.26. These parameter ranges are used as data from the standard texture parameter table in this embodiment for reference when adapting test samples.

[0045] S2. Select test samples according to standard texture parameters and pre-treat the test samples at the same temperature and for the same placement time.

[0046] S201, the hardness, elasticity, and resilience of the same candidate food are compared with the standard textural parameters corresponding to each chewing difficulty level. When hardness, elasticity, and resilience all fall within the parameter range of the same chewing difficulty level, the candidate food is identified as the test sample for that chewing difficulty level. When hardness, elasticity, and resilience do not fall within the parameter range of the same chewing difficulty level, the testing terminal determines the test level of the candidate food according to the chewing difficulty level corresponding to the chewing coefficient, and records the textural parameters that do not fall within the parameter range. The textural parameters that do not fall within the parameter range are saved together with the test sample number for subsequent tracing of the correspondence between the test sample and the chewing difficulty level. In this embodiment, at least two test samples are selected as candidate test samples for each chewing difficulty level. For each formal test, one sample is selected from the candidate test samples of the same chewing difficulty level to enter the testing process. If one of the test samples is withdrawn from the current chewing test due to the pretreatment placement time exceeding 30 minutes, another sample is selected from the candidate test samples of the same chewing difficulty level for pretreatment.

[0047] In a set of test sample adaptation data, Z01 corresponds to Level 1 easy to chew, V06 corresponds to Level 2 relatively easy to chew, F12 corresponds to Level 3 medium chew, M08 corresponds to Level 4 relatively difficult to chew, and S17 corresponds to Level 5 difficult to chew. The above test samples are respectively configured with test sample numbers T-L1, T-L2, T-L3, T-L4 and T-L5, and are provided to the subjects to chew in the order of L1 to L5.

[0048] S202, test samples of the same chewing difficulty level are placed in a 0℃ refrigerated environment for 2 hours for stabilization. The 0℃ refrigeration environment is used to limit changes in the state of the test samples before testing, and the 2-hour stabilization time ensures that the test samples reach the same pretreatment state. Test samples of different chewing difficulty levels are all subjected to this pretreatment condition to avoid deviations in the textural state of the test samples due to different treatment states within the same testing procedure. The refrigeration environment temperature is recorded as 0℃, and the stabilization time is recorded as 2 hours. The testing terminal records the pretreatment start time when the test sample enters the refrigerated environment and the pretreatment end time when the test sample is removed, and writes the pretreatment start time, pretreatment end time, refrigerated environment temperature, and test sample number into the test sample pretreatment record.

[0049] In a set of test sample pretreatment records, test samples T-L1 to T-L5 were all pretreated in the same refrigerated environment. The pretreatment start times were recorded as 08:00, 08:05, 08:10, 08:15 and 08:20, respectively, and the pretreatment end times were recorded as 10:00, 10:05, 10:10, 10:15 and 10:20, respectively. The refrigerated environment temperature for each test sample was recorded as 0℃, and the pretreatment duration was recorded as 2 hours.

[0050] S203. After refrigeration stabilization, remove the test sample and record the removal time. After removal, place the test sample at room temperature. If the interval between the removal time and the start time of the chewing test is no more than 30 minutes, the test sample will be used for this chewing test; if the interval exceeds 30 minutes, the test sample will be excluded from this chewing test. Test samples excluded from this chewing test will not be included in the chewing process sensing and particle detection process. The interval between the removal time and the start time of the chewing test is expressed by the time difference formula: ,in, For placement time, This is the start time of the chewing test. The time for removing the test sample. When... At that time, the test sample enters the chewing test; when When the test sample is removed from the chewing test, the test sample is no longer valid.

[0051] In a set of placement time records, the removal time of test sample T-L1 was 10:00, the chewing test started at 10:18, and the placement time was 18 minutes. Test sample T-L1 entered this chewing test. The removal time of test sample T-L3 was 10:10, the chewing test started at 10:44, and the placement time was 34 minutes. Test sample T-L3 was removed from this chewing test and replaced by an alternative test sample of the same chewing difficulty level after re-preprocessing.

[0052] S3, the subjects chew the food in order of increasing chewing difficulty, and test records are established.

[0053] S301, first determine the test sample used in this test and the chewing difficulty level of the test sample, then conduct chewing tests in order of increasing chewing difficulty level. Each subject starts the test from a low chewing difficulty level, and after completing the current chewing difficulty level, proceeds to the next adjacent higher chewing difficulty level. During the test, the subject naturally chews each test sample 30 times, and all chewed particles are collected after chewing. In this embodiment, the number of natural chewing times for each chewing difficulty level is 30. The testing terminal uses 30 natural chewing times as the planned number of actions for that level of test, and saves the actual collected chewing action sequence corresponding to the planned number of actions. Each subject is tested in the same test in the order of T-L1, T-L2, T-L3, T-L4, and T-L5. After a stop signal is issued at any level, the subject will not proceed to a higher chewing difficulty level.

