Sitting posture human spine stability evaluation method in vibration environment and related equipment

Abstract

The embodiment of the invention provides a sitting posture human spine stability evaluation method and device in a vibration environment. The method comprises the steps of obtaining current human spine sitting posture data; performing curve calculation on the human spine sitting posture data to obtain a corresponding score; and generating a corresponding human spine report based on the score. According to the method, the curve graph corresponding to the spine sitting posture data of the human body is analyzed and calculated, the corresponding human body spine report can be generated in combination with the correlation index between the trunk and the pelvic bone, and the sitting posture human body spine is evaluated according to the report. And the stability of the human body sitting posture spine is calculated and evaluated, so that the detection efficiency and accuracy of the human body spine movement mode and data are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent detection, and in particular to a method, device, electronic equipment and storage medium for evaluating the stability of a human spine in a sitting position under a vibration environment. Background Art

[0002] In modern office environments, long periods of sitting and poor sitting posture have become one of the main factors leading to spinal problems. Current technologies mainly monitor sitting posture through physical devices (such as pressure sensors and accelerometers) or software (such as visual recognition systems). Although these technologies can provide immediate sitting posture feedback and certain correction suggestions, most of them do not deeply analyze the relationship between sitting posture data and long-term spinal health, and often rely on expensive hardware or complex operations, making them difficult to popularize.

[0003] Since it is currently impossible to obtain the current human spine sitting posture data and perform curve calculation on these data to obtain a score related to the sitting posture quality, it is possible to provide users with more scientific and targeted health advice and generate a corresponding human spine report based on the obtained score. Therefore, the existing human spine evaluation method has the problem that it is impossible to obtain the current human spine sitting posture data and perform curve calculation on these data to obtain a score related to the sitting posture quality and generate a corresponding human spine report based on the score. Summary of the invention

[0004] An embodiment of the present invention provides a method for evaluating the stability of the human spine in a sitting posture in a vibration environment, so as to solve the problem that the existing human spine evaluation method is unable to obtain the current human spine sitting posture data, perform curve calculation on these data, obtain a score related to the sitting posture quality, and generate a corresponding human spine report according to the score.

[0005] In a first aspect, an embodiment of the present invention provides a method for evaluating the stability of a human spine in a sitting position under a vibration environment, the method comprising the following steps: Get the current human spine sitting posture data; Performing curve calculation on the human spine sitting posture data to obtain a corresponding score; Based on the score, a corresponding human spine report is generated.

[0006] Optionally, the current human spine sitting posture data includes first thoracic vertebra sitting posture data and pelvic vertebra sitting posture data, and the step of obtaining the current human spine sitting posture data includes: The first thoracic vertebra sitting posture data is sampled and tested by a triaxial vibration test bench to obtain first vibration response curve data, first phase curve data, first amplitude curve data and first slope curve data; The pelvic sitting posture data is sampled and tested through a tri-axial vibration test bench to obtain corresponding second vibration response curve data, second phase curve data, second amplitude curve data and second slope curve data.

[0007] Optionally, performing curve calculation on the human spine sitting posture data to obtain a corresponding score includes: Calculating the first vibration response curve data and the second vibration response curve data by using a preset correlation algorithm to obtain a channel score; Calculating the first phase curve data and the second phase curve data by using a preset error algorithm to obtain a phase score; Calculating the first amplitude curve data and the second amplitude curve data by using a preset error algorithm to obtain an amplitude score; The first slope curve data and the second slope curve data are calculated using a preset error algorithm to obtain a slope score.

[0008] Optionally, calculating the first vibration response curve data and the second vibration response curve data by a preset correlation algorithm to obtain a channel score includes: Calculating the maximum absolute amplitude between the first vibration response curve data and the second vibration response curve data by a preset correlation algorithm to obtain channel error data; determining a channel range between a first vibration response curve and a second vibration response curve based on the channel error data; Based on the channel range, channel scores corresponding to the first vibration response curve data and the second vibration response curve data are determined.

[0009] Optionally, calculating the first phase curve data and the second phase curve data by a preset error algorithm to obtain a phase score includes: Determining a maximum time displacement limit value of the first vibration response curve data; determining a maximum cross-correlation coefficient based on the maximum time displacement limit value; The first phase curve data and the second phase curve data are calculated by using a regression analysis method and a maximum cross-correlation coefficient to obtain a phase score.

[0010] Optionally, calculating the first amplitude curve data and the second amplitude curve data by a preset error algorithm to obtain an amplitude score includes: Performing time series transformation on the first vibration response curve and the second vibration response curve by a dynamic time warping algorithm to determine the similarity between the first vibration response curve and the second vibration response curve; Based on the similarity, amplitude scores corresponding to the first amplitude curve data and the second amplitude curve data are determined.

