Non-drug intervention strategy making method and system for patients with insomnia disorder

Abstract

The invention provides a non-drug intervention strategy making method and system for an insomnia patient, and the method comprises the steps: obtaining a traditional Chinese medicine physiological reference parameter of the patient, mapping the traditional Chinese medicine physiological reference parameter to a continuous physiological waveform, removing a static component matched with a traditional Chinese medicine physiological reference from the continuous physiological waveform, and obtaining a non-drug intervention strategy of the patient; obtaining a pure stress shock waveform triggered by external disturbance, and calculating a permeation gain of the environment characteristics to the pure stress shock waveform in the environment path; calculating the interference intensity of the traditional Chinese medicine syndrome characteristic data on the pure stress shock wave form in the syndrome path; performing state object division on the current sleep state of the patient based on the ratio relationship between the permeation gain and the interference intensity; and dynamically adjusting the output weights of the physical environment adjustment instruction, the traditional Chinese medicine syndrome adjustment instruction and the cognitive intervention instruction in a preset non-drug intervention library based on the recognition result of the state object and the recovery characteristic time parameter of the physiological steady state in the corresponding state. And a dynamic self-adaptive household non-drug intervention scheme is provided.

Description

A method and system for developing non-pharmacological intervention strategies for patients with insomnia. Technical Field

[0001] This application relates to the field of health management technology, specifically a method and system for developing non-pharmacological intervention strategies for patients with insomnia. Background Technology

[0002] Insomnia is a condition that affects an individual's ability to fall asleep normally or leads to a decline in sleep quality. Insomnia can affect quality of life, causing fatigue, poor concentration, low mood or irritability during the day, and in severe cases, it can also affect work, study and interpersonal relationships.

[0003] Chinese patent CN119252437a discloses a processing system, device, and storage medium for insomnia intervention. The system includes a user terminal and a sleep intervention analysis device. The user terminal is used to collect treatment period data information of insomnia patients during CBTI treatment. The sleep intervention analysis device is used to configure the patient's CBTI treatment requirement information, then compare the patient's treatment period data information with the aforementioned CBTI treatment requirement information, obtain the difference information between the treatment period data information and the CBTI treatment requirement information to obtain the patient's treatment item gap information, and generate a sleep management suggestion report including the treatment item gap information to be displayed to the patient.

[0004] The aforementioned existing technologies describe an individual's response to changes in the external environment during sleep by comparing differences in physiological signals across different brain regions or time periods. While this method has some value in improving sleep state recognition, it focuses primarily on assessing and determining sleep quality, with outputs remaining at the analytical level. It lacks solutions ranging from identifying triggers to selecting and dynamically adjusting intervention strategies, making it difficult to meet the comprehensive needs of individual intervention and control in home care and non-pharmacological intervention scenarios. Therefore, overcoming these technical problems and shortcomings is a key issue that needs to be addressed. Summary of the Invention

[0005] To overcome the aforementioned problems in the prior art, this application provides a method and system, which adopts the following technical solution:

[0006] Firstly, this application provides a method for developing non-pharmacological intervention strategies for patients with insomnia, including:

[0007] The system acquires environmental characteristic data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome characteristic data collected within a third preset time period.

[0008] Based on TCM syndrome characteristic data, TCM physiological baseline parameters of patients are obtained, and TCM physiological baseline parameters are mapped onto continuous physiological waveforms. Static components that match TCM physiological baselines are removed from the continuous physiological waveforms to obtain pure stress waveforms triggered by external disturbances.

[0009] A dual-path attribution model is constructed based on the pure stress waveform, which combines the environmental path and the syndrome path. In the environmental path, the penetration gain of environmental features on the pure stress waveform is calculated; in the syndrome path, the interference intensity of TCM syndrome feature data on the pure stress waveform is calculated.

[0010] Based on the ratio of penetration gain to interference intensity, the patient's current sleep state is divided into state objects.

[0011] Based on the identification results of the state objects and the recovery characteristic time parameters of the physiological homeostasis under the corresponding state, the output weights of physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions and cognitive intervention instructions are dynamically adjusted in the preset non-drug intervention library.

[0012] Furthermore, the output weights of physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions are dynamically adjusted in the preset non-drug intervention library. This includes: increasing the weight of physical regulation instructions for environmentally sensitive insomnia disorder, increasing the weight of traditional Chinese medicine syndrome regulation instructions for syndrome-dominant insomnia disorder, and implementing weighted combination interventions for complex induced insomnia disorder based on the relative magnitude of penetration gain and interference intensity.

[0013] Secondly, this application also provides a system for developing non-pharmacological intervention strategies for patients with insomnia disorders, including:

[0014] The data acquisition module is used to acquire environmental characteristic data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome characteristic data acquired within a third preset time period.

[0015] The pure stress waveform acquisition module is used to acquire the patient's TCM physiological baseline parameters based on TCM syndrome feature data, map the TCM physiological baseline parameters to a continuous physiological waveform, remove the static components that match the TCM physiological baseline from the continuous physiological waveform, and acquire the pure stress waveform triggered by external disturbance.

[0016] The dual-path attribution module is used to construct a dual-path attribution model that combines environmental and syndrome paths based on the pure stress waveform. In the environmental path, it calculates the penetration gain of environmental features on the pure stress waveform; in the syndrome path, it calculates the interference intensity of TCM syndrome feature data on the pure stress waveform.

