Sleep depth adjusting method, system and device based on sleep staging

Abstract

The invention discloses a sleep depth adjusting method, system and device based on sleep stages, and belongs to the technical field of sleep medicine. The problem that in the prior art, the infusion speed of an infusion pump cannot be automatically adjusted according to the sleep stages is solved, polysleep monitoring is conducted on a patient through the polysleep monitor, sleep data of the patient are obtained and processed, the processed sleep data are analyzed, the current sleep stages of the patient are determined, and therefore the patient can be more accurately infused. A target control target is preset, the current sleep stage is compared with the preset target control target, and the sedative infusion speed corresponding to the current sleep stage is determined, so that the sedative infusion speed of an infusion pump is automatically adjusted, the sedative infusion effect is improved, the infusion speed of the infusion pump is monitored in real time through sensing equipment, and the sedative infusion speed of the infusion pump is monitored in real time. Whether the infusion speed is abnormal or not is monitored and judged, and an early warning notice is sent out under the abnormal condition, so that normal infusion is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of sleep medicine, and in particular to a method, system and device for regulating sleep depth based on sleep staging. Background Art

[0002] Human sleep consists of two alternating sleep periods, one is non-rapid eye movement sleep (NREM) and the other is rapid eye movement sleep (REM). Among them, non-rapid eye movement sleep is divided into three stages, namely: sleep stage 1 (N1), sleep stage 2 (N2), and sleep stage 3 (N3). The typical sleep process of a healthy adult is as follows: awakening-non-rapid eye movement sleep, namely NREM stage (sleep stage 1-sleep stage 2-sleep stage 3-sleep stage 2)-rapid eye movement stage, namely REM stage-non-rapid eye movement sleep (sleep stage 1-sleep stage 2-sleep stage 3-sleep stage 2)-rapid eye movement stage-non-rapid eye movement stage-rapid eye movement stage-awakening. Since sleep is related to the infusion of sedative drugs, different infusion speeds need to be adjusted at different sleep depths, but the existing technology cannot automatically adjust the infusion speed of the infusion pump according to the sleep stage; therefore, it does not meet the existing needs. In this regard, we propose a sleep depth adjustment method, system and device based on sleep stage. Summary of the invention

[0003] The purpose of the present invention is to provide a sleep depth adjustment method, system and device based on sleep staging, which performs polysomnography on patients through a polysomnography monitor, obtains and processes the patient's sleep data, analyzes the processed sleep data, determines the patient's current sleep stage, presets a target control target, compares the current sleep stage with the preset target control target, determines the sedative drug infusion speed corresponding to the current sleep stage, and automatically adjusts the sedative drug infusion speed of the infusion pump, and uses a sensor device to monitor the infusion speed of the infusion pump in real time, determines whether the infusion speed is abnormal through monitoring, and issues an early warning notification in abnormal situations, thereby solving the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a method for adjusting sleep depth based on sleep staging, comprising the following steps:

[0005] S1: Perform polysomnography on the patient through a polysomnography monitor, collect various parameters of the patient during sleep, and finally obtain the patient's sleep data, process the obtained sleep data, and analyze the processed sleep data to determine the patient's current sleep stage through analysis;

[0006] Among them, sleep stages are divided into four cycles, namely: NREM stage 1, NREM stage 2, NREM stage 3 and REM sleep;

[0007] S2: preset target control target, which is the sedative drug infusion rate under different sleep stages, obtain the patient's current sleep stage, compare the current sleep stage with the preset target control target, determine the sedative drug infusion rate corresponding to the current sleep stage through comparison, and automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison result;

[0008] S3: Based on the target control objectives and comparison results, the infusion speed of the infusion pump is monitored in real time using sensing equipment. The infusion speed is judged to be abnormal through monitoring, and an early warning notification is issued in abnormal situations.

[0009] Furthermore, the specific process of S1 is as follows:

[0010] S1.1: The polysomnography monitor contains multiple sensors, which are placed on the corresponding parts of the patient to ensure that the multiple sensors fit the patient's skin and remain stable;

[0011] S1.2: After the polysomnography is set up, set the polysomnography parameters, including recording time and sampling frequency;

[0012] S1.3: After the polysomnography parameters are set, the polysomnography is started on the patient. The polysomnography collects various parameters of the patient during sleep in real time, and finally obtains the patient's sleep data and performs data processing;

[0013] S1.4: During the monitoring period, the polysomnography monitor is regularly tested to determine whether there is any abnormality in the data collection of the polysomnography monitor;

[0014] S1.5: Prepare a sleep data training set in advance and train a sleep quality assessment model through a machine learning algorithm;

[0015] S1.6: Input the processed sleep data into the trained sleep quality assessment model to conduct real-time assessment of the user's sleep quality and determine the patient's current sleep stage.

[0016] Furthermore, the data processing includes:

[0017] Filtering: The sleep data is filtered through filtering technology to remove high-frequency and low-frequency noise in the sleep data;

[0018] Outlier processing: detect outliers in sleep data and process them using outlier processing methods;

[0019] Normalization: The sleep data is normalized to eliminate the dimensional differences in the sleep data.

[0020] Furthermore, the specific process of S2 is as follows:

[0021] S2.1: Based on the four cycles of sleep staging, preset target control targets are the infusion rates of sedative drugs under different sleep stages;

[0022] S2.2: Obtain the patient's current sleep stage, compare the current sleep stage with the preset target control target, and determine the sedative drug infusion rate corresponding to the current sleep stage based on the comparison;

[0023] S2.3: Automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison results;

[0024] When the patient's current sleep stage is in NREM stage 1, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage 1;

[0025] When the patient's current sleep stage is in NREM stage II, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage II;

[0026] When the patient's current sleep stage is in NREM stage III, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage III;

[0027] When the patient's current sleep stage is REM sleep, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to REM sleep.

