Tracheostomy fixation device and method of controlling the same

Abstract

The application discloses a tracheotomy fixing device and a control method thereof, and relates to the field of medical devices.The device comprises a fixing base assembly, an adjustable fixing belt system, an intelligent monitoring and adjusting module, a pressure sore prevention auxiliary structure and a wireless communication module.The fixing device can realize real-time acquisition of pressure data in the fixing area through a pressure sensor array, analysis and processing of the pressure data by an intelligent control unit, automatic adjustment of the tightness of the fixing belt by driving an electric adjusting actuator when an abnormal pressure trend is identified, and output of graded alarm information by an alarm unit, so that stable fixation of a tracheal cannula and safe management of pressure are realized.The fixing device can also improve the skin contact environment through a pressure reduction and air permeation structure, reduce the risk of pressure sores, support data interaction with a nursing terminal, and improve nursing efficiency.The application can realize a change from passive fixation to active safety management, and has good clinical application value.

Description

Technical Field

[0001] This specification relates to the field of medical devices, and more specifically, this application relates to a tracheotomy fixation device and its control method. Background Technology

[0002] Tracheostomy is a common procedure in airway management for critically ill patients, but the stability of the tracheostomy tube and the prevention of local pressure ulcers have always been challenges in clinical nursing. Current fixation methods mostly rely on manual adjustment with gauze or elastic bandages, lacking real-time monitoring and quantitative assessment of the pressure state in the fixation area. When the patient coughs, swallows, or changes position, the force on the fixation band can easily change, potentially leading to excessive local pressure, skin damage, or tube displacement or even dislodgement.

[0003] Meanwhile, because nursing staff mainly rely on experience to judge the tightness of the device, it is difficult to detect pressure change trends in a timely manner, resulting in delayed adjustments and a heavy nursing burden. Although some improved devices have added adjustment structures or alarm functions, most can only achieve passive monitoring or simple threshold reminders, lacking the ability to predict abnormal pressure trends and automatically adjust, and the false alarm rate is high, making it difficult to meet the needs of continuous clinical monitoring.

[0004] Therefore, there is an urgent need for an integrated tracheotomy fixation device and its control method that can achieve real-time pressure sensing, trend prediction and adaptive adjustment, so as to improve fixation safety and reduce nursing complexity. Summary of the Invention

[0005] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key features and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0006] In a first aspect, the present invention provides a tracheotomy fixation device, comprising: A fixed base assembly, the fixed base assembly including a cannula connection portion for connecting a tracheal cannula and a base body; An adjustable fixing strap system is connected to both sides of the aforementioned base body; The intelligent monitoring and adjustment module is installed within the aforementioned fixed base assembly. The intelligent monitoring and adjustment module includes a pressure sensor array, an intelligent control unit, an electric adjustment actuator, and an alarm unit. The pressure sensor array is used to collect pressure data of a fixed area. The intelligent control unit is used to generate adjustment control signals based on the pressure data. The electric adjustment actuator is connected to the aforementioned adjustable fixing belt system and is used to automatically adjust the tension of the fixing belt. The alarm unit is used to output graded alarm information. An anti-pressure ulcer auxiliary structure is provided in the aforementioned fixation base assembly and the patient contact area; The wireless communication module is disposed in the base body and electrically connected to the intelligent control unit. The wireless communication module is used to interact with an external care terminal.

[0007] In one feasible implementation, the above-mentioned sleeve connection part is a semi-circular buckle structure, the above-mentioned sleeve connection part is provided with a rotary locking knob, and the inner side of the above-mentioned sleeve connection part is provided with a silicone anti-slip pad. The aforementioned adjustable fixing belt system includes a main fixing belt and a detachable auxiliary stabilizing belt. The auxiliary stabilizing belt is connected to the main fixing belt via a quick-connect interface to form a triangular stabilizing structure.

[0008] In one feasible implementation, the pressure sensing array is a multi-point thin-film pressure sensing structure, which is respectively disposed on the base body and the main fixing belt. The aforementioned intelligent control unit includes a microcontroller and an artificial intelligence algorithm module, used to predict pressure change trends and control the aforementioned electric regulating actuator to adjust the tension.

[0009] In one feasible implementation, the aforementioned pressure ulcer prevention auxiliary structure includes a pressure-reducing pad layer and a breathable pore structure, wherein the pressure-reducing pad layer comprises a sponge and silicone gel composite structure.

[0010] Secondly, this application also proposes a control method for controlling the tracheotomy fixation device of the first aspect, comprising: Pressure data of the fixed area of ​​the tracheostomy tube is collected using the aforementioned pressure sensor array. The aforementioned intelligent control unit filters the pressure data and extracts pressure change characteristics. The validity of the above pressure change characteristics is determined based on the false alarm prevention algorithm to obtain valid abnormal signals; The pressure prediction model is used to predict the trend of pressure changes within a preset time period in the future, so as to obtain the prediction results. When the predicted result exceeds the preset safety threshold, the electric adjusting actuator is controlled to adjust the tension of the adjustable fixing belt system, and the alarm unit outputs graded alarm information.

[0011] In one feasible implementation, the above-mentioned intelligent control unit filters the pressure data and extracts pressure change features, including: The pressure data above is subjected to low-pass filtering to remove instantaneous high-frequency interference signals; Based on the continuously sampled pressure data, the pressure change rate and pressure fluctuation amplitude are calculated, and the pressure change feature vector is generated. When a change in body position is detected, the sampling frequency of the pressure data is temporarily increased and the pressure change feature vector is updated.

[0012] In one feasible implementation, the above-mentioned determination of the validity of the pressure change characteristics based on the false alarm prevention algorithm to obtain a valid abnormal signal includes: The aforementioned pressure change feature vectors are input into the false alarm prevention model for multi-dimensional judgment. Anomaly screening is performed based on the pressure fluctuation amplitude and duration mentioned above. When the duration is less than a preset time threshold, it is determined to be a false alarm signal. The above abnormal screening results are corrected by combining the above information on body position changes, and the above effective abnormal signals are generated.

[0013] In one feasible implementation, the above-mentioned prediction of pressure change trends within a preset time period based on a pressure prediction model to obtain prediction results includes: Based on the above effective abnormal signals, the above historical pressure data and the above pressure change feature vector within the preset time window are obtained to construct a continuous time series input. The continuous time series input above is subjected to trend decomposition processing to obtain the pressure growth trend and instantaneous fluctuation. Based on the aforementioned pressure growth trend, the forecast lead time parameters are calculated, and the aforementioned forecast results are generated based on these forecast lead time parameters.

[0014] In one feasible implementation, when the predicted result exceeds a preset safety threshold, the electric adjusting actuator is controlled to adjust the tension of the adjustable fixing belt system, and a graded alarm message is output through the alarm unit, including: Based on the aforementioned pressure risk level, a corresponding adjustment command is generated, and the adjustment amount of the aforementioned electric adjustment actuator is calculated. A pulse control signal is sent to the aforementioned electric adjusting actuator to drive the aforementioned adjustable fixing belt system to perform graded tension adjustment; The alarm unit is synchronously controlled to output a graded alarm signal corresponding to the aforementioned pressure risk level.

