Method and system for evaluating psychological intervention effect of mother of premature infant

Abstract

The invention discloses a premature infant mother psychological intervention effect assessment method and system, and relates to the technical field of psychological assessment. A premature infant mother psychological intervention effect evaluation system comprises a data arrangement module and an effect evaluation module. By analyzing the behavior analysis data set and the face analysis data set of the evaluated mother at the same time, the psychological state of the mother can be comprehensively evaluated from multiple angles; the behavior analysis model and the face analysis model respectively provide independent evaluation of behavior performance and emotional response, so that the evaluation result is more comprehensive and accurate, and the emotional fluctuation and psychological change of the mother and the response to the premature infant can be effectively identified; through multi-level and multi-dimensional behavior analysis, the mood, psychological stress and behavior mode of the mother are deeply recognized, the behavior mode of the mother is considered, the internal mechanism of the mood can be deeply discussed, and therefore powerful data support is provided for psychological intervention.

Description

Technical Field

[0001] The present invention relates to the technical field of psychological assessment, and in particular to a method and system for assessing the effect of psychological intervention on mothers of premature infants. Background Art

[0002] After the birth of a premature baby, the mother often faces tremendous psychological pressure, including anxiety, depression, post-traumatic stress disorder and other emotional problems. These problems not only affect the mother's physical and mental health, but may also affect the care and parent-child relationship of the baby; therefore, psychological intervention for mothers of premature babies is particularly important. Existing intervention methods usually help mothers reduce their psychological burden through psychological counseling, group counseling, cognitive behavioral therapy and other means; however, the evaluation of the intervention effect lacks standardization and scientificity, which makes it difficult to accurately understand the actual effect of the intervention measures. Psychological evaluation only through psychological scales is too one-sided; therefore, the evaluation of the effect of psychological intervention for mothers of premature babies needs to introduce a more comprehensive evaluation method, especially the evaluation of mother-child interaction behavior, which not only helps to reflect the mother's psychological state, but also can reveal the parent-child relationship and the quality of interaction between the mother and the premature baby. Summary of the invention

[0003] The present invention aims to provide a method and system for evaluating the effect of psychological intervention on mothers of premature infants, so as to conduct a more comprehensive psychological evaluation on mothers of premature infants.

[0004] A method for evaluating the effect of psychological intervention on mothers of premature infants, comprising the following steps: After psychological intervention, psychological observation and assessment are conducted on the assessed mothers. Behavior analysis datasets and facial analysis datasets of the assessed mothers and the corresponding premature infants are collected during the psychological observation and assessment. The total time of psychological observation and assessment is recorded as T0. The behavior analysis dataset includes behavioral contact images P t ; The facial analysis dataset includes facial expression images E t ; t=1, 2, ..., T0; where t represents a discrete time point within the total time T0; The behavior analysis data set is analyzed using the psychological assessment behavior analysis model to obtain the behavior assessment results; the psychological assessment behavior analysis model uses multi-level and multi-dimensional behavior analysis to achieve psychological assessment based on action analysis; The facial analysis data set is analyzed using the psychological assessment facial analysis model to obtain the facial psychological assessment results. The psychological assessment facial analysis model is trained and optimized in combination with the YOLOv5 model and the TAM module to achieve psychological assessment based on facial emotion recognition. A comprehensive assessment is conducted based on the behavioral assessment results and facial psychological assessment results to obtain the psychological intervention assessment results.

[0005] As a preferred technical solution of the present invention, the psychological assessment behavior analysis model includes an image processing layer, a feature analysis layer and an output layer; The image processing layer is used to process the behavior contact image P t Perform feature segmentation to obtain the behavioral contact component P （b）（t） ; Among them, b=b1, b2, b3 and b4; b1 is the left hand movement, b2 is the right hand movement, b3 is the upper body movement; b4 is the lower limb movement; The feature analysis layer is used to analyze the behavioral contact component P （b）（t） Perform group feature analysis to obtain the evaluation feature result G （b） ; The output layer is used to convert all the evaluation feature results G （b） Perform feature fusion to obtain behavior evaluation results.