[0028] Furthermore, the specific process of S3 is as follows:

[0029] S3.1: A sensing device is set at the infusion pump. The sensing device adopts a flow rate sensor, and the infusion speed of the infusion pump is monitored in real time through the set sensing device;

[0030] S3.2: Obtain monitoring data of the infusion pump through real-time monitoring, and analyze the monitoring data based on the target control objectives and comparison results;

[0031] S3.3: Analyze and determine whether there is any abnormality in the infusion speed of the infusion pump, and determine whether the current infusion speed of the infusion pump conforms to the infusion speed adjusted after the comparison result;

[0032] If there is no abnormality in the infusion speed of the infusion pump, it is determined that the current infusion speed of the infusion pump is consistent with the infusion speed adjusted by the comparison result;

[0033] If the infusion speed of the infusion pump is abnormal, it is determined that the current infusion speed of the infusion pump does not conform to the infusion speed adjusted after the comparison result;

[0034] S3.4: When the judgment result shows that an abnormal situation exists, an early warning notification is sent to the monitoring end, and the medical staff checks the abnormal infusion pump according to the early warning notification.

[0035] Furthermore, the ratio between the input change and the output change of the flow velocity sensor is monitored in real time, and the sensitivity of the flow velocity sensor is adjusted, including:

[0036] Arrange a second flow velocity sensor with the same model and specification as the flow velocity sensor at the same monitoring position as the flow velocity sensor as a reference flow velocity sensor;

[0037] Monitor the infusion rate of the infusion pump via a reference flow rate sensor;

[0038] Obtaining a flow rate change rate of the measured fluid according to the infusion speed of the infusion pump;

[0039] Real-time monitoring of the sensor output signal of the flow velocity sensor;

[0040] Acquire the sensor signal change rate of flow rate monitoring according to the sensor output signal of the flow rate sensor;

[0041] The sensitivity evaluation coefficient of the flow velocity sensor is obtained according to the flow velocity change rate of the measured fluid and the change rate of the sensor signal of the flow velocity monitoring; wherein the sensitivity evaluation coefficient of the flow velocity sensor is obtained by the following formula:

[0042]

[0043] Where Q represents the sensitivity evaluation coefficient of the flow velocity sensor; n represents the number of data collection times of the flow velocity sensor; P ci P represents the rate of change of the sensor signal of the flow sensor during the i-th data collection relative to the previous data collection; ri P represents the rate of change of the flow rate of the measured fluid in the ith data collection of the reference flow rate sensor corresponding to the flow rate sensor relative to the previous data collection; rmax It indicates the maximum value of the rate of change of the flow velocity of the measured fluid when the data of the reference flow velocity sensor corresponding to the flow velocity sensor is collected relative to the last data collection; P cmax Indicates the flow rate change rate of the flow sensor corresponding to the maximum value of the flow rate change rate of the measured fluid; P rmin Indicates the minimum value of the flow rate change rate of the measured fluid of the reference flow rate sensor corresponding to the flow rate sensor relative to the last data collection; P cmin Indicates the flow rate change rate of the flow rate sensor corresponding to the minimum value of the flow rate change rate of the measured fluid;

[0044] Whether the sensitivity of the flow velocity sensor needs to be adjusted is determined according to the sensitivity evaluation coefficient.

[0045] Further, determining whether the sensitivity of the flow velocity sensor needs to be adjusted according to the sensitivity evaluation coefficient includes:

[0046] Comparing the sensitivity evaluation coefficient with a preset evaluation coefficient threshold;

[0047] When the sensitivity evaluation coefficient is lower than a preset evaluation coefficient threshold, it is determined that the sensitivity of the flow velocity sensor needs to be adjusted;

[0048] The sensitivity compensation amount is obtained according to the flow velocity change rate of the measured fluid and the change rate of the sensor signal of the flow velocity monitoring; wherein the sensitivity compensation amount is obtained by the following formula:

[0049]

[0050] Where, L represents the sensitivity compensation amount; L min Indicates the minimum flow rate that the flow sensor can collect; L p It indicates the value of zero drift corresponding to the flow sensor; Q indicates the sensitivity evaluation coefficient of the flow sensor; Q y represents a preset evaluation coefficient threshold; λ represents an adjustment coefficient, and the adjustment coefficient is obtained by the following formula:

[0051]

[0052] Where λ represents the adjustment coefficient; n represents the number of data collection times of the flow velocity sensor; P ci P represents the rate of change of the sensor signal of the flow sensor during the i-th data collection relative to the previous data collection; ri Indicates the rate of change of the flow velocity of the measured fluid of the i-th data collection of the reference flow velocity sensor corresponding to the flow velocity sensor relative to the previous data collection;

[0053] The adjusted sensitivity corresponding to the flow rate sensor is obtained according to the sensitivity compensation amount; wherein the adjusted sensitivity is obtained by the following formula:

[0054] L t =(1+L)·L x

[0055] Among them, L t Indicates the sensitivity after adjustment; L indicates the sensitivity compensation amount; L x Indicates the sensitivity before adjustment.

[0056] Furthermore, the S3.4 includes the following process:

[0057] S3.4.1: Immediately send an early warning notification to the monitoring end when there is an abnormality in the infusion speed of the infusion pump;

[0058] S3.4.2: After receiving the warning notification, the medical staff performs a known feedback operation on the warning notification through the monitoring terminal, and stops the warning notification after completing the known feedback operation;

[0059] S3.4.3: Monitor the duration of known feedback operations by medical staff, determine whether medical staff respond to warning notifications in a timely manner based on the monitoring duration, and issue warning notifications to medical staff who do not respond in a timely manner;

[0060] Among them, the monitoring duration is divided into 0s-60s, 60s-180s and more than 180s;

[0061] If the monitoring duration is 0s-60s, it is judged that the medical staff responds to the warning notification in time;

[0062] If the monitoring duration is 60s-180s, it is judged that the medical staff did not respond in time and a warning notice is issued to the medical staff;

[0063] If the monitoring time is longer than 180 seconds, it is judged that the medical staff has not responded in a timely manner, and a warning notice is issued to the medical staff, and the warning notice is also sent to the medical staff's superior.