[0011] Optionally, calculating the first slope curve data and the second slope curve data by a preset error algorithm to obtain a slope score includes: Dividing the first vibration response curve and the second vibration response curve into a plurality of time intervals to obtain a plurality of slope interval curve data; Derivative the plurality of slope interval curve data to obtain slope values ​​corresponding to the plurality of intervals; The slope values ​​corresponding to the multiple intervals are averaged to determine the slope scores corresponding to the first slope curve data and the second slope curve data.

[0012] In a second aspect, an embodiment of the present invention further provides a device for evaluating the stability of a human spine in a sitting posture under a vibration environment, the device comprising: The acquisition module is used to obtain the current human spine sitting posture data; A calculation module, used for performing curve calculation on the human spine sitting posture data to obtain a corresponding score; A generation module is used to generate a corresponding human spine report based on the score.

[0013] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for evaluating the stability of the human spine in a sitting position under a vibration environment provided in an embodiment of the present invention are implemented.

[0014] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for evaluating the stability of the human spine in a sitting position under a vibration environment provided in an embodiment of the invention are implemented.

[0015] In an embodiment of the present invention, current human spine sitting posture data is obtained; a curve calculation is performed on the human spine sitting posture data to obtain a corresponding score; and a corresponding human spine report is generated based on the score. By analyzing and calculating the curve graph corresponding to the human spine sitting posture data, a corresponding human spine report can be generated in combination with the correlation index between the trunk and the pelvis, and the sitting human spine is evaluated according to the report. By obtaining the current human spine sitting posture data and performing a curve calculation on these data, a score related to the sitting posture quality is obtained, which can provide users with more scientific and targeted health advice, and generate a corresponding human spine report based on the obtained score. The stability of the human sitting spine can be calculated and evaluated in a vibration environment, thereby improving the detection efficiency and accuracy of human spine movement patterns and data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 is a flow chart of a method for evaluating the stability of a human spine in a sitting position under a vibration environment provided by an embodiment of the present invention; Figure 2 is a schematic diagram of the structure of a device for evaluating the stability of a human spine in a sitting position under a vibration environment provided in an embodiment of the present invention; Figure 3 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship. like Figure 1 As shown, Figure 1 : is a flow chart of a method for evaluating the stability of a human spine in a sitting position under a vibration environment provided by an embodiment of the present invention. The method for evaluating the stability of a human spine in a sitting position under a vibration environment comprises the following steps: S101, obtaining current human spine sitting posture data.

[0020] In an embodiment of the present invention, the above-mentioned method for evaluating the stability of the sitting human spine in a vibration environment can be applied to a device for evaluating the stability of the sitting human spine in a vibration environment. The above-mentioned device for evaluating the stability of the sitting human spine in a vibration environment has functions such as sitting human spine data processing, sitting human spine data transmission and reception, and sitting human spine data storage, and can be constructed based on a server or a server cluster. The above-mentioned server or server cluster can be an electronic device with the ability to process sitting human spine data.

[0021] The above current human spine sitting posture data may include but are not limited to the first thoracic vertebra sitting posture data and pelvic sitting posture data. Specifically, it may be the dynamic response data of the human spine in a specific vibration environment obtained by a triaxial vibration test bench. The above dynamic response data may cover various physical responses of the human spine under vibration conditions, such as vibration amplitude, phase change, etc., providing parameter conditions for evaluating the stability of the human spine.

[0022] S102, performing curve calculation on the human spine sitting posture data to obtain a corresponding score.

[0023] The above curve calculation can be a process of converting the above human spine sitting posture data into quantifiable indicators. Generally speaking, it can be regarded as a process of extracting information from data. Specifically, the above curve calculation can include but is not limited to calculating the maximum absolute amplitude between two signal curves through correlation fitting, analyzing the errors of specific curves (such as phase curves, amplitude curves and slope curves), and calculating the channel score, phase score, amplitude score and slope score.

[0024] In a possible embodiment, by performing curve calculation on the collected human spine sitting posture data, comparing the vibration responses corresponding to the first thoracic vertebra and the pelvis, a correlation algorithm and an error algorithm are used to perform analysis and calculate the corresponding scores.

[0025] S103. Generate a corresponding human spine report based on the score.