[0006] As a preferred technical solution of the present invention, the behavior contact image P is processed by using a preset human body millimeter wave radar point cloud matrix in the image processing layer. t Perform spatial variation alignment to obtain the preprocessed behavioral contact image P t '; obtaining physical characteristic data of the mother being evaluated, and obtaining physical characteristic data; Based on the preprocessed behavior contact image P t 'Extract motion trajectory and obtain motion trajectory sequence; Based on the body feature data and motion trajectory sequence, the preprocessed behavior contact image P t 'Perform feature fusion to obtain enhanced behavior contact image R t ; To enhance the behavior contact image R t Output the body part features to obtain the behavioral contact component P （b）（t） .

[0007] As a preferred technical solution of the present invention, the behavior contact component P is selected in the feature analysis layer. （b）（t-q） , behavioral contact component P （b）（t） and behavioral contact component P （b）（t+q） Composition behavior contact group component F q ; Behavioral contact grouping component F q Perform internal cross analysis to obtain the behavior emotion probability matrix Z q ; Behavioral contact grouping component F q Perform time series emotion analysis to obtain the behavior time series emotion probability matrix J q ; According to the behavior emotion probability matrix Z q and behavior time series emotion probability matrix Jq , using the formula H q = GMU(Z q , J q ) for feature fusion to obtain the grouped behavior evaluation result H q ; GMU() represents the fusion matrix unit; Randomly change the value of q and repeat the above steps several times to obtain several groups of grouped behavior evaluation results H q ; Among them, q satisfies the following conditions: t - q > 0; t + q < T0; q ∈ the preset time span range; Combine all the grouped behavior evaluation results H q to obtain the evaluation feature result G （b） .

[0008] As a preferred technical solution of the present invention, the psychological evaluation facial analysis model is used to extract features from the facial expression image E t to obtain the facial psychological evaluation result; Use the YOLOv5 model as the basic structure of the psychological evaluation facial analysis model; aiming at the characteristics of the psychological evaluation facial analysis model, introduce the TAM module to replace the bottleneck layer in the backbone network of the YOLOv5 model; stack several TAM modules to form the facial feature extraction unit in the psychological evaluation facial analysis model; at the same time, use the global pooling layer to output the final facial psychological evaluation result.

[0009] As a preferred technical solution of the present invention, the specific steps for comprehensive evaluation based on the behavior evaluation result and the facial psychological evaluation result include: Obtain historical psychological scale data; extract features from the historical psychological scale data to obtain the scale evaluation result; Record the behavior evaluation result as A1, the facial psychological evaluation result as A2, and the scale evaluation result as A3; combine A1, A2 and A3 to obtain the psychological intervention result set; From the psychological intervention result set, randomly select two elements to calculate the difference degree to obtain the psychological intervention mutual exclusion difference degree; If all the psychological intervention mutual exclusion difference degrees are less than the preset psychological intervention difference degree, then perform weighted fusion on the psychological intervention result set to obtain the psychological intervention evaluation result; Otherwise, extract the elements corresponding to the psychological intervention mutual exclusion difference degree greater than the preset psychological intervention difference degree to obtain abnormal elements; if the abnormal element is A1 or A2, perform a psychological observation evaluation again; otherwise, perform weighted fusion based on A1 and A2 to obtain the psychological intervention evaluation result.

[0010] A psychological intervention effect evaluation system for premature mothers, including: The data sorting module includes a data acquisition unit; the data acquisition unit is used to conduct psychological observation and evaluation on the evaluated mother after psychological intervention, and collect the behavior analysis data set and facial analysis data set of the evaluated mother and the corresponding premature infant in the psychological observation and evaluation; the total time of the psychological observation and evaluation is recorded as T0; the behavior analysis data set includes the behavior contact image P t ; The facial analysis dataset includes facial expression images E t ; t=1, 2, ..., T0; where t represents a discrete time point within the total time T0; Effect evaluation module, including action recognition unit, face recognition unit and comprehensive analysis unit; The action recognition unit is used to analyze the behavior analysis data set using the psychological assessment behavior analysis model to obtain the behavior assessment results; the psychological assessment behavior analysis model uses multi-level and multi-dimensional behavior analysis to achieve psychological assessment based on action analysis; The facial recognition unit is used to analyze the facial analysis data set using the psychological evaluation facial analysis model to obtain the facial psychological evaluation results; the psychological evaluation facial analysis model is trained and optimized in combination with the YOLOv5 model and the TAM module to achieve psychological evaluation based on facial emotion recognition; The comprehensive analysis unit is used to conduct a comprehensive assessment based on the behavioral assessment results and the facial psychological assessment results to obtain the psychological intervention assessment results.

