Intelligent oxygen cabin nursing system for promoting nerve injury recovery

Abstract

The invention discloses an intelligent oxygen cabin nursing system for promoting nerve injury recovery, and belongs to the technical field of intelligent nursing. Comprising a monitoring module, a central processing module and an intelligent oxygen cabin, wherein the monitoring module is connected to the central processing module in a wireless or wired manner; the central processing module is connected with the intelligent oxygen cabin and used for adjusting the intelligent oxygen cabin. By integrating the multi-source physiological information and applying the analytic hierarchy process to quantify the effect of the multi-source physiological information in evaluating the nerve injury recovery state, not only are the scientificity and accuracy of judgment improved, but also powerful support can be provided for personalized treatment. Compared with an original method, the method pays more attention to the mutual relation between individual differences and physiological parameters, and is suitable for precise medical practice in the medical field.

Description

Technical Field

[0001] The present invention relates to the field of intelligent nursing technology, and more specifically to an intelligent oxygen chamber nursing system for promoting recovery of nerve damage. Background Art

[0002] The recovery of nerve injury (such as spinal cord injury, peripheral nerve injury, etc.) is a complex physiological process involving nerve regeneration, microenvironment regulation and metabolic support.

[0003] Traditional rehabilitation methods (such as hyperbaric oxygen chambers) mainly promote tissue repair by increasing blood oxygen concentration, but they have a single environmental parameter and rely only on oxygen concentration regulation, ignoring the impact of temperature, humidity, etc. on the microenvironment of neural repair; they lack dynamic adaptation and cannot dynamically adjust treatment parameters according to the patient's real-time physiological state (such as heart rate, blood oxygen, and electromyographic signals); data fusion is insufficient, and multimodal physiological data (such as venous pressure and skin galvanic response) have not been effectively integrated for recovery stage judgment, resulting in delayed treatment plans. At the same time, in the existing technology, although there are attempts to integrate sensors in smart oxygen chambers, most of them use simple threshold control or linear adjustment, and are not combined with clinical data models for neural injury recovery, making it difficult to achieve accurate stage adaptation and parameter optimization.

[0004] Therefore, how to provide an intelligent oxygen chamber care system for promoting recovery from nerve injury is a problem that technical personnel in this field urgently need to solve. Summary of the invention

[0005] In view of this, the present invention provides an intelligent oxygen chamber care system for promoting recovery of nerve damage, thereby achieving precise, personalized and intelligent care.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent oxygen chamber care system for promoting nerve injury recovery, comprising:

[0008] Monitoring module, central processing module, intelligent oxygen chamber;

[0009] Wherein, the monitoring module is connected to the central processing module wirelessly or by wire;

[0010] The central processing module is connected to the smart oxygen chamber and is used to adjust the smart oxygen chamber.

[0011] Furthermore, the monitoring module includes:

[0012] Physiological information detection unit, including: heart rate sensor, blood oxygen saturation sensor, respiratory rate sensor, venous pressure sensor, arterial pressure sensor, skin galvanic response sensor and electromyography sensor;

[0013] The environmental information detection unit includes: an oxygen concentration sensor, a temperature sensor and a humidity sensor.

[0014] Furthermore, the intelligent oxygen chamber comprises:

[0015] Oxygen concentration drive unit, temperature drive unit and humidity drive unit.

[0016] Furthermore, the central processing module includes:

[0017] A data processing unit, which pre-processes the information obtained by the monitoring module;

[0018] The feedback unit, combined with the clinical data of nerve injury recovery, determines the current recovery period through the pre-processed data of the physiological information detection unit;

[0019] The regulating unit executes corresponding instructions to regulate the intelligent oxygen chamber based on the fusion result and the recovery period.

[0020] Furthermore, the data processing unit integrates the physiological information obtained by the monitoring module, including:

[0021] Establish the local state equation and observation equation for each sensor;

[0022] Perform Kalman filtering on each sensor;

[0023] By fusing each sensor by weighted average, local estimation and global estimation are performed to achieve data fusion.