[0064] Sleep depth regulation system based on sleep stages, including:

[0065] Sleep monitoring and analysis system for:

[0066] Perform polysomnography on the patient, set the parameters of the polysomnography in advance, and the polysomnography collects various parameters of the patient's sleep in real time;

[0067] During the monitoring period, the polysomnography monitor is regularly tested for abnormal data collection, and the patient's sleep data is finally obtained and processed;

[0068] The processed sleep data is input into the trained sleep quality assessment model to conduct real-time assessment of the user's sleep quality and determine the patient's current sleep stage;

[0069] Target-controlled infusion systems for:

[0070] Based on the preset target control targets of the four cycles of sleep staging, the patient's current sleep staging is obtained, and the current sleep staging is compared with the preset target control targets;

[0071] Determine the sedative drug infusion rate corresponding to the current sleep stage by comparison, and automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison result;

[0072] Use sensor equipment to monitor the infusion speed of the infusion pump in real time, determine whether there is any abnormality in the infusion speed of the infusion pump through monitoring, and send an early warning notification to the monitoring end in case of abnormality;

[0073] Monitor the known feedback operation market of medical staff to early warning notifications, determine whether medical staff respond to early warning notifications in a timely manner based on the monitoring time, and issue warning notifications to medical staff who do not respond in time.

[0074] A sleep depth adjustment device based on sleep stages, comprising:

[0075] Polysomnography, which is used to:

[0076] Perform polysomnography on the patient, use the polysomnography monitor to collect various parameters of the patient's sleep, and finally obtain sleep data;

[0077] Infusion pumps for:

[0078] Infuse sedative drugs into the patient's body;

[0079] Flow rate sensors for:

[0080] It is installed on the infusion pump and monitors the infusion speed of the infusion pump in real time through the flow rate sensor. When the infusion speed of the infusion pump exceeds or falls below the set range, an early warning notification is sent to the monitoring end.

[0081] Compared with the prior art, the present invention has the following beneficial effects:

[0082] 1. The present invention performs polysomnography on a patient through a polysomnography monitor to obtain sleep data of the patient, performs filtering processing, outlier processing and normalization processing on the obtained sleep data to ensure the accuracy and reliability of the sleep data, thereby facilitating the subsequent analysis of sleep data, preparing a sleep data training set in advance, training a sleep quality assessment model through a machine learning algorithm, inputting the processed sleep data into the trained sleep quality assessment model, performing real-time assessment of the user's sleep quality, determining the patient's current sleep stage, clarifying the infusion speed corresponding to different sleep stages through preset target control targets, comparing the current sleep stage with the preset target control targets, determining the sedative drug infusion speed corresponding to the current sleep stage, thereby automatically adjusting the sedative drug infusion speed of the infusion pump, and through the above process, the infusion speed of the patient's sedative drug can be adjusted according to the sleep stage, and this process does not require manual participation, and at the same time, effectively improves the infusion effect of the sedative drug.

[0083] 2. The present invention monitors the infusion speed of the infusion pump in real time through the sensing device to obtain the monitoring data of the infusion pump. Based on the target control target and the comparison result, the monitoring data can be analyzed to determine whether there is any abnormality in the infusion speed of the infusion pump. If there is any abnormality, the monitoring end immediately issues an early warning notification and monitors in real time the known feedback operation duration of the medical staff when receiving the early warning notification. Therefore, it can be determined whether the medical staff responds to the early warning notification in time according to the monitoring duration, and the medical staff who do not respond in time will be warned, so as to effectively urge the medical staff to investigate the abnormal situation and ensure the normal infusion. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a flow chart of the sleep depth adjustment method based on sleep staging of the present invention;

[0085] Figure 2 It is a schematic diagram of the process of sleep data collection and analysis of the present invention;

[0086] Figure 3 It is a schematic diagram of the process of adjusting the sedative drug infusion rate of the present invention;

[0087] Figure 4 It is a schematic diagram of the process of abnormal monitoring of sedative drug infusion rate of the present invention;

[0088] Figure 5 A schematic diagram of the process of monitoring the time it takes for medical staff to respond to early warning notifications according to the present invention;

[0089] Figure 6 It is a schematic diagram of the overall structure of the sleep depth regulating device based on sleep staging of the present invention. DETAILED DESCRIPTION

[0090] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0091] In order to solve the problem that the existing technology cannot automatically adjust the infusion speed of the infusion pump according to the sleep stage, please refer to Figure 1-Figure 6 , this embodiment provides the following technical solutions:

[0092] like Figure 1 As shown, the sleep depth adjustment method based on sleep staging includes the following steps:

[0093] S1: Perform polysomnography on the patient through a polysomnography monitor, collect various parameters of the patient during sleep, and finally obtain the patient's sleep data, process the obtained sleep data, and analyze the processed sleep data to determine the patient's current sleep stage through analysis;

[0094] Among them, sleep stages are divided into four cycles, namely: NREM stage 1, NREM stage 2, NREM stage 3 and REM sleep;

[0095] S2: preset target control target, which is the sedative drug infusion rate under different sleep stages, obtain the patient's current sleep stage, compare the current sleep stage with the preset target control target, determine the sedative drug infusion rate corresponding to the current sleep stage through comparison, and automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison result;

[0096] Among them, the target control goal is set according to the four cycles of sleep staging, and the infusion rate of sedative drugs corresponding to NREM stage 1, NREM stage 2, NREM stage 3 and REM sleep is set respectively;

[0097] S3: Based on the target control objectives and comparison results, the infusion speed of the infusion pump is monitored in real time using sensing equipment. The infusion speed is judged to be abnormal through monitoring, and an early warning notification is issued in abnormal situations.

