Later-period rehabilitation respiratory training system for internal medicine nursing

Abstract

The invention provides a later rehabilitation respiratory training system for internal medicine nursing, and relates to the technical field of auxiliary medical systems. The later rehabilitation respiratory training system for medical nursing comprises a respiratory sensor module used for detecting the respiratory frequency, depth and mode of a patient; the data processing module is used for processing and analyzing the data acquired by the sensor; the user interface module comprises a display screen and an interactive interface and is used for displaying the training data and the guidance information; the feedback module feeds back a training effect through sound, vibration or visual signals; the storage module is used for storing training data and analysis results; and the communication module realizes data transmission with external equipment. The system can collect and analyze breathing data of a patient in real time and provide feedback, the patient and medical staff can timely connect the breathing condition and quickly adjust a training scheme, so that the training effect is improved, and meanwhile, the system can dynamically adjust the training scheme along with the change of the breathing condition of the patient, and continuous optimization of the training process is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of auxiliary medical systems, in particular to a late-stage rehabilitation breathing training system for internal medicine nursing. Background Art

[0002] With the continuous development of modern medicine, the rehabilitation care of respiratory diseases has received more and more attention. Respiratory diseases such as chronic obstructive pulmonary disease, asthma, pneumonia, etc. occupy an important position in internal medicine nursing. The rehabilitation process of these diseases usually requires long-term and systematic breathing training to improve the patient's respiratory function and quality of life. Breathing training refers to two types of training: inhalation training and exhalation training. Inhalation is an active process, which requires active contraction to expand the chest cavity and reduce the pressure in the lungs. When the pressure in the lungs is lower than atmospheric pressure, air will be inhaled into the lungs. Exhalation breathing training has a significant help on the efficiency of gas exchange in the body. This kind of training is especially indispensable for the rehabilitation of postoperative patients. In order to help patients with breathing training, a rehabilitation breathing training system is needed.

[0003] Traditional respiratory rehabilitation training mainly relies on manual guidance and simple equipment, such as respiratory trainers, etc. These methods still have some shortcomings and areas for improvement. Traditional methods mainly rely on the patient's self-perception and the experience and judgment of nursing staff. They lack objective data support, and it is difficult to accurately evaluate the training effect. There is a lack of real-time monitoring and analysis of the patient's respiratory data. The training plan is difficult to adjust according to the patient's specific situation, resulting in poor training results. At the same time, patients cannot obtain effective feedback in time during the training process, and it is difficult to make timely adjustments, which easily leads to unsatisfactory training results. Data recording during the training process mainly relies on manual recording, which makes it difficult to conduct long-term data tracking and analysis, and it is impossible to achieve remote monitoring and sharing of data. Therefore, technical personnel in this field provide a late-stage rehabilitation respiratory training system for internal medicine nursing to solve the problems raised in the above background technology. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides a post-rehabilitation respiratory training system for internal medicine nursing, which solves the problems of the prior art methods such as difficulty in quantifying the training effect, low degree of personalization, untimely feedback and inconvenient data management.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a late rehabilitation respiratory training system for internal medicine nursing, comprising:

[0008] A breathing sensor module is used to detect the patient's breathing rate, depth and pattern; a data processing module is used to process and analyze the data collected by the sensor; a user interface module includes a display screen and an interactive interface, which are used to display training data and guidance information; a feedback module is used to feedback the training effect through sound, vibration or visual signals; a storage module is used to store training data and analysis results; and a communication module is used to realize data transmission with external devices.