[0017] The state object segmentation module is used to segment the patient's current sleep state based on the ratio of penetration gain to interference intensity.

[0018] The non-drug intervention module is used to dynamically adjust the output weights of physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions in a preset non-drug intervention library based on the identification results of the state object and the recovery characteristic time parameters of the physiological homeostasis in the corresponding state.

[0019] Thirdly, this application provides an electronic device, comprising:

[0020] One or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions that, when executed by the device, cause the device to perform the method as described in the first aspect.

[0021] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when run on a computer, causes the computer to perform the method described in the first aspect.

[0022] Fifthly, this application provides a computer program that, when executed by a computer, performs the method described in the first aspect.

[0023] In one possible design, the program in the fifth aspect can be stored wholly or partially on a storage medium packaged with the processor, or it can be stored wholly or partially on a memory not packaged with the processor.

[0024] This application has the following beneficial effects:

[0025] 1. This application acquires environmental characteristic data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome characteristic data collected within a third preset time period. Based on the TCM syndrome characteristic data, it obtains the patient's TCM physiological baseline parameters, maps these parameters onto the continuous physiological waveform, and removes static components matching the TCM physiological baseline from the continuous physiological waveform to obtain a pure stress waveform triggered by external disturbances. This application solves the problem of background noise interference in physiological signals caused by individual differences in insomnia syndrome types by using a pure stress waveform, significantly improving the signal-to-noise ratio for environmental sensitivity determination.

[0026] 2. This application constructs a dual-path attribution model based on the pure stress waveform, which combines the environmental path and the syndrome path. In the environmental path, the penetration gain of environmental features on the pure stress waveform is calculated; in the syndrome path, the interference intensity of TCM syndrome feature data on the pure stress waveform is calculated. This application quantifies the source of physiological stress by decomposing the physiological fluctuations of patients during sleep into the parallel causal contributions of external environmental interference and insomnia syndrome-related factors.

[0027] 3. This application classifies patients’ current sleep state based on the ratio of penetration gain to interference intensity, providing quantitative indicators for non-pharmacological intervention for patients with insomnia.

[0028] 4. This application dynamically adjusts the output weights of physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions in a preset non-drug intervention library based on the identification results of the state object and the recovery characteristic time parameters of the physiological homeostasis under the corresponding state. Through the dynamic adjustment of weights, the state object is dynamically associated with the non-drug intervention strategy, realizing the combined intervention of physical environment regulation and traditional Chinese medicine syndrome regulation. The intervention effect can be corrected according to the patient's physiological response, realizing a solution from cause identification to intervention strategy selection and dynamic adjustment, meeting the comprehensive needs of individual intervention control in home care and non-drug intervention scenarios. Attached Figure Description

[0029] Figure 1 is a flowchart of a method for developing a non-pharmacological intervention strategy for patients with insomnia according to an embodiment of this application;

[0030] Figure 2 is a framework diagram of a non-pharmacological intervention strategy development method for patients with insomnia provided in an embodiment of this application;

[0031] Figure 3 is a schematic diagram of the data acquisition process according to an embodiment of this application;

[0032] Figure 4 is a flowchart of the pure stress waveform acquisition process according to an embodiment of this application;

[0033] Figure 5 is a schematic diagram of the penetration gain acquisition process according to an embodiment of this application;

[0034] Figure 6 is a system flowchart of an embodiment of this application;

[0035] Figure 7 is a schematic diagram of a computer device according to an embodiment of this application. Detailed Implementation

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0037] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0038] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0039] Please refer to Figures 1 and 2. Figure 1 is a flowchart of a method for developing a non-pharmacological intervention strategy for patients with insomnia provided in an embodiment of this application. Figure 2 is a framework diagram of a method for developing a non-pharmacological intervention strategy for patients with insomnia provided in an embodiment of this application. The implementation process is as follows:

[0040] Step S1: Obtain environmental feature data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome feature data collected at a third preset time period.

[0041] It should be noted that the environmental characteristic data for the first preset time period refers to the external physical environment of the patient from the onset of sleep to the first appearance of stable sleep physiological characteristics. The continuous physiological waveforms within the second preset time period represent the dynamic physiological responses formed by the patient during sleep. The TCM syndrome characteristic data collected at the third preset time period represent the patient's insomnia syndrome characteristics.

[0042] Specifically, the process involves acquiring environmental characteristic data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome characteristic data collected at a third preset time period. Please refer to Figure 3 for details, including:

[0043] Step 11: Collect environmental feature data through an environmental sensing unit set in the sleep area to represent the external physical environment status of the patient before falling asleep.

[0044] It should be noted that the environmental characteristic data in this application can be obtained through environmental sensors of wearable devices in the patient's sleep area, environmental acquisition units set up in the bedroom, or environmental monitoring devices in smart homes.

[0045] It should be noted that the start time of the first preset time period is calculated from at least one of the following: when the patient enters a bedridden state and the body position remains stable for more than a preset duration, or when the bedroom light intensity is lower than a preset threshold, and no heart rate variability is detected as an indication of falling asleep.

[0046] Constructing environmental feature data includes: continuously collecting acoustic, thermal, and light environmental parameters of the patient's sleep environment during a first preset time period, such as ambient noise intensity, ambient light intensity, ambient temperature, and their rate of change. Statistical features and trends are extracted for each environmental parameter, and the features corresponding to different environmental parameters are vectorized and combined to form an environmental feature vector for the first preset time period.