[0098] like Figure 2 As shown, the specific process of S1 is as follows:

[0099] S1.1: The polysomnography monitor contains multiple sensors, which are placed on the corresponding parts of the patient to ensure that the multiple sensors fit the patient's skin and remain stable;

[0100] S1.2: After the polysomnography is set up, set the polysomnography parameters, including recording time and sampling frequency;

[0101] S1.3: After the polysomnography parameters are set, the polysomnography is started on the patient. The polysomnography collects various parameters of the patient during sleep in real time, and finally obtains the patient's sleep data and performs data processing;

[0102] Among them, data processing includes:

[0103] Filtering: The sleep data is filtered through filtering technology to remove high-frequency and low-frequency noise in the sleep data;

[0104] Outlier processing: detect outliers in sleep data and process them using outlier processing methods;

[0105] Normalization: Normalize the sleep data to eliminate the dimensional differences in the sleep data;

[0106] S1.4: During the monitoring period, the polysomnography monitor is regularly tested to determine whether there is any abnormality in the data collection of the polysomnography monitor;

[0107] S1.5: Prepare a sleep data training set in advance and train a sleep quality assessment model through a machine learning algorithm;

[0108] S1.6: Input the processed sleep data into the trained sleep quality assessment model to conduct real-time assessment of the user's sleep quality and determine the patient's current sleep stage.

[0109] Technical effect of the above content: polysomnography can be used to perform polysomnography on patients, and the polysomnography includes multiple sensors, including electrocardiogram sensors, respiratory sensors, electromyogram sensors, and eye movement sensors, etc. The electrocardiogram sensor is placed on the patient's chest, the respiratory sensor is placed on the patient's chest or near the nose, the electromyogram sensor is placed near the patient's jaw, and the eye movement sensor is placed above the patient's eyelids. After the installation is completed, the polysomnography parameters are set, and the polysomnography parameters perform data collection according to the set parameters. Multiple sensors are installed on the corresponding parts of the patient, and various parameters of the patient's sleep can be collected in real time, thereby obtaining the patient's sleep data. It should be noted that during the monitoring period, the polysomnography will be tested. , ensure that the connection of multiple sensors is normal and the data collection is correct. If multiple sensors are found to be loose or the data collection is abnormal, adjust and repair the polysomnography monitor in time. The obtained sleep data needs to be processed. By filtering, outlier processing and normalization of the sleep data, the accuracy and reliability of the sleep data can be guaranteed, and the quality of the sleep data can be improved, which is conducive to the subsequent analysis of the sleep data. Before analyzing the sleep data, use the pre-prepared sleep data training set and train the sleep quality assessment model through the machine learning algorithm. Then, input the processed sleep data into the trained sleep quality assessment model to conduct real-time assessment of the user's sleep quality, so as to determine the patient's current sleep stage and provide data support for the subsequent infusion of sedative drugs.

[0110] like Figure 3 As shown, the specific process of S2 is as follows:

[0111] S2.1: Based on the four cycles of sleep staging, preset target control targets are the infusion rates of sedative drugs under different sleep stages;

[0112] S2.2: Obtain the patient's current sleep stage, compare the current sleep stage with the preset target control target, and determine the sedative drug infusion rate corresponding to the current sleep stage based on the comparison;

[0113] S2.3: Automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison results;

[0114] When the patient's current sleep stage is in NREM stage 1, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage 1;

[0115] When the patient's current sleep stage is in NREM stage II, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage II;

[0116] When the patient's current sleep stage is in NREM stage III, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage III;

[0117] When the patient's current sleep stage is REM sleep, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to REM sleep.

[0118] The technical effects of the above content are as follows: the target control target is set in advance according to the four cycles of sleep staging, that is, the four cycles of sleep staging correspond to different infusion speeds, the current sleep stage of the patient determined by analysis is obtained, and the current sleep stage is compared with the preset target control target. The sedative drug infusion speed corresponding to the current sleep stage can be determined by comparison. If the patient's current sleep stage is in NREM stage I, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage I; if the patient's current sleep stage is in NREM stage II, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage II; if the patient's current sleep stage is in NREM stage III, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage III; if the patient's current sleep stage is in REM sleep, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to REM sleep, thereby realizing automatic adjustment of the sedative drug infusion speed of the infusion pump according to the sleep stage, effectively improving the infusion effect of sedative drugs, and no manual intervention is required.

[0119] like Figure 4 and Figure 5 As shown, the specific process of S3 is as follows:

[0120] S3.1: A sensing device is set at the infusion pump. The sensing device adopts a flow rate sensor, and the infusion speed of the infusion pump is monitored in real time through the set sensing device;

[0121] S3.2: Obtain monitoring data of the infusion pump through real-time monitoring, and analyze the monitoring data based on the target control objectives and comparison results;

[0122] S3.3: Analyze and determine whether there is any abnormality in the infusion speed of the infusion pump, and determine whether the current infusion speed of the infusion pump conforms to the infusion speed adjusted after the comparison result;

[0123] If there is no abnormality in the infusion speed of the infusion pump, it is determined that the current infusion speed of the infusion pump is consistent with the infusion speed adjusted by the comparison result;

[0124] If the infusion speed of the infusion pump is abnormal, it is determined that the current infusion speed of the infusion pump does not conform to the infusion speed adjusted after the comparison result;

[0125] S3.4: When the judgment result shows that an abnormal situation exists, an early warning notification is sent to the monitoring end, and the medical staff checks the abnormal infusion pump according to the early warning notification.

[0126] Specifically, real-time monitoring of the ratio between the input change and the output change of the flow velocity sensor and adjusting the sensitivity of the flow velocity sensor include:

[0127] Arrange a second flow velocity sensor with the same model and specification as the flow velocity sensor at the same monitoring position as the flow velocity sensor as a reference flow velocity sensor;

[0128] The infusion rate of the infusion pump is monitored by a reference flow rate sensor;

[0129] Obtaining a flow rate change rate of the measured fluid according to the infusion speed of the infusion pump;

[0130] Real-time monitoring of the sensor output signal of the flow velocity sensor;

[0131] Acquire the sensor signal change rate of flow rate monitoring according to the sensor output signal of the flow rate sensor;

[0132] The sensitivity evaluation coefficient of the flow velocity sensor is obtained according to the flow velocity change rate of the measured fluid and the change rate of the sensor signal of the flow velocity monitoring; wherein the sensitivity evaluation coefficient of the flow velocity sensor is obtained by the following formula:

[0133]