[0024] Furthermore, the feedback and adjustment unit executes corresponding instructions to adjust the smart oxygen chamber based on the fusion result, including:

[0025] Generate environmental parameter adjustment values ​​based on the fusion results, and use PID controller and Sigmoid function to smooth the environmental parameter adjustment values;

[0026] A PWM pulse signal is generated according to the processed control quantity to control the oxygen concentration driving unit, the temperature driving unit and the humidity driving unit.

[0027] Furthermore, the expression of the Sigmoid function is:

[0028]

[0029] Where f(x) is the Sigmoid function about x, a is the offset, b is the slope factor, and c is the offset correction coefficient.

[0030] Furthermore, the feedback unit, in combination with clinical data of nerve injury recovery, determines the current recovery period through pre-processed data of the physiological information detection unit, including:

[0031] Combined with clinical data on nerve injury recovery, a comparison matrix was established:

[0032]

[0033] In the formula, n represents the physiological index to be compared, which are m 1 ,m 2 ,...,m n , M is the comparison matrix, m ij m 11 ,...,m nn , represents the importance ratio of the i-th indicator to the j-th indicator. If m i Relative to m j More importantly, m ij >1; otherwise, m ij <1, when two indicators are equally important, m ij =1;

[0034] The relative importance of the neurological injury recovery status was obtained based on the comparison matrix;

[0035] Based on the relative importance results, thresholds of physiological indicators corresponding to different stages of nerve injury recovery are set;

[0036] The preprocessed data of the physiological information detection unit and the physiological index threshold are judged to obtain the current recovery period.

[0037] Furthermore, it also includes a user interface for displaying the data monitored by the monitoring module and the data fusion results of the central processing module, and for manually adjusting the intelligent oxygen chamber.

[0038] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses an intelligent oxygen chamber care system for promoting nerve injury recovery. By integrating multi-source physiological information and using the analytic hierarchy process to quantify its role in assessing the recovery status of nerve injury, it not only improves the scientificity and accuracy of the judgment, but also can provide strong support for personalized treatment. Compared with the original method, this method pays more attention to individual differences and the relationship between physiological parameters, and is suitable for precision medicine practice in the medical field. It has the following beneficial effects:

[0039] Through the physiological information detection unit, the system can monitor the patient's physiological status in real time and transmit the data to the central processing module for analysis;

[0040] Kalman filtering and weighted average fusion technology are used to pre-process multi-source sensor data to improve data accuracy and reliability;

[0041] Based on the fused data and clinical data of nerve injury recovery, the current recovery period can be determined, and the environmental parameters in the smart oxygen chamber can be adjusted accordingly to achieve personalized care.

[0042] Use PID controller and Sigmoid function to smooth the environmental parameter adjustment value to ensure a smooth adjustment process and avoid discomfort to patients;

[0043] It provides an intuitive user interface to facilitate medical staff to view monitoring data and fusion results, and supports manual adjustment functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0045] Figure 1 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0046] 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.

[0047] See also Figure 1 The embodiment of the present invention discloses an intelligent oxygen chamber nursing system for promoting nerve injury recovery, comprising:

[0048] Monitoring module, central processing module, intelligent oxygen chamber;

[0049] Wherein, the monitoring module is connected to the central processing module wirelessly or by wire;

[0050] The central processing module is connected to the smart oxygen chamber and is used to adjust the smart oxygen chamber.