[0011] The present invention has the following advantages: The present invention can comprehensively evaluate the mother's psychological state from multiple perspectives by simultaneously analyzing the behavior analysis data set and the facial analysis data set of the evaluated mother; the behavior analysis model and the facial analysis model respectively provide independent evaluations of behavioral performance and emotional response, making the evaluation results more comprehensive and accurate. This multidimensional evaluation method can effectively identify the mother's emotional fluctuations, psychological changes and reactions to premature infants; through multi-level and multi-dimensional behavior analysis, the mother's emotions, psychological pressure and behavior patterns can be more deeply identified. This multi-level analysis not only takes into account the mother's behavior pattern, but also deeply explores the internal mechanism of her emotions, thereby providing strong data support for psychological intervention.

[0012] The present invention combines behavioral contact components at different time points in the feature analysis layer to perform internal emotion probability output and time-series emotion analysis, thereby capturing the mother's emotional fluctuations from multiple angles and time dimensions and carefully analyzing the emotional changes in the behavioral interaction process; through this multi-dimensional emotion evaluation, the mother's psychological state can be more comprehensively understood; by randomly changing the value of the time span, the analysis time window can be dynamically adjusted. This flexible time span selection can adapt to the evaluation needs in different situations and avoid the limitations that may be brought about by a fixed time window. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 The present invention is a schematic diagram of the structure of a system for evaluating the effect of psychological intervention on mothers of premature infants adopted in an embodiment of the present invention. DETAILED DESCRIPTION