[0134] Where Q represents the sensitivity evaluation coefficient of the flow velocity sensor; n represents the number of data collection times of the flow velocity sensor; P ci P represents the rate of change of the sensor signal of the flow sensor during the i-th data collection relative to the previous data collection; riP represents the rate of change of the flow rate of the measured fluid in the ith data collection of the reference flow rate sensor corresponding to the flow rate sensor relative to the previous data collection; rmax It indicates the maximum value of the rate of change of the flow velocity of the measured fluid when the data of the reference flow velocity sensor corresponding to the flow velocity sensor is collected relative to the last data collection; P cmax Indicates the flow rate change rate of the flow sensor corresponding to the maximum value of the flow rate change rate of the measured fluid; P rmin Indicates the minimum value of the flow rate change rate of the measured fluid of the reference flow rate sensor corresponding to the flow rate sensor relative to the last data collection; P cmin Indicates the flow rate change rate of the flow rate sensor corresponding to the minimum value of the flow rate change rate of the measured fluid;

[0135] Whether the sensitivity of the flow velocity sensor needs to be adjusted is determined according to the sensitivity evaluation coefficient.

[0136] The technical effect of the above technical solution is: by deploying a reference flow velocity sensor of the same model and specification as the flow velocity sensor to be measured at the same location, the measurement data of the two can be compared in real time. This "dual sensor" setting can effectively reduce the measurement inaccuracy caused by a single sensor due to its own error or environmental interference, thereby improving the accuracy and reliability of the overall flow velocity measurement.

[0137] The calculation method of the sensitivity evaluation coefficient (Q) proposed in the technical solution comprehensively considers the ratio of the change rate of the flow sensor's sensor signal to the change rate of the actual flow rate of the measured fluid, and introduces correction factors for the maximum and minimum change rates. This method can dynamically and accurately evaluate the sensitivity state of the flow sensor. When the sensitivity deviates from the ideal range, the system can decide whether to make adjustments based on the value of the sensitivity evaluation coefficient (Q) to ensure that the sensor always maintains a high-precision working state.

[0138] By real-time monitoring and adjusting the sensitivity of the flow sensor, the system can automatically adapt to different working environments and fluid conditions to maintain measurement stability and consistency. This is especially important for application scenarios that require long-term and continuous monitoring of flow rate changes, such as medical infusion pumps and industrial production processes.

[0139] When a flow rate sensor fails or its performance deteriorates, the abnormal change in the sensitivity evaluation coefficient can serve as an important basis for fault diagnosis. This helps to discover and solve problems in a timely manner and avoid measurement errors or production accidents caused by sensor failure.

[0140] The technical proposal describes in detail the entire process from data collection, processing to sensitivity evaluation, providing clear and actionable guidance for the data processing flow of the flow measurement system. This helps improve data processing efficiency and ensure the accuracy and timeliness of measurement results.

[0141] In summary, this technical solution significantly improves the accuracy, stability and reliability of flow rate measurement by introducing a reference flow rate sensor, dynamically evaluating and adjusting the sensor sensitivity, and provides strong support for applications in related fields.

[0142] Specifically, determining whether the sensitivity of the flow velocity sensor needs to be adjusted according to the sensitivity evaluation coefficient includes:

[0143] Comparing the sensitivity evaluation coefficient with a preset evaluation coefficient threshold;

[0144] When the sensitivity evaluation coefficient is lower than a preset evaluation coefficient threshold, it is determined that the sensitivity of the flow velocity sensor needs to be adjusted;

[0145] The sensitivity compensation amount is obtained according to the flow velocity change rate of the measured fluid and the change rate of the sensor signal of the flow velocity monitoring; wherein the sensitivity compensation amount is obtained by the following formula:

[0146]

[0147] Where, L represents the sensitivity compensation amount; L min Indicates the minimum flow rate that the flow sensor can collect; L p It indicates the value of zero drift corresponding to the flow sensor; Q indicates the sensitivity evaluation coefficient of the flow sensor; Q y represents a preset evaluation coefficient threshold; λ represents an adjustment coefficient, and the adjustment coefficient is obtained by the following formula:

[0148]

[0149] Where λ represents the adjustment coefficient; n represents the number of data collection times of the flow velocity sensor; P ci P represents the rate of change of the sensor signal of the flow sensor during the i-th data collection relative to the previous data collection; ri Indicates the rate of change of the flow velocity of the measured fluid of the i-th data collection of the reference flow velocity sensor corresponding to the flow velocity sensor relative to the previous data collection;

[0150] The adjusted sensitivity corresponding to the flow rate sensor is obtained according to the sensitivity compensation amount; wherein the adjusted sensitivity is obtained by the following formula:

[0151] L t =(1+L)·L x

[0152] Among them, L t Indicates the sensitivity after adjustment; L indicates the sensitivity compensation amount; L x Indicates the sensitivity before adjustment.

[0153] The technical effect of the above technical solution is that by comparing the sensitivity evaluation coefficient (Q) with the preset evaluation coefficient threshold (Qy), the system can accurately determine whether the flow rate sensor needs sensitivity adjustment. This method is based on data analysis and comparison, avoids the uncertainty caused by subjective judgment, and improves the accuracy and reliability of adjustment.

[0154] The calculation of sensitivity compensation (L) comprehensively considers the minimum flow rate acquisition capability (Lmin), zero drift (Lp), sensitivity evaluation coefficient (Q), preset evaluation coefficient threshold (Qy) and adjustment coefficient (λ) of the flow sensor. This calculation method not only considers the inherent characteristics of the sensor, but also considers the dynamic changes in the actual measurement process, so it can determine the required compensation more scientifically.

[0155] The calculation of the adjustment coefficient (λ) depends on the data acquisition times (n) of the flow sensor, the rate of change of the sensor signal (Pci) and the rate of change of the flow rate of the measured fluid (Pr i). This dynamic calculation method allows the adjustment coefficient to be adjusted as the measurement environment changes, thereby more accurately reflecting the actual performance status of the sensor and providing a more accurate reference for sensitivity compensation.

[0156] Based on the sensitivity compensation (L) and the sensitivity before adjustment (Lx), the adjusted sensitivity (Lt) can be calculated. This adjustment strategy not only takes into account the current performance status of the sensor, but also allows flexible adjustments as needed to adapt to different measurement requirements and application scenarios.