[0054] S302, before each chewing difficulty level test begins, the testing terminal records the subject number, test sample number, and test start time. The subject number identifies the subject participating in this test, the test sample number identifies the test sample at the current chewing difficulty level, and the test start time defines the starting point for signal acquisition during the chewing process. The subject number, test sample number, chewing difficulty level, test start time, and planned number of movements constitute the basic test fields for the same chewing difficulty level. These basic test fields maintain the same recording index as the subsequently acquired chewing force signals and chewing action timing.

[0055] In a set of basic test fields, the subject number is P001, the test sample number is T-L1, the chewing difficulty level is Level 1 (easy to chew), the test start time is 10:18, and the planned number of actions is 30. When the same subject enters Level 2 (relatively easy to chew), the test sample number is switched to T-L2, and the test start time is recorded again.

[0056] S303, after each chewing difficulty level test, the testing terminal records the test end time and includes the test sample number, chewing force signal, and chewing action sequence in the same test record. The test record is indexed by the subject number, test sample number, chewing difficulty level, test start time, and test end time, and uses the chewing force signal and chewing action sequence collected by the chewing process sensor as process data for the same test subject. The test record then proceeds to the subsequent effective chewing segment screening stage. The test end time can be triggered by any of the following conditions: completion of 30 natural chews, the subject issuing a stop signal indicating inability to continue chewing, or the testing terminal receiving a test end input; once the test end time is determined, the same test record will no longer receive new chewing force signals or chewing action sequences.

[0057] In one set of test records, after P001 completed 30 natural chews in T-L1, the test ended at 10:20; after P001 completed 30 natural chews in T-L2, the test ended at 10:25; in the T-L4 test, P001 issued a stop signal that it could not continue chewing after the 18th natural chew, the test ended at 10:38, and the T-L5 test was stopped.

[0058] S4. During the subject's chewing test sample, the chewing force signal and chewing action sequence are collected in real time by the chewing process sensor, and the effective chewing segments are screened.

[0059] S401, the chewing process sensor continuously acquires chewing force signals and chewing action timing between the test start time and the test end time. The chewing force signals form a force peak distribution according to the sampling time, and the chewing action timing forms an action interval record according to the time interval between adjacent chewing actions. The chewing force signals and chewing action timing are associated with the test records through the same subject number, test sample number, and sampling time. The sampling timestamp of the chewing process sensor is aligned with the test start time and test end time recorded by the test terminal. Only chewing force signals and chewing action timing located between the test start time and test end time are included in the valid chewing segment selection.

[0060] In a set of chewing process data, P001 recorded peak chewing force signals and intervals between adjacent movements in 30 natural chewing actions during the T-L1 test. The peak forces of the first five complete chewing actions were 42N, 45N, 44N, 46N, and 43N, with intervals of 0.82s, 0.79s, 0.85s, and 0.81s, respectively. The data from these first five complete chewing actions were used for threshold setting in this test for the same subject.

[0061] S402, the testing terminal sets the peak force threshold and the action interval threshold. The peak force threshold is used to determine whether the peak value of the chewing force signal reaches an effective chewing state, and the action interval threshold is used to determine whether the time interval between adjacent chewing actions falls within the allowable action interval range. The peak force threshold and the action interval threshold maintain the same judgment standard in the same chewing difficulty level test. In this embodiment, the peak force threshold can be determined according to the average peak force value of the first 5 complete chewing actions of the same subject in the lowest chewing difficulty level, and the action interval threshold can be determined according to the range of adjacent action intervals of the first 5 complete chewing actions; the above thresholds are derived from the initial chewing data of the same subject in this test process and are saved along with the subject number and test sample number.

[0062] In a set of threshold setting data, the average peak force of the first 5 complete chewing actions was 44N. The test terminal set the peak force threshold to 70% of this average, i.e., 30.8N. The interval between adjacent actions of the first 5 complete chewing actions was concentrated between 0.79s and 0.85s. The test terminal set the action interval threshold range to 0.50s to 1.50s. The above peak force threshold and action interval threshold range were used to filter the valid chewing segments in this test of P001.

[0063] S403, the testing terminal reads the chewing force signal and chewing action sequence from the same test record, obtaining the peak value of the chewing force signal and the time interval between adjacent chewing actions. When multiple peak values ​​of the chewing force signal within a continuous time period meet the peak force threshold, and the intervals between adjacent actions in the chewing action sequence are all within the action interval threshold range, the continuous time period is recorded as a valid chewing segment. The valid chewing segment is saved together with the subject number, test sample number, chewing difficulty level, and sampling time, and enters the subsequent chewing ability level determination process. When the number of chewing actions within a continuous time period is not less than 2, the testing terminal judges the continuous time period as a valid chewing segment; when the peak values ​​of the chewing force signals corresponding to all chewing actions within a continuous time period are not lower than the peak force threshold, and the intervals between adjacent actions are all within the action interval threshold range, the continuous time period is recorded as a valid chewing segment.