[0009] Preferably, the breathing sensor module comprises the following steps:

[0010] S1. Sensor selection, including but not limited to pressure sensors, acceleration sensors, thermistor sensors and piezoelectric sensors;

[0011] S2. Sensor layout: Select appropriate sensor layout according to patient comfort and data collection requirements, including but not limited to chest-worn, abdominal patch, and nasal probe;

[0012] S3. Signal acquisition: perform preliminary processing on the raw signal collected by the sensor, use an amplifier to amplify the sensor signal to increase the signal strength, use a filter to remove high-frequency and low-frequency noise, retain useful breathing signals, and convert analog signals into digital signals for subsequent processing;

[0013] S4. Data processing: further processing the collected digital signals to extract respiratory parameters, calculate the number of breaths per minute by detecting the respiratory cycle, calculate the depth of each breath by detecting the amplitude of the respiratory waveform, identify different respiratory patterns by analyzing the shape of the respiratory waveform, and use filtering algorithms to further remove noise and interference in the signal;

[0014] S5. Data transmission, the processed respiratory data is transmitted to the data processing module or external device via USB, serial port or Bluetooth, Wi-Fi;

[0015] S6. Data storage, using flash memory or SD card storage media to store data, and storing the data to an external device through a communication interface;

[0016] S7. Real-time feedback, breathing data needs to be fed back to the patient in real time so as to carry out breathing training. A display module is designed, including a display screen, a speaker and a vibrator, to realize the real-time feedback function.

[0017] Preferably, the data processing module comprises the following steps:

[0018] S1. Data reception: receiving data through a wired or wireless interface, parsing the received data format, and ensuring the consistency and integrity of the data;

[0019] S2. Data preprocessing: using digital filters to remove high-frequency and low-frequency noise, retaining useful respiratory signals, using denoising algorithms to further remove noise from the signal, and using smoothing algorithms to make the data curve smoother;

[0020] S3. Extraction of respiratory parameters, calculating the respiratory frequency by detecting the respiratory cycle, calculating the respiratory depth by detecting the amplitude of the respiratory waveform, and identifying different respiratory patterns by analyzing the shape of the respiratory waveform;

[0021] S4. Data analysis and evaluation: analyze the changing trend of respiratory parameters over time, determine whether the patient's respiratory condition has improved, detect abnormal values ​​in respiratory parameters, determine whether there is respiratory abnormality, and evaluate the training effect based on the changes in respiratory parameters.

[0022] Preferably, the feedback module comprises the following steps:

[0023] S1. Feedback information generation: Generate feedback information based on the received data, including training guidance, abnormal warnings and training suggestions. Provide personalized training guidance based on changes in breathing parameters. If abnormal breathing is detected, issue a warning message in time. Provide follow-up training suggestions based on the training effect.

[0024] S2. Presenting feedback information: presenting the generated feedback information to the patient or medical staff in an intuitive and understandable manner, displaying the feedback information through a display screen, LED light or graphical interface, providing sound prompts through speakers or headphones, and providing vibration prompts through a vibrator;

[0025] S3. Real-time feedback. Feedback information needs to be delivered to patients in real time so that timely adjustments and training can be made. The feedback module needs to receive and process the latest data sent by the data processing module in real time, and update the feedback information immediately based on the latest data to ensure that patients can get feedback in a timely manner.

[0026] S4. User interaction, allowing patients or medical staff to input training parameters, including but not limited to training time, breathing target, allowing selection of different training modes, and allowing viewing of historical training data and feedback information;

[0027] S5. Exception handling: if data is lost, the feedback module prompts the patient or medical staff; if the connection is interrupted, the feedback module needs to establish a connection or prompt the user to check the connection; if an error occurs in the system, the feedback module needs to prompt an error message.

[0028] Preferably, the storage module comprises the following steps:

[0029] S1. Data reception, firstly, needs to receive data from the breathing sensor module and the data processing module, receive the data through a wired or wireless interface, parse the received data format, and ensure the consistency and integrity of the data;

[0030] S2. Data classification: The received data needs to be classified so that they can be stored and managed separately. The raw data collected by the respiratory sensor is stored, and the results analyzed by the data processing module are stored, including but not limited to respiratory rate, depth and pattern. The feedback information generated by the feedback module is stored, including training guidance and abnormal warnings.

[0031] S3. Data storage: select the appropriate storage medium and storage method according to the classified data, select flash memory, SD card or cloud storage, define the data storage format, which is CSV, JSON or database, and write the classified data into the storage medium;

[0032] S4. Data management: stored data needs to be managed for subsequent viewing, retrieval and deletion. Indexes are created for stored data for quick retrieval. Stored data can be retrieved based on indexes or keywords, and no longer needed data can be deleted as needed.