[0047] By using environmental characteristics data of the sleep initiation period, we can reflect the potential stimuli of the external environment on sleep initiation before the patient falls asleep, and provide a data basis for the analysis of environmental disturbances and the correlation between physiological responses.

[0048] Step 12: Collect physiological waveform data using a non-invasive physiological monitoring device to represent the dynamic physiological response formed by the patient after falling asleep.

[0049] It should be noted that, in the home setting, physiological waveform data is collected in a non-invasive manner, that is, through at least one of wearable devices or monitoring modules integrated into the bed.

[0050] It should be noted that the definition of the second time period includes at least one of the following: the heart rate fluctuation amplitude enters the preset stable range and exceeds the preset duration; the respiratory rhythm shows stable periodic characteristics; the frequency of body movement events is lower than the preset body movement threshold. When at least one of these conditions is met, the corresponding time interval is marked as the second preset time period.

[0051] It should be noted that continuous physiological waveform data includes at least: heart rate time series waveforms; respiratory rate, respiratory amplitude, or respiratory cycle variation waveforms; and body movement intensity timestamp sequences. The physiological waveform data is continuously sampled using an adaptive sampling frequency to reflect the dynamic changes in physiological state during sleep.

[0052] This application acquires continuous physiological waveform data from patients to obtain their physiological responses under relatively stable conditions, providing temporally continuous physiological data for insomnia syndrome decoupling, stress identification, and state analysis.

[0053] Step 13: Collect TCM syndrome characteristic data of patients during non-sleep time to represent the TCM insomnia syndrome characteristics of patients.

[0054] It should be noted that the TCM syndrome characteristic data is obtained through mobile terminals by acquiring patients' self-reports and symptom selections; through wearable devices by acquiring patients' physiological indicators such as pulse or body temperature; through terminal devices by collecting patients' tongue and facial color image information; and through voice interaction by acquiring subjective descriptions of feelings related to TCM consultation.

[0055] It should be noted that the collected information from the four diagnostic methods is structured and multidimensional parameters that characterize the TCM insomnia syndrome are extracted to form TCM syndrome characteristics.

[0056] It should be noted that the sleep scene in this application is not limited to a specific spatial location or form.

[0057] This application collects environmental characteristic data, continuous physiological waveform data, and TCM syndrome characteristic data at different time periods while the individual is at home. This enables phased modeling of external environmental conditions, physiological responses during sleep, and individual insomnia syndrome characteristics, providing a data foundation for the analysis of the relationship between environment and insomnia syndrome and for non-drug intervention.

[0058] Step S2: Based on the TCM syndrome characteristic data, obtain the TCM physiological baseline parameters of the patient, map the TCM physiological baseline parameters onto the continuous physiological waveform, remove the static components that match the TCM physiological baseline from the continuous physiological waveform, and obtain the pure stress waveform triggered by external disturbance.

[0059] Specifically, please refer to Figure 4. The specific process of obtaining the pure stress waveform triggered by external disturbance includes:

[0060] Step 21: Identify the patient's insomnia syndrome type based on TCM syndrome characteristic data, and obtain the TCM benchmark parameter set corresponding to the insomnia syndrome type. Input the collected TCM syndrome characteristic data into a preset insomnia syndrome type determination model to determine the patient's insomnia syndrome type. Based on the insomnia syndrome type, obtain the corresponding TCM physiological benchmark parameter set from the insomnia syndrome type-physiological prior parameter library. The insomnia syndrome type determination model in this application can employ a machine learning model, using labeled historical data for training. This allows the model to learn the mapping relationship between the four diagnostic methods and the insomnia syndrome type. Suitable models include support vector machines and random forests. The insomnia syndrome type determination model outputs the probability distribution of each insomnia syndrome type, thereby achieving the determination of the patient's insomnia syndrome type.

[0061] Step 22: By performing empirical mode decomposition on the continuous physiological waveform, the projection component of the continuous physiological waveform onto the insomnia syndrome reference direction is defined as the TCM physiological reference matching term among the decomposed multi-order components. The formula for empirical mode decomposition of the continuous physiological waveform is: ,in It is a continuous physiological waveform sequence. For intrinsic modal components, For residual components, This represents the number of intrinsic modal components. For each The spectral energy distribution and rhythm stability index are calculated and matched with corresponding parameters in the TCM benchmark parameter set to obtain the insomnia syndrome matching weights. ,in This represents the probability of the corresponding component being driven by the endogenous mechanism of insomnia. This is a set of physiological baseline parameters for Traditional Chinese Medicine (TCM). When a certain component has concentrated energy within the dominant frequency band of the insomnia syndrome and remains stable over a long period of a second preset time interval, its corresponding weight value increases, and this component is identified as a static physiological component related to the insomnia syndrome. The formula for constructing the baseline projection components of the insomnia syndrome is as follows: , in For the projected components.

[0062] Step 23: Remove the TCM physiological benchmark matching terms from the original continuous physiological waveform to obtain a pure stress waveform free from insomnia syndrome noise interference. The formula is as follows: ,in This is a pure stress waveform.

[0063] The pure stress waveform obtained in this application retains the instantaneous stress jumps caused by external environmental interference, dynamically eliminates individual differences, and enhances the causal relationship between physiological signals and environmental factors.