[0157] By real-time monitoring, evaluation and adjustment of the flow sensor sensitivity, the system can maintain high measurement stability and reliability. Even when the measurement environment changes or sensor performance fluctuates, the system can respond quickly and adjust to the optimal state, thus ensuring the accuracy and consistency of the measurement results.

[0158] The flow rate sensor after sensitivity adjustment can more accurately reflect the actual flow rate changes of the measured fluid, thereby improving the measurement performance. This is especially important for application scenarios that require high-precision flow rate measurement, such as medical infusion pumps, industrial production processes, etc.

[0159] In summary, this technical solution significantly improves the stability and reliability of the flow rate measurement system and optimizes the measurement performance through precise sensitivity evaluation, scientific sensitivity compensation calculation and flexible sensitivity adjustment strategy.

[0160] Among them, S3.4 includes the following sub-steps:

[0161] S3.4.1: Immediately send an early warning notification to the monitoring end when there is an abnormality in the infusion speed of the infusion pump;

[0162] S3.4.2: After receiving the warning notification, the medical staff performs a known feedback operation on the warning notification through the monitoring terminal, and stops the warning notification after completing the known feedback operation;

[0163] S3.4.3: Monitor the duration of known feedback operations by medical staff, determine whether medical staff respond to warning notifications in a timely manner based on the monitoring duration, and issue warning notifications to medical staff who do not respond in a timely manner;

[0164] Among them, the monitoring duration is divided into 0s-60s, 60s-180s and more than 180s;

[0165] If the monitoring duration is 0s-60s, it is judged that the medical staff responds to the warning notification in time;

[0166] If the monitoring duration is 60s-180s, it is judged that the medical staff did not respond in time and a warning notice is issued to the medical staff;

[0167] If the monitoring time is longer than 180 seconds, it is judged that the medical staff has not responded in a timely manner, and a warning notice is issued to the medical staff, and the warning notice is also sent to the medical staff's superior.

[0168] The technical effect of the above content: after automatically adjusting the sedative drug infusion speed of the infusion pump according to the sleep staging, the flow rate sensor can be used to monitor the infusion speed of the infusion pump in real time. The monitoring data of the infusion pump can be obtained through real-time monitoring by the flow rate sensor, and the monitoring data is analyzed based on the target control target and the comparison result. Through the analysis, it is determined whether there is any abnormality in the infusion speed of the infusion pump, that is, whether the current infusion speed of the infusion pump conforms to the infusion speed adjusted by the comparison result. If there is no abnormality in the infusion speed of the infusion pump, the flow rate sensor can continue to be used to monitor the infusion speed of the infusion pump in real time. If the infusion speed of the infusion pump is abnormal, If there is an abnormality in the injection speed, an early warning notification will be immediately sent to the monitoring end for the attention of medical staff. After receiving the early warning notification, the medical staff will perform a known feedback operation on the early warning notification through the monitoring end. Once the medical staff remembers the known feedback operation, the early warning notification will stop being sent, because the abnormal situation of the infusion pump has been known to the medical staff. The duration of monitoring the medical staff's known feedback operation can supervise the medical staff's memory, and determine whether the medical staff responds to the early warning notification in time based on the monitoring time, and warn the medical staff who do not respond in time, which helps to ensure that the medical staff responds to important early warning notifications in time.

[0169] Specifically, this embodiment further proposes a sleep depth adjustment system based on sleep staging, including:

[0170] Sleep monitoring and analysis system for:

[0171] Perform polysomnography on the patient, set the parameters of the polysomnography in advance, and the polysomnography collects various parameters of the patient's sleep in real time;

[0172] During the monitoring period, the polysomnography monitor is regularly tested for abnormal data collection, and the patient's sleep data is finally obtained and processed;

[0173] The processed sleep data is input into the trained sleep quality assessment model to conduct real-time assessment of the user's sleep quality and determine the patient's current sleep stage;

[0174] Target-controlled infusion systems for:

[0175] Based on the preset target control targets of the four cycles of sleep staging, the patient's current sleep staging is obtained, and the current sleep staging is compared with the preset target control targets;

[0176] Determine the sedative drug infusion rate corresponding to the current sleep stage by comparison, and automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison result;

[0177] Use sensor equipment to monitor the infusion speed of the infusion pump in real time, determine whether there is any abnormality in the infusion speed of the infusion pump through monitoring, and send an early warning notification to the monitoring end in case of abnormality;

[0178] Monitor the known feedback operation market of medical staff to early warning notifications, determine whether medical staff respond to early warning notifications in a timely manner based on the monitoring time, and issue warning notifications to medical staff who do not respond in time.

[0179] Specifically, this embodiment further proposes a sleep depth adjustment device based on sleep staging, comprising:

[0180] Polysomnography, which is used to:

[0181] Perform polysomnography on the patient, use the polysomnography monitor to collect various parameters of the patient's sleep, and finally obtain sleep data;

[0182] Infusion pumps for:

[0183] Infuse sedative drugs into the patient's body;

[0184] Flow rate sensors for:

[0185] It is installed on the infusion pump and monitors the infusion speed of the infusion pump in real time through the flow rate sensor. When the infusion speed of the infusion pump exceeds or falls below the set range, an early warning notification is sent to the monitoring end.

[0186] The technical effects of the above contents are as follows: the sleep monitoring and analysis system includes a polysomnogram, which performs polysomnography on the patient through the polysomnogram to obtain the patient's sleep data, and processes and analyzes the acquired sleep data to determine the patient's current sleep stage. The target-controlled infusion system includes an infusion pump and a flow rate sensor, which infuses sedatives into the patient's body through the infusion pump, and monitors the infusion speed of the infusion pump in real time through the flow rate sensor. When the infusion speed of the infusion pump exceeds or falls below a set range, an early warning notification can be sent to the monitoring end to ensure the normal operation of the infusion pump.