[0033] S5. Data backup and recovery. In order to prevent data loss, data backup is required and data recovery is performed when necessary. The stored data should be backed up regularly to other storage media or the cloud. When data is lost or damaged, the data should be restored from the backup.

[0034] Preferably, the communication module comprises the following steps:

[0035] S1. Determine the communication requirements, clarify the communication requirements inside and outside the system, the data transmission between modules inside the system, and the data transmission between the system and external devices;

[0036] S2. Selecting a communication protocol, including but not limited to a wired communication protocol, a wireless communication protocol, and a cloud communication protocol;

[0037] S3. Design the communication interface, including Bluetooth module, Wi-Fi module, serial port module, driver module and communication protocol stack;

[0038] S4. Implement data packaging and unpacking, pack the original data according to the requirements of the communication protocol, including adding a header, a tail and a checksum, and unpacking the received data according to the requirements of the communication protocol to restore the original data;

[0039] S5. Implement data transmission, send the packaged data through the communication interface, receive data from the communication interface, and unpack it;

[0040] S6. Implement error detection and correction, detect errors in data transmission through the check code, and take appropriate corrective measures based on the results of error detection;

[0041] S7. Achieve secure communication, encrypt sensitive data to prevent data leakage, authenticate both parties in communication, and prevent unauthorized access;

[0042] S8. Realize remote communication, establish connection with cloud server through the Internet, and synchronize local data to cloud server.

[0043] (III) Beneficial effects

[0044] The present invention provides a late-stage rehabilitation breathing training system for internal medicine nursing, which has the following beneficial effects:

[0045] 1. In the present invention, the system can collect and analyze the patient's respiratory data in real time and provide timely feedback, so that the patient and medical staff can connect the respiratory status in time and quickly adjust the training plan, thereby improving the training effect. At the same time, as the patient's respiratory status changes, the system can dynamically adjust the training plan to ensure continuous optimization of the training process.

[0046] 2. In the present invention, the system can monitor the respiratory rate, as well as the depth and pattern of breathing, and provide comprehensive respiratory data, which helps to more comprehensively evaluate the patient's respiratory condition and formulate a more scientific rehabilitation plan.

[0047] 3. In the present invention, the system can store the training data locally or in the cloud, which is convenient for subsequent data viewing and analysis. It can also perform trend analysis on long-term data to help medical staff understand the patient's rehabilitation progress and develop longer-term rehabilitation plans. It can transmit data to the cloud server via the Internet to facilitate remote monitoring and management by medical staff. Medical staff can provide remote guidance and suggestions based on the remote monitoring data to further improve the effectiveness of rehabilitation training. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the overall system of the present invention. DETAILED DESCRIPTION

[0049] 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.

[0050] Embodiment 1:

[0051] like Figure 1 As shown, an embodiment of the present invention provides a late rehabilitation respiratory training system for internal medicine nursing, comprising:

[0052] A breathing sensor module is used to detect the patient's breathing rate, depth and pattern; a data processing module is used to process and analyze the data collected by the sensor; a user interface module includes a display screen and an interactive interface, which are used to display training data and guidance information; a feedback module is used to feedback the training effect through sound, vibration or visual signals; a storage module is used to store training data and analysis results; and a communication module is used to realize data transmission with external devices.

[0053] The respiration sensor module includes the following steps:

[0054] S1. Sensor selection, including but not limited to pressure sensors, acceleration sensors, thermistor sensors and piezoelectric sensors;

[0055] S2. Sensor layout: Select appropriate sensor layout according to patient comfort and data collection requirements, including but not limited to chest-worn, abdominal patch, and nasal probe;

[0056] S3. Signal acquisition: perform preliminary processing on the raw signal collected by the sensor, use an amplifier to amplify the sensor signal to increase the signal strength, use a filter to remove high-frequency and low-frequency noise, retain useful breathing signals, and convert analog signals into digital signals for subsequent processing;