[0014] In order to enable persons skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0015] Embodiment 1, a method for evaluating the effect of psychological intervention on mothers of premature infants, comprising the following steps: After psychological intervention, psychological observation and assessment are conducted on the assessed mothers. Behavior analysis datasets and facial analysis datasets of the assessed mothers and the corresponding premature infants are collected during the psychological observation and assessment. The total time of psychological observation and assessment is recorded as T0. The behavior analysis dataset includes behavioral contact images P t ; The facial analysis dataset includes facial expression images E t ; t=1, 2, ..., T0; where t represents a discrete time point within the total time T0; In the psychological observation assessment, the camera is set to capture the interaction between the mother and the premature baby without interfering with the mother's behavior. The camera is set at different angles to capture the mother's posture, movements, gestures and details of the interaction with the premature baby. At the same time, a facial recognition camera is installed to analyze the mother's facial expression, such as smile, frown, eye contact and other emotional expressions. In the psychological observation assessment, the mother needs to be informed of the purpose of the observation to ensure the availability of the data. Discrete points represent specific time points of observation within the total time T0; at these time points, assessment data are collected, such as mothers' behavior and facial expression images; each discrete point can represent a specific moment in a time period, usually used to describe the state or change of a time period, rather than a continuous process; The behavior analysis data set is analyzed using the psychological assessment behavior analysis model to obtain the behavior assessment results; the psychological assessment behavior analysis model uses multi-level and multi-dimensional behavior analysis to achieve psychological assessment based on action analysis; The psychological assessment behavior analysis model includes an image processing layer, a feature analysis layer, and an output layer; The image processing layer is used to process the behavior contact image P t Perform feature segmentation to obtain the behavioral contact component P （b）（t） ; Among them, b=b1, b2, b3 and b4; b1 is the left hand movement, b2 is the right hand movement, b3 is the upper body movement; b4 is the lower limb movement; The feature analysis layer is used to analyze the behavioral contact component P （b）（t）Perform group feature analysis to obtain the evaluation feature result G （b） ; The output layer is used to convert all the evaluation feature results G （b） Perform feature fusion to obtain behavior evaluation results; The image processing layer performs feature segmentation on the behavior contact image and identifies the behavior of each part of the mother's body, such as the left hand, right hand, upper body, and lower limbs separately. This method helps to more accurately identify and analyze the specific behavior of the mother when interacting with the premature baby, rather than simply analyzing the overall behavior. This detailed processing can reveal the differences in the mother's behavior in different parts of the body and help to more comprehensively understand her psychological state. The feature analysis layer performs feature analysis on each component of the mother's behavior, such as the left hand and right hand. By extracting the features of these segmented behaviors, the model can identify specific behavior patterns and further judge the mother's emotions or psychological state. For example, the difference between the mother's left and right hand movements may reflect her emotional investment or emotional fluctuations. Based on the analysis of behavioral features at different time points, the model can dynamically evaluate the mother's emotional changes. For example, the mother's behavior may change over time during contact with the baby. This change may reflect her gradual adaptation to the mother role or fluctuations in her emotional state. Real-time behavior tracking makes psychological evaluation closer to the mother's actual psychological state. In the image processing layer, the preset human body millimeter wave radar point cloud matrix is ​​used to process the behavior contact image P t Perform spatial variation alignment to obtain the preprocessed behavioral contact image P t '; obtaining physical characteristic data of the mother being evaluated, and obtaining physical characteristic data; Based on the preprocessed behavior contact image P t 'Extract motion trajectory and obtain motion trajectory sequence; Based on the body feature data and motion trajectory sequence, the preprocessed behavior contact image P t 'Perform feature fusion to obtain enhanced behavior contact image R t ; To enhance the behavior contact image R t Output the body part features to obtain the behavioral contact component P （b）（t） ; The image processing layer is trained based on the CNN model; The preset millimeter-wave radar point cloud matrix is ​​used to align the behavior contact images in space to ensure that the image data is accurately registered in space. The beneficial effect of this step is that the deviation of the image data caused by the shooting angle or environmental changes is reduced, ensuring the accuracy of the subsequent analysis; through this alignment, the interaction behavior between the mother and the baby can be more accurately connected with the physical characteristics, thus laying the foundation for the subsequent feature extraction and fusion; by obtaining the physical characteristic data of the evaluated mother, detailed physical information is provided for the subsequent behavior analysis. The beneficial effect of this step is that the dynamic changes of various parts of the mother's body, such as hands, upper limbs, lower limbs, etc., can be identified, and the mother's body movement pattern can be accurately captured by extracting the motion trajectory coordinate sequence, which enables the subsequent analysis to reflect the specific behavior of the mother's interaction with the baby from a dynamic perspective, and can analyze the emotional response and behavior pattern more finely; In the feature fusion process, the quality of the behavioral contact image is enhanced based on the pre-processed image and the mother's body feature data and motion trajectory coordinate sequence, making the image clearer and more layered when showing the mother's behavior; through feature fusion, the details in the behavioral image are enhanced, which helps to improve the recognition accuracy of the mother's behavior, for example, distinguishing her different body movements such as the difference between the left hand and the right hand and the emotional indications of the movements such as tension or relaxation. This enhanced image enables the system to more accurately reflect the subtle emotional changes of the mother during the interaction; Select the behavioral contact component P in the feature analysis layer （b）（t-q） , behavioral contact component P （b）（t） and behavioral contact component P （b）（t+q） Composition behavior contact group component F q ; Behavioral contact grouping component F q Perform internal cross analysis to obtain the behavior emotion probability matrix Z q ; Behavioral contact grouping component F q Perform time series emotion analysis to obtain the behavior time series emotion probability matrix J q ; According to the behavior emotion probability matrix Z q and behavior time series emotion probability matrix J q , using the formula H q =GMU(Z q , J q ) to perform feature fusion and obtain the grouping behavior evaluation result H q ; GMU() represents fusion matrix unit; Randomly change the value of q, repeat the above steps several times, and obtain several groups of group behavior evaluation results H q ; Among them, q satisfies the following conditions: t - q > 0; t + q < T0; q ∈ the preset time span range; the preset time span range is set by professional technicians according to the actual situation; Combine all the grouped behavior evaluation results H q to obtain the evaluation feature result G （b） ; At the feature analysis layer, by combining the behavior contact components at different time points, internal emotion probability output and temporal emotion analysis are carried out. This method can capture the mother's emotional fluctuations from multiple angles and time dimensions, and carefully analyze the emotional changes of the mother during the behavior interaction process. Through this multi-dimensional emotion evaluation, the mother's mental state can be more comprehensively understood, such as emotions like anxiety, relaxation, and joy; by randomly changing the value of the time span, the analysis time window can be dynamically adjusted. This flexible time span selection can adapt to the evaluation needs in different situations and avoid the limitations that may be brought by a fixed time window; for example, some behavior patterns may require a longer time span to be accurately captured, while other patterns may require a shorter time window. This dynamic adjustment improves the adaptability and accuracy of the model in different scenarios; in the temporal emotion analysis, by capturing the mother's emotional state at different moments, the evolution of the mother's emotions over time can be analyzed. This temporal analysis helps to reveal the gradual changes in the mother's emotions during a specific behavior process, especially at the moments when the emotions