[0015] In one feasible implementation, the above method further includes: The patient's positional change information is obtained through the above-mentioned intelligent control unit. When the detected positional change information exceeds the preset acceleration threshold, the sampling frequency of the pressure sensing array is temporarily increased. After the preset time has elapsed, the sampling frequency will be restored to the initial frequency.

[0016] In summary, compared with related technologies that rely primarily on manual experience to adjust the tightness of the fixation strap and lack real-time monitoring and proactive intervention capabilities, this invention significantly improves fixation stability, pressure safety, and nursing efficiency through the synergistic design of structure and control functions. The combination of the cannula connection structure and the adjustable fixation strap ensures stable fixation of the tracheostomy tube even when the patient coughs, turns over, or becomes agitated, addressing the issues of uneven force distribution and easy loosening associated with traditional single-strap methods. Pressure monitoring in the fixation area, combined with intelligent control, identifies and automatically adjusts pressure change trends, allowing the fixation strap tightness to return to a safe range. This reduces the risk of pressure ulcers caused by continuous local high pressure and decreases the need for frequent manual adjustments by nursing staff. A tiered alarm mechanism provides different alerts based on the level of risk, improving the timeliness of abnormality identification while avoiding the nursing burden of a single alarm mode. Furthermore, the pressure-reducing and breathable structure improves the stress and microenvironment at the skin contact interface, contributing to enhanced comfort and safety during long-term wear. Furthermore, the device supports data interaction with external nursing terminals, enabling nursing staff to remotely monitor the fixation status and perform necessary interventions, thereby improving overall nursing efficiency. This invention realizes a shift from traditional passive fixation to proactive safety management, and has significant application value in terms of fixation reliability, pressure ulcer prevention and control, and ease of clinical use.

[0017] Other advantages, objectives and features of this application will be apparent in part from the description which follows, and in part from what those skilled in the art will understand through study and practice of this application. Attached Figure Description

[0018] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit this specification. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A top-view structural schematic diagram of a tracheotomy fixation device provided in an embodiment of this application; Figure 2 This is a structural schematic diagram of a tracheotomy fixation device provided in the front view of an embodiment of this application; Figure 3 This is a schematic flowchart of a control method provided in an embodiment of this application. Detailed Implementation

[0019] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. The technical solutions of the embodiments of this application will now be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0020] Please see Figure 1 and Figure 2 , Figure 1 This is a top view structural diagram of a tracheotomy fixation device provided in an embodiment of this application. Figure 2 A structural schematic diagram of a tracheotomy fixation device provided in the main view of an embodiment of this application may specifically include: The fixed base assembly 10 includes a cannula connection portion 101 for connecting a tracheal cannula and a base body 102. An adjustable fixing strap system 20 is connected to both sides of the base body 102; The intelligent monitoring and adjustment module 30 is disposed within the fixed base assembly 10. The intelligent monitoring and adjustment module 30 includes a pressure sensor array 301, an intelligent control unit 302, an electric adjustment actuator 303, and an alarm unit 304. The pressure sensor array 301 is used to collect pressure data of a fixed area. The intelligent control unit 302 is used to generate adjustment control signals based on the pressure data. The electric adjustment actuator 303 is connected to the adjustable fixing belt system 20 and is used to automatically adjust the tension of the fixing belt. The alarm unit 304 is used to output graded alarm information. The pressure ulcer prevention auxiliary structure 40 is disposed in the aforementioned fixed base assembly 10 and the patient contact area; The wireless communication module 50 is disposed within the base body 102 and electrically connected to the intelligent control unit 302. The wireless communication module 50 is used to interact with an external care terminal.

[0021] For example, Figure 1The tracheostomy fixation device 10 shown is used to reliably fix the tracheostomy tube in patients after tracheostomy and achieve pressure safety management. The entire device uses a fixation base assembly 10 as the main support and mounting body. The fixation base assembly 10 includes a tube connection part 101 and a base body 102. The tube connection part 101 forms a detachable mechanical connection with the tracheostomy tube, clamping the outer wall of the tube through a semi-encircling limiting and locking structure, thereby maintaining the axial position stability of the tube even when the patient coughs, turns over, or becomes agitated. The base body 102 serves as the integrated carrier for various functional modules. Its shape conforms to the patient's neck skin, providing a mounting surface for pressure monitoring and decompression structures, and also providing encapsulation and protection space for the electrical control and communication units. The adjustable fixation strap system 20 is connected to both sides of the base body 102. After being worn, the adjustable fixation strap system 20 wraps around the patient's neck to form a ring-shaped fixation path. By applying symmetrical force on both sides, the fixation base assembly 10 is stably attached to the area around the patient's incision, and provides an execution object for tightening control during subsequent adjustment.

[0022] An intelligent monitoring and adjustment module 30 is installed within the aforementioned fixed base assembly 10. This module is the core unit for controlling the device. Specifically, a pressure sensor array 301 is distributed within the fixed force-bearing area to collect pressure data in real time during device wearing. This pressure data not only reflects the current tightness of the fixation strap but also characterizes the local skin pressure state, thus providing a quantitative basis for pressure ulcer risk identification. An intelligent control unit 302 is electrically connected to the pressure sensor array 301 and receives the pressure data. After filtering and feature extraction, the intelligent control unit 302 generates an adjustment control signal for control. When an abnormal pressure trend is detected or the pressure reaches a preset risk threshold, the intelligent control unit 302 outputs an adjustment command to the electric adjustment actuator 303. The electric adjustment actuator 303 is connected to the adjustable fixation strap system 20. Upon receiving the adjustment control signal, it makes a slight adjustment to the effective length or tension of the fixation strap, causing the tightness to return to a safe range, thereby achieving adaptive and stable fixation without relying on frequent manual intervention by nurses. The alarm unit 304 works in conjunction with the intelligent control unit 302. When the pressure is in different risk ranges, the alarm unit 304 outputs corresponding graded alarm information to prompt nurses or nursing staff to pay attention and take timely action. The low-risk state is used to indicate that the device is operating normally, the medium-risk state is used to indicate that there may be a tendency for pressure to rise or shift, and the high-risk state is used to indicate that there is a risk of pressure sores or tube dislodgement, which requires priority intervention.

[0023] To reduce the risk of pressure ulcers caused by prolonged pressure on local skin, the device 10 is also equipped with an anti-pressure ulcer auxiliary structure 40. This structure 40 is located between the fixed base assembly 10 and the patient contact area. Through a pressure-reducing pad and a breathable structure, it improves the pressure distribution and microenvironment at the contact interface, ensuring stable fixation while preventing the formation of local high-pressure points and reducing the risk of damage from skin moisture and friction. Furthermore, a wireless communication module 50 is disposed within the base body 102 and electrically connected to the intelligent control unit 302. The wireless communication module 50 transmits the pressure data, adjustment status information, and graded alarm information to an external nursing terminal. It also supports receiving control commands from the external nursing terminal, enabling nursing staff to view pressure changes in the fixed area, device operating status, and alarm event records on a ward workstation, PDA, or mobile terminal, and to lock or manually intervene in the device's automatic adjustment strategy when necessary. Through the above-mentioned structural coordination, the tracheostomy fixation device 10 achieves stable fixation of the tracheal cannula, continuous monitoring and risk identification of the pressure in the fixation area, adaptive adjustment of the tightness of the fixation strap, and real-time information interaction with the nursing end, thereby improving fixation safety, reducing the risk of pressure ulcers, and improving nursing efficiency.

[0024] Compared to related technologies that rely heavily on manual experience to adjust the tightness of the fixation strap and lack real-time monitoring and proactive intervention capabilities, this invention significantly improves fixation stability, pressure safety, and nursing efficiency through a synergistic design of structure and control functions. The combination of a cannula connection structure and an adjustable fixation strap ensures stable fixation of the tracheostomy tube even when the patient coughs, turns over, or becomes agitated, addressing the issues of uneven stress and easy loosening associated with traditional single-strap methods. Pressure monitoring in the fixation area, combined with intelligent control, identifies and automatically adjusts pressure change trends, allowing the fixation strap tightness to return to a safe range. This reduces the risk of pressure ulcers caused by continuous local pressure and decreases the need for frequent manual adjustments by caregivers. A tiered alarm mechanism provides different alerts based on risk levels, improving the timeliness of abnormality identification while avoiding the burden of a single alarm mode. Furthermore, the pressure-reducing and breathable structure improves the stress and microenvironment at the skin contact interface, contributing to enhanced comfort and safety during long-term wear. Furthermore, the device supports data interaction with external nursing terminals, enabling nursing staff to remotely monitor the fixation status and perform necessary interventions, thereby improving overall nursing efficiency. In summary, this invention achieves a shift from traditional passive fixation to proactive safety management, demonstrating significant application value in terms of fixation reliability, pressure ulcer prevention and control, and ease of clinical use.

[0025] In summary, compared with related technologies that rely primarily on manual experience to adjust the tightness of the fixation strap and lack real-time monitoring and proactive intervention capabilities, this invention significantly improves fixation stability, pressure safety, and nursing efficiency through the synergistic design of structure and control functions. The combination of the cannula connection structure and the adjustable fixation strap ensures stable fixation of the tracheostomy tube even when the patient coughs, turns over, or becomes agitated, addressing the issues of uneven force distribution and easy loosening associated with traditional single-strap methods. Pressure monitoring in the fixation area, combined with intelligent control, identifies and automatically adjusts pressure change trends, allowing the fixation strap tightness to return to a safe range. This reduces the risk of pressure ulcers caused by continuous local high pressure and decreases the need for frequent manual adjustments by nursing staff. A tiered alarm mechanism provides different alerts based on the level of risk, improving the timeliness of abnormality identification while avoiding the nursing burden of a single alarm mode. Furthermore, the pressure-reducing and breathable structure improves the stress and microenvironment at the skin contact interface, contributing to enhanced comfort and safety during long-term wear. Furthermore, the device supports data interaction with external nursing terminals, enabling nursing staff to remotely monitor the fixation status and perform necessary interventions, thereby improving overall nursing efficiency. This invention realizes a shift from traditional passive fixation to proactive safety management, and has significant application value in terms of fixation reliability, pressure ulcer prevention and control, and ease of clinical use.

[0026] In one feasible implementation, the sleeve connection part 101 is a semi-circular buckle structure, the sleeve connection part 101 is provided with a rotary locking knob, and the inner side of the sleeve connection part 101 is provided with a silicone anti-slip pad. The adjustable fixing strap system 20 includes a main fixing strap 201 and a detachable auxiliary stabilizing strap 202. The auxiliary stabilizing strap 202 is connected to the main fixing strap 201 through a quick-connect interface 203 to form a triangular stabilizing structure.

[0027] For example, the aforementioned tracheostomy tube connection 101 adopts a semi-circular snap-fit ​​structure, with its shape arc-shaped to cover the outer periphery of the tracheostomy tube, thereby forming radial limiting and guiding positioning of the tracheostomy tube without completely closing and surrounding it. When the tracheostomy fixation device 10 is installed, the nursing staff places the tracheostomy tube into the snap-fit ​​receiving cavity of the aforementioned tracheostomy tube connection 101. The aforementioned semi-circular structure first provides an initial mechanical clamping force, so that the tracheostomy tube is basically constrained in both the axial and radial directions, avoiding the risk of displacement caused by the tube's instantaneous swing due to the patient's coughing, swallowing, or changes in body position. To further enhance connection reliability, the aforementioned sleeve connection part 101 is equipped with a rotary locking knob. During rotation, the rotary locking knob drives the locking structure to tighten the buckle opening or apply pressure to the limiting member, switching the semi-encircling buckle from an assemblable state to a locked and fixed state. This achieves self-adaptive clamping for tracheal sleeves of different outer diameters and avoids loosening or misalignment caused by single-point force application of traditional straps. The inner side of the aforementioned sleeve connection part 101 is provided with a silicone anti-slip pad. This silicone anti-slip pad, on the one hand, increases the friction coefficient of the contact surface to suppress micro-slippage of the sleeve within the buckle; on the other hand, it flexibly buffers and disperses local pressure, reducing wear or stress concentration caused by direct pressure from hard plastic on the sleeve, making the locked connection more stable and safer.

[0028] Furthermore, the aforementioned adjustable fixation system 20 includes a main fixation strap 201 and a detachable auxiliary stabilizing strap 202. The main fixation strap 201, as the primary load-bearing component, connects to the base body 102 at both ends and wraps around the patient's neck to form a circumferential fixation path, thereby stably fitting the fixation base assembly 10 to the periphery of the patient's tracheostomy area. Since a single circumferential fixation may slip or deflect when the patient opens their mouth, raises their neck, or becomes agitated, the detachable auxiliary stabilizing strap 202 is connected to the main fixation strap 201 via a quick-connect interface 203, forming a triangular stabilizing structure together with the auxiliary stabilizing strap 202. This triangular stabilizing structure utilizes geometric stability to transform the load-bearing path from a single-direction tension to multi-directional force constraints, restricting the displacement of the fixation base assembly 10 in both vertical and horizontal directions. This reduces the probability of displacement of the cannula connection 101 relative to the tracheostomy tube and improves overall torsional resistance. The quick-connect interface 203 allows for rapid switching between routine care and emergency procedures using the auxiliary stabilization strap 202. When the patient is stable, the strap 202 can be installed to improve fixation stability. When rapid wound exposure, dressing changes, or emergency airway management are required, the quick-connect interface 203 enables quick unlocking and disassembly, reducing installation and removal time and minimizing impact on airway patency. Through the synergy of the semi-encircling locking buckle and the triangular stabilization strap structure, this embodiment ensures a secure tracheostomy tube connection while also prioritizing wearing comfort and ease of care. Structurally, it provides a stable and controllable mechanical foundation for subsequent pressure monitoring and intelligent adjustment.

[0029] In one feasible implementation, the pressure sensing array 301 is a multi-point thin-film pressure sensing structure, which is respectively disposed on the base body 102 and the main fixing belt 201. The aforementioned intelligent control unit 302 includes a microcontroller 3021 and an artificial intelligence algorithm module 3022, which is used to predict the pressure change trend and control the aforementioned electric regulating actuator 303 to adjust the tension.

[0030] For example, the pressure sensor array 301 adopts a multi-point thin-film pressure sensor structure to achieve spatially distributed monitoring of the force state of the tracheotomy fixation area. Specifically, the pressure sensor array 301 is respectively disposed on the base body 102 and the main fixation strap 201. Multiple thin-film pressure sensor points disposed on the base body 102 reflect the local pressure at the interface between the base body 102 and the patient's neck skin, thereby identifying abnormal states such as unilateral lifting, excessive local pressure, or concentrated force. Multiple thin-film pressure sensor points disposed on the main fixation strap 201 reflect the tension changes of the fixation strap and its changing trend at different force positions, thereby identifying problems such as overall looseness of the fixation strap, excessive tightness in certain areas, or uneven force distribution between the left and right sides. Because the thin-film pressure sensor has the characteristics of thinness, good flexibility, and minimal impact on the contact interface, continuous pressure acquisition can be achieved without significantly increasing the feeling of a foreign body, and the traditional fixation process based on experience to determine tightness can be transformed into a quantifiable pressure data feedback process.

[0031] The pressure data collected by the pressure sensor array 301 is input to the intelligent control unit 302 for processing. The intelligent control unit 302 includes a microcontroller 3021 and an artificial intelligence algorithm module 3022. The microcontroller 3021 serves as the core hardware carrier for data acquisition and control execution, performing real-time tasks such as sampling and reading pressure data, filtering and denoising, feature calculation, and outputting control signals, and uniformly scheduling and managing the working status of each module. The artificial intelligence algorithm module 3022, based on the pressure time series and feature parameters provided by the microcontroller 3021, predicts pressure change trends and assesses risks, thereby generating adjustment strategies for the actuator. By upgrading pressure data from current value monitoring to trend-level prediction, the artificial intelligence algorithm module 3022 can identify trends such as continuous pressure increases in fixed areas, expansion of local high-pressure points, or tension shifts in fixed belts in advance, avoiding passive measures only taken after the pressure exceeds a threshold, which can lead to the accumulation of pressure sores or displacement risks.

[0032] At the execution level, when the intelligent control unit 302 determines that adjustment is needed, the microcontroller 3021 outputs a corresponding adjustment control signal to the electric adjustment actuator 303. The electric adjustment actuator 303 is connected to the adjustment structure of the main fixing belt 201 and is used to finely adjust the effective length or tension of the fixing belt, so that the tightness of the fixing belt returns to the target range. For example, when the pressure sensor array 301 shows that the pressure in a certain area of ​​the base body 102 is continuously increasing and showing a trend of expansion, the artificial intelligence algorithm module 3022 can determine that there is a risk of pressure sores and generate a pressure relief adjustment strategy. Based on this, the microcontroller 3021 drives the electric adjustment actuator 303 to perform a slight relaxation to reduce the stress level in the high-pressure area. When the pressure sensing point of the main fixing strap 201 indicates a decrease in the overall tension of the fixing strap and accompanied by instability in the force on the base body 102, the artificial intelligence algorithm module 3022 can determine that there is a risk of displacement or dislodgement and generate a stabilizing adjustment strategy. Based on this, the microcontroller 3021 drives the electric adjustment actuator 303 to perform a slight tightening to restore stable fit and locking reliability. Through the collaborative work of the multi-point thin-film pressure sensing array 301 and the intelligent control unit 302 containing the microcontroller 3021 and the artificial intelligence algorithm module 3022, this embodiment realizes distributed sensing of the pressure state of the fixing area, intelligent prediction of pressure trends, and automatic adjustment of the tightness of the fixing strap. This ensures the reliability of the cannula fixation while reducing the risk of pressure sores caused by local continuous high pressure and reducing the workload of nursing staff due to frequent manual adjustments.

[0033] In one feasible embodiment, the aforementioned pressure ulcer prevention auxiliary structure 40 includes a pressure-reducing pad 401 and a breathable pore structure 402, wherein the pressure-reducing pad 401 includes a composite structure of sponge 4011 and silicone gel 4012.

[0034] For example, the aforementioned pressure ulcer prevention auxiliary structure 40 is disposed in the area where the aforementioned fixation base assembly 10 contacts the patient's skin, in order to reduce the risk of skin damage caused by continuous local pressure while ensuring the reliability of fixation.

[0035] Specifically, the aforementioned pressure ulcer prevention auxiliary structure 40 includes a pressure-reducing pad layer 401 and a breathable pore structure 402. The pressure-reducing pad layer 401 employs a composite structure of sponge 4011 and silicone gel 4012, providing both deformation buffering and pressure distribution mechanisms. The sponge 4011, acting as an elastic support layer, undergoes controllable compression deformation when the base body 102 is subjected to tension and pressed against the skin. This absorbs some of the concentrated load and provides rebound support, preventing the hard edges or local protrusions of the base body 102 from directly creating high-pressure points on the skin. The silicone gel 4012, acting as a pressure-distributing layer, possesses good flexibility and interfacial lubrication, enabling adaptive adhesion under conditions of skin micro-undulations and neck curvature. This redistributes pressure that might otherwise be concentrated at a few contact points to a larger contact area, thereby reducing the pressure level per unit area and minimizing epidermal damage caused by shear friction.

[0036] Furthermore, the aforementioned ventilated structure 402 is disposed in the corresponding area of ​​the covering layer or base that comes into contact with the skin, improving the local microenvironment by forming microchannels that connect with the outside world. Since the neck area of ​​tracheotomy patients is often accompanied by sweat, exudate, or damp dressings, prolonged application of the fixation device can cause local heat, increased humidity, and skin maceration, significantly increasing the risk of pressure sores and dermatitis. The aforementioned ventilated structure 402 promotes air exchange and moisture diffusion during device wear, maintaining the skin surface temperature and humidity within a relatively stable range and reducing the retention of sweat and exudate beneath the padding. The ventilated structure 402, combined with the low-friction properties of the aforementioned silicone gel 4012, reduces interfacial shear stress during dynamic conditions such as swallowing and slight neck movements, preventing skin damage caused by the combined effects of pressure, friction, and moisture.

[0037] In practical applications, the aforementioned pressure-reducing pad 401 and the aforementioned ventilated structure 402 work synergistically: when the fixation strap system 20 is tightened to ensure the stability of the sleeve, the aforementioned sponge 4011 preferentially bears the load and buffers instantaneous pressure, the aforementioned silicone gel 4012 further expands the force-bearing area and evenly distributes the pressure, and the aforementioned ventilated structure 402 continuously improves local ventilation and moisture dissipation conditions, thereby enabling the fixation base assembly 10 to maintain good skin compatibility even in long-term wear scenarios. Through the aforementioned anti-pressure ulcer auxiliary structure 40, this embodiment can significantly reduce the risk of local high pressure points and skin maceration without sacrificing fixation stability, providing tracheotomy patients with safer, more comfortable, and sustainable fixation and care conditions.

[0038] Secondly, such as Figure 3 As shown, Figure 3 This is a schematic flowchart of a control method provided for an embodiment of this application. This application also proposes a control method for controlling a tracheotomy fixation device in a first aspect, comprising: S210. Collect pressure data of the fixed area of ​​the tracheostomy tube through the pressure sensor array described above. S220. The above-mentioned intelligent control unit filters the pressure data and extracts the pressure change characteristics. S230. The validity of the above pressure change characteristics is determined based on the false alarm prevention algorithm to obtain valid abnormal signals; S240. Based on the pressure prediction model, predict the pressure change trend within a preset time period in the future to obtain the prediction results; S250. When the prediction result exceeds the preset safety threshold, control the electric adjusting actuator to adjust the tension of the adjustable fixing belt system, and output graded alarm information through the alarm unit.

[0039] For example, in step S210, pressure data of the tracheostomy tube fixation area is collected through the aforementioned pressure sensor array. This pressure data includes both local pressure information of the area where the base contacts the skin and pressure change information related to the force applied to the fixation strap. Multi-point acquisition reflects the spatial distribution and temporal changes of pressure, enabling the device to not only sense whether the pressure is too tight or too loose, but also to identify conditions closely related to clinical risk, such as whether the force is uniform, whether local high-pressure points exist, and whether these high-pressure points are expanding.

[0040] In step S220, the aforementioned intelligent control unit filters the pressure data and extracts pressure change features. The purpose is to convert the raw sensor signal into a stable feature input that can be used for subsequent judgment and prediction. Since swallowing, coughing, or brief muscle contractions can cause instantaneous pressure spikes, directly using the raw pressure value for alarms or adjustments can easily lead to false triggers. Therefore, the intelligent control unit first performs noise reduction and smoothing on the pressure data to weaken the impact of short-term high-frequency disturbances. Based on this, pressure change features are further extracted, such as the rate of pressure change, the amplitude of pressure fluctuations, the duration of pressure, and the offset trend of multi-point pressure distribution, enabling the system to move from single-point instantaneous values ​​to a trend-based level for risk identification.

[0041] In step S230, the validity of the aforementioned pressure change characteristics is determined based on the false alarm prevention algorithm to obtain a valid abnormal signal. This step is used to filter out meaningless short-term fluctuations in common clinical disturbance scenarios, avoiding frequent alarms and ineffective adjustments. Specifically, the false alarm prevention algorithm comprehensively judges the aforementioned pressure change characteristics. When the pressure fluctuation reaches an abnormal amplitude but has a short duration and exhibits transient characteristics matching body position or physiological movements, it is judged as a false alarm and only logged. When the pressure abnormality meets the conditions of persistence and trend, it is output as the valid abnormal signal and enters the subsequent prediction stage, thereby ensuring that the data entering the prediction and adjustment link has sufficient credibility and risk indication.

[0042] In step S240, the pressure change trend within a preset time period is predicted based on the pressure prediction model to obtain the prediction result. The significance of this step lies in elevating risk management from a passive response triggered by a threshold to a trend-driven early intervention. In tracheostomy fixation scenarios, pressure ulcers often do not occur instantaneously, but are the result of long-term high local pressure combined with factors such as moisture and friction. Similarly, the risk of tube dislodgement or displacement is often induced by trend changes such as gradual loosening of the fixation straps and force shift. Therefore, after receiving the effective abnormal signal, the pressure prediction model infers the pressure evolution over a future period based on recent pressure change characteristics to obtain the prediction result. This allows the system to identify the risk trend that is about to exceed the limit before the pressure reaches the high-risk threshold, thus gaining a time window for automatic adjustment and nursing intervention.

[0043] In step S250, when the predicted result exceeds a preset safety threshold, the electric adjusting actuator is controlled to adjust the tension of the adjustable fixation strap system, and the alarm unit outputs graded alarm information, thus forming an execution closed loop. Specifically, when the intelligent control unit determines that the predicted result indicates that the future pressure will enter an unsafe range, it first generates an adjustment control signal and drives the electric adjusting actuator to make a slight adjustment to the tension of the fixation strap, so that the pressure in the fixation area returns to the safe range. At the same time, to meet clinical safety requirements and interpretability, the alarm unit outputs graded alarm information corresponding to the risk level, enabling nursing staff to promptly know the current risk level, whether the adjustment action has occurred, and whether further manual intervention is needed. Through the synergistic mechanism of automatic adjustment and graded alarm, on the one hand, the device prioritizes pressure correction within a controllable range to reduce the duration of risk; on the other hand, in cases of high risk or when the condition remains abnormal after adjustment, a clear prompt is issued to the nursing staff to ensure the dual goals of airway fixation safety and skin protection.

[0044] In one feasible implementation, the above-mentioned intelligent control unit filters the pressure data and extracts pressure change features, including: The pressure data above is subjected to low-pass filtering to remove instantaneous high-frequency interference signals; Based on the continuously sampled pressure data, the pressure change rate and pressure fluctuation amplitude are calculated, and the pressure change feature vector is generated. When a change in body position is detected, the sampling frequency of the pressure data is temporarily increased and the pressure change feature vector is updated.

[0045] For example, the aforementioned intelligent control unit filters the pressure data and extracts pressure change features, aiming to convert the raw pressure signal collected by the pressure sensor array into a stable, discriminable feature input that can be used for subsequent false alarm prevention and trend prediction, thereby avoiding false alarms or ineffective adjustments caused by noise interference from the patient's instantaneous movements.

[0046] Specifically, the pressure data is first subjected to low-pass filtering to remove transient high-frequency interference signals. In tracheostomy fixation scenarios, swallowing, coughing, speaking, or brief neck muscle movements often introduce millisecond to second-level spike fluctuations. These fluctuations often do not represent a true change in the tightness of the fixation strap. If used directly for risk assessment, they can easily trigger false alarms and frequently drive the actuator. The aforementioned intelligent control unit uses low-pass filtering to suppress the amplitude and high-frequency components of short-term spikes, making the pressure curve more reflective of the slow drift and continuous change trend of the fixation force, providing a stable baseline for subsequent calculations.

[0047] After filtering, the pressure change rate and pressure fluctuation amplitude are calculated based on the continuously sampled pressure data, generating the aforementioned pressure change feature vector. The pressure change rate characterizes the pressure's increasing or decreasing trend over time, reflecting processes such as the gradual tightening of the fixing strap, the relaxation caused by the subsiding of skin swelling, and the pressure rise caused by the migration of force on the base. The pressure fluctuation amplitude characterizes the degree of pressure fluctuation within a certain time window, reflecting whether the force is stable and whether there are repeated fluctuations caused by uneven local force or slight slippage. By combining these indicators to form the pressure change feature vector, the intelligent control unit not only obtains a single-point pressure value but also a comprehensive description of the change trend and stability. This allows subsequent false alarm prevention algorithms to distinguish between short-term disturbances and continuous anomalies based on the feature vector, while also providing a more informative input sequence for the pressure prediction model.

[0048] Furthermore, when a positional change signal is detected, the sampling frequency of the aforementioned pressure data is temporarily increased and the aforementioned pressure change feature vector is updated, thereby enhancing the dynamic capture capability for high-risk periods. Clinically, when patients turn over, raise their necks, or adjust their pillow positions, the force state of the fixation system changes significantly in a short period of time. This may lead to the fixation straps becoming excessively tight, creating local high-pressure points, or it may cause the force on the fixation straps to shift, resulting in base displacement or even traction on the sleeve. If the sampling frequency is still low, it is easy to miss key transient processes or cause feature calculation lag. Therefore, after recognizing the positional change signal, the aforementioned intelligent control unit temporarily increases the sampling frequency, making the pressure data more dense within the positional change window, thereby more accurately calculating the rate of pressure change and fluctuation amplitude, and updating the aforementioned pressure change feature vector in a timely manner, ensuring that subsequent effectiveness judgments and trend predictions respond based on the latest force state.

[0049] In one feasible implementation, the above-mentioned determination of the validity of the pressure change characteristics based on the false alarm prevention algorithm to obtain a valid abnormal signal includes: The aforementioned pressure change feature vectors are input into the false alarm prevention model for multi-dimensional judgment. Anomaly screening is performed based on the pressure fluctuation amplitude and duration mentioned above. When the duration is less than a preset time threshold, it is determined to be a false alarm signal. The above abnormal screening results are corrected by combining the above information on body position changes, and the above effective abnormal signals are generated.

[0050] For example, the effectiveness of the pressure change characteristics based on the false alarm prevention algorithm is determined and effective abnormal signals are obtained. This is mainly used to distinguish between short-term, risk-free disturbances and continuous, risk-oriented abnormal changes in the real clinical environment of tracheostomy fixation, thereby avoiding nursing interference, patient discomfort and excessive actuator movement caused by frequent false alarms or ineffective adjustments.

[0051] Specifically, the aforementioned pressure change feature vector is first input into the false alarm prevention model for multi-dimensional judgment. This feature vector consists of the pressure change rate, pressure fluctuation amplitude, and related time-series characteristics, reflecting the trend and stability of pressure changes. After receiving the pressure change feature vector, the false alarm prevention model performs joint analysis to determine whether the current pressure fluctuation conforms to the statistical characteristics of abnormal events or clinical risk patterns, thereby upgrading from single-threshold judgment to multi-dimensional feature judgment.

[0052] After completing the multi-dimensional judgment, anomaly screening is performed based on the pressure fluctuation amplitude and duration. This screening step introduces a persistence constraint to ensure that the system only responds to pressure changes with the potential for continuous risk accumulation. Since actions such as swallowing, coughing, and brief head and neck movements typically cause instantaneous pressure spikes or short-cycle fluctuations, although the pressure fluctuation amplitude may reach an abnormal threshold at certain moments, the duration is usually short and then quickly returns to stability. Therefore, this implementation uses duration as a key judgment dimension: when the duration is less than a preset time threshold, it is judged as a false alarm signal, and this signal can be used only for event recording or model statistics without triggering the prediction and execution chain. Only when the duration meets the preset time threshold and the pressure fluctuation amplitude reaches an abnormal condition is it retained as a candidate anomaly and enters the next correction process, thereby significantly reducing the probability of false alarms caused by transient spikes.

[0053] Furthermore, the above-mentioned anomaly screening results are corrected by combining the above-mentioned body position change information to generate the above-mentioned effective anomaly signals, in order to adapt to the complexity of pressure changes in typical scenarios such as turning over and neck lifting. Body position changes often cause relative displacement between the fixation base component and the skin contact surface, changes in the force path of the fixation strap, and migration of local force points, resulting in different forms of pressure curves, such as increased amplitude but short-term recovery or small amplitude but continuous upward trend. If the screening is based solely on the amplitude and duration of pressure fluctuations, misjudgments are likely to occur in certain body position change scenarios. This embodiment also introduces the above-mentioned body position change information as a contextual constraint. When a significant change in body position information is detected, the judgment criteria for the above-mentioned candidate anomalies are corrected. For example, higher weight is given to short-term but drastic fluctuations to prevent missed detections, or the weight of brief impacts caused by body position changes is reduced to reduce false alarms, so that the judgment results are more consistent with real nursing scenarios. Finally, the abnormal events obtained through multi-dimensional judgment, continuous screening, and body position information correction are output as the above-mentioned effective anomaly signals, enabling the system to maintain sufficient sensitivity to real risk signals while reducing ineffective interventions, and achieving a low false alarm and high availability intelligent fixation control effect.

[0054] In one feasible implementation, the above-mentioned prediction of pressure change trends within a preset time period based on a pressure prediction model to obtain prediction results includes: Based on the above effective abnormal signals, the above historical pressure data and the above pressure change feature vector within the preset time window are obtained to construct a continuous time series input. The continuous time series input above is subjected to trend decomposition processing to obtain the pressure growth trend and instantaneous fluctuation. Based on the aforementioned pressure growth trend, the forecast lead time parameters are calculated, and the aforementioned forecast results are generated based on these forecast lead time parameters.

[0055] For example, a pressure prediction model is used to predict the trend of pressure changes within a preset time period in the future. The aim is to improve the identification of pressure risk in fixed areas from a passive response after reaching a threshold to a trend-driven early intervention, thereby reserving a time window for automatic adjustment and care treatment before pressure ulcers form or the risk of fixation failure accumulates.

[0056] Specifically, after step S230 outputs the aforementioned valid anomaly signal, the system considers the current pressure change to have persistence and risk indication, and only then enters the prediction process to ensure higher reliability of the prediction input and reduce meaningless calculations. Based on the aforementioned valid anomaly signal, the system obtains the aforementioned historical pressure data and the aforementioned pressure change feature vector within a preset time window to construct a continuous time series input. The aforementioned historical pressure data is used to characterize the absolute level and spatial distribution changes of pressure, while the aforementioned pressure change feature vector is used to characterize dynamic characteristics such as the rate of pressure change, fluctuation amplitude, and stability. The combination of the two can simultaneously cover the current pressure level and the trend of change, enabling the prediction model to understand the law of pressure evolution over time rather than relying solely on a single pressure value.

[0057] After obtaining the aforementioned continuous time series input, trend decomposition is performed on it to obtain the pressure growth trend and instantaneous fluctuation. Since the pressure signal in a tracheostomy fixation scenario is typically composed of two superimposed components—one being the low-to-medium frequency trend change caused by slow variations in fixation strap tightness, reduction of skin swelling, or shift in the force path; and the other being the instantaneous fluctuation introduced by swallowing, coughing, or brief neck movements—if this distinction is not made, the prediction model is easily swayed by short-term disturbances, leading to over-prediction or false triggering. This implementation uses trend decomposition to separate the aforementioned continuous time series input into a pressure growth trend that reflects long-term risk accumulation and an instantaneous fluctuation that reflects short-term disturbances. This allows subsequent predictions to focus more on the trend components related to pressure ulcer risk and fixation reliability, while retaining an interpretation path for instantaneous fluctuations to avoid misjudging them as continuous deterioration.

[0058] Furthermore, a predictive lead time parameter is calculated based on the aforementioned pressure growth trend, and the aforementioned prediction result is generated based on the predicted lead time parameter, thereby realizing the proactive control logic driven by the lead time. The aforementioned predictive lead time parameter is used to quantify the approach speed of the pressure trend relative to the safety threshold and the remaining safety margin. It can be understood as the time scale or the urgency of intervention required by the system in advance within a preset time period in the future. When the pressure growth trend indicates that the pressure will approach or exceed the safety threshold at a relatively rapid pace, the aforementioned predictive lead time parameter increases accordingly, indicating that earlier intervention or a stronger intervention magnitude is required. When the pressure growth trend is slower or shows a downward trend, the aforementioned predictive lead time parameter decreases accordingly, indicating that the current fixed state can be maintained or only minor intervention is required. The aforementioned prediction result generated based on the aforementioned predictive lead time parameter therefore not only includes the level that the future pressure may reach, but also implies information on the timing of intervention and the urgency of the risk. Through the aforementioned prediction process, this embodiment can identify a continuously rising risk trend in advance before the pressure reaches a high-risk level, reduce the duration of abnormal pressure, and reduce the probability of pressure sores and cannula displacement, thereby improving the safety and nursing efficiency of the tracheostomy fixation device.

[0059] In one feasible implementation, when the predicted result exceeds a preset safety threshold, the electric adjusting actuator is controlled to adjust the tension of the adjustable fixing belt system, and a graded alarm message is output through the alarm unit, including: Based on the aforementioned pressure risk level, a corresponding adjustment command is generated, and the adjustment amount of the aforementioned electric adjustment actuator is calculated. A pulse control signal is sent to the aforementioned electric adjusting actuator to drive the aforementioned adjustable fixing belt system to perform graded tension adjustment; The alarm unit is synchronously controlled to output a graded alarm signal corresponding to the aforementioned pressure risk level.

[0060] For example, when the prediction result exceeds the preset safety threshold, the electric adjustment actuator is controlled to adjust the tightness of the adjustable fixing belt system and the alarm unit outputs graded alarm information. This is mainly used to transform the risk prediction result into an executable, quantifiable, and traceable adjustment action and nursing prompt, thereby forming a closed-loop intervention mechanism.

[0061] Specifically, when the above prediction results indicate that the pressure in a fixed area will enter an unsafe range within a preset time period in the future, the above intelligent control unit first calculates the pressure risk level based on the prediction results, and then enters the execution decision process accordingly, so as to avoid over-adjustment or under-adjustment caused by triggering a single threshold.

[0062] In the first stage of decision-making, a corresponding adjustment command is generated based on the aforementioned pressure risk level, and the adjustment amount of the electric adjustment actuator is calculated. The adjustment command specifies the adjustment direction and intensity, where the adjustment direction indicates tightening or loosening of the fixing belt, and the adjustment intensity indicates the displacement step size or tension increase / decrease for each adjustment. The adjustment amount of the electric adjustment actuator is determined by the deviation between the aforementioned pressure risk level and the safety threshold, giving the adjustment behavior quantifiable and controllable characteristics. For example, when the aforementioned pressure risk level is high and the predicted pressure significantly exceeds the safety threshold, the system generates a larger adjustment amount to quickly reduce local high pressure or correct force deviation. When the aforementioned pressure risk level is medium and the predicted pressure only slightly exceeds the limit, the system generates a smaller adjustment amount for minor correction, avoiding loosening due to excessive loosening or creating new high-pressure points due to excessive tightening. By mapping the risk level to the adjustment amount, the device can achieve graded intervention matching the risk level, balancing fixing stability and pressure safety.

[0063] In the second stage of decision-making, a pulse control signal is sent to the aforementioned electric adjusting actuator to drive the adjustable belt system to perform graded tension adjustment. Since the electric adjusting actuator typically employs stepper drive or an equivalent pulse control method, the intelligent control unit can precisely control the number of rotation steps or linear displacement of the actuator by outputting a pulse sequence, thereby translating the adjustment amount into actual changes in the tension of the belt. During the graded tension adjustment process, the stress state of the adjustable belt system undergoes predictable changes, causing the pressure in the fixed area to return to the target safe range. Through the discretized output of the pulse control signal, the adjustment process can achieve minute and repeatable adjustment actions, facilitating both rapid and stable control and subsequent evaluation and correction of the adjustment effect in the feedback loop.

[0064] In the third stage of decision-making, the alarm units are synchronously controlled to output graded alarm signals corresponding to the aforementioned pressure risk levels, thereby achieving coordination and consistency between adjustment actions and nursing reminders. On the one hand, when the system is automatically adjusting, it is still necessary to inform nursing staff of the current risk level and system status so that they can confirm, verify, or intervene further when necessary. On the other hand, graded alarms can prevent alarm fatigue caused by using the same intensity of alerts for all abnormalities.

[0065] The aforementioned alarm unit outputs different levels of alerts based on the pressure risk level. For example, at low risk, it outputs visual alerts to indicate normal device operation or requiring only minor attention; at medium risk, it outputs intermittent audible and visual alerts to remind nursing staff to strengthen observation; and at high risk, it outputs continuous audible and visual alerts to indicate the need for priority intervention. This implementation can convert the predicted pressure risk into actionable adjustment of the endotracheal tube tension within seconds and present the risk information transparently to the nursing staff through a synchronous, tiered alarm system. This effectively controls local pressure levels while improving the reliability of endotracheal tube fixation, reducing the risk of pressure ulcers and tube dislodgement, and improving nursing management efficiency.

[0066] In one feasible implementation, the above method further includes: The patient's positional change information is obtained through the above-mentioned intelligent control unit. When the detected positional change information exceeds the preset acceleration threshold, the sampling frequency of the pressure sensing array is temporarily increased. After the preset time has elapsed, the sampling frequency will be restored to the initial frequency.

[0067] For example, in addition to completing routine pressure collection and intelligent judgment, the above method further introduces a position-triggered adaptive sampling mechanism to improve the ability to capture pressure transients and force transfer in typical nursing scenarios such as patients turning over, raising their necks, nodding their heads, or becoming agitated, thereby reducing the risk of missed detections and delayed responses caused by sparse sampling.

[0068] Specifically, the system acquires patient positional change information through the aforementioned intelligent control unit. This positional change information can be generated by an accelerometer or equivalent motion sensing unit installed within the device, and is read and analyzed in real time by the intelligent control unit. When the detected positional change information exceeds a preset acceleration threshold, the system determines that the patient is in a state of significant positional change. At this time, the force point of the contact surface between the fixed base assembly and the skin may shift rapidly, and the tension of the fixation band may also undergo short-term abrupt changes. If the initial sampling frequency is still used for pressure acquisition, it is easy to encounter problems such as insufficient acquisition of key transient processes, averaged pressure peaks, or time lag between the occurrence and identification of abnormalities.

[0069] Therefore, after the triggering condition is met, the sampling frequency of the aforementioned pressure sensor array is temporarily increased, making the pressure data more dense within the body position change window. This allows for a more accurate depiction of the pressure change rate, fluctuation amplitude, and migration trajectory of multi-point pressure distribution. Through high-frequency sampling, the system can distinguish between short-term impact-type pressure fluctuations caused by body position changes and persistent high pressure or fixed loosening trends induced by body position changes. It also provides more reliable timing information to subsequent filtering, pressure change feature extraction, and false alarm prevention processes. For example, when turning over causes a short-term spike in pressure at a certain sensing point followed by a rapid drop, high-frequency sampling can reflect its short duration and fast return characteristics, facilitating suppression in the false alarm prevention stage. When body position changes cause a continuous shift in the base's stress point, resulting in a continuous increase in local pressure, high-frequency sampling can capture the upward trend earlier, providing advance notice for subsequent prediction and adjustment.

[0070] After the aforementioned positional change process concludes, the sampling frequency returns to the initial frequency after a preset time period. This ensures monitoring accuracy during high-risk periods while controlling system power consumption and data processing load. By setting a preset time window, the system maintains high-frequency sampling for a short period after a positional change is triggered. Once the pressure fluctuation reaches a relatively stable state, it automatically reverts to the initial sampling frequency, achieving an adaptive acquisition strategy of high accuracy during critical periods and low load during stable periods. Thus, this embodiment dynamically adjusts the sampling frequency triggered by positional changes, enabling the device to possess stronger pressure anomaly detection capabilities and faster control response capabilities in high-risk dynamic clinical scenarios. This further enhances the stability of tracheostomy fixation and the reliability of pressure ulcer prevention, while reducing the additional inspection burden on nursing staff regarding the fixation status after positional changes.

[0071] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A tracheotomy fixation device based on artificial intelligence, characterized in that, include: A fixed base assembly, the fixed base assembly including a cannula connection portion for connecting a tracheostomy tube and a base body; An adjustable fixing strap system is connected to both sides of the base body; An intelligent monitoring and adjustment module is disposed within the fixed base assembly. The intelligent monitoring and adjustment module includes a pressure sensor array, an intelligent control unit, an electric adjustment actuator, and an alarm unit. The pressure sensor array is used to collect pressure data of a fixed area. The intelligent control unit is used to generate adjustment control signals based on the pressure data. The electric adjustment actuator is connected to the adjustable fixing belt system and is used to automatically adjust the tension of the fixing belt. The alarm unit is used to output graded alarm information. An anti-pressure ulcer auxiliary structure is provided in the fixation base assembly and the patient contact area; A wireless communication module is disposed within the base body and electrically connected to the intelligent control unit. The wireless communication module is used to interact with an external care terminal.

2. The tracheotomy fixation device according to claim 1, characterized in that, The sleeve connection part is a semi-circular buckle structure, the sleeve connection part is provided with a rotary locking knob, and the inner side of the sleeve connection part is provided with a silicone anti-slip pad. The adjustable fixing belt system includes a main fixing belt and a detachable auxiliary stabilizing belt. The auxiliary stabilizing belt is connected to the main fixing belt through a quick-connect interface to form a triangular stabilizing structure.

3. The tracheotomy fixation device according to claim 2, characterized in that, The pressure sensing array is a multi-point thin-film pressure sensing structure, which is respectively disposed on the base body and the main fixing belt; The intelligent control unit includes a microcontroller and an artificial intelligence algorithm module, which is used to predict the pressure change trend and control the electric regulating actuator to adjust the tension.

4. The tracheotomy fixation device according to claim 1, characterized in that, The pressure ulcer prevention auxiliary structure includes a pressure-reducing pad layer and a breathable pore structure. The pressure-reducing pad layer includes a composite structure of sponge and silicone gel.

5. A control method for controlling the tracheotomy fixation device according to any one of claims 1 to 4, characterized in that, include: Pressure data of the fixed area of ​​the tracheostomy tube is collected through the pressure sensor array; The intelligent control unit filters the pressure data and extracts pressure change characteristics. The validity of the pressure change characteristics is determined based on the false alarm prevention algorithm to obtain valid abnormal signals; The pressure prediction model is used to predict the trend of pressure changes within a preset time period in the future, so as to obtain the prediction results. When the prediction result exceeds the preset safety threshold, the electric adjusting actuator is controlled to adjust the tension of the adjustable fixing belt system, and the alarm unit outputs graded alarm information.

6. The control method according to claim 5, characterized in that, The step of filtering the pressure data and extracting pressure change features by the intelligent control unit includes: The pressure data is low-pass filtered to remove transient high-frequency interference signals; The pressure change rate and pressure fluctuation amplitude are calculated based on the continuously sampled pressure data, and the pressure change feature vector is generated. When a change in body position is detected, the sampling frequency of the pressure data is temporarily increased and the pressure change feature vector is updated.

7. The control method according to claim 5, characterized in that, The method of determining the validity of the pressure change characteristics based on the false alarm prevention algorithm to obtain valid abnormal signals includes: The pressure change feature vector is input into the false alarm prevention model for multi-dimensional judgment. Anomalies are filtered based on the pressure fluctuation amplitude and duration. When the duration is less than a preset time threshold, it is determined to be a false alarm signal. The abnormal screening results are corrected by combining the body position change information to generate the effective abnormal signal.

8. The control method according to claim 5, characterized in that, The method of predicting pressure change trends within a preset time period based on a pressure prediction model to obtain prediction results includes: Based on the effective abnormal signals, the historical pressure data and the pressure change feature vector within a preset time window are obtained to construct a continuous time series input. The continuous time series input is subjected to trend decomposition processing to obtain the pressure growth trend and instantaneous fluctuation. The forecast lead time parameter is calculated based on the pressure growth trend, and the forecast result is generated based on the forecast lead time parameter.

9. The control method according to claim 5, characterized in that, When the prediction result exceeds a preset safety threshold, the electric adjusting actuator is controlled to adjust the tension of the adjustable fixing belt system, and the alarm unit outputs graded alarm information, including: Based on the pressure risk level, a corresponding adjustment command is generated, and the adjustment amount of the electric adjustment actuator is calculated; A pulse control signal is sent to the electric adjusting actuator to drive the adjustable fixing belt system to perform graded tension adjustment; The alarm unit is synchronously controlled to output a graded alarm signal corresponding to the pressure risk level.

10. The control method according to claim 5, characterized in that, The method further includes: The intelligent control unit acquires patient position change information, and when the detected position change information exceeds a preset acceleration threshold, the sampling frequency of the pressure sensing array is temporarily increased. After the preset time has elapsed, the sampling frequency will be restored to the initial frequency.

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