[0057] S4. Data processing: further processing the collected digital signals to extract respiratory parameters, calculate the number of breaths per minute by detecting the respiratory cycle, calculate the depth of each breath by detecting the amplitude of the respiratory waveform, identify different respiratory patterns by analyzing the shape of the respiratory waveform, and use filtering algorithms to further remove noise and interference in the signal;

[0058] S5. Data transmission, the processed respiratory data is transmitted to the data processing module or external device via USB, serial port or Bluetooth, Wi-Fi;

[0059] S6. Data storage, using flash memory or SD card storage media to store data, and storing the data to an external device through a communication interface;

[0060] S7. Real-time feedback, breathing data needs to be fed back to the patient in real time so as to carry out breathing training. A display module is designed, including a display screen, a speaker and a vibrator, to realize the real-time feedback function.

[0061] The data processing module includes the following steps:

[0062] S1. Data reception: receiving data through a wired or wireless interface, parsing the received data format, and ensuring the consistency and integrity of the data;

[0063] S2. Data preprocessing: using digital filters to remove high-frequency and low-frequency noise, retaining useful respiratory signals, using denoising algorithms to further remove noise from the signal, and using smoothing algorithms to make the data curve smoother;

[0064] S3. Extraction of respiratory parameters, calculating the respiratory frequency by detecting the respiratory cycle, calculating the respiratory depth by detecting the amplitude of the respiratory waveform, and identifying different respiratory patterns by analyzing the shape of the respiratory waveform;

[0065] S4. Data analysis and evaluation: analyze the changing trend of respiratory parameters over time, determine whether the patient's respiratory condition has improved, detect abnormal values ​​in respiratory parameters, determine whether there is respiratory abnormality, and evaluate the training effect based on the changes in respiratory parameters.

[0066] The feedback module includes the following steps:

[0067] S1. Feedback information generation: Generate feedback information based on the received data, including training guidance, abnormal warnings and training suggestions. Provide personalized training guidance based on changes in breathing parameters. If abnormal breathing is detected, issue a warning message in time. Provide follow-up training suggestions based on the training effect.

[0068] S2. Presenting feedback information: presenting the generated feedback information to the patient or medical staff in an intuitive and understandable manner, displaying the feedback information through a display screen, LED light or graphical interface, providing sound prompts through speakers or headphones, and providing vibration prompts through a vibrator;

[0069] S3. Real-time feedback. Feedback information needs to be delivered to patients in real time so that timely adjustments and training can be made. The feedback module needs to receive and process the latest data sent by the data processing module in real time, and update the feedback information immediately based on the latest data to ensure that patients can get feedback in a timely manner.

[0070] S4. User interaction, allowing patients or medical staff to input training parameters, including but not limited to training time, breathing target, allowing selection of different training modes, and allowing viewing of historical training data and feedback information;

[0071] S5. Exception handling: if data is lost, the feedback module prompts the patient or medical staff; if the connection is interrupted, the feedback module needs to establish a connection or prompt the user to check the connection; if an error occurs in the system, the feedback module needs to prompt an error message.

[0072] The storage module includes the following steps:

[0073] S1. Data reception, firstly, needs to receive data from the breathing sensor module and the data processing module, receive the data through a wired or wireless interface, parse the received data format, and ensure the consistency and integrity of the data;

[0074] S2. Data classification: The received data needs to be classified so that they can be stored and managed separately. The raw data collected by the respiratory sensor is stored, and the results analyzed by the data processing module are stored, including but not limited to respiratory rate, depth and pattern. The feedback information generated by the feedback module is stored, including training guidance and abnormal warnings.

[0075] S3. Data storage: select the appropriate storage medium and storage method according to the classified data, select flash memory, SD card or cloud storage, define the data storage format, which is CSV, JSON or database, and write the classified data into the storage medium;

[0076] S4. Data management: stored data needs to be managed for subsequent viewing, retrieval and deletion. Indexes are created for stored data for quick retrieval. Stored data can be retrieved based on indexes or keywords, and no longer needed data can be deleted as needed.