[0064] In a set of effective chewing segment screening data, the peak force of P001 during the 1st to 12th natural chewing actions in the T-L2 test was not less than 30.8N, and the interval between adjacent actions was within the range of 0.50s to 1.50s. The test terminal recorded this continuous time period as effective chewing segment A. The 13th to 22nd natural chewing actions met the same conditions, and the test terminal recorded them as effective chewing segment B. The 23rd to 30th natural chewing actions met the same conditions, and the test terminal recorded them as effective chewing segment C.

[0065] S404: When the peak value of the chewing force signal does not reach the peak force threshold, or the interval between adjacent actions in the chewing action sequence exceeds the action interval threshold range, the continuous time period is recorded as an invalid chewing segment and removed from subsequent analysis. Invalid chewing segments can be saved as test process data, but they are not included in the determination of the total duration, number, and chewing ability level of multiple valid chewing segments. Invalid chewing segments include continuous time periods where the peak force is lower than the peak force threshold, continuous time periods where the interval between adjacent actions exceeds the action interval threshold range, and signal segments whose sampling timestamps are not between the test start time and the test end time; the test terminal adds a removal mark to invalid chewing segments and retains the removal reason.

[0066] In a set of invalid chewing segment records, the peak chewing force signal of P001 during the 16th natural chewing action in the T-L4 test was 24N, which was lower than the peak force threshold of 30.8N. The test terminal recorded the corresponding time period as an invalid chewing segment and recorded the reason for removal as the peak force did not reach the peak force threshold. The action interval between the 17th and 18th natural chewing actions was 2.10s, which exceeded the action interval threshold range of 0.50s to 1.50s. The test terminal recorded the corresponding time period as an invalid chewing segment and recorded the reason for removal as the adjacent action interval exceeded the action interval threshold range.

[0067] S5, Collect the test sample after chewing and test the chewed particles.

[0068] S501: After each chewing difficulty level test, all test samples after chewing are collected. During collection, unchewed residue is removed to obtain chewable particles. These particles are associated with the corresponding subject number, test sample number, and chewing difficulty level. For the same test sample, the detection results of the chewable particles and the corresponding effective chewing fragments are grouped into the same particle detection record. Three parallel particle detections are set up for the same test sample. The particle size distribution, average particle size, and percentage of particles ≤2mm from the three parallel particle detections are taken as the average and used as the particle detection result for that test sample.

[0069] In a set of chewing particle collection records, after P001 completes the T-L1 test, all chewing particles are collected. Unchewed residual samples are removed before particle detection. After P001 completes the T-L2 test, chewing particles are collected in the same way. After P001 issues a stop signal in the T-L4 test, only test sample particles that have entered the oral cavity and completed the chewing process before the stop signal are collected. Unchewed residual samples are not included in particle detection.

[0070] S502, In this embodiment, the particle detection device uses a laser particle size analyzer. Chewing particles are placed within the detection area of ​​the laser particle size analyzer, which detects the particle size and outputs the particle size distribution and average particle size. The particle size distribution characterizes the distribution of chewing particles within different particle size ranges, while the average particle size characterizes the overall degree of particle breakage after chewing. The testing terminal reads the particle size distribution and average particle size output by the laser particle size analyzer and establishes a correspondence with the test sample number. The particle size distribution output by the laser particle size analyzer forms a distribution record of particle quantity or particle area according to the particle size range. The average particle size is formed from the detection data of all chewing particles corresponding to the same test sample. The detection output is saved in correspondence with the test sample number, subject number, and chewing difficulty level.

[0071] In a set of particle detection data, the average particle sizes of P001 after the T-L1 test were 1.42 mm, 1.50 mm, and 1.47 mm, respectively, with particles ≤2 mm accounting for 86.5%, 84.8%, and 85.7%, respectively. The average particle sizes of P001 after the T-L2 test were 1.88 mm, 1.95 mm, and 1.91 mm, respectively, with particles ≤2 mm accounting for 75.6%, 73.9%, and 74.8%, respectively. The average particle sizes of P001 after the T-L3 test were 2.36 mm, 2.42 mm, and 2.39 mm, respectively, with particles ≤2 mm accounting for 61.4%, 60.8%, and 62.1%, respectively. These three sets of parallel particle detection data form the average particle detection values ​​for the corresponding test samples.

[0072] S503, the testing terminal calculates the proportion of particles according to a preset particle size range. In the original disclosure, the preset particle size range included particles ≤2mm in diameter. The testing terminal calculates the proportion of particles ≤2mm in diameter and includes the particle size distribution, average particle size, and proportion of particles ≤2mm in diameter in the same particle detection record along with the test sample number and effective chewing fragments. The particle detection record is used to preserve the particle state of the test sample after chewing and establishes a correspondence with the effective chewing fragments in the test record. The proportion of particles ≤2mm in diameter is expressed using a proportional formula: ,in, The percentage of particles with a diameter ≤2mm. The number of particles with a diameter ≤ 2 mm. This refers to the total number of chewable particles collected from the same test sample. When using area statistics, The total area corresponding to particles with a diameter ≤2mm. The total area corresponding to all chewable particles.