[0064] Step S3: Construct a dual-path attribution model based on the pure stress waveform, which combines the environmental path and the syndrome path. Calculate the penetration gain of environmental features on the pure stress waveform in the environmental path; calculate the interference intensity of TCM syndrome feature data on the pure stress waveform in the syndrome path.

[0065] It should be noted that the penetration gain of environmental features on the pure stress waveform is calculated in the environmental path to represent the amplification effect of environmental disturbance on the physiological stress amplitude, while the interference intensity of TCM syndrome feature data on the pure stress waveform is calculated in the syndrome path to represent the degree of dominance of TCM insomnia syndrome-related factors on physiological state fluctuations.

[0066] In one possible implementation, the penetration gain of environmental features on the pure stress waveform is calculated in the environmental path, as shown in Figure 5, including:

[0067] Step 31: The environmental feature data is energized to generate an environmental input reward characterizing the intensity of external disturbances. Within a preset time window, acoustic parameters, thermal environment parameters, and light environment parameters are energized to obtain the corresponding environmental energy components, i.e.: ,in Indicates the first The energy value of the environmental parameter within the current time window. This represents the environmental weighting function, indicating the degree of influence of different environmental parameters on sleep. Indicates the first Class environment parameters at time The collected environmental values.

[0068] By weighted fusion of the energy of different environmental parameters, the environmental input intensity characterizing the intensity of external disturbance is obtained, i.e.: ,in Indicates environmental input rewards. Indicates the first Normalized weight coefficients corresponding to class environment parameters, This indicates the number of environmental parameters.

[0069] Step 32: Based on the amplitude change of physiological stress response reflected in the pure stress waveform, calculate the correlation between input reward and amplitude change on the time axis. Based on the correlation analysis results, define the proportion of physiological stress change caused by unit environmental energy fluctuation as osmotic gain.

[0070] It should be noted that the magnitude of the change is expressed as: , in It represents the magnitude of change in the physiological stress response within each time period.

[0071] On a unified timeline, a correlation analysis is performed on the input reward and the magnitude of change, namely: ,in This indicates the coupling strength between environmental disturbances and physiological stress.

[0072] Within a time interval where the correlation meets a preset correlation threshold, the proportion of physiological stress change caused by a unit environmental energy fluctuation is defined as the osmotic gain, i.e.: and ,in For penetration gain, To preset relevant thresholds, It represents the statistical expectation.

[0073] In one possible implementation, calculating the interference intensity of TCM syndrome characteristic data on the pure stress waveform within the syndrome pathway includes:

[0074] The syndrome pathway set is determined based on the syndrome differentiation of patients' insomnia. For example, the Qi deficiency pathway affects respiration and heart rate; the Yin deficiency pathway affects the amplification factor of high-frequency heart rate fluctuations, etc.

[0075] The deviation and change of TCM syndrome feature data within a preset window are extracted to form a TCM perturbation vector. The TCM perturbation vector includes the deviation of tongue appearance parameters from the baseline, the stable decrease in sound diagnosis, and short-term changes in subjective symptom scores.

[0076] Stress response indicators related to the syndrome pathway are extracted from the pure stress waveform to form a stress response vector. The stress response vector includes instantaneous heart rate increase, high-frequency or mid-frequency energy changes, and the degree of abrupt changes in respiratory rhythm amplitude.

[0077] Under the constraint of syndrome path, the coupling strength between the TCM perturbation vector and the stress response vector is calculated, and the coupling strength is used as the interference strength of TCM syndrome characteristic data on the pure stress waveform.

[0078] Step S4: Based on the ratio of penetration gain to interference intensity, the patient's current sleep state is divided into state objects. Based on the decay and stabilization process of the pure stress waveform, the recovery characteristic time parameters of physiological homeostasis in the corresponding state are calculated. The state objects include environmentally sensitive insomnia disorder, syndrome-dominant insomnia disorder, and complex induced insomnia disorder.

[0079] It should be noted that the complex induced insomnia disorder state is an environment-symptom complex induced insomnia disorder state.

[0080] In this embodiment, the patient's current sleep state is classified into state objects, including a first preset threshold and a second preset threshold. When the ratio of penetration gain to interference intensity is greater than the first preset threshold, it is determined to be an environment-sensitive insomnia disorder state. When the ratio of penetration gain to interference intensity is less than the second preset threshold, it is determined to be a syndrome-dominant insomnia disorder state. When the ratio of penetration gain to interference intensity is less than or equal to the first preset threshold and greater than or equal to the second preset threshold, it is a combination of environment-syndrome-induced insomnia disorder state.

[0081] In this embodiment of the application, based on the decay and stabilization process of the pure stress waveform, the recovery characteristic time parameters of the physiological homeostasis under the corresponding state are calculated, including:

[0082] In pure stress waveform In the middle, detect the end time of external disturbance. As the starting point for stabilization analysis, at least one of the following conditions must be met to determine the end of the external disturbance: the environmental input reward drops below a preset threshold; the pure stress waveform reaches a local extreme and enters a monotonically decaying range; or the rate of change of the physiological waveform energy is lower than a preset threshold.

[0083] In the interval The amplitude of the pure stress waveform is fitted with an exponential decay within the range, i.e.: ,in Indicates the initial stress level. Indicates the stress decay rate. This indicates the steady-state offset baseline.