[0051] In a specific embodiment, the whole process of using the intelligent oxygen chamber nursing system for promoting nerve injury recovery of the present invention for a patient who is receiving intelligent oxygen chamber nursing includes:

[0052] Initial setup: The patient enters the smart oxygen chamber, and all sensors start working to monitor physiological and environmental information in real time;

[0053] Data fusion: The data processing unit pre-processes and fuses the collected multi-source data to generate a comprehensive evaluation report;

[0054] Recovery period judgment: The feedback unit combines clinical data to determine that the patient is currently in the acute phase and sets the corresponding physiological indicator threshold accordingly;

[0055] Environmental regulation: The regulation unit generates control instructions through the PID controller and Sigmoid function according to the current recovery period and fusion results to adjust the oxygen concentration, temperature and humidity in the oxygen chamber;

[0056] Dynamic monitoring: The system continuously monitors the patient's physiological state and dynamically adjusts environmental parameters according to changes to ensure optimal recovery conditions;

[0057] User interaction: Medical staff can view various data through the user interface and make manual adjustments when necessary.

[0058] In a specific embodiment, the monitoring module includes:

[0059] Physiological information detection unit, including: heart rate sensor, blood oxygen saturation sensor, respiratory rate sensor, venous pressure sensor, arterial pressure sensor, skin galvanic response sensor and electromyography sensor;

[0060] The environmental information detection unit includes: an oxygen concentration sensor, a temperature sensor and a humidity sensor.

[0061] Specifically, the sensors of the physiological information detection unit collect heart rate (80 bpm), blood oxygen (98%), and electromyographic signals (μV-level noise);

[0062] The environmental information detection unit detects the oxygen concentration (25%), temperature (28°C), and humidity (60%) in the oxygen chamber;

[0063] In a specific embodiment, the smart oxygen chamber comprises:

[0064] Oxygen concentration drive unit, temperature drive unit and humidity drive unit.

[0065] In a specific embodiment, the central processing module includes:

[0066] A data processing unit, which pre-processes the information obtained by the monitoring module;

[0067] The feedback unit, combined with the clinical data of nerve injury recovery, determines the current recovery period through the pre-processed data of the physiological information detection unit;

[0068] The regulating unit executes corresponding instructions to regulate the intelligent oxygen chamber based on the fusion result and the recovery period.

[0069] Specifically, the data processing unit performs Kalman filtering to denoise the electromyographic signal, fuses the heart rate and blood oxygen data, with weighting coefficients of 0.3 for heart rate, 0.5 for blood oxygen, and 0.2 for electromyography, and outputs a comprehensive physiological index (resilience score 75).

[0070] In a specific embodiment, the data processing unit integrates the physiological information obtained by the monitoring module, including:

[0071] Establish the local state equation and observation equation for each sensor;

[0072] Perform Kalman filtering on each sensor;

[0073] By fusing each sensor by weighted average, local estimation and global estimation are performed to achieve data fusion.

[0074] Specifically, for N sensors, the local state equation of each sensor is:

[0075]

[0076] in, is the state vector of sensor i at time k; is the state transition matrix; is the control input matrix; is the control input vector; is the process noise.

[0077] The observation equation for each sensor is:

[0078]

[0079] in: is the observation vector of sensor i at time k; is the observation matrix; is the observation noise.

[0080] Each sensor performs Kalman filtering independently, which is divided into two steps: prediction and update:

[0081] predict:

[0082]

[0083]

[0084] renew:

[0085]

[0086]

[0087]

[0088] The local estimates of each sensor are fused by weighted averaging:

[0089]

[0090] Among them, the weight matrix According to the local estimated covariance calculate:

[0091]

[0092] The global estimated covariance is:

[0093]

[0094] In a specific embodiment, the feedback and adjustment unit executes corresponding instructions to adjust the smart oxygen chamber based on the fusion result, including:

[0095] Generate environmental parameter adjustment values ​​based on the fusion results, and use PID controller and Sigmoid function to smooth the environmental parameter adjustment values;

[0096] A PWM pulse signal is generated according to the processed control quantity to control the oxygen concentration driving unit, the temperature driving unit and the humidity driving unit.

[0097] In a specific embodiment, the expression of the Sigmoid function is:

[0098]

[0099] Where f(x) is the Sigmoid function of x, a is the offset, b is the slope factor, and c is the offset correction coefficient.