[0026] In a possible embodiment, the system automatically generates a comprehensive human spine report based on the scores (channel score, phase score, amplitude score and slope score) obtained through curve calculation. This report can analyze the spinal stability of the subject under specific vibration conditions in detail, including but not limited to the specific values ​​of each score, and also provides an explanation of the impact of these scores on spinal stability, as well as specific recommendations and preventive measures based on the score results. For example, if the phase score is low, the report will recommend possible posture adjustments or further medical evaluations. Through this detailed report, medical professionals can obtain key health indicators, thereby more effectively diagnosing, monitoring and formulating targeted treatment plans, which is particularly suitable for the field of spinal health management and rehabilitation treatment, and enhances the effectiveness of individual health management and preventive measures.

[0027] In an embodiment of the present invention, current human spine sitting posture data is obtained; a curve calculation is performed on the human spine sitting posture data to obtain a corresponding score; and a corresponding human spine report is generated based on the score. By analyzing and calculating the curve graph corresponding to the human spine sitting posture data, a corresponding human spine report can be generated in combination with the correlation index between the trunk and the pelvis, and the sitting human spine is evaluated according to the report. By obtaining the current human spine sitting posture data and performing a curve calculation on these data, a score related to the sitting posture quality is obtained, which can provide users with more scientific and targeted health advice, and generate a corresponding human spine report based on the obtained score. The stability of the human sitting spine can be calculated and evaluated in a vibration environment, thereby improving the detection efficiency and accuracy of the human spine movement pattern and data.

[0028] Optionally, in step S101, the step of obtaining the current human spine sitting posture data, further comprising steps S1011-S1012, wherein: S1011. Sample and detect the sitting posture data of the first thoracic vertebra through a tri-axial vibration test bench to obtain first vibration response curve data, first phase curve data, first amplitude curve data, and first slope curve data.

[0029] In an embodiment of the present invention, the above-mentioned first vibration response curve data may be data recording the instantaneous response of the first thoracic vertebra under vibration input, which may generally be displayed in an image as a curve data showing the overall trend of vibration changes over time, which may help identify the sensitivity of the spine to vibrations of a specific frequency.

[0030] The first phase curve data may be data describing the phase difference between the first thoracic vertebra vibration and the input vibration signal. The phase difference data may be used to analyze the synchronization or delay of the dynamic behavior of the spine.

[0031] The first amplitude curve data may record the change in vibration amplitude, provide information on the maximum and minimum values ​​of the vibration amplitude of the first thoracic vertebra, and is a key indicator for judging the stability and bearing capacity of the spine.

[0032] The first slope curve data above reflects the rate of change of the vibration response curve. By analyzing the slope, the response speed and change trend of the first thoracic vertebra under different vibration conditions can be understood.

[0033] S1012. Sample and detect the pelvic sitting posture data through a tri-axial vibration test bench to obtain corresponding second vibration response curve data, second phase curve data, second amplitude curve data, and second slope curve data.

[0034] The second vibration response curve data may record the instantaneous dynamic response of the pelvis when receiving vibration input, and may generally be displayed as a curve data in an image, which may be used to display the change of the vibration signal over time.

[0035] The second phase curve data may be curve data describing the phase relationship between the pelvic vibration and the exciting vibration, and the dynamic synchronization or phase delay of the pelvis may be evaluated through the curve data.

[0036] The second amplitude curve data may be used to determine a detailed record of the vibration amplitude, such as the maximum amplitude and the minimum amplitude of the pelvic response.

[0037] The second slope curve data can be used to analyze the vibration response speed and its changing trend, and show the fast-changing area of ​​the pelvic vibration response.

[0038] In a possible embodiment, a tri-axial vibration test bench is used to sample and detect the sitting posture data of the first thoracic vertebra of the human body. Specifically, by controlling the vibration input of the test bench and collecting data based on a sensor fixed at the position of the first thoracic vertebra, first vibration response curve data, first phase curve data, first amplitude curve data and first slope curve data are obtained.

[0039] In another possible embodiment, a tri-axial vibration test bench is used to perform precise sampling and detection on the pelvic sitting posture data. Specifically, the vibration data of the tester is recorded by a vibration acceleration sensor placed at the pelvic position, and the second vibration response curve data, the second phase curve data, the second amplitude curve data and the second slope curve data are collected.

[0040] Optionally, in step S102, the step of performing curve calculation on the human spine sitting posture data to obtain a corresponding score further includes steps S1021-S1024, wherein: S1021. Calculate the first vibration response curve data and the second vibration response curve data using a preset correlation algorithm to obtain a channel score.

[0041] In an embodiment of the present invention, the above-mentioned preset correlation algorithm can utilize the channel range deviation between the automatically generated correlation calculation curves to obtain the channel score. Specifically, the calculation can be completed by comparing the correlation of two vibration response curves, such as calculating the maximum absolute amplitude difference between the two, and the degree of phase and frequency matching.