[0077] S5. Data backup and recovery. In order to prevent data loss, data backup is required and data recovery is performed when necessary. The stored data should be backed up regularly to other storage media or the cloud. When data is lost or damaged, the data should be restored from the backup.

[0078] The communication module includes the following steps:

[0079] S1. Determine the communication requirements, clarify the communication requirements inside and outside the system, the data transmission between modules inside the system, and the data transmission between the system and external devices;

[0080] S2. Selecting a communication protocol, including but not limited to a wired communication protocol, a wireless communication protocol, and a cloud communication protocol;

[0081] S3. Design the communication interface, including Bluetooth module, Wi-Fi module, serial port module, driver module and communication protocol stack;

[0082] S4. Implement data packaging and unpacking, pack the original data according to the requirements of the communication protocol, including adding a header, a tail and a checksum, and unpacking the received data according to the requirements of the communication protocol to restore the original data;

[0083] S5. Implement data transmission, send the packaged data through the communication interface, receive data from the communication interface, and unpack it;

[0084] S6. Implement error detection and correction, detect errors in data transmission through the check code, and take appropriate corrective measures based on the results of error detection;

[0085] S7. Achieve secure communication, encrypt sensitive data to prevent data leakage, authenticate both parties in communication, and prevent unauthorized access;

[0086] S8. Realize remote communication, establish connection with cloud server through the Internet, and synchronize local data to cloud server.

[0087] 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 late-stage rehabilitation respiratory training system for internal medicine nursing, characterized in that: include: A breathing sensor module to detect the patient's breathing rate, depth and pattern; Data processing module, which processes and analyzes the data collected by the sensor; A user interface module, including a display screen and an interactive interface, for displaying training data and guidance information; A feedback module, which provides feedback on training effects through sound, vibration or visual signals; a storage module, which is used to store training data and analyze results; Communication module, realizes data transmission with external devices.

2. A late-stage rehabilitation respiratory training system for internal medicine nursing according to claim 1, characterized in that: The breathing sensor module comprises the following steps: S1. Sensor selection, including but not limited to pressure sensors, acceleration sensors, thermistor sensors and piezoelectric sensors; S2. Sensor layout: Select appropriate sensor layout according to patient comfort and data collection requirements, including but not limited to chest-worn, abdominal patch, and nasal probe; S3. Signal acquisition: perform preliminary processing on the raw signal collected by the sensor, use an amplifier to amplify the sensor signal to increase the signal strength, use a filter to remove high-frequency and low-frequency noise, retain useful breathing signals, and convert analog signals into digital signals for subsequent processing; S4. Data processing: further processing the collected digital signals to extract respiratory parameters, calculate the number of breaths per minute by detecting the respiratory cycle, calculate the depth of each breath by detecting the amplitude of the respiratory waveform, identify different respiratory patterns by analyzing the shape of the respiratory waveform, and use filtering algorithms to further remove noise and interference in the signal; S5. Data transmission, the processed respiratory data is transmitted to the data processing module or external device via USB, serial port or Bluetooth, Wi-Fi; S6. Data storage, using flash memory or SD card storage media to store data, and storing the data to an external device through a communication interface; S7. Real-time feedback, breathing data needs to be fed back to the patient in real time so as to carry out breathing training. A display module is designed, including a display screen, a speaker and a vibrator, to realize the real-time feedback function.

3. A late-stage rehabilitation respiratory training system for internal medicine nursing according to claim 1, characterized in that: The data processing module comprises the following steps: S1. Data reception: receiving data through a wired or wireless interface, parsing the received data format, and ensuring the consistency and integrity of the data; S2. Data preprocessing: using digital filters to remove high-frequency and low-frequency noise, retaining useful respiratory signals, using denoising algorithms to further remove noise from the signal, and using smoothing algorithms to make the data curve smoother; S3. Extraction of respiratory parameters, by detecting the respiratory cycle to calculate the respiratory frequency, detecting the amplitude of the respiratory waveform to calculate the respiratory depth, and analyzing the shape of the respiratory waveform to identify different respiratory patterns; S4. Data analysis and evaluation: analyze the changing trend of respiratory parameters over time, determine whether the patient's respiratory condition has improved, detect abnormal values ​​in respiratory parameters, determine whether there is respiratory abnormality, and evaluate the training effect based on the changes in respiratory parameters.