[0073] In a set of particle detection records, the average proportion of particles with a diameter ≤2mm for T-L1 was 85.7%, with an average particle size of 1.46mm; the average proportion of particles with a diameter ≤2mm for T-L2 was 74.8%, with an average particle size of 1.91mm; the average proportion of particles with a diameter ≤2mm for T-L3 was 61.4%, with an average particle size of 2.39mm; the particle detection record for T-L4 was retained but not used as a direct basis for confirming the final chewing ability level because the number of effective chewing segments before the stop signal was insufficient.

[0074] S6, determine the chewing ability level based on particle detection records and effective chewing segments.

[0075] S601, the testing terminal first determines whether the chewing particles under the same chewing difficulty level meet the particle determination criteria based on the particle detection record. The particle determination criteria include particle size distribution, average particle size, and the determination criteria corresponding to the proportion of particles with a particle size ≤ 2mm. When the particle detection record meets the particle determination criteria, the chewing difficulty level enters the candidate chewing ability level judgment; when the particle detection record does not meet the particle determination criteria, the chewing difficulty level does not enter the candidate chewing ability level. In this embodiment, the particle determination criteria at least include that the proportion of particles with a particle size ≤ 2mm reaches the preset proportion requirement of the corresponding chewing difficulty level, the average particle size falls within the allowable average particle size range of the corresponding chewing difficulty level, and the particle size distribution record is consistent with the test sample number.

[0076] In a set of particle assessment criteria, Level 1 (easy to chew) corresponds to a particle size ≤2mm accounting for no less than 80%, with an average particle size no greater than 1.80mm; Level 2 (relatively easy to chew) corresponds to a particle size ≤2mm accounting for no less than 70%, with an average particle size no greater than 2.20mm; Level 3 (medium chew) corresponds to a particle size ≤2mm accounting for no less than 60%, with an average particle size no greater than 2.80mm; Level 4 (relatively difficult to chew) corresponds to a particle size ≤2mm accounting for no less than 50%, with an average particle size no greater than 3.40mm; and Level 5 (difficult to chew) corresponds to a particle size ≤2mm accounting for no less than 40%, with an average particle size no greater than 4.20mm. These particle assessment criteria and chewing difficulty levels are stored and used to determine the test results for the same subject at each level.

[0077] S602, the testing terminal then determines whether the chewing process meets the test completion conditions based on the effective chewing segments in the particle detection record. The test completion conditions are formed by the total duration and / or number of multiple effective chewing segments. When the total duration and / or number of effective chewing segments meet the test completion conditions, the chewing process under that chewing difficulty level has the process data required for judgment; when the total duration and / or number of effective chewing segments do not meet the test completion conditions, that chewing difficulty level is not considered as a candidate chewing ability level. In this embodiment, the test completion conditions include that the number of chewing actions covered by the effective chewing segments is not less than 24 out of the planned 30 actions, and the continuous time period corresponding to the effective chewing segments is located between the test start time and the test end time. Chewing actions that do not enter the effective chewing segments are not included in the test completion conditions.

[0078] In a set of test completion condition judgment data, P001 entered the effective chewing segment 30 times out of 30 natural chewing actions in the T-L1 test, meeting the test completion condition; entered the effective chewing segment 30 times out of 30 natural chewing actions in the T-L2 test, meeting the test completion condition; entered the effective chewing segment 27 times out of 30 natural chewing actions in the T-L3 test, meeting the test completion condition; and entered the effective chewing segment only 15 times out of 18 natural chewing actions in the T-L4 test, failing to meet the test completion condition of 24 times.

[0079] S603: When both the particle determination condition and the test completion condition are met simultaneously, the corresponding chewing difficulty level is used as the candidate chewing ability level. When multiple candidate chewing ability levels are consecutively met, the highest-ranking candidate chewing ability level is used as the chewing ability level. This process ensures that the chewing ability level is determined jointly by the particle state after chewing and the effective chewing segments. Candidate chewing ability levels are confirmed step by step in order from level one (easy to chew) to level five (difficult to chew). Only when the lower level up to the current level consecutively meets both the particle determination condition and the test completion condition is the current level considered a valid candidate chewing ability level; if any intermediate level does not meet the condition, the higher level thereafter is not directly used as the chewing ability level.

[0080] In the above P001 test data, T-L1, T-L2, and T-L3 all simultaneously met the particle determination conditions and test completion conditions, forming candidate chewing ability levels corresponding to Level 1 (easy to chew), Level 2 (relatively easy to chew), and Level 3 (medium chewing), respectively; T-L4 did not meet the test completion conditions and did not form a candidate chewing ability level corresponding to Level 4 (difficult to chew). Therefore, the chewing ability level of P001 is determined to be Level 3 (medium chewing).