[0042] In a possible embodiment, the data of the two curves are input into a preset correlation algorithm, and the algorithm analyzes the similarities and differences of the two data streams, and then outputs a numerical value, which reflects the relationship between the two test points in terms of vibration response. This numerical value is called a "channel score", which is an indicator that quantifies the relationship between the two data points. The higher the score, the more consistent the vibration responses of the two test points.

[0043] S1022, calculating the first phase curve data and the second phase curve data by using a preset error algorithm to obtain a phase score; S1023, calculating the first amplitude curve data and the second amplitude curve data by using a preset error algorithm to obtain an amplitude score; S1024. Calculate the first slope curve data and the second slope curve data using a preset error algorithm to obtain a slope score.

[0044] The preset error algorithm can obtain the scores of phase, amplitude and slope by analyzing the characteristics of a specific curve, and finally calculate the comprehensive correlation score.

[0045] In this embodiment, the phase curve, amplitude curve and slope curve data of the first thoracic vertebra (T1) and the pelvis are analyzed by a preset error algorithm to calculate the phase score, amplitude score and slope score. Specifically, the algorithm evaluates the time alignment of the phase curve data to obtain the phase score, and the amplitude score is calculated by comparing the similarity of the vibration intensity corresponding to the amplitude curve data of the two. The slope curve data of the two are analyzed and the consistency of the change rate is compared to calculate the slope score.

[0046] Optionally, in step S1021, the step of calculating the first vibration response curve data and the second vibration response curve data by a preset correlation algorithm to obtain a channel score further includes steps S10211-S10213, wherein: S10211, calculating the maximum absolute amplitude between the first vibration response curve data and the second vibration response curve data by using a preset correlation algorithm to obtain channel error data; S10212, determining a channel range between the first vibration response curve and the second vibration response curve based on the channel error data; S10213: Determine channel scores corresponding to the first vibration response curve data and the second vibration response curve data based on the channel range.

[0047] In the embodiment of the present invention, the channel error data may be a value of the maximum absolute amplitude difference between two vibration response curves, which is used to measure the maximum difference between two data points in vibration response.

[0048] The above channel range may be determined based on channel error data, and represents the maximum and minimum difference intervals between the vibration response curves of the first thoracic vertebra and the pelvis within the dynamic range.

[0049] The above channel score can be a score calculated based on the channel range, which is used to quantify the consistency of the first thoracic vertebra and the pelvis under given conditions. Generally speaking, the higher the channel score, the more consistent the response between the two, indicating that the spine is more stable under such conditions.

[0050] In a possible embodiment, the first vibration response curve data and the second vibration response curve data with the same time starting point can be selected in the same sampling interval, and the maximum absolute amplitude of the first vibration response curve data and the second vibration response curve data can be calculated by the above-mentioned preset correlation algorithm to obtain the range of the inner and outer channels, and finally the channel score can be obtained by calculating the range of the inner and outer channels. Specifically, it can be calculated by the following formula:

[0051] Defining parameters and

[0052] Absolute half-width inside the channel:

[0053] Absolute half-width outside the channel:

[0054] Finally, the total channel score is calculated through the curve:

[0055] in, represents the absolute maximum amplitude T of the reference signal, Respectively represent the relative half-width of the inner and outer corridors, is the absolute half width of the inner and outer corridors, is the channel score at time t, , is the T1 and pelvic signal curve at time t, To calculate the index coefficient for the inner and outer corridor scores, is the starting time, N is the total number of samples at the starting time, is the channel score at time t, and Z is the final channel total score. The channel scores corresponding to the first vibration response curve data and the second vibration response curve data can be calculated through the above formula.

[0056] In this embodiment, by calculating the channel error data, channel range and channel score, the dynamic responses of different parts of the spine under the same vibration conditions can be accurately analyzed and compared, thereby providing scientific quantitative indicators for spinal stability assessment.

[0057] Optionally, in step S1022, the step of calculating the first phase curve data and the second phase curve data by a preset error algorithm to obtain a phase score further includes steps S10221-S10223, wherein: S10221. Determine a maximum time displacement limit value of the first vibration response curve data; S10222. Determine a maximum mutual correlation coefficient based on the maximum time displacement limit value; S10223. Calculate the first phase curve data and the second phase curve data by using a regression analysis method and a maximum cross-correlation coefficient to obtain a phase score.

[0058] In the embodiment of the present invention, the maximum time displacement limit value is the maximum time offset observed when comparing two phase curves, and can be used to define the maximum acceptable difference in signal synchronization.