[0100] In a specific embodiment, the feedback unit, in combination with clinical data of nerve injury recovery, determines the current recovery period through pre-processed data of the physiological information detection unit, including:

[0101] Combined with clinical data on nerve injury recovery, a comparison matrix was established:

[0102]

[0103] In the formula, n represents the physiological index to be compared, which are m 1 ,m 2 ,...,m n , M is the comparison matrix, m ij m 11 ,...,m nn , represents the importance ratio of the i-th indicator to the j-th indicator. If mi Relative to m j More importantly, m ij >1; otherwise, m ij <1, when two indicators are equally important, m ij =1;

[0104] The relative importance of the neurological injury recovery status was obtained based on the comparison matrix;

[0105] Based on the relative importance results, thresholds of physiological indicators corresponding to different stages of nerve injury recovery are set;

[0106] The preprocessed data of the physiological information detection unit and the physiological index threshold are judged to obtain the current recovery period (acute period, recovery period, stable period).

[0107] Specific clinical data on nerve injury recovery include:

[0108] Review the latest medical research papers, systematic reviews, and clinical guidelines to understand the changing patterns of different physiological indicators during nerve injury recovery and their relative importance. Focus on studies that have been verified by large-scale clinical trials and form reports;

[0109] Discuss with neurologists, rehabilitation therapists and other experts in related fields to obtain their views and experiences on different physiological indicators in clinical practice and form a report.

[0110] Based on the reported results of the above literature review and expert consultation, a reasonable comparison matrix was constructed.

[0111] Specifically, this embodiment determines three main physiological indicators: heart rate (HR), blood oxygen saturation (SpO2) and electromyography (EMG), and the relative importance of them is obtained as follows based on literature and expert opinions:

[0112]

[0113] Specifically, HR is 3 times more important than SpO2; HR is 5 times more important than EMG; and SpO2 is 2 times more important than EMG.

[0114] In a specific embodiment, the weight of each physiological indicator is calculated using the geometric mean method or the eigenvector method. This embodiment uses the geometric mean method:

[0115] For HR:

[0116]

[0117] For SpO2:

[0118]

[0119] For EMG:

[0120]

[0121] These values ​​are then normalized so that their sum equals 1.

[0122] In a specific embodiment, the method further comprises: using a consistency ratio (CR) to check the consistency of the comparison matrix. If the CR is less than 0.1, the matrix is ​​considered to have acceptable consistency; otherwise, the comparison matrix needs to be re-evaluated and adjusted.

[0123] In a specific embodiment, the method further includes: verifying the effectiveness of the established model through small-scale experiments, and further adjusting the weights according to the experimental results.

[0124] Specifically, the regulating unit calculates the oxygen concentration deviation (+3%), smoothes it through a Sigmoid function (a=2, b=0.5, c=1), and outputs a PWM duty cycle to the oxygen driving unit;

[0125] Specifically, the temperature driving unit receives the PID control amount (proportional gain Kp=2.5), and reduces the temperature from 28° C. to 26° C. within 10 seconds, and the humidity is adjusted synchronously.

[0126] In a specific embodiment, it also includes a user interface for displaying the data monitored by the monitoring module and the data fusion results of the central processing module, and for manually adjusting the intelligent oxygen chamber.

[0127] Specifically, the doctor checked the EMG fusion results through the interface, found abnormal fluctuations, and manually set the upper limit of oxygen concentration to 30%;

[0128] Specifically, the system records manual operations and updates comparison matrix weights to optimize subsequent automatic adjustment logic.

[0129] Effect verification:

[0130] Through the coordinated regulation of oxygen concentration, temperature, and humidity, the microenvironment of nerve repair is optimized and the release of inflammatory factors is reduced (for example, IL-6 decreases by about 30%).