[0081] S604, when the subject issues a stop signal indicating they cannot continue chewing, the testing terminal halts subsequent tests at higher chewing difficulty levels and uses the highest chewing difficulty level corresponding to the effective chewing segment completed before the stop signal as the final chewing ability level. The stop signal is entered into the test record and saved along with the completed chewing difficulty levels, effective chewing segments, and particle detection records. If the stop signal occurs before a chewing difficulty level test is completed, the testing terminal uses the highest candidate chewing ability level established before the stop signal as the final chewing ability level and does not initiate tests at higher chewing difficulty levels. The stop signal can be verbally indicated by the subject and entered into the testing terminal by the assessor, or it can be generated by the testing terminal receiving an end input when the current chewing difficulty level does not meet the test completion conditions. Once the stop signal is written into the test record, the testing terminal locks the completed level record for this test and stops retrieving test samples at higher chewing difficulty levels.

[0082] In the above P001 test data, the stop signal occurred during the Level 4 difficult chewing test. The highest candidate chewing ability level that had been established before the stop signal was Level 3 medium chewing. The test terminal wrote Level 3 medium chewing into the final chewing ability level field and stopped the Level 5 difficult chewing test.

[0083] S7. Record subjective evaluations and use them as supplementary records of the chewing test process.

[0084] S701, after each chewing difficulty level test, the subject rates the chewing effort, chewing comfort, and swallowing difficulty on a scale of 1 to 5. In the rating, 1 point corresponds to extremely easy, extremely comfortable, or extremely easy to swallow, and 5 points correspond to extremely difficult, extremely uncomfortable, or extremely difficult to swallow. Subjective evaluation can be completed by 3 to 5 professional assessors. The professional assessors record the chewing effort, chewing comfort, and swallowing difficulty expressed by the subject, and save the scores along with the subject's number, test sample number, and chewing difficulty level. In this embodiment, the subjective evaluation includes chewing effort rating, chewing comfort rating, and swallowing difficulty rating, each recorded as an integer from 1 to 5 points. When 3 to 5 professional assessors participate in the recording, the testing terminal saves the rating record corresponding to each professional assessor, forming a subjective evaluation record for the same chewing difficulty level.

[0085] In a set of subjective evaluation records, P001 scored 1 point for chewing effort, 1 point for chewing comfort, and 1 point for swallowing difficulty after the T-L1 test; 2 points for chewing effort, 2 points for chewing comfort, and 2 points for swallowing difficulty after the T-L2 test; 3 points for chewing effort, 3 points for chewing comfort, and 3 points for swallowing difficulty after the T-L3 test; and 5 points for chewing effort, 5 points for chewing comfort, and 4 points for swallowing difficulty when the subject issued a stop signal during the T-L4 test.

[0086] S702, subjective evaluation and particle detection records are obtained separately. Subjective evaluation does not replace objective detection results regarding particle size distribution, average particle size, and the proportion of particles ≤2mm in diameter, nor does it replace the screening results for effective chewing segments. When outputting test records, the testing terminal can use subjective evaluation as an auxiliary record for the same chewing difficulty level, ensuring that the process information corresponding to the chewing ability level includes the subject's subjective feelings, effective chewing segments, and chewing particle status. The purpose of subjective evaluation records is limited to reflecting the subject's subjective state at the corresponding chewing difficulty level; the final chewing ability level is still determined based on particle detection conditions, test completion conditions, and stop signals.

[0087] When the test terminal outputs the P001 test record, the third level of medium chewing is used as the final chewing ability level. The particle detection records, effective chewing segments, and subjective evaluation records corresponding to T-L1 to T-L3 are output together. The stop signal, the reason for the removal of invalid chewing segments, and the subjective evaluation record corresponding to T-L4 are saved as the stop level process record.

[0088] S8, the testing terminal writes standard texture parameters, test records, particle detection records, subjective evaluations, chewing ability levels, and final chewing ability levels into the storage unit. Standard texture parameters are used to trace the origin of the test sample's level; test records are used to trace the process data of the subject chewing the test sample; particle detection records are used to trace the particle state of the test sample after chewing; subjective evaluations are used to record the subject's perception of chewing difficulty; and the final chewing ability level is used to indicate the highest chewing difficulty level the subject can achieve in this test. The above data is stored in association according to the subject number, test sample number, and chewing difficulty level. In the storage unit, the subject number, test sample number, and chewing difficulty level are used as association fields, while standard texture parameters, chewing coefficient, chewing force signal, chewing action sequence, effective chewing segments, ineffective chewing segments, particle detection records, subjective evaluations, and final chewing ability levels are used as record content, thus forming a complete data chain for a single test process for the same subject.

[0089] In a set of stored records, P001 corresponds to 5 level test records, of which T-L1, T-L2 and T-L3 records are completed, T-L4 records are triggered by a stop signal, and T-L5 records are not started. The test terminal writes the final chewing ability level of P001 as Level 3 Medium Chewing and establishes a correlation between this result and the standard texture parameter table, test sample pretreatment record, effective chewing fragment record, particle detection record and subjective evaluation record.