4. A late-stage rehabilitation respiratory training system for internal medicine nursing according to claim 1, characterized in that: The feedback module comprises the following steps: S1. Feedback information generation: Generate feedback information based on the received data, including training guidance, abnormal warnings and training suggestions. Provide personalized training guidance based on changes in breathing parameters. If abnormal breathing is detected, issue a warning message in time. Provide follow-up training suggestions based on the training effect. S2. Presenting feedback information: presenting the generated feedback information to the patient or medical staff in an intuitive and understandable manner, displaying the feedback information through a display screen, LED light or graphical interface, providing sound prompts through speakers or headphones, and providing vibration prompts through a vibrator; S3. Real-time feedback. Feedback information needs to be delivered to patients in real time so that timely adjustments and training can be made. The feedback module needs to receive and process the latest data sent by the data processing module in real time, and update the feedback information immediately based on the latest data to ensure that patients can get feedback in a timely manner. S4. User interaction, allowing patients or medical staff to input training parameters, including but not limited to training time, breathing target, allowing selection of different training modes, and allowing viewing of historical training data and feedback information; S5. Exception handling: if data is lost, the feedback module prompts the patient or medical staff; if the connection is interrupted, the feedback module needs to establish a connection or prompt the user to check the connection; if an error occurs in the system, the feedback module needs to prompt an error message.

5. The late rehabilitation respiratory training system for internal medicine nursing according to claim 1, characterized in that: The storage module comprises the following steps: S1. Data reception, firstly, needs to receive data from the breathing sensor module and the data processing module, receive the data through a wired or wireless interface, parse the received data format, and ensure the consistency and integrity of the data; S2. Data classification: The received data needs to be classified so that they can be stored and managed separately. The raw data collected by the respiratory sensor is stored, and the results analyzed by the data processing module are stored, including but not limited to respiratory rate, depth and pattern. The feedback information generated by the feedback module is stored, including training guidance and abnormal warnings. S3. Data storage: select the appropriate storage medium and storage method according to the classified data, select flash memory, SD card or cloud storage, define the data storage format, which is CSV, JSON or database, and write the classified data into the storage medium; S4. Data management: stored data needs to be managed for subsequent viewing, retrieval and deletion. Indexes are created for stored data for quick retrieval. Stored data can be retrieved based on indexes or keywords, and no longer needed data can be deleted as needed. S5. Data backup and recovery. In order to prevent data loss, data backup is required and data recovery is performed when necessary. The stored data should be backed up regularly to other storage media or the cloud. When data is lost or damaged, the data should be restored from the backup.

6. A late-stage rehabilitation respiratory training system for internal medicine nursing according to claim 1, characterized in that: The communication module comprises the following steps: S1. Determine the communication requirements, clarify the communication requirements inside and outside the system, the data transmission between modules inside the system, and the data transmission between the system and external devices; S2. Selecting a communication protocol, including but not limited to a wired communication protocol, a wireless communication protocol, and a cloud communication protocol; S3. Design communication interface, including Bluetooth module, Wi-Fi module, serial port module, driver module and communication protocol stack; S4. Implement data packaging and unpacking, pack the original data according to the requirements of the communication protocol, including adding a header, a tail and a checksum, and unpacking the received data according to the requirements of the communication protocol to restore the original data; S5. Implement data transmission, send the packaged data through the communication interface, receive data from the communication interface, and unpack it; S6. Implement error detection and correction, detect errors in data transmission through the check code, and take appropriate corrective measures based on the results of error detection; S7. Achieve secure communication, encrypt sensitive data to prevent data leakage, authenticate both parties in communication, and prevent unauthorized access; S8. Realize remote communication, establish connection with cloud server through the Internet, and synchronize local data to cloud server.

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