[0084] In this embodiment of the application, it is assumed that the physiological homeostasis range is When satisfied If the duration is not less than a preset time period, the physiological state is considered to have stabilized. The recovery characteristic time parameter of the corresponding physiological homeostasis is calculated, i.e.: ,in Indicates the recovery feature time parameter. This indicates the time point at which the pure stress waveform first enters and remains in the steady-state region. This indicates the starting point for the stabilization analysis.

[0085] Step S5: Based on the identification results of the state object and the recovery characteristic time parameters of the physiological homeostasis in the corresponding state, dynamically adjust the output weights of physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions and cognitive intervention instructions in the preset non-drug intervention library.

[0086] In this embodiment of the application, the expression for the preset non-drug intervention library is: ,in This represents the set of instructions for adjusting the physical environment. This represents a set of instructions for regulating syndromes in Traditional Chinese Medicine. This represents a set of instructions for cognitive behavioral intervention.

[0087] Specifically, a pre-defined non-pharmacological intervention library is constructed, which includes a physical environment regulation instruction set, a traditional Chinese medicine (TCM) syndrome regulation instruction set, and a cognitive behavioral intervention instruction set. The physical environment regulation instruction set is used to adjust parameters related to the sleep environment; the TCM syndrome regulation instruction set is used to schedule non-pharmacological regulation methods related to the patient's insomnia syndrome; and the cognitive behavioral intervention instruction set is used to correct the patient's functional disordered cognition and maladaptive sleep behaviors. The cognitive behavioral intervention instructions are digitally transformed from clinical insomnia cognitive behavioral interventions into executable and quantifiable instructions.

[0088] Based on the identification results of the state objects, initial weights are assigned to the physical environment regulation instruction set, the traditional Chinese medicine syndrome regulation instruction set, and the cognitive behavioral intervention instruction set, respectively. For example, when the state is identified as environmentally sensitive insomnia disorder, the weight of the physical environment regulation instruction is increased; when the state is identified as syndrome-dominant insomnia disorder, the weight of the traditional Chinese medicine syndrome regulation instruction is increased; when the state is identified as insomnia disorder induced by a combination of environment and syndrome, relatively balanced initial weights are set for the two types of instructions; when a high correlation is found between stress waveforms and pre-sleep anxiety, the weight of cognitive behavioral intervention is increased.

[0089] By introducing a recovery index that reflects the ability to restore physiological homeostasis, the initial weights are dynamically adjusted. When the recovery characteristic time parameter indicates a slow rate of physiological state stabilization, the overall output weight of the intervention instruction is increased; when the recovery characteristic time parameter indicates a fast rate of physiological state stabilization, the output intensity of the intervention instruction is reduced.

[0090] After the weight adjustment is completed, the physical environment regulation instructions, TCM syndrome regulation instructions and cognitive intervention instructions are combined according to their corresponding weights to generate non-drug intervention output instructions for execution.

[0091] For example, the set of instructions for adjusting the physical environment is as follows: The TCM syndrome regulation instruction set is as follows: The cognitive behavioral intervention instruction set is as follows: ,in This indicates a noise adjustment command. This indicates a command to adjust the lighting. This indicates a temperature adjustment command. This indicates a humidity adjustment command. This indicates a breathing regulation instruction. This indicates acupoint stimulation instructions. This indicates the Five Elements Music Selection Command. Indicates the time period for appreciation. This indicates instructions for sleep hygiene education. This indicates a stimulus control command. This indicates a sleep restriction instruction. This indicates a cognitive correction instruction. This indicates a psychological relaxation instruction.

[0092] The recovery feature time parameter is normalized to the recovery exponent, i.e.: Then, the initial weights are dynamically adjusted based on the recovery index, that is: , , ,in .in , , The modulation coefficient, The initial weighting coefficients for the physical environment adjustment commands. The initial weighting coefficients for TCM syndrome differentiation and regulation instructions. The initial weighting coefficients for cognitive behavioral intervention instructions, when The larger the scale, the more it tends to be regulated by physical environment or by traditional Chinese medicine syndromes. The weights of the dynamically adjusted real-time execution physical environment control commands are used to adjust the weights of the commands. The weights for dynamically adjusted real-time execution of TCM syndrome differentiation and regulation instructions. To dynamically adjust the weights of real-time execution of cognitive behavioral intervention instructions, when The smaller the child, the more appropriate the intervention should be.

[0093] Then the final non-pharmacological intervention output instruction is output, that is , This is the final composite control sequence to be executed.

[0094] In one possible implementation, when the composite control sequence includes instructions for regulating the physical environment, where home physical environment regulation is crucial for improving sleep quality, a suitable sleep environment is created by controlling environmental factors such as temperature, humidity, light, and noise. This includes adjusting the indoor temperature to a suitable range, such as 18°C-22°C, via smart devices; maintaining the humidity of the sleep environment at an ideal level, such as 40%-60%, via humidifiers or dehumidifiers; adjusting the brightness of lights via smart lighting fixtures to simulate natural day-night cycles and help regulate the biological clock; and reducing external environmental noise by closing windows to maintain a quiet sleep environment.