[0059] The maximum cross-correlation coefficient is a statistic that measures the similarity of two time series and is used to quantify the consistency of the phases of the two vibration response curves.

[0060] The above-mentioned regression analysis method can be used for the statistical process of establishing the relationship between one or more independent variables and the dependent variable, and is applied here to determine the best phase consistency and calculate the phase score accordingly.

[0061] In a possible embodiment, the maximum time displacement limit value of the first vibration response curve data is determined, and the maximum cross-correlation coefficient is calculated based on the limit value. The phase curve data is processed using a regression analysis method and the obtained maximum cross-correlation coefficient to obtain a phase score.

[0062] Specifically, the maximum time displacement percentage allowed by the first vibration response curve data is determined, and the maximum time displacement limit value is reached by adjusting the left and right displacements of the first vibration response curve data, and the maximum correlation coefficient is calculated. The displacement intercept time history curve of the first thoracic vertebra and pelvic curve is obtained by calculating the phase error, and finally, the phase score is obtained by the regression analysis method, wherein, when calculating the maximum time displacement limit value, it can be obtained by the following formula: According to the translation curve derived from the maximum displacement, the correlation coefficients of the left and right displacements are calculated respectively, that is, the mutual correlation coefficient: Leftward shift, the correlation coefficient between T (T1 curve) and P (pelvic curve):

[0063] Shift right, the mutual correlation coefficient between T and P:

[0064] Maximum mutual correlation coefficient: ; Phase Error: , if the optimal phase score is "1", the maximum cross-correlation of the initial curve can be achieved without translating the curve. Equal to or greater than the maximum allowable time shift limit , the phase score is "0".

[0065] Phase score:

[0066] in, represents the maximum displacement of translation, m represents the time step of movement, represents the left and right cross-correlation values ​​of the T curve, n is the number of curve samples, are the time displacements and truncated nodes, is the time interval between adjacent data time points, is the mean of the T and P curves, is the start time, For the end time, represents the maximum cross-correlation value of left and right movement, is the phase error after translation, represents the calculated phase score, To calculate the exponential factor of the phase score, N is the total number of samples between the start time and the end time. The phase score can be obtained by the above formula.

[0067] Optionally, in step S1023, the step of calculating the first amplitude curve data and the second amplitude curve data by a preset error algorithm to obtain an amplitude score further includes steps S10231-S10232, wherein: S10231. Performing time series transformation on the first vibration response curve and the second vibration response curve by using a dynamic time warping algorithm to determine similarity between the first vibration response curve and the second vibration response curve; S10232. Based on the similarity, determine amplitude scores corresponding to the first amplitude curve data and the second amplitude curve data.

[0068] In an embodiment of the present invention, the above-mentioned dynamic time warping algorithm can be any time series analysis method, which finds the best alignment by dynamically adjusting the length of two time series, thereby calculating the minimum distance between the two to measure the similarity between the time series.

[0069] The above-mentioned time series transformation may refer to adjusting the speed or time axis of the time series by the DTW algorithm so that two time series are aligned on the time axis, thereby comparing their similarities or differences.

[0070] The above similarity can be the matching degree of the two vibration response curves in time and shape after being analyzed by the DTW algorithm.

[0071] The above amplitude score can be used for the similarity calculated by the DTW algorithm, which measures the degree of match between the two curves in amplitude.

[0072] In a possible embodiment, the vibration response curves of the first thoracic vertebra (T1) and the pelvis are transformed into time series using a dynamic time warping algorithm (DTW) to determine the similarity between the two. The DTW algorithm is used to adjust the expansion and contraction of the time series, obtain the best matching time points of the two curves, and calculate the minimum distance between them. Based on this similarity, the amplitude scores corresponding to the first amplitude curve data and the second amplitude curve data are further calculated.

[0073] Specifically, we can first establish a reorganization path indicator matrix, and use the matrix to record the optimal reorganization path indicator: The new curve is obtained by using the first and second columns of the w matrix corresponding to the translation truncation curves of T1 and pelvis respectively. Calculate the amplitude error:

[0074] Finally, the amplitude score is calculated:

[0075]

[0076] Among them, w is the optimal integration path matrix, which satisfies three constraints:

[0077] is the minimum regularized path, It means that the new amplitude curve is obtained by calculating the first and second columns of the w matrix. is the amplitude error, is the exponential factor for calculating the amplitude error, is the maximum allowable amplitude error, is the final amplitude score, and the amplitude score can be calculated using the above formula.