[0131] Based on the comparison matrix and clinical data model, the acute phase, recovery phase, and stable phase are divided to improve the matching degree between the treatment plan and the physiological state by 40%;

[0132] Kalman filtering eliminates sensor noise (increases signal-to-noise ratio by 15dB), and weighted averaging fuses multi-source data, reducing the error rate of electromyographic signals to less than 5%;

[0133] The Sigmoid function is combined with the PID controller to avoid sudden changes in parameters (overshoot is reduced by 60%), and the response time of the PWM pulse-driven oxygen concentration unit is shortened to 0.5 seconds;

[0134] The user interface displays fusion data and recovery stages in real time, and supports doctors to manually modify parameters (such as forced oxygen restriction in the acute phase) to improve safety.

[0135] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0136] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent oxygen chamber care system for promoting nerve injury recovery, characterized in that: include: Monitoring module, central processing module, intelligent oxygen chamber; Wherein, the monitoring module is connected to the central processing module wirelessly or by wire; The central processing module is connected to the smart oxygen chamber and is used to adjust the smart oxygen chamber.

2. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 1, characterized in that: The monitoring module comprises: Physiological information detection unit, including: heart rate sensor, blood oxygen saturation sensor, respiratory rate sensor, venous pressure sensor, arterial pressure sensor, skin galvanic response sensor and electromyography sensor; The environmental information detection unit includes: an oxygen concentration sensor, a temperature sensor and a humidity sensor.

3. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 1, characterized in that: The intelligent oxygen chamber comprises: Oxygen concentration drive unit, temperature drive unit and humidity drive unit.

4. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 3, characterized in that: The central processing module comprises: A data processing unit, which pre-processes the information obtained by the monitoring module; The feedback unit, combined with the clinical data of nerve injury recovery, determines the current recovery period through the pre-processed data of the physiological information detection unit; The regulating unit executes corresponding instructions to regulate the intelligent oxygen chamber based on the fusion result and the recovery period.

5. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 4, characterized in that: The data processing unit integrates the physiological information obtained by the monitoring module, including: Establish the local state equation and observation equation for each sensor; Perform Kalman filtering on each sensor; By fusing each sensor by weighted average, local estimation and global estimation are performed to achieve data fusion.

6. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 4, characterized in that: The feedback and adjustment unit executes corresponding instructions to adjust the smart oxygen chamber based on the fusion result, including: Generate environmental parameter adjustment values ​​based on the fusion results, and use PID controller and Sigmoid function to smooth the environmental parameter adjustment values; A PWM pulse signal is generated according to the processed control quantity to control the oxygen concentration driving unit, the temperature driving unit and the humidity driving unit.

7. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 6, characterized in that: The expression of the Sigmoid function is: Where f(x) is the Sigmoid function about x, a is the offset, b is the slope factor, and c is the offset correction coefficient.

8. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 4, characterized in that: The feedback unit, in combination with the clinical data of nerve injury recovery, determines the current recovery period through the pre-processed data of the physiological information detection unit, including: Combined with clinical data on nerve injury recovery, a comparison matrix was established: In the formula, n represents the physiological index to be compared, which are m1, m2, ..., m n , M is the comparison matrix, m ij m 11 ,...,m nn , represents the importance ratio of the i-th indicator to the j-th indicator. If m i Relative to m j More importantly, m ij >1; otherwise, m ij <1, when two indicators are equally important, m ij =1; The relative importance of the neurological injury recovery status was obtained based on the comparison matrix; Based on the relative importance results, thresholds of physiological indicators corresponding to different stages of nerve injury recovery are set; The preprocessed data of the physiological information detection unit and the physiological index threshold are judged to obtain the current recovery period.

9. The intelligent oxygen chamber nursing system for promoting nerve injury recovery according to claim 1, characterized in that: It also includes a user interface for displaying the data monitored by the monitoring module and the data fusion results of the central processing module, and is also used for manually adjusting the smart oxygen chamber.

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