[0095] In one possible implementation, when the composite control sequence includes TCM syndrome regulation instructions, breathing instructions are regulated based on the patient's insomnia syndrome characteristics, recommending acupoint stimulation locations, types of TCM sound therapy, and rhythm guidance types. Recommended acupoint stimulation locations include acupoint massage video feeds, with video content including live demonstrations of acupoint location methods and image displays. Each acupoint is massaged for 2 minutes, 1-2 times daily.

[0096] Breathing is a key tool for regulating the nervous system, promoting sleep by regulating heart rate, reducing anxiety, and stabilizing emotions. Deep abdominal breathing can relieve stress, improve sleep, and activate the parasympathetic nervous system, helping the body relax and enter a sleep state.

[0097] For example, it is recommended to practice breathing exercises 30-60 minutes before bedtime, for 5-10 minutes. Example instructions: Inhale, count to 4, hold for 2 seconds, then slowly exhale through your mouth, counting to 6. With each inhale, imagine you are inhaling fresh air; with each exhale, release tension and stress from your body. You can practice breathing exercises while sitting or lying down, keeping your body relaxed.

[0098] For liver qi stagnation transforming into fire syndrome, based on the pathogenesis and treatment principles of liver qi stagnation transforming into fire syndrome, the recommended main acupoints for massage, the recommended musical instruments based on the Five Elements, and the corresponding listening times are shown in Table 1 below:

[0099]

[0100] Table 1. Liver Qi Stagnation Transforming into Fire Syndrome

[0101] For phlegm-heat disturbance syndrome, based on the pathogenesis and treatment principles of phlegm-heat disturbance syndrome, the recommended main acupoints for massage, the recommended music based on the Five Elements, and the corresponding listening times are shown in Table 2 below:

[0102]

[0103] Table 2 Phlegm-Heat Disturbance Syndrome

[0104] For the syndrome of deficiency of both heart and spleen, based on the pathogenesis and treatment principles of this syndrome, the recommended main acupoints for massage, the recommended musical instruments based on the Five Elements, and the corresponding times for listening are shown in Table 3 below:

[0105]

[0106] Table 3. Syndrome of Deficiency of Both Heart and Spleen

[0107] For the syndrome of deficiency of heart and gallbladder qi, based on the pathogenesis and treatment principles of this syndrome, the recommended main acupoints for massage, the recommended musical instruments based on the Five Elements, and the corresponding times for listening are shown in Table 4 below:

[0108]

[0109] Table 4. Heart and Gallbladder Qi Deficiency Syndrome

[0110] For the syndrome of heart-kidney disharmony, based on the pathogenesis and treatment principles of heart-kidney disharmony, the recommended main acupoints for massage, the recommended musical instruments based on the Five Elements, and the corresponding times for appreciation are shown in Table 5 below:

[0111]

[0112] Table 5. Heart-Kidney Disharmony Syndrome

[0113] This application combines the characteristics of a patient's insomnia syndrome with the selection of corresponding acupoint stimulation, Five Elements music selection, and corresponding listening times to precisely regulate the patient's insomnia disorder and help patients with different insomnia syndromes obtain high-quality sleep.

[0114] In one possible implementation, when the composite control sequence includes cognitive behavioral intervention instructions, the sleep hygiene education instructions aim to improve environmental factors and personal habits. Examples of cognitive behavioral intervention instructions including sleep hygiene education instructions include: when there are luminous electronic devices in the sleep environment, reminding the patient to turn off or cover the light source to avoid the luminous devices affecting sleep. When the patient experiences prolonged daytime sleep, an instruction is output to increase the patient's physical activity and avoid going to bed too early. However, when instructing the patient to increase their physical activity, a video of Baduanjin (Eight Pieces of Brocade) can be shown. Baduanjin is a traditional Chinese health-preserving exercise, an independent and complete set of guided exercises, a type of ancient Qigong. Practicing Baduanjin is a form of physical and mental cultivation, suitable for all ages, and is hailed as a national fitness exercise. Practicing it 1-2 times daily helps modern people find physical balance and inner peace in their fast-paced lives.

[0115] Stimulus control instructions establish a positive connection between sleep and the bed, eliminating the negative association of non-sleep activities. Specifically, when the system detects that the patient does not have a sleep waveform within a preset time period while in bed, it sends a stimulus control instruction to the patient: "If we detect that you are not sleepy now, please leave the bedroom and do some activities. Come back to sleep when you feel sleepy."

[0116] Sleep restriction instructions limit time spent in bed, improve sleep concentration and efficiency, and help the body re-establish a stable sleep rhythm. For example, when it's detected that a patient spends a long time in bed but has very little actual sleep, an adjustment instruction is issued: such as "Please adjust your bedtime to 11:00 PM and your wake-up time to 5:30 AM to help you fall asleep quickly and improve sleep quality."

[0117] Cognitive corrective instructions help alleviate tension and anxiety caused by excessive worry about sleep problems and reduce the situation where the more you want to sleep, the less you can fall asleep. For example, if the patient is detected to be tense before bedtime, the patient is advised that it is okay even if they do not sleep well tonight, they can still cope normally tomorrow, please relax and do not worry excessively about the sleep results.

[0118] Psychological relaxation instructions promote sleep by reducing muscle tension. They are coordinated with TCM syndrome regulation instructions, such as playing soothing music through TCM syndrome regulation instructions, combined with muscle relaxation training to reduce muscle tension. This helps patients experience a deep sense of relaxation by relaxing different muscle groups in different parts of the body. Practicing this 1-2 times a day can improve blood pressure, relieve stress, and improve sleep quality.