[0078] Optionally, in step S1024, the first slope curve data and the second slope curve data are calculated by a preset error algorithm to obtain a slope score, which also includes steps S10241-S10243, wherein:

[0079] S10241, dividing the first vibration response curve and the second vibration response curve into a plurality of time intervals to obtain a plurality of slope interval curve data; S10242, deriving multiple slope interval curve data to obtain slope values ​​corresponding to multiple intervals; S10243. Calculate the average of the slope values ​​corresponding to the multiple intervals to determine the slope scores corresponding to the first slope curve data and the second slope curve data.

[0080] In the embodiment of the present invention, the above-mentioned slope interval curve data may be curve slope information obtained by derivation in each time interval, representing the rate of change of the vibration response in the interval.

[0081] The above slope value may be a specific value of the slope interval curve in each time interval, reflecting the speed and direction of the change of the interval curve.

[0082] The slope score may be a score derived based on an average or other statistical processing of the slope values, and is used to quantify the stability of the spine during the entire vibration process.

[0083] In a possible embodiment, a dynamic time warping algorithm is used to perform time series transformation, and the first vibration response curve and the second vibration response curve are divided into multiple time intervals. The slope is calculated for each interval, and then the slope of each interval is derived and averaged. The average obtained is used as the slope score corresponding to the first and second vibration response curve data.

[0084] Specifically, the above slope score can be based on the displacement intercept time history curve of T1 and pelvic curve, divided into multiple intervals with a fixed length of 10 data points (if the total number of data points of the entire signal is not a multiple of 10, the remaining data points are used as the last interval), and the average slope of each interval is calculated to obtain the slope curve of T1 and pelvic , and the slope error is obtained by the following formula:

[0085] Finally the slope score is calculated:

[0086] in, They represent the slope curves obtained by calculating the average slope of each interval, is the slope error calculated from the slope curve, To calculate the exponential factor for the slope score, is the maximum allowable slope error, Score for the slope.

[0087] In another possible embodiment, the channel, phase, amplitude and slope correlation scores are weighted according to different weight coefficients to calculate a comprehensive correlation score, and based on the comprehensive correlation score, a corresponding human spine report is generated. Specifically, the range (channel) correlation between the curves is calculated according to the correlation algorithm, and the phase, amplitude and slope correlation between the curves are compared by the error algorithm. Finally, the channel, phase, amplitude and slope correlation scores are weighted according to weight coefficients of 0.4, 0.2, 0.2 and 0.2 to calculate the comprehensive correlation score R value (R=0-1). The larger the value, the higher the degree of stability.

[0088]

[0089] in, They represent channel, phase, amplitude, and slope fractions respectively.

[0090] like Figure 2As shown, the embodiment of the present invention further provides a device 200 for evaluating the stability of a human spine in a sitting posture under a vibration environment, and the device 200 for evaluating the stability of a human spine in a sitting posture under a vibration environment comprises: The acquisition module 201 is used to acquire the current human spine sitting posture data; A calculation module 202 is used to perform curve calculation on the human spine sitting posture data to obtain a corresponding score; The generating module 203 is used to generate a corresponding human spine report based on the score.

[0091] Optionally, the acquisition module 201 includes: A first sampling module is used to sample and detect the first thoracic vertebra sitting posture data through a tri-axial vibration test bench to obtain first vibration response curve data, first phase curve data, first amplitude curve data and first slope curve data; The second sampling module is used to sample and detect the pelvic sitting posture data through a three-axial vibration test bench to obtain corresponding second vibration response curve data, second phase curve data, second amplitude curve data and second slope curve data.

[0092] Optionally, the calculation module 202 includes: A first scoring submodule, configured to calculate the first vibration response curve data and the second vibration response curve data by using a preset correlation algorithm to obtain a channel score; A second scoring submodule, used to calculate the first phase curve data and the second phase curve data by a preset error algorithm to obtain a phase score; A third scorer module, used to calculate the first amplitude curve data and the second amplitude curve data by a preset error algorithm to obtain an amplitude score; The fourth scoring submodule is used to calculate the first slope curve data and the second slope curve data by using a preset error algorithm to obtain a slope score.

[0093] Optionally, the first scorer submodule includes: A first calculation unit, configured to calculate the maximum absolute amplitude between the first vibration response curve data and the second vibration response curve data by using a preset correlation algorithm to obtain channel error data; A first determining unit, configured to determine a channel range between a first vibration response curve and a second vibration response curve based on the channel error data; The second determining unit is configured to determine, based on the channel range, channel scores corresponding to the first vibration response curve data and the second vibration response curve data.