fluctuate greatly; for example, the process of the mother changing from anxiety to gradually relaxation, or from confusion to generating comfort. This temporal emotion analysis can effectively help to understand the mother's emotional response in psychological intervention; by repeatedly changing the value of the time span multiple times and obtaining several groups of evaluation results of the behavior contact evaluation of the grouped mothers to be evaluated, the stability and robustness of the emotion analysis are ensured. The combination of multiple evaluation results can eliminate some accidental errors or inconsistencies, making the final evaluation result more reliable and accurate; multiple evaluation results can also provide more solid data support for subsequent interventions; Use the psychological evaluation facial analysis model to analyze the facial analysis data set to obtain the facial psychological evaluation result; the psychological evaluation facial analysis model is trained and optimized by combining the YOLOv5 model and the TAM module to achieve psychological evaluation based on facial emotion recognition; The psychological evaluation facial analysis model is used to extract features from the facial expression image E t to obtain the facial psychological evaluation result; Use the YOLOv5 model as the basic structure of the psychological evaluation facial analysis model; according to the characteristics of the psychological evaluation facial analysis model, introduce the TAM module to replace the bottleneck layer in the backbone network of the YOLOv5 model; stack several TAM modules to form the facial feature extraction unit in the psychological evaluation facial analysis model; at the same time, use the global pooling layer to output the final facial psychological evaluation result; The TAM module, or temporal adaptive module, is a temporal modeling module used in deep learning models. It is particularly suitable for processing time series data, such as video understanding, action recognition, time series prediction and other tasks. The core idea of ​​TAM is to enable the network to better capture and utilize time series information by adaptively modeling feature changes in the time dimension. The specific steps for training the psychological assessment facial analysis model include: Collect several groups of facial emotion recognition training samples, combine the several groups of facial emotion recognition training samples to obtain a facial emotion recognition training set; perform model training based on the facial emotion recognition training set to obtain an initial psychological evaluation facial analysis model; if the initial psychological evaluation facial analysis model passes the model evaluation, use the initial psychological evaluation facial analysis model as the psychological evaluation facial analysis model in the psychological evaluation facial analysis model; otherwise, continue to perform model training using the facial emotion recognition training set; Combining the training and optimization of the YOLOv5 model and the TAM module, the psychological assessment facial analysis model can accurately identify the facial emotions of the mother being assessed. The target detection capability of YOLOv5 combined with the advantages of the TAM module in facial recognition can better identify the details of facial expressions and improve the recognition accuracy of facial emotions, especially under complex and dynamic emotional changes. The TAM module is introduced to replace the bottleneck layer in the backbone network of the YOLOv5 model, and multiple TAM modules are stacked to form a facial feature extraction unit, which effectively improves the expressiveness and processing speed of facial feature extraction. By training several groups of facial emotion recognition samples and continuously optimizing the training model, the feature extraction method can be adaptively adjusted according to different emotional data sets to improve the sensitivity and accuracy of the mother's facial expressions. The global pooling layer in the psychological assessment facial analysis model effectively integrates the local features in the facial expression image into global information, helping the model to identify and analyze facial emotions from a global perspective. This layer helps to avoid over-reliance on emotional information in a single local area, thereby enhancing the overall emotion recognition ability and ensuring that the mother's overall facial emotions are accurately captured. A comprehensive assessment is conducted based on the behavioral assessment results and the facial psychological assessment results to obtain the psychological intervention assessment results; The specific steps of conducting a comprehensive assessment based on the behavioral assessment results and the facial psychological assessment results include: Obtain historical psychological scale data; perform feature extraction on the historical psychological scale data to obtain scale evaluation results; The behavioral assessment result is recorded as A1, the facial psychological assessment result is recorded as A2, and the scale assessment result is recorded as A3; A1, A2, and A3 are combined to obtain a set of psychological intervention results; From the psychological intervention result set, select any two elements to calculate the difference degree, and obtain the psychological intervention mutually exclusive difference degree; If all mutually exclusive differences of psychological interventions are less than the preset psychological intervention difference, the psychological intervention result set is weighted and fused to obtain the psychological intervention evaluation result; the preset psychological intervention difference is set by professional and technical personnel according to actual conditions; Otherwise, extract the elements whose psychological intervention mutually exclusive difference is greater than the preset psychological intervention difference to obtain abnormal elements; if the abnormal element is A1 or A2, re-perform psychological observation and evaluation; otherwise, perform weighted fusion based on A1 and A2 to obtain the psychological intervention evaluation result; By combining the mother's behavior, facial expression and scale data for comprehensive evaluation, the mother's mental state can be fully understood from multiple perspectives. This multi-dimensional evaluation method helps to make up for the limitations that may be brought about by a single evaluation dimension, thereby improving the accuracy and reliability of the psychological intervention effect evaluation; obtaining and analyzing the historical psychological scale data of the evaluated mother can provide background and comparison for the current psychological intervention effect evaluation. This method helps the system identify the long-term changes in the mother's mental state, provides more comprehensive data support for the evaluation of the intervention effect, and helps to understand whether the intervention has effectively improved the mother's mental health; by calculating the difference between the behavior, facial expression and scale results, the contradictions or inconsistencies between different evaluation results can be automatically identified. This difference calculation mechanism can effectively identify abnormal evaluation results, thereby triggering re-evaluation or adjustment of intervention measures in a timely manner when problems are found. This automated detection greatly improves the efficiency and accuracy of the evaluation process; by weighted fusion of different evaluation results, the evaluation results of each dimension can be integrated to form a more accurate psychological intervention effect evaluation. This weighted fusion method can give different weights according to the importance of different evaluation dimensions, thereby ensuring the comprehensiveness and accuracy of the evaluation results; In this embodiment, a psychological observation assessment includes the following steps: the assessor needs to communicate with the mother being assessed during the assessment preparation stage, explain the purpose and process of the psychological observation assessment, and ensure that the mother understands and agrees to participate in the assessment; at this time, the assessor will also set up necessary equipment, including cameras, sensors, etc., to record the behavior and facial expression data of the mother and the premature baby in real time; at the same time, the assessor collects data at preset time points, and the system begins to monitor the behavior and facial expression of the mother being assessed; after the data is collected, it enters the data processing and analysis stage, and the mother's behavior contact image is processed using a psychological assessment behavior analysis model to analyze her behavior pattern, movement frequency and emotional response; the mother's facial expression is analyzed through facial expression images to determine her emotional changes; the behavior analysis results and facial emotion analysis results are combined to obtain a comprehensive psychological assessment result to assess the mother's emotional and behavioral changes after psychological intervention; the assessment results will be sorted and presented to the assessor or psychological intervention expert. At this stage, the assessor judges the mother's performance in the psychological intervention based on the results, understands the improvement of her mental health, and provides further intervention suggestions if necessary. The assessor will also communicate the assessment results with the mother to explain her mental state and emotional changes.