[0119] In this embodiment, the generated non-pharmacological intervention strategy is verified by a physician and then pushed to the patient's terminal.

[0120] Please refer to Figure 6, which is a schematic diagram of a non-pharmacological intervention strategy development system for patients with insomnia provided in an embodiment of this application. The specific modules include:

[0121] The data acquisition module 601 is used to acquire environmental characteristic data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome characteristic data acquired within a third preset time period.

[0122] The pure stress waveform acquisition module 602 is used to acquire the patient's TCM physiological baseline parameters based on TCM syndrome feature data, map the TCM physiological baseline parameters to a continuous physiological waveform, remove static components that match the TCM physiological baseline from the continuous physiological waveform, and acquire the pure stress waveform triggered by external disturbance.

[0123] The dual-path attribution module 603 is used to construct a dual-path attribution model that combines environmental and syndrome paths based on the pure stress waveform. In the environmental path, it calculates the penetration gain of environmental features on the pure stress waveform; in the syndrome path, it calculates the interference intensity of TCM syndrome feature data on the pure stress waveform.

[0124] The state object segmentation module 604 is used to segment the patient's current sleep state based on the ratio of penetration gain to interference intensity.

[0125] The non-drug intervention module 605 is used to dynamically adjust the output weights of physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions in a preset non-drug intervention library based on the identification results of the state object and the recovery characteristic time parameters of the physiological homeostasis under the corresponding state.

[0126] This application obtains the patient's TCM physiological baseline parameters, maps these parameters to a continuous physiological waveform, and removes static components matching the TCM physiological baseline from the continuous physiological waveform to obtain a pure stress waveform triggered by external disturbances. Based on the pure stress waveform, a dual-path attribution model is constructed, which combines environmental and syndrome pathways. In the environmental pathway, the penetration gain of environmental features on the pure stress waveform is calculated; in the syndrome pathway, the interference intensity of TCM syndrome feature data on the pure stress waveform is calculated. Based on the ratio of penetration gain to interference intensity, the patient's current sleep state is classified into state objects. Based on the identification results of the state objects and the recovery characteristic time parameters of physiological homeostasis in the corresponding state, the output weights of physical environment regulation instructions, TCM syndrome regulation instructions, and cognitive intervention instructions are dynamically adjusted in a preset non-drug intervention library. This application provides a dynamically adaptive home-based non-drug intervention program by distinguishing the syndrome manifestations of different syndrome types of insomnia disorders.

[0127] To address the aforementioned technical problems, this application also provides a computer device. Please refer to Figure 7 for details; Figure 7 is a basic structural block diagram of the computer device according to this embodiment.

[0128] The computer device 7 includes a memory 7a, a processor 7b, and a network interface 7c that are interconnected via a system bus. It should be noted that only the computer device 7 with components 7a-7c is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0129] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0130] The memory 7a includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 7a may be an internal storage unit of the computer device 7, such as the hard disk or memory of the computer device 7. In other embodiments, the memory 7a may also be an external storage device of the computer device 7, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 7. Of course, the memory 7a may also include both the internal storage unit and its external storage device of the computer device 7. In this embodiment, the memory 7a is typically used to store the operating system and various application software installed on the computer device 7, such as program code for a non-pharmacological intervention strategy formulation method for patients with insomnia disorder. In addition, the memory 7a can also be used to temporarily store various types of data that have been output or will be output.

[0131] In some embodiments, the processor 7b may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 7b is typically used to control the overall operation of the computer device 7. In this embodiment, the processor 7b is used to run program code stored in the memory 7a or to process data, for example, to run program code for a method of developing a non-pharmacological intervention strategy for patients with insomnia.

[0132] The network interface 7c may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 7 and other electronic devices.

[0133] This application also provides another embodiment, namely, a non-volatile computer-readable storage medium storing a program for a method of developing a non-pharmacological intervention strategy for a patient with insomnia disorder, which can be executed by at least one processor to perform the steps of the method of developing a non-pharmacological intervention strategy for a patient with insomnia disorder as described above.

[0134] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0135] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A method for developing a non-pharmacological intervention strategy for patients with insomnia disorder, characterized in that, include: The system acquires environmental feature data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome feature data collected within a third preset time period. Based on the TCM syndrome feature data, the system acquires the patient's TCM physiological baseline parameters, maps the TCM physiological baseline parameters to the continuous physiological waveform, removes static components that match the TCM physiological baseline from the continuous physiological waveform, and acquires the pure stress waveform triggered by external disturbance. A dual-path attribution model, combining environmental and syndrome pathways, is constructed based on the pure stress waveform. In the environmental pathway, the penetration gain of environmental features on the pure stress waveform is calculated; in the syndrome pathway, the interference intensity of TCM syndrome feature data on the pure stress waveform is calculated. Based on the ratio of penetration gain to interference intensity, the patient's current sleep state is classified into state objects. Based on the identification results of the state objects and the recovery characteristic time parameters of physiological homeostasis in the corresponding state, the output weights of physical environment regulation instructions, TCM syndrome regulation instructions, and cognitive intervention instructions are dynamically adjusted within a pre-set non-drug intervention library.