[0187] Working principle: Perform polysomnography on patients through polysomnography to obtain the patients' sleep data, filter the obtained sleep data, process outliers and normalize them to ensure the accuracy and reliability of the sleep data, use the sleep data training set prepared in advance, and train the sleep quality assessment model through machine learning algorithm, input the processed sleep data into the trained sleep quality assessment model, conduct real-time assessment of the user's sleep quality, determine the patient's current sleep stage, and clarify the infusion speed corresponding to different sleep stages by pre-setting target control targets. Compare the current sleep stage with the preset target control targets to determine the sedative drug infusion speed corresponding to the current sleep stage. degree, thereby automatically adjusting the infusion speed of the sedative drug of the infusion pump, effectively improving the infusion effect of the sedative drug. During the infusion process, the infusion speed of the infusion pump is monitored in real time through the sensor equipment to obtain the monitoring data of the infusion pump. Based on the target control target and the comparison result, the monitoring data can be analyzed to determine whether there is any abnormality in the infusion speed of the infusion pump. If there is any abnormality, the monitoring end will immediately issue an early warning notification and monitor the known feedback operation time of the medical staff when receiving the early warning notification in real time, so as to determine whether the medical staff responds to the early warning notification in time according to the monitoring time, and warn the medical staff who do not respond in time to ensure the normal infusion.

[0188] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0189] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A sleep depth adjustment method based on sleep staging, characterized in that: The following steps are involved: S1: Perform polysomnography on the patient through a polysomnography monitor, collect various parameters of the patient during sleep, and finally obtain the patient's sleep data, process the obtained sleep data, and analyze the processed sleep data to determine the patient's current sleep stage through analysis; Among them, sleep stages are divided into four cycles, namely: NREM stage 1, NREM stage 2, NREM stage 3 and REM sleep; S2: preset target control target, which is the sedative drug infusion rate under different sleep stages, obtain the patient's current sleep stage, compare the current sleep stage with the preset target control target, determine the sedative drug infusion rate corresponding to the current sleep stage through comparison, and automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison result; S3: Based on the target control objectives and comparison results, the infusion speed of the infusion pump is monitored in real time using sensing equipment. The infusion speed is judged to be abnormal through monitoring, and an early warning notification is issued in abnormal situations.

2. The sleep depth adjustment method based on sleep staging according to claim 1, characterized in that: The specific process of S1 is as follows: S1.1: The polysomnography monitor contains multiple sensors, which are placed on the corresponding parts of the patient to ensure that the multiple sensors fit the patient's skin and remain stable; S1.2: After the polysomnography is set up, set the polysomnography parameters, including recording time and sampling frequency; S1.3: After the polysomnography parameters are set, the polysomnography is started on the patient. The polysomnography collects various parameters of the patient during sleep in real time, and finally obtains the patient's sleep data and performs data processing; S1.4: During the monitoring period, the polysomnography monitor is regularly tested to determine whether there is any abnormality in the data collection of the polysomnography monitor; S1.5: Prepare a sleep data training set in advance and train a sleep quality assessment model through a machine learning algorithm; S1.6: Input the processed sleep data into the trained sleep quality assessment model to conduct real-time assessment of the user's sleep quality and determine the patient's current sleep stage.

3. The sleep depth adjustment method based on sleep staging according to claim 2, characterized in that: The data processing includes: Filtering: The sleep data is filtered through filtering technology to remove high-frequency and low-frequency noise in the sleep data; Outlier processing: detect outliers in sleep data and process them using outlier processing methods; Normalization: The sleep data is normalized to eliminate the dimensional differences in the sleep data.

4. The sleep depth adjustment method based on sleep staging according to claim 1, characterized in that: The specific process of S2 is as follows: S2.1: Based on the four cycles of sleep staging, preset target control targets are the infusion rates of sedative drugs under different sleep stages; S2.2: Obtain the patient's current sleep stage, compare the current sleep stage with the preset target control target, and determine the sedative drug infusion rate corresponding to the current sleep stage based on the comparison; S2.3: Automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison results; When the patient's current sleep stage is in NREM stage 1, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage 1; When the patient's current sleep stage is in NREM stage II, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage II; When the patient's current sleep stage is in NREM stage III, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to NREM stage III; When the patient's current sleep stage is REM sleep, the infusion pump is automatically adjusted to the sedative drug infusion speed corresponding to REM sleep.

5. The sleep depth adjustment method based on sleep staging according to claim 1, characterized in that: The specific process of S3 is as follows: S3.1: A sensing device is set at the infusion pump. The sensing device adopts a flow rate sensor, and the infusion speed of the infusion pump is monitored in real time through the set sensing device; S3.2: Obtain monitoring data of the infusion pump through real-time monitoring, and analyze the monitoring data based on the target control objectives and comparison results; S3.3: Analyze and determine whether there is any abnormality in the infusion speed of the infusion pump, and determine whether the current infusion speed of the infusion pump conforms to the infusion speed adjusted after the comparison result; If there is no abnormality in the infusion speed of the infusion pump, it is determined that the current infusion speed of the infusion pump is consistent with the infusion speed adjusted by the comparison result; If the infusion speed of the infusion pump is abnormal, it is determined that the current infusion speed of the infusion pump does not conform to the infusion speed adjusted after the comparison result; S3.4: When the judgment result shows that an abnormal situation exists, an early warning notification is sent to the monitoring end, and the medical staff checks the abnormal infusion pump according to the early warning notification.