[0016] Example 2, a psychological intervention effect evaluation system for premature infant mothers, see Figure 1 As shown, including: The data sorting module includes a data acquisition unit; the data acquisition unit is used to conduct psychological observation and evaluation on the evaluated mother after psychological intervention, and collect the behavior analysis data set and facial analysis data set of the evaluated mother and the corresponding premature infant in the psychological observation and evaluation; the total time of the psychological observation and evaluation is recorded as T0; the behavior analysis data set includes the behavior contact image P t ; The facial analysis dataset includes facial expression images E t ; t=1, 2, ..., T0; where t represents a discrete time point within the total time T0; Effect evaluation module, including action recognition unit, face recognition unit and comprehensive analysis unit; The action recognition unit is used to analyze the behavior analysis data set using the psychological assessment behavior analysis model to obtain the behavior assessment results; the psychological assessment behavior analysis model uses multi-level and multi-dimensional behavior analysis to achieve psychological assessment based on action analysis; The facial recognition unit is used to analyze the facial analysis data set using the psychological evaluation facial analysis model to obtain the facial psychological evaluation results; the psychological evaluation facial analysis model is trained and optimized in combination with the YOLOv5 model and the TAM module to achieve psychological evaluation based on facial emotion recognition; The comprehensive analysis unit is used to conduct a comprehensive assessment based on the behavioral assessment results and the facial psychological assessment results to obtain the psychological intervention assessment results.