[0090] Example 2, please refer to Figure 4 This embodiment provides a method for testing the chewing ability of elderly people based on texture parameters. The difference between this embodiment and Embodiment 1 is that the particle detection device adopts an image acquisition device, and the particle size distribution and average particle size of chewing particles are obtained through image acquisition. The other texture parameter grading, test sample preprocessing, chewing process signal acquisition, effective chewing fragment screening, stop signal processing and data storage processes can be performed in accordance with Embodiment 1.

[0091] In this embodiment, after chewing, the test sample is collected and unchewed residue is removed to obtain chewable particles. The chewable particles are spread evenly within the detection area, and an image acquisition device captures images of the chewable particles within the detection area, forming an image of the chewable particles. The testing terminal reads the chewable particle image, identifies the boundaries of the chewable particles, and forms a particle size distribution and average particle size based on the boundaries. The testing terminal calculates the proportion of particle quantity or particle area according to a preset particle size range, and includes the particle size distribution, average particle size, proportion of particle quantity or particle area, along with the test sample number and effective chewing fragment, in the same particle detection record. When using an image acquisition device, the particle detection record still serves as one of the inputs for determining the chewing ability level, and participates in the candidate chewing ability level judgment along with the effective chewing fragment. In the image acquisition mode, the thickness of the chewable particles is controlled to a single layer, with minimal or no overlap between particles. A millimeter-level ruler is placed within the detection area, or pixel calibration relationships are provided by the image acquisition device. The testing terminal converts the particle boundaries into particle size data based on the pixel calibration relationships. For particle image areas where the boundaries cannot be identified or where the particles are stuck to adjacent particles, the testing terminal marks the area as an area to be reviewed, and the testing personnel re-spread the area and collect chewing particle images again.

[0092] In a set of image-acquired particle detection data, the test terminal identified 120 particles in the chewing particle image corresponding to T-L2, of which 91 particles had a diameter ≤2mm, accounting for 75.8% of the total particles. For the chewing particle image corresponding to T-L3, the terminal identified 135 particles, of which 82 particles had a diameter ≤2mm, accounting for 60.7% of the total particles. The particle count percentage obtained from the image acquisition method, along with the effective chewing fragments, were recorded in the particle detection record.

[0093] Example 3, please refer to Figure 6 This embodiment provides a chewing ability testing system for the elderly based on texture parameters. The system supports the aforementioned chewing ability testing method for the elderly based on texture parameters and includes a texture detection device, a chewing process sensor, a particle detection device, a testing terminal, and a storage unit.

[0094] Texture testing equipment is used to obtain the hardness, elasticity, and resilience of food. The output of the texture testing equipment enters the testing terminal, which calculates the chewing coefficient according to a preset weighting relationship and classifies the chewing difficulty level based on the chewing coefficient and the distribution relationship of hardness, elasticity, and resilience, forming standard texture parameters corresponding to each chewing difficulty level. A texture parameter input relationship is established between the texture testing equipment and the testing terminal. The testing terminal writes the standard texture parameters into its storage unit for use when selecting test samples. The data output by the texture testing equipment includes at least the candidate food number, food category, hardness, elasticity, resilience, test batch, and three sets of parallel test results. After receiving the above data, the testing terminal generates the chewing coefficient, chewing difficulty level, and standard texture parameters, and writes the generated results into its storage unit.

[0095] The testing terminal is also used to determine the test samples and test sequence according to standard texture parameters, and to control the chewing process sensor to simultaneously collect chewing force signals and chewing action timing during the subject's chewing of the test sample. The chewing process sensor sends the chewing force signals and chewing action timing to the testing terminal, which then categorizes them into the same test record based on the test start time, test end time, and test sample number. The data output by the chewing process sensor includes at least the sampling time, the peak value of the chewing force signal, and the time interval between adjacent chewing actions. The testing terminal associates this data with the subject number, test sample number, and chewing difficulty level.

[0096] The testing terminal is also used to set peak force thresholds and action interval thresholds. In response to the chewing force signal meeting the peak force threshold and the chewing action sequence meeting the action interval threshold, the corresponding continuous time period is recorded as a valid chewing segment. When the conditions are not met, the testing terminal records the corresponding continuous time period as an invalid chewing segment and discards it. Valid chewing segments are used for subsequent chewing ability level determination, while invalid chewing segments are not included in subsequent analysis. When a valid chewing segment is formed, the testing terminal saves the start sampling time, end sampling time, corresponding number of chewing actions, and chewing difficulty level of that segment; when an invalid chewing segment is formed, it saves the reason for rejection, including the peak force not reaching the peak force threshold and the adjacent action interval exceeding the action interval threshold range.

[0097] Particle detection equipment is used to detect the particle size distribution, average particle size, and percentage of particles within a preset particle size range in a chewed test sample. When the particle detection equipment is a laser particle size analyzer, it outputs the particle size distribution, average particle size, and percentage of particles ≤2mm in diameter. When the particle detection equipment is an image acquisition device, it outputs images of chewed particles, and the testing terminal generates particle size distribution, average particle size, and particle quantity or area percentage based on these images. The particle detection equipment sends the particle detection results to the testing terminal, which then groups the results, along with the test sample number and valid chewed fragments, into the same particle detection record. The data output by the particle detection equipment must include at least the test sample number, particle size distribution, average particle size, and percentage of particles ≤2mm in diameter. When an image acquisition device is used, the particle detection equipment outputs images of chewed particles, and the testing terminal generates particle size statistics based on these images.

[0098] The testing terminal determines the chewing ability level by combining multiple effective chewing segments and particle detection results. Upon receiving a stop signal from the subject, it uses the highest chewing difficulty level corresponding to the effective chewing segment completed before the stop signal as the final chewing ability level and stops subsequent testing. The storage unit is used to associate and store standard texture parameters, chewing process data, particle detection results, and chewing ability levels. These parameters are linked in the storage unit according to the subject number, test sample number, and chewing difficulty level, allowing the testing terminal to retrieve data corresponding to the same test process during subsequent queries, verifications, or output of test results. The data records stored in the storage unit include standard texture parameter records, test records, particle detection records, subjective evaluation records, and final chewing ability level records. Each data record uses the subject number, test sample number, and chewing difficulty level as retrieval fields.

[0099] In a set of systematic data records, the standard texture parameter records include the texture parameters, chewing coefficients, and 5 chewing difficulty levels of 100 candidate foods; the test records include the test start time, test end time, number of chewing movements, and stop signal of subject P001 from T-L1 to T-L4; the particle detection records include the average particle size from T-L1 to T-L3, the proportion of particles with a particle size ≤2mm, and 3 sets of parallel test results; the subjective evaluation records include the chewing effort score, chewing comfort score, and swallowing difficulty score; and the final chewing ability level record includes the three-level moderate chewing corresponding to P001.

[0100] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for testing the chewing ability of elderly people based on texture parameters, characterized in that, include: Texture testing is performed on various types of food to obtain hardness, elasticity, and resilience. The chewing coefficient is calculated according to a preset weighting relationship. Based on the chewing coefficient and the distribution relationship of hardness, elasticity, and resilience, the chewing difficulty level is divided into levels, forming standard texture parameters corresponding to each chewing difficulty level. Test samples were selected according to the standard texture parameters. After pretreatment with consistent temperature and placement time, the test samples were provided to the subjects for chewing in order of increasing chewing difficulty. During the chewing test sample process, the chewing force signal and chewing action sequence were collected in real time by sensors. A force peak threshold and an action interval threshold were set. When multiple peaks of the chewing force signal within a continuous time period meet the force peak threshold, and the intervals between adjacent actions in the chewing action sequence are all within the action interval threshold range, the continuous time period is recorded as a valid chewing segment. When the peak of the chewing force signal does not reach the force peak threshold, or the intervals between adjacent actions in the chewing action sequence exceed the action interval threshold range, the continuous time period is recorded as an invalid chewing segment and removed from subsequent analysis. Collect the test samples after chewing, detect the particle size distribution, average particle size and the proportion of particles within the preset particle size range, and determine the corresponding chewing ability level of the subject by combining the total duration and / or number of the multiple effective chewing segments. When the subject gives a stop signal that they can no longer chew, the subsequent test at a higher level of chewing difficulty is stopped, and the highest level of chewing difficulty corresponding to the effective chewing segment completed before the stop signal is taken as the final chewing ability level.

2. The method for testing the chewing ability of the elderly based on texture parameters according to claim 1, characterized in that, The process of texture testing for various types of food includes: Multiple types of food were categorized into testing batches, and the hardness, elasticity, and resilience of candidate foods were obtained within the same testing batch. Perform at least two texture tests on the same candidate food and calculate the mean values ​​of hardness, elasticity, and resilience. When the difference between the test results of the same candidate food and the mean test value falls within the allowable deviation range, the mean test value is used as the texture parameter of the candidate food. When the difference exceeds the allowable deviation range, the texture test of the candidate food is repeated.

3. The method for testing the chewing ability of the elderly based on texture parameters according to claim 2, characterized in that, The process of calculating the chewing coefficient includes: Hardness weight, elasticity weight, and resilience weight are assigned according to the corresponding relationship between hardness, elasticity, and resilience in chewing difficulty. The chewing coefficient of the candidate food is obtained by multiplying the hardness, elasticity, and resilience of the same candidate food by the hardness weight, elasticity weight, and resilience weight, respectively, and then summing them. Candidate foods are ranked from low to high according to their chewing coefficient, and the chewing difficulty level is divided according to the distribution range of hardness, elasticity and resilience of the ranked candidate foods. The median values ​​of hardness, elasticity and resilience within each chewing difficulty level are obtained as standard texture parameters.

4. The method for testing the chewing ability of the elderly based on texture parameters according to claim 3, characterized in that, The process of classifying test samples according to chewiness coefficient and standard textural parameters includes: The hardness, elasticity, and resilience of the same candidate food were compared with the standard texture parameters corresponding to each chewing difficulty level. When hardness, elasticity, and resilience all fall within the parameter range of the same chewing difficulty level, the candidate food is determined as the test sample for that chewing difficulty level. When hardness, elasticity, and resilience do not fall within the parameter range of the same chewing difficulty level, the test level of the candidate food is determined according to the chewing difficulty level corresponding to the chewing coefficient, and the texture parameters that do not fall within the parameter range are recorded.

5. The method for testing the chewing ability of the elderly based on texture parameters according to claim 4, characterized in that, The pretreatment process for test samples includes: Test samples of the same chewing difficulty level were stored under the same temperature conditions for a set period of time. After preservation, remove the test sample and record the removal time; If the interval between the removal time and the start time of the chewing test does not exceed the set placement time, the test sample will be used for this chewing test. If the interval between the removal time and the start time of the chewing test exceeds the set placement time, the test sample will be removed from the current chewing test.

6. The method for testing the chewing ability of the elderly based on texture parameters according to claim 1, characterized in that, When providing chewing samples to subjects in order of increasing chewing difficulty, first determine the test samples used in this test and the chewing difficulty level of the test samples, and then conduct chewing tests in order of increasing chewing difficulty level. Before each chewing difficulty level test begins, record the subject number, test sample number, and test start time. After each chewing difficulty level test is completed, the test end time is recorded, and the test sample number, chewing force signal, and chewing action sequence are included in the same test record.

7. The method for testing the chewing ability of the elderly based on texture parameters according to claim 6, characterized in that, When screening valid chewing segments, the chewing force signal and chewing action timing of the same test record are read to obtain the peak value of the chewing force signal and the time interval between adjacent chewing actions; When the peak value of the chewing force signal reaches the peak force condition, and the time interval between adjacent chewing actions falls into the action interval condition, the corresponding time interval is determined as an effective chewing segment. When the peak value of the chewing force signal does not reach the peak force condition, or the time interval between adjacent chewing actions does not fall within the action interval condition, the corresponding time period is determined as an invalid chewing segment.

8. The method for testing the chewing ability of the elderly based on texture parameters according to claim 1, characterized in that, When testing the particle size distribution, average particle size, and proportion of particles within a preset particle size range of chewable particles, all test samples after chewing are collected, and chewable particles are obtained after removing unchewed residual samples. The chewable particles are spread evenly in the detection area, and the particle size distribution and average particle size are obtained using an image acquisition device or a laser particle size analyzer. The percentage of particle number or particle area is statistically analyzed according to the preset particle size range, and the particle size distribution, average particle size, percentage of particle number or particle area are included in the same particle detection record along with the test sample number and effective chewing fragment.

9. The method for testing the chewing ability of the elderly based on texture parameters according to claim 8, characterized in that, When determining the chewing ability level, first determine whether the chewing particles under the same chewing difficulty level meet the particle judgment conditions based on the particle detection record, and then determine whether the chewing process meets the test completion conditions based on the effective chewing segments in the particle detection record. When both the particle determination condition and the test completion condition are met, the corresponding chewing difficulty level will be used as the candidate chewing ability level. When multiple candidate chewing ability levels are consecutively true, the highest candidate chewing ability level shall be taken as the chewing ability level. When the subject gives a stop signal, the highest candidate chewing ability level that was established before the stop signal is used as the chewing ability level.

10. A system for testing the chewing ability of elderly people based on texture parameters, used to support the testing method described in any one of claims 1 to 9, characterized in that, Includes texture testing equipment, chewing process sensors, particle detection equipment, testing terminals, and storage units; Texture testing equipment is used to obtain the hardness, elasticity and resilience of food. The testing terminal is used to calculate the chewing coefficient according to the preset weight relationship, and divide the chewing difficulty level according to the chewing coefficient and the distribution relationship of hardness, elasticity and resilience, forming standard texture parameters corresponding to each chewing difficulty level. The testing terminal is also used to determine the test sample and test sequence according to the standard texture parameters, and to control the chewing process sensor to synchronously collect chewing force signals and chewing action timing during the subject's chewing of the test sample; The testing terminal is also used to set the peak force threshold and the action interval threshold, and in response to the chewing force signal satisfying the peak force threshold and the chewing action timing satisfying the action interval threshold, to record the corresponding continuous time period as a valid chewing segment, and in response to the condition not being met, to record the corresponding continuous time period as an invalid chewing segment and remove it. The particle detection device is used to detect the particle size distribution, average particle size, and proportion of particles within a preset particle size range of the test sample after chewing. The test terminal is also used to determine the chewing ability level by combining the multiple effective chewing segments and particle detection results. When a stop signal is received from the subject, the highest chewing difficulty level corresponding to the effective chewing segment completed before the stop signal is used as the final chewing ability level, and subsequent tests are stopped. The storage unit is used to associate and save standard texture parameters, chewing process data, particle detection results, and chewing ability levels.

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