6. The method for adjusting sleep depth based on sleep staging according to claim 5, characterized in that: Real-time monitoring of the ratio between the input change and the output change of the flow velocity sensor, and adjusting the sensitivity of the flow velocity sensor, including: Arrange a second flow velocity sensor with the same model and specification as the flow velocity sensor at the same monitoring position as the flow velocity sensor as a reference flow velocity sensor; Monitor the infusion rate of the infusion pump via a reference flow rate sensor; Obtaining a flow rate change rate of the measured fluid according to the infusion speed of the infusion pump; Real-time monitoring of the sensor output signal of the flow velocity sensor; Acquire the sensor signal change rate of flow rate monitoring according to the sensor output signal of the flow rate sensor; The sensitivity evaluation coefficient of the flow velocity sensor is obtained according to the flow velocity change rate of the measured fluid and the change rate of the sensor signal of the flow velocity monitoring; wherein the sensitivity evaluation coefficient of the flow velocity sensor is obtained by the following formula: Where Q represents the sensitivity evaluation coefficient of the flow velocity sensor; n represents the number of data collection times of the flow velocity sensor; P ci P represents the rate of change of the sensor signal of the flow sensor during the i-th data collection relative to the previous data collection; ri P represents the rate of change of the flow rate of the measured fluid in the ith data collection of the reference flow rate sensor corresponding to the flow rate sensor relative to the previous data collection; rmax It indicates the maximum value of the rate of change of the flow velocity of the measured fluid when the data of the reference flow velocity sensor corresponding to the flow velocity sensor is collected relative to the last data collection; P cmax Indicates the flow rate change rate of the flow sensor corresponding to the maximum value of the flow rate change rate of the measured fluid; P rmin Indicates the minimum value of the flow rate change rate of the measured fluid of the reference flow rate sensor corresponding to the flow rate sensor relative to the last data collection; P cmin Indicates the flow rate change rate of the flow rate sensor corresponding to the minimum value of the flow rate change rate of the measured fluid; Whether the sensitivity of the flow velocity sensor needs to be adjusted is determined according to the sensitivity evaluation coefficient.

7. The method for adjusting sleep depth based on sleep staging according to claim 6, characterized in that: Determining whether the sensitivity of the flow velocity sensor needs to be adjusted according to the sensitivity evaluation coefficient includes: Comparing the sensitivity evaluation coefficient with a preset evaluation coefficient threshold; When the sensitivity evaluation coefficient is lower than a preset evaluation coefficient threshold, it is determined that the sensitivity of the flow velocity sensor needs to be adjusted; The sensitivity compensation amount is obtained according to the flow velocity change rate of the measured fluid and the change rate of the sensor signal of the flow velocity monitoring; wherein the sensitivity compensation amount is obtained by the following formula: Where, L represents the sensitivity compensation amount; L min Indicates the minimum flow rate that the flow sensor can collect; L p It indicates the value of zero drift corresponding to the flow sensor; Q indicates the sensitivity evaluation coefficient of the flow sensor; Q y represents a preset evaluation coefficient threshold; λ represents an adjustment coefficient, and the adjustment coefficient is obtained by the following formula: Where λ represents the adjustment coefficient; n represents the number of data collection times of the flow velocity sensor; P ci P represents the rate of change of the sensor signal of the flow sensor during the i-th data collection relative to the previous data collection; ri Indicates the rate of change of the flow velocity of the measured fluid of the i-th data collection of the reference flow velocity sensor corresponding to the flow velocity sensor relative to the previous data collection; The adjusted sensitivity corresponding to the flow rate sensor is obtained according to the sensitivity compensation amount; wherein the adjusted sensitivity is obtained by the following formula: L t =(1+L)·L x Among them, L t Indicates the sensitivity after adjustment; L indicates the sensitivity compensation amount; L x Indicates the sensitivity before adjustment.

8. The method for adjusting sleep depth based on sleep staging according to claim 5, characterized in that: The S3.4 includes the following process: S3.4.1: Immediately send an early warning notification to the monitoring end when there is an abnormality in the infusion speed of the infusion pump; S3.4.2: After receiving the warning notification, the medical staff performs a known feedback operation on the warning notification through the monitoring terminal, and stops the warning notification after completing the known feedback operation; S3.4.3: Monitor the duration of known feedback operations by medical staff, determine whether medical staff respond to warning notifications in a timely manner based on the monitoring duration, and issue warning notifications to medical staff who do not respond in a timely manner; Among them, the monitoring duration is divided into 0s-60s, 60s-180s and more than 180s; If the monitoring duration is 0s-60s, it is judged that the medical staff responds to the warning notification in time; If the monitoring duration is 60s-180s, it is judged that the medical staff did not respond in time and a warning notice is issued to the medical staff; If the monitoring time is longer than 180 seconds, it is judged that the medical staff has not responded in a timely manner, and a warning notice is issued to the medical staff, and the warning notice is also sent to the medical staff's superior.

9. A sleep depth adjustment system based on sleep staging, used to implement the sleep depth adjustment method based on sleep staging according to claim 8, characterized in that: include: Sleep monitoring and analysis system for: Perform polysomnography on the patient, set the parameters of the polysomnography in advance, and the polysomnography collects various parameters of the patient's sleep in real time; During the monitoring period, the polysomnography monitor is regularly tested for abnormal data collection, and the patient's sleep data is finally obtained and processed; The processed sleep data is input into the trained sleep quality assessment model to conduct real-time assessment of the user's sleep quality and determine the patient's current sleep stage; Target-controlled infusion systems for: Based on the preset target control targets of the four cycles of sleep staging, the patient's current sleep staging is obtained, and the current sleep staging is compared with the preset target control targets; Determine the sedative drug infusion rate corresponding to the current sleep stage by comparison, and automatically adjust the sedative drug infusion rate of the infusion pump according to the comparison result; Use sensor equipment to monitor the infusion speed of the infusion pump in real time, determine whether there is any abnormality in the infusion speed of the infusion pump through monitoring, and send an early warning notification to the monitoring end in case of abnormality; Monitor the known feedback operation market of medical staff to early warning notifications, determine whether medical staff respond to early warning notifications in a timely manner based on the monitoring time, and issue warning notifications to medical staff who do not respond in time.

10. A sleep depth adjustment device based on sleep staging, controlled by the sleep depth adjustment system based on sleep staging according to claim 9, characterized in that: include: Polysomnography, which is used to: Perform polysomnography on the patient, use the polysomnography monitor to collect various parameters of the patient's sleep, and finally obtain sleep data; Infusion pumps for: Infuse sedative drugs into the patient's body; Flow rate sensors for: It is installed on the infusion pump and monitors the infusion speed of the infusion pump in real time through the flow rate sensor. When the infusion speed of the infusion pump exceeds or falls below the set range, an early warning notification is sent to the monitoring end.

Images