[0017] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention. Parts not described in detail in this specification belong to the prior art known to those skilled in the art.

Claims

1. A method for evaluating the effect of psychological intervention on mothers of premature infants, characterized in that: Including the following steps: Conduct psychological observation and evaluation on the evaluated mother after psychological intervention. In the psychological observation and evaluation, collect the behavioral analysis data set and facial analysis data set of the evaluated mother and the corresponding premature infant; record the total time of the psychological observation and evaluation as T0; The behavior analysis dataset includes behavioral contact images P t ; The facial analysis dataset includes facial expression images E t ; t=1, 2, ..., T0; where t represents a discrete time point within the total time T0; Analyze the behavioral analysis data set using the psychological evaluation behavioral analysis model to obtain the behavioral evaluation result; the psychological evaluation behavioral analysis model uses multi-level and multi-dimensional behavioral analysis to achieve psychological evaluation based on action analysis; Analyze the facial analysis data set using the psychological evaluation facial analysis model to obtain the facial psychological evaluation result; the psychological evaluation facial analysis model combines the YOLOv5 model and the TAM module for training and optimization to achieve psychological evaluation based on facial emotion recognition; Conduct a comprehensive evaluation based on the behavioral evaluation result and the facial psychological evaluation result to obtain the psychological intervention evaluation result.

2. A method for evaluating the effect of psychological intervention for mothers of premature infants according to claim 1, characterized in that: The psychological evaluation behavioral analysis model includes an image processing layer, a feature analysis layer, and an output layer; The image processing layer is used to process the behavior contact image P t Perform feature segmentation to obtain the behavioral contact component P （b）（t） ; Among them, b=b1, b2, b3 and b4; b1 is the left hand movement, b2 is the right hand movement, b3 is the upper body movement; b4 is the lower limb movement; The feature analysis layer is used to analyze the behavioral contact component P （b）（t） Perform group feature analysis to obtain the evaluation feature result G （b） ; The output layer is used to convert all the evaluation feature results G （b） Perform feature fusion to obtain behavior evaluation results.

3. A method for evaluating the effect of psychological intervention for mothers of premature infants according to claim 2, characterized in that: In the image processing layer, the preset human body millimeter wave radar point cloud matrix is ​​used to process the behavior contact image P t Perform spatial variation alignment to obtain the preprocessed behavioral contact image P t '; Obtain the physical characteristic data of the evaluated mother to obtain the physical characteristic data; Based on the preprocessed behavior contact image P t 'Extract motion trajectory and obtain motion trajectory sequence; Based on the body feature data and motion trajectory sequence, the preprocessed behavior contact image P t 'Perform feature fusion to obtain enhanced behavior contact image R t ; To enhance the behavior contact image R t Output the body part features to obtain the behavioral contact component P （b）（t） .