2. The method for developing non-pharmacological intervention strategies for patients with insomnia according to claim 1, characterized in that, Obtaining a pure stress waveform triggered by external disturbances includes: identifying the patient's insomnia syndrome type based on TCM syndrome characteristic data, and obtaining the TCM benchmark parameter set corresponding to the insomnia syndrome type; performing empirical mode decomposition on the continuous physiological waveform, defining the projection component of the continuous physiological waveform on the insomnia syndrome benchmark direction as the TCM physiological benchmark matching term among the decomposed multi-order components; and removing the TCM physiological benchmark matching term from the original continuous physiological waveform to obtain a pure stress waveform free from insomnia syndrome noise interference.

3. The method for developing non-pharmacological intervention strategies for patients with insomnia according to claim 1, characterized in that, The calculation method of penetration gain includes: energizing environmental characteristic data to generate environmental input reward to characterize the intensity of external disturbance; calculating the correlation between input reward and amplitude change on the time axis based on the amplitude change of physiological stress response in the pure stress waveform; and defining the proportion of physiological stress change caused by unit environmental energy fluctuation as penetration gain based on the correlation analysis results.

4. The method for developing non-pharmacological intervention strategies for patients with insomnia according to claim 1, characterized in that, The interference intensity of TCM syndrome feature data on the pure stress waveform is calculated in the syndrome pathway, including: determining the syndrome pathway set based on the syndrome differentiation of patients' insomnia; extracting the deviation and change of TCM syndrome feature data within a preset window to form a TCM perturbation vector; extracting stress response indicators related to the syndrome pathway from the pure stress waveform to form a stress response vector; and calculating the coupling strength between the TCM perturbation vector and the stress response vector under the constraint of the syndrome pathway, and using the coupling strength as the interference intensity of TCM syndrome feature data on the pure stress waveform.

5. The method for developing non-pharmacological intervention strategies for patients with insomnia according to claim 1, characterized in that, The patient's current sleep state is classified into two categories: a first preset threshold and a second preset threshold. When the ratio of penetration gain to interference intensity is greater than the first preset threshold, the patient is classified as having an environment-sensitive insomnia disorder. When the ratio of penetration gain to interference intensity is less than the second preset threshold, the patient is classified as having a syndrome-dominant insomnia disorder. When the ratio of penetration gain to interference intensity is less than or equal to the first preset threshold and greater than or equal to the second preset threshold, the patient is classified as having an environment-syndrome combined induced insomnia disorder.

6. The method for developing non-pharmacological intervention strategies for patients with insomnia according to claim 1, characterized in that, Based on the decay and stabilization process of the pure stress waveform, the recovery characteristic time parameters of physiological homeostasis under the corresponding state are calculated, including: in the pure stress waveform In the middle, detect the end time of external disturbance. As the starting point for stabilization analysis; the amplitude of the pure stress waveform is fitted with exponential decay within a preset time interval; the physiological steady-state interval of the game is... When satisfied If the duration is not less than the preset time period, then the physiological state has stabilized; calculate the recovery characteristic time parameter of the physiological homeostasis under the corresponding state, that is: ,in Indicates the recovery feature time parameter. This indicates the time point at which the pure stress waveform first enters and remains in the steady-state region. This indicates the starting point for the stabilization analysis.

7. The method for developing non-pharmacological intervention strategies for patients with insomnia according to claim 1, characterized in that, Based on the identification results of state objects and the recovery characteristic time parameters of physiological homeostasis under the corresponding state, the output weights of physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions are dynamically adjusted in a preset non-drug intervention library. This includes: constructing a preset non-drug intervention library, which includes physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions; assigning initial weights to physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions according to the identification results of state objects; dynamically adjusting the initial weights by introducing a recovery index that reflects the ability to restore physiological homeostasis; and combining physical environment regulation instructions, traditional Chinese medicine syndrome regulation instructions, and cognitive intervention instructions according to their corresponding weights to generate non-drug intervention output instructions for execution.

8. A system for developing non-pharmacological intervention strategies for patients with insomnia disorder, used to implement the methods of claims 1-7, characterized in that, include: The data acquisition module is used to acquire environmental characteristic data within a first preset time period, continuous physiological waveforms within a second preset time period, and TCM syndrome characteristic data acquired within a third preset time period. The pure stress waveform acquisition module is used to acquire the patient's TCM physiological baseline parameters based on TCM syndrome feature data, map the TCM physiological baseline parameters to a continuous physiological waveform, remove the static components that match the TCM physiological baseline from the continuous physiological waveform, and acquire the pure stress waveform triggered by external disturbance. The dual-path attribution module is used to construct a dual-path attribution model that combines environmental and syndrome pathways based on the pure stress waveform. In the environmental pathway, it calculates the penetration gain of environmental features on the pure stress waveform; in the syndrome pathway, it calculates the interference intensity of TCM syndrome feature data on the pure stress waveform. The state object segmentation module is used to segment the patient's current sleep state into state objects based on the ratio of penetration gain to interference intensity. The non-pharmacological intervention module is used to dynamically adjust the output weights of physical environment regulation instructions, TCM syndrome regulation instructions, and cognitive intervention instructions in a preset non-pharmacological intervention library based on the identification results of state objects and the recovery characteristic time parameters of physiological homeostasis in the corresponding state.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing computer instructions thereon, characterized in that, When executed by the processor, this instruction implements the steps of the method as described in any one of claims 1-7.

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