Flexible electrode for an implantable myocardial contractility modulation device

Abstract

The application provides a flexible electrode of an implantable myocardial contraction regulating device, wherein the flexible electrode is integrated with a contact pressure sensor, an electrode impedance sensor and a temperature sensor. The algorithm control unit performs a closed-loop control method, which obtains state parameters such as contact pressure through the sensors, and adaptively adjusts parameters of an electric stimulation signal based on the state parameters through an algorithm formula. The core is that the method further comprises a closed-loop feedback correction step, that is, based on an adjustment deviation, a core adjustment coefficient in the algorithm formula is dynamically adjusted, so that self-correction of the algorithm itself is realized. The application can accurately quantify and maintain stable contact of the electrode, and can resist long-term parameter drift through a self-correction mechanism, thereby ensuring long-term stability and safety of stimulation.

Description

Technical Field

[0001] This invention relates to the field of implantable medical device technology, and more specifically, to a flexible electrode for an implantable myocardial contraction regulation device. Background Technology

[0002] Implantable cardiac contractility modulating (CCM) devices improve cardiac function by applying electrical stimulation to myocardial tissue. The flexible electrodes in contact with the myocardial surface are key components ensuring effective transmission of the stimulation signal. To improve performance, some existing technologies employ closed-loop feedback to regulate electrical stimulation. For example, some methods monitor electrical or thermal parameters such as electrode impedance and temperature to adjust the power or frequency of energy delivery, aiming to achieve a stable stimulation effect.

[0003] However, the aforementioned existing technical solutions have inherent drawbacks. First, their assessment of the physical fit between the electrode and the myocardium is indirect and imprecise. Under the influence of continuous cardiac pulsation and respiratory movements, relying solely on electrical parameters such as impedance makes it difficult to accurately distinguish between poor fit caused by slight electrode peeling and impedance changes due to physiological changes such as tissue edema. This inaccuracy prevents the system from quantitatively assessing the reliability of the electrode's physical fit, leading to unstable stimulation effects. Second, existing control mechanisms lack the ability to self-correct against long-term parameter drift. During long-term operation of the implanted device, the electrode itself will experience performance degradation due to factors such as material aging and tissue fluid corrosion, causing drift in the internal model parameters upon which the control system relies for decision-making, rendering the initial calibration inaccurate. Existing technologies lack a mechanism to self-correct the control model itself to adapt to this long-term parameter drift, resulting in a decline in the long-term operational accuracy and stability of the system over time. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to provide a flexible electrode for an implantable myocardial contraction regulation device.

[0005] A flexible electrode for an implantable myocardial contraction modulation device according to the present invention comprises: The sensing and monitoring layer integrates a contact pressure sensor, an electrode impedance sensor, and a temperature sensor. The algorithm control unit is configured as follows: State parameters are obtained through the sensing and monitoring layer; Based on the state parameters, the parameters of the electrical stimulation signal applied to the flexible electrode are calculated and adjusted using a preset algorithm formula; Based on the adjustment deviation between the preset target physiological parameters and the physiological parameter evaluation values ​​obtained from the state parameters, one or more core adjustment coefficients that serve as weighting factors in the algorithm formula are dynamically adjusted. The methods for calculating and adjusting the parameters of the electrical stimulation signal applied to the flexible electrode using a preset algorithm formula include: Based on the bonding pressure, contact resistance, and operating temperature in the aforementioned state parameters, a bonding state coefficient is calculated to quantify the bonding state; and Based on the adhesion state coefficient, at least one of the amplitude, pulse width, and frequency of the electrical stimulation signal is adjusted.

[0006] Furthermore, the calculation result is obtained through a preset algorithm formula, and the corresponding electrical stimulation signal parameter is searched in a preset lookup table based on the calculation result; The lookup table is updated based on the dynamically adjusted core adjustment coefficient.

[0007] Furthermore, the algorithm control unit is also configured as follows: When the state parameter exceeds the preset safety threshold, the application of the electrical stimulation signal is stopped.