4. A method for evaluating the effect of psychological intervention for mothers of premature infants according to claim 3, characterized in that: Select the behavioral contact component P in the feature analysis layer （b）（t-q） , behavioral contact component P （b）（t） and behavioral contact component P （b）（t+q） Composition behavior contact group component F q ; Behavioral contact grouping component F q Perform internal cross analysis to obtain the behavior emotion probability matrix Z q ; Behavioral contact grouping component F q Perform time series emotion analysis to obtain the behavior time series emotion probability matrix J q ; According to the behavior emotion probability matrix Z q and behavior time series emotion probability matrix J q , using the formula H q =GMU(Z q , J q ) to perform feature fusion and obtain the grouping behavior evaluation result H q ; GMU() represents fusion matrix unit; Randomly change the value of q, repeat the above steps several times, and obtain several groups of group behavior evaluation results H q ; Wherein, q satisfies the following conditions: t - q > 0; t + q < T0; q ∈ the preset time span range; All group behavior evaluation results H q Combine and get the evaluation feature result G （b） .

5. A method for evaluating the effect of psychological intervention for mothers of premature infants according to claim 4, characterized in that: Psychological evaluation facial analysis model for facial expression images E t Perform feature extraction to obtain facial psychological assessment results; Use the YOLOv5 model as the basic structure of the psychological evaluation facial analysis model; aiming at the characteristics of the psychological evaluation facial analysis model, introduce the TAM module to replace the bottleneck layer in the backbone network of the YOLOv5 model; stack several TAM modules to form the facial feature extraction unit in the psychological evaluation facial analysis model; at the same time, use the global pooling layer to output the final facial psychological evaluation result.

6. A method for evaluating the effect of psychological intervention on mothers of premature infants according to claim 5, characterized in that: The specific steps of the comprehensive evaluation based on the behavioral evaluation result and the facial psychological evaluation result include: Obtain the historical psychological scale data; extract the features of the historical psychological scale data to obtain the scale evaluation result; Record the behavioral evaluation result as A1, the facial psychological evaluation result as A2, and the scale evaluation result as A3; combine A1, A2, and A3 to obtain the psychological intervention result set; Select any two elements from the psychological intervention result set to calculate the difference degree to obtain the psychological intervention mutual exclusion difference degree; If all the psychological intervention mutual exclusion difference degrees are less than the preset psychological intervention difference degree, then perform weighted fusion on the psychological intervention result set to obtain the psychological intervention evaluation result; Otherwise, extract the elements corresponding to the psychological intervention mutual exclusion difference degree greater than the preset psychological intervention difference degree to obtain abnormal elements; if the abnormal element is A1 or A2, then conduct a psychological observation and evaluation again; otherwise, perform weighted fusion based on A1 and A2 to obtain the psychological intervention evaluation result.

7. A psychological intervention effect evaluation system for premature infant mothers, characterized in that: The system applies the method for evaluating the psychological intervention effect of a premature infant mother described in any one of claims 1 - 6 above, including: The data sorting module includes a data acquisition unit; the data acquisition unit is used to conduct psychological observation and evaluation on the evaluated mother after psychological intervention, and collect the behavior analysis data set and facial analysis data set of the evaluated mother and the corresponding premature infant in the psychological observation and evaluation; the total time of the psychological observation and evaluation is recorded as T0; the behavior analysis data set includes the behavior contact image P t ; The facial analysis dataset includes facial expression images E t ; t=1, 2, ..., T0; where t represents a discrete time point within the total time T0; The effect evaluation module includes an action recognition unit, a facial recognition unit, and a comprehensive analysis unit; The action recognition unit is used to analyze the behavioral analysis data set using the psychological evaluation behavioral analysis model to obtain the behavioral evaluation result; the psychological evaluation behavioral analysis model uses multi-level and multi-dimensional behavioral analysis to achieve psychological evaluation based on action analysis; The facial recognition unit is used to analyze the facial analysis data set using the psychological evaluation facial analysis model to obtain the facial psychological evaluation results; the psychological evaluation facial analysis model is trained and optimized in combination with the YOLOv5 model and the TAM module to achieve psychological evaluation based on facial emotion recognition; The comprehensive analysis unit is used to conduct a comprehensive assessment based on the behavioral assessment results and the facial psychological assessment results to obtain the psychological intervention assessment results.

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