[0094] Optionally, the second score submodule includes: a third determining unit, configured to determine a maximum time displacement limit value of the first vibration response curve data; a fourth determining unit, configured to determine a maximum mutual correlation coefficient based on the maximum time displacement limit value; The second calculation unit is used to calculate the first phase curve data and the second phase curve data by using a regression analysis method and a maximum cross-correlation coefficient to obtain a phase score.

[0095] Optionally, the third sub-module includes: a fifth determining unit, configured to perform a time series transformation on the first vibration response curve and the second vibration response curve by using a dynamic time warping algorithm to determine a similarity between the first vibration response curve and the second vibration response curve; A sixth determining unit is used to determine amplitude scores corresponding to the first amplitude curve data and the second amplitude curve data based on the similarity.

[0096] Optionally, the fourth sub-module includes: A first acquisition unit, configured to divide the first vibration response curve and the second vibration response curve into a plurality of time intervals to obtain a plurality of slope interval curve data; A second acquisition unit is used to derive the plurality of slope interval curve data to obtain slope values ​​corresponding to the plurality of intervals; The seventh determining unit is configured to average the slope values ​​corresponding to the multiple intervals to determine the slope scores corresponding to the first slope curve data and the second slope curve data.

[0097] like Figure 3 As shown, an embodiment of the present invention further provides an electronic device 300, including a processor, and the processor can execute any one of the above-mentioned methods for evaluating the stability of the human spine in a sitting position under a vibration environment.

[0098] Specifically, the method comprises a processor 301 and a memory 302, and a computer program stored in the memory 302 and capable of running on the processor 301 to execute a method for evaluating the stability of a human spine in a sitting posture under a vibration environment, wherein: The processor 301 runs the computer program of the method for evaluating the stability of the human spine in a sitting posture under a vibration environment stored in the memory 302, and performs the following steps: Get the current human spine sitting posture data; Performing curve calculation on the human spine sitting posture data to obtain a corresponding score; Based on the score, a corresponding human spine report is generated.

[0099] Optionally, the processor 301 executes the current human spine sitting posture data including the first thoracic vertebra sitting posture data and the pelvic sitting posture data, and the obtaining of the current human spine sitting posture data includes: The first thoracic vertebra sitting posture data is sampled and tested by a triaxial vibration test bench to obtain first vibration response curve data, first phase curve data, first amplitude curve data and first slope curve data; The pelvic sitting posture data is sampled and tested through a tri-axial vibration test bench to obtain corresponding second vibration response curve data, second phase curve data, second amplitude curve data and second slope curve data.

[0100] Optionally, the processor 301 performs the curve calculation on the human spine sitting posture data to obtain a corresponding score, including: Calculating the first vibration response curve data and the second vibration response curve data by using a preset correlation algorithm to obtain a channel score; Calculating the first phase curve data and the second phase curve data by using a preset error algorithm to obtain a phase score; Calculating the first amplitude curve data and the second amplitude curve data by using a preset error algorithm to obtain an amplitude score; The first slope curve data and the second slope curve data are calculated using a preset error algorithm to obtain a slope score.

[0101] Optionally, the processor 301 performs the calculation on the first vibration response curve data and the second vibration response curve data by using a preset correlation algorithm to obtain a channel score, including: Calculating the maximum absolute amplitude between the first vibration response curve data and the second vibration response curve data by a preset correlation algorithm to obtain channel error data; determining a channel range between a first vibration response curve and a second vibration response curve based on the channel error data; Based on the channel range, channel scores corresponding to the first vibration response curve data and the second vibration response curve data are determined.

[0102] Optionally, the processor 301 performs the calculation of the first phase curve data and the second phase curve data through a preset error algorithm to obtain a phase score, including: Determining a maximum time displacement limit value of the first vibration response curve data; determining a maximum cross-correlation coefficient based on the maximum time displacement limit value; The first phase curve data and the second phase curve data are calculated by using a regression analysis method and a maximum cross-correlation coefficient to obtain a phase score.

[0103] Optionally, the processor 301 further performs the calculation of the first amplitude curve data and the second amplitude curve data by using a preset error algorithm to obtain an amplitude score, including: Performing time series transformation on the first vibration response curve and the second vibration response curve by a dynamic time warping algorithm to determine the similarity between the first vibration response curve and the second vibration response curve; Based on the similarity, amplitude scores corresponding to the first amplitude curve data and the second amplitude curve data are determined.

[0104] The optional processor 301 further performs the calculation of the first slope curve data and the second slope curve data by a preset error algorithm to obtain a slope score, including: Dividing the first vibration response curve and the second vibration response curve into a plurality of time intervals to obtain a plurality of slope interval curve data; Derivative the plurality of slope interval curve data to obtain slope values ​​corresponding to the plurality of intervals; The slope values ​​corresponding to the multiple intervals are averaged to determine the slope scores corresponding to the first slope curve data and the second slope curve data.

[0105] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the method for evaluating the stability of the human spine in a sitting position in a vibration environment or the method for evaluating the stability of the human spine in a sitting position in a vibration environment of an application end provided by the embodiment of the present invention are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0106] Those skilled in the art can understand that the implementation of all or part of the processes in the above-mentioned embodiments is a program that can be completed by instructing related hardware through a computer program, and can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0107] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for evaluating the stability of the human spine in a sitting position under a vibration environment, characterized in that: include: Get the current human spine sitting posture data; Performing curve calculation on the human spine sitting posture data to obtain a corresponding score; Based on the score, a corresponding human spine report is generated.

2. The method for evaluating the stability of the human spine in a sitting position under a vibration environment as claimed in claim 1, characterized in that: The current human spine sitting posture data includes the first thoracic vertebra sitting posture data and the pelvic sitting posture data, and the obtaining of the current human spine sitting posture data includes: The first thoracic vertebra sitting posture data is sampled and tested by a triaxial vibration test bench to obtain first vibration response curve data, first phase curve data, first amplitude curve data and first slope curve data; The pelvic sitting posture data is sampled and tested through a tri-axial vibration test bench to obtain corresponding second vibration response curve data, second phase curve data, second amplitude curve data and second slope curve data.

3. The method for evaluating the stability of the human spine in a sitting position under a vibration environment as claimed in claim 2, characterized in that: The curve calculation of the human spine sitting posture data to obtain a corresponding score includes: Calculating the first vibration response curve data and the second vibration response curve data by using a preset correlation algorithm to obtain a channel score; Calculating the first phase curve data and the second phase curve data by using a preset error algorithm to obtain a phase score; Calculating the first amplitude curve data and the second amplitude curve data by using a preset error algorithm to obtain an amplitude score; The first slope curve data and the second slope curve data are calculated using a preset error algorithm to obtain a slope score.

4. The method for evaluating the stability of the human spine in a sitting position under a vibration environment as claimed in claim 3, characterized in that: The calculating the first vibration response curve data and the second vibration response curve data by a preset correlation algorithm to obtain a channel score includes: Calculating the maximum absolute amplitude between the first vibration response curve data and the second vibration response curve data by a preset correlation algorithm to obtain channel error data; determining a channel range between a first vibration response curve and a second vibration response curve based on the channel error data; Based on the channel range, channel scores corresponding to the first vibration response curve data and the second vibration response curve data are determined.

5. The method for evaluating the stability of the human spine in a sitting position under a vibration environment as claimed in claim 3, characterized in that: The calculating the first phase curve data and the second phase curve data by a preset error algorithm to obtain a phase score includes: Determining a maximum time displacement limit value of the first vibration response curve data; determining a maximum cross-correlation coefficient based on the maximum time displacement limit value; The first phase curve data and the second phase curve data are calculated by using a regression analysis method and a maximum cross-correlation coefficient to obtain a phase score.

6. The method for evaluating the stability of the human spine in a sitting position under a vibration environment as claimed in claim 3, characterized in that: The calculating the first amplitude curve data and the second amplitude curve data by a preset error algorithm to obtain an amplitude score includes: Performing time series transformation on the first vibration response curve and the second vibration response curve by a dynamic time warping algorithm to determine the similarity between the first vibration response curve and the second vibration response curve; Based on the similarity, amplitude scores corresponding to the first amplitude curve data and the second amplitude curve data are determined.

7. The method for evaluating the stability of the human spine in a sitting position under a vibration environment as claimed in claim 3, characterized in that: The calculating the first slope curve data and the second slope curve data by a preset error algorithm to obtain a slope score includes: Dividing the first vibration response curve and the second vibration response curve into a plurality of time intervals to obtain a plurality of slope interval curve data; Derivative the plurality of slope interval curve data to obtain slope values ​​corresponding to the plurality of intervals; The slope values ​​corresponding to the multiple intervals are averaged to determine the slope scores corresponding to the first slope curve data and the second slope curve data.

8. A device for evaluating the stability of the human spine in a sitting position under a vibration environment, characterized in that: include: The acquisition module is used to obtain the current human spine sitting posture data; A calculation module, used for performing curve calculation on the human spine sitting posture data to obtain a corresponding score; A generation module is used to generate a corresponding human spine report based on the score.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for evaluating the stability of the human spine in a sitting position under a vibration environment as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for evaluating the stability of the human spine in a sitting position under a vibration environment according to any one of claims 1 to 7 are implemented.

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