[0008] Furthermore, the preset algorithm formula includes:

[0009] in, Let be the fitting state coefficient at time t. For the pressure to fit at time t, To match the pressure reference value, Let be the electrode contact impedance deviation at time t. This is the reference value for electrode contact impedance. Let be the electrode temperature deviation at time t. This is the reference value for the electrode operating temperature. Let be the amount of electrode tensile deformation at time t. This is the reference value for tensile deformation.

[0010] Furthermore, the flexible electrode also includes: The flexible substrate layer forms the flexible support substrate for the entire electrode; An intermediate conductive layer is connected to the flexible substrate layer, and the sensor of the sensing and monitoring layer is embedded between the flexible substrate layer and the intermediate conductive layer, or is located on the same plane as the intermediate conductive layer.

[0011] Furthermore, the intermediate conductive layer is an interdigitated electrode array structure, which includes multiple pairs of staggered electrode contacts and wires connecting these contacts.

[0012] Furthermore, the flexible electrode also includes: An insulating protective layer covers the intermediate conductive layer and the sensing and monitoring layer; The interface layer uses a flexible printed circuit to bring out the wires of the intermediate conductive layer and the signal leads of each sensor in the sensing and monitoring layer, and bring them together to a miniature connector.

[0013] Furthermore, the algorithm control unit is also configured to calculate the impedance compensation amount based on the acquired contact impedance and operating temperature using an adaptive electrode impedance compensation formula. According to the impedance compensation amount Adjust output impedance .

[0014] Furthermore, the algorithm control unit is also configured to, based on the bonding state coefficient at time t... and output impedance The electrical stimulation signal parameters applied to the intermediate conductive layer are dynamically calculated and adjusted.

[0015] Furthermore, the algorithm control unit is also configured to execute a correction cycle at a low frequency, the correction cycle being: Assess performance deviations over a period of time, including deviations in fit adjustment, impedance compensation, or stimulation parameter adjustment. Correct and adjust the fit adjustment coefficient, impedance compensation coefficient, and stimulation amplitude adjustment coefficient through closed-loop feedback.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. Achieving precise quantification and stable fit: By integrating a contact pressure sensor and combining multi-dimensional parameter fusion quantification, this invention achieves precise and dynamic quantitative evaluation of the physical fit of the electrodes, solving the problem of inaccurate judgment relying on indirect parameters in existing technologies. This ensures reliable and stable fit between the electrodes and the myocardium, and guarantees efficient transmission of stimulation signals.

[0017] 2. Ensure long-term operational accuracy and stability: By introducing a closed-loop feedback correction mechanism, this invention can dynamically adjust the core coefficients of the algorithm itself, thereby actively counteracting parameter drift caused by factors such as electrode aging and environmental changes, enabling the system to have self-adaptive and self-correcting capabilities, and ensuring control accuracy and operational stability throughout the entire design life cycle.

[0018] 3. Improved safety and energy efficiency: By accurately judging the fit, stimulation parameters can be allocated as needed. Precise stimulation is achieved when the fit is good, and energy output is automatically reduced when the fit is poor. This avoids potential damage to tissues and significantly saves energy, making it especially suitable for implantable devices that need to operate for a long time.

[0019] 4. Superior overall performance: The multi-layer structure design of this invention takes into account biocompatibility, fatigue resistance and mechanical properties, which can effectively reduce the inflammatory response and the risk of secondary surgery in patients, and has good clinical application prospects. Attached Figure Description

[0020] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the architecture of an adaptive flexible electrode system provided in an embodiment of this application; Figure 2 This is an exploded view of the layered structure of the flexible electrode provided in the embodiments of this application; Figure 3 This is a top view of the intermediate conductive layer of the flexible electrode provided in an embodiment of this application; Figure 4 A flowchart of a closed-loop control method provided in an embodiment of this application; Figure 5 This is a signaling interaction timing diagram of one method embodiment provided in this application. Detailed Implementation

[0021] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0022] Example 1 This embodiment discloses a flexible electrode and control method for an implantable myocardial contraction modulation device, which aims to achieve precise quantification of electrode contact state, adaptive adjustment of stimulation signal, and adaptive correction of long-term system stability in the implantable myocardial contraction modulation device.

[0023] Reference Figure 1 This document illustrates the overall architecture of an adaptive flexible electrode system according to an embodiment of this application. In this embodiment, the system mainly includes an implant 10 and an external control module 20. The implant 10 is the portion implanted into the patient's body, and its core components may include a flexible electrode 11, an algorithm control unit 12, a mid-frequency electrical stimulation module 13, and a wireless power supply module 14. Accordingly, the external control module 20 is used to monitor, configure parameters, receive data, and charge the implant 10 externally.

[0024] Specifically, the flexible electrode 11, as a key component directly interacting with myocardial tissue, is responsible not only for transmitting electrical stimulation signals to the myocardium but also for simultaneously sensing its physical contact state with the myocardium. The algorithm control unit 12, as the system's control core, receives sensor data from the flexible electrode 11, executes the core closed-loop control algorithm, and generates adjustment commands accordingly. The intermediate-frequency electrical stimulation module 13 responds to the commands of the algorithm control unit 12, generates electrical stimulation pulses with specific parameters (e.g., amplitude, pulse width, frequency), and applies them to the myocardial tissue through the flexible electrode 11. The wireless power supply module 14 receives energy from the external control module 20, powers all electronic components within the implant 10, and can integrate wireless communication functionality. It is understood that the external control module 20 and the implant 10 communicate and transfer energy wirelessly. For example, the external control module 20 can send configuration commands to the algorithm control unit 12 or receive its uploaded status logs and alarm information, while simultaneously charging the wireless power supply module 14 wirelessly.

[0025] Figure 2 and Figure 3 An exploded view of the layered structure of the flexible electrode 11 in an embodiment of this application and a top view of the intermediate conductive layer 112 are shown respectively. In one embodiment of this application, the flexible electrode 11 adopts a precise micro-layered structure design, aiming to achieve an optimized balance between mechanical properties, electrical properties, and biocompatibility. To ensure its minimally invasiveness and good flexibility, the overall thickness of the flexible electrode 11 can be controlled to be less than 0.1 mm (e.g., 0.07 mm), its width can be 2 mm, and its length can be 8 mm.

[0026] Specifically, the hierarchical structure, from bottom to top, includes: Flexible substrate layer 111: This layer constitutes the flexible support substrate for the entire electrode, giving the electrode the ability to adapt to the surface morphology and pulsating deformation of the myocardium. As an optional implementation, the flexible substrate layer 111 is preferably made of medical-grade polyimide material with a thickness of 0.035 mm. The reason for choosing this material is that its Young's modulus can be precisely controlled within the range of 1 to 5 gigapascals (e.g., 3 gigapascals in this embodiment). It is understood that although this modulus range differs by orders of magnitude from the Young's modulus of human myocardial tissue (approximately 0.05 to 0.5 megapascals), good mechanical compliance can still be achieved through the flexible design of the overall structure, thereby avoiding stress concentration and excessive compression of myocardial tissue caused by severe modulus mismatch. In addition, micro- and nano-textured treatments can be applied to its surface to increase the contact area and friction with myocardial tissue, thereby improving the stability of the fit.

[0027] Intermediate conductive layer 112: This layer, disposed on top of the flexible substrate layer 111, is the core layer for performing electrical stimulation. In this embodiment, the intermediate conductive layer 112 is made of a 0.012 mm thick platinum-iridium alloy film (e.g., a platinum to iridium mass ratio of 90:10), which possesses excellent conductivity, corrosion resistance, and biocompatibility. This layer is patterned into a specific geometry using micromachining processes such as magnetron sputtering. Figure 3 As shown, a preferred design is to fabricate it as an interdigitated electrode array structure, which includes multiple pairs of staggered electrode contacts 112a and wires 112b connecting these contacts. For example, five independent electrode contacts 112a can be provided, each with an area of ​​approximately 0.15 square millimeters. This interdigitated array design helps to increase the effective edge length of the electrodes within a limited area, thereby reducing the contact resistance at the electrode-tissue interface and making the current distribution more uniform, thus improving the efficiency and accuracy of stimulation. To further reduce contact resistance, a medical-grade conductive gel with a thickness not exceeding 0.005 mm can be coated on the surface of the electrode contacts 112a.

[0028] Sensing and monitoring layer 113: This layer is one of the core innovations that distinguishes this application from the prior art, as it endows the electrodes with the ability to "sense" their own working state. It should be noted that the sensing and monitoring layer 113 is not a single physical layer, but rather refers to a group of miniature sensors integrated into the electrode structure. In this embodiment, these sensors can be embedded between the substrate flexible layer 111 and the intermediate conductive layer 112, or located on the same plane as the intermediate conductive layer 112. Figure 2 As shown, the sensing and monitoring layer 113 integrates at least three different types of sensors: one or more miniature contact pressure sensors 113a, an electrode impedance sensor 113b, and a temperature sensor 113c. The contact pressure sensor 113a (e.g., a piezoresistive or capacitive sensor with dimensions of 0.5 mm × 0.5 mm × 0.02 mm) is used to measure the contact pressure between the flexible electrode 11 and the myocardial tissue in real time, with a range covering 0.03 to 0.2 Newtons. This is a key parameter for directly quantifying the physical fit. The electrode impedance sensor 113b is used to measure the contact impedance between the electrode and the tissue. This impedance value is not only related to the fit but also affected by factors such as the physiological state of the tissue (e.g., edema) and the aging of the electrode itself. The temperature sensor 113c is used to monitor the real-time temperature of the electrode's working area. On the one hand, this serves as a basis for safety monitoring to prevent damage to the tissue caused by heat generated by electrical stimulation; on the other hand, temperature changes also affect the impedance value, so it can be used to compensate for the impedance measurement results.

[0029] Insulating protective layer 114: This layer covers the intermediate conductive layer 112 and the sensing monitoring layer 113, encapsulating all parts except the effective area where the electrode contact 112a needs to contact the myocardium. In this embodiment, the insulating protective layer 114 is made of medical-grade parylene with a thickness of 0.013 mm. This material has excellent biocompatibility, chemical inertness, and moisture barrier properties, effectively protecting the internal conductive pathways and sensors from bodily fluid corrosion, while also achieving electrical insulation to ensure that current flows only from the preset electrode contact 112a, thereby avoiding current leakage and unintended stimulation of surrounding tissues.

[0030] Connection interface layer 115: This layer serves as the interface for electrical connection between the flexible electrode 11 and other circuits (mainly the algorithm control unit 12) inside the implant 10. In this embodiment, the connection interface layer 115 can be implemented using flexible printed circuit technology, leading out the wires 112b of the intermediate conductive layer 112 and the signal leads of each sensor in the sensing and monitoring layer 113, and converging them into a miniature connector to achieve a reliable and flexible connection.

[0031] Reference Figure 4 The diagram illustrates a flowchart of a closed-loop control method provided in an embodiment of this application. This method is executed by an algorithm control unit 12, and its core idea lies in constructing a four-in-one closed-loop control logic integrating "sensing-quantization-adjustment-correction". It is understood that the algorithm control unit 12 can be a low-power microcontroller and can employ 16-bit fixed-point arithmetic to balance computational accuracy and power consumption.

[0032] The specific process of this method is as follows: Step S10 (Start Step): This step is entered after the system is powered on or woken up. The algorithm control unit 12 first performs initialization, loading a set of pre-calibrated offline reference parameters and initial adjustment coefficients. These parameters form the basis of system operation, such as the reference value of the fitting pressure representing the ideal fitting pressure. (e.g., 0.12 Newtons), electrode contact resistance reference value (e.g., 500Ω), electrode operating temperature reference value (e.g., 37℃), and a series of core adjustment coefficients used for subsequent calculations, including but not limited to the bonding state adjustment coefficient. (e.g., 0.88), impedance compensation coefficient (e.g., 0.78), stimulus amplitude adjustment coefficient (e.g., 0.90) and closed-loop correction factor (e.g., 0.95).

[0033] Step S20 (Status Parameter Acquisition Step): The system enters a high-frequency execution main loop. In this step, the algorithm control unit 12 sends an acquisition command to the sensing and monitoring layer 113 via the connection interface layer 115. This acquisition action is performed periodically at a fixed time interval (e.g., every 7 milliseconds). The algorithm control unit 12 reads the current real-time measurement values ​​from the contact pressure sensor 113a, electrode impedance sensor 113b, and temperature sensor 113c, respectively, to obtain a set of status parameters, including the real-time contact pressure. Real-time contact impedance and real-time operating temperature .

[0034] Step S30 (Calculation of Fitting State Coefficient): After obtaining the real-time state parameters, the algorithm control unit 12 does not use these parameters in isolation, but integrates them into a single indicator that can accurately quantify the current fitting reliability—the fitting state coefficient—through a multi-parameter fusion formula. The value of this coefficient typically ranges from 0 to 1; the closer its value is to 1, the more ideal the fit. As a specific implementation method, this fit quantification formula can be expressed as:

[0035] in: Let be the fitting state coefficient at time t. To ensure real-time pressure application. To match the pressure reference value. Pressure item. It characterizes how close the real-time pressure is to the ideal value. This refers to the real-time electrode contact impedance deviation, i.e. The impedance term reflects the negative impact of impedance deviation on the bonding quality through an exponentially decaying function; that is, the greater the deviation, the smaller the value of this term. The value of 0.08 is an empirical weight. This is the reference value for electrode contact impedance. For real-time electrode temperature deviation, i.e. . The reference temperature for electrode operation is 37°C. The temperature term uses a linear penalty term to represent the impact of temperature anomalies on the fit assessment; where 0.02 is the empirical weight. This represents the tensile deformation of the flexible electrode, which can be estimated indirectly using an additional strain sensor or based on the change in impedance between different contacts in the electrode array. This indicates that excessive stretching of the electrode will reduce the bonding quality; 0.01 is an empirical weight. The tensile deformation reference value is calculated by multiplying the electrode length by the allowable percentage of deformation, such as 8mm × 35% = 2.8mm. This formula allows the system to fuse information from multiple dimensions, resulting in a more accurate assessment of the fit than any single parameter.

[0036] Step S40 (Calculating Impedance Compensation and Adjusting Output Impedance): Since the contact impedance of the electrodes can drift due to various factors such as temperature, electrode aging, and tissue physiological changes, compensation is needed to ensure a constant actual electrical stimulation energy applied to the myocardium. The algorithm control unit 12 calculates the impedance compensation amount based on the acquired contact impedance and operating temperature using the electrode impedance adaptive compensation formula. A specific formula is as follows:

[0037] in: This is the electrode impedance compensation amount calculated at time t. It is the impedance compensation coefficient, one of the core coefficients that can be adjusted by closed-loop correction. This is a temperature correction factor used to correct for impedance variations at different temperatures. In the formula... The greater the temperature deviation, the greater the compensation weight should be adjusted accordingly. The introduction of this term allows for a reduction in compensation weight when the fit is poor, thus avoiding overcompensation under uncertain conditions. After calculating the compensation amount, the algorithm control unit 12 adjusts the output impedance of the intermediate frequency electrical stimulation module 13 accordingly. This is to compensate for the measured impedance deviation.

[0038] Step S50 (Adjusting Stimulation Parameters): After obtaining a precise assessment of the fit... and the compensated output impedance Subsequently, the core task of the algorithm control unit 12 is to dynamically calculate and adjust the electrical stimulation signal parameters applied to the intermediate conductive layer 112 to achieve "on-demand stimulation." These parameters mainly include the amplitude, pulse width, and frequency of the stimulation signal. For example, for adjusting the stimulation amplitude, the following adaptive adjustment formula for stimulation parameters can be used:

[0039] in: This represents the adjusted stimulus amplitude. This serves as the baseline value for the stimulus amplitude. The amplitude adjustment coefficient is another core coefficient that can be adjusted by closed-loop correction. The core of this formula lies in combining the adjusted amplitude with the fit state coefficient. Directly related. When When the value is close to 1 (good fit), the stimulation amplitude is close to the reference value to ensure stimulation efficiency; when... When the fit deteriorates, the stimulation amplitude is also reduced accordingly to conserve energy and avoid ineffective or risky strong stimulation under poor fit. The formula also considers the compensated output impedance. and temperature deviation The influence of this can be used for fine-tuning. Similarly, corresponding formulas can be designed to adjust the stimulation pulse width. and frequency .

[0040] Step S60 (Transmission of Stimulus Signal): The algorithm control unit 12 will transmit the calculated new stimulus parameters ( , , The signal is sent to the intermediate frequency electrical stimulation module 13 in the form of an adjustment command. The intermediate frequency electrical stimulation module 13 immediately generates a corresponding electrical stimulation pulse sequence according to the command and applies it precisely to the myocardial tissue through the connection interface layer 115 and the intermediate conductive layer 112.

[0041] Step S70 (Safety Check Step): Simultaneously or after each transmission of a stimulus signal, the algorithm control unit 12 performs a safety check, comparing the real-time status parameters acquired in step S20 with a set of preset safety thresholds. These thresholds include, but are not limited to: maximum operating temperature (e.g., 40°C), maximum / minimum contact resistance (e.g., greater than 1500Ω or less than 50Ω, the latter potentially indicating a short circuit), maximum contact pressure (e.g., 0.25 Newtons, to prevent pressure damage), and maximum tensile deformation (e.g., 35%, indicating a risk of breakage).

[0042] Step S80 (Return Step): If the safety check passes, meaning all parameters are within safe limits, the main loop completes one iteration, and the process returns to step S20, ready for the next data acquisition and adjustment. This high-frequency loop (once every 7 milliseconds in this example) ensures the system's rapid response to physiological activities such as myocardial contractions and respiration.

[0043] If any parameter is found to exceed the safety threshold in step S70, the process will not return to S80, but will trigger an emergency handling mechanism (see Embodiment 4 for details), such as immediately stopping stimulation and sending an alarm to the external control module 20.

[0044] In addition to the aforementioned high-frequency main loop, the control method of this application also includes a parallel or low-frequency correction loop, which is key to achieving long-term system stability.

[0045] Step S90 (Calculate Adjustment Deviation Step): This step is executed in the correction loop, but at a much lower frequency than the main loop, for example, once every 100 milliseconds or longer. The algorithm control unit 12 evaluates the system's performance deviation over a period of time. This deviation can take many forms, such as fit state adjustment deviation (e.g., ... This can be due to several factors, including: a persistently low average value below a target value; impedance compensation bias (e.g., significant energy transfer fluctuations remaining after compensation); or bias in stimulation parameter adjustment. A simple bias assessment can be based on the difference between a pre-set target physiological parameter and an assessment value of the physiological parameter calculated from the current state parameters. For example, if the goal is to maintain... If the value is above 0.9, but the actual average value is only 0.75, then there is an adjustment bias.

[0046] Step S91 (Correcting the Core Adjustment Coefficient): Based on the adjustment deviation calculated in step S90, the algorithm control unit 12 dynamically and minutely adjusts the core adjustment coefficient applied in step S10 using a closed-loop feedback correction formula. For example, for the fitting state adjustment coefficient... The correction can be performed using the following formula:

[0047] in: This is the adjusted coefficient for the corrected fit. This is the adjustment coefficient for the current fit. The closed-loop correction coefficient determines the correction rate. The logic of this formula is that when... When it is lower (deviates from 1), the correction term Greater than 1, thus increasing This increases the weight of the fit state in subsequent calculations, thereby driving the system to more actively improve the fit. Similarly, it is possible to design for... , The correction formulas for other core coefficients are also included. These finely adjusted new coefficients will replace the old values ​​and be used in subsequent calculations in the main loop.

[0048] Through this low-frequency correction cycle, the system can continuously learn and adapt. For example, when the flexible electrode 11 ages due to long-term use, causing its mechanical and electrical properties to drift, this drift manifests as a continuous adjustment deviation. The closed-loop correction mechanism can capture this deviation and automatically adjust the core coefficients within the algorithm to compensate for this drift, thereby enabling the entire system to maintain its control accuracy and stability over an operating cycle of several years (e.g., a design life greater than 5 years) without external intervention.

[0049] Figure 5The timing sequence of signaling interactions between the main entities of the system in this embodiment is illustrated. As shown in the figure, the sensing and monitoring layer periodically sends sensing data to the algorithm control unit 12. After performing the above calculations internally, the algorithm control unit 12 issues an adjustment command to the intermediate frequency electrical stimulation module 13, which then outputs stimulation pulses. During normal operation, the algorithm control unit 12 can also selectively and periodically send status synchronization signals to the external control module 20 for remote monitoring. In the event of an anomaly (such as a safety check failure), the algorithm control unit 12 will immediately send an alarm signal to the external control module 20.

[0050] The working process of this embodiment can be summarized as follows: After implantation, the flexible electrode 11 is tightly attached to the surface of the pulsating myocardium. When the myocardium contracts, the electrode is pressed tightly, and the contact pressure... When the size increases and the fit becomes tighter, the calculated fit state coefficient is... The value will approach 1. At this point, the algorithm control unit 12 will instruct the intermediate frequency electrical stimulation module 13 to output a stimulation signal with high energy close to the reference value to ensure the best therapeutic effect. When the patient takes a deep breath or changes position, causing slight traction on the electrodes, reducing the contact pressure, or even creating a small gap, The value will decrease significantly. The algorithm will immediately capture this change and automatically reduce the amplitude and / or pulse width of the stimulation signal. This not only saves battery energy but also avoids ineffective stimulation of non-target areas in the event of poor fit, and even avoids the risk of inducing arrhythmia. If the electrode material ages after long-term operation, causing its inherent impedance to continuously increase, this change will be sensed by the closed-loop feedback correction mechanism (steps S90 and S91), and the system will gradually increase the impedance compensation-related coefficients (such as...). This enhances the compensation effect for impedance drift, thereby maintaining the stability of stimulus energy output on a macroscopic level.

[0051] The expected beneficial effect of this embodiment is that: through this technical solution, long-term stable adhesion between the electrode and the myocardium can be achieved, thereby increasing the adhesion coefficient. The time percentage of the signal with an amplitude greater than or equal to 0.8 exceeds 95%. Due to stable adhesion and adaptive parameter adjustment, the transmission loss of the stimulation signal can be controlled below 2%, and the fluctuation of the stimulation amplitude is less than 4%. Thanks to the "on-demand stimulation" strategy, the average power consumption of the system is significantly optimized, with standby power consumption below 0.5 microamps and even in operation, the average power consumption can be controlled at around 3.5 microamps, which makes it possible for the implanted device to achieve a design life of up to 5 years or even longer. At the same time, the optimized material and structural design ensures that the electrode can withstand more than one million cycles of bending without functional breakage, and the rate of tissue inflammation is extremely low.

[0052] Example 2 This embodiment aims to illustrate that the core closed-loop control algorithm proposed in this application has good hardware versatility, and its performance does not depend on a specific combination of materials or structures. By replacing the key materials and sensor types in the flexible electrode 11, this embodiment verifies the algorithm's adaptability on hardware platforms with different physical characteristics.

[0053] In this embodiment, the overall layered structure of the flexible electrode 11, namely the structure comprising a base flexible layer 111, an intermediate conductive layer 112, a sensing and monitoring layer 113, and an insulating protective layer 114, is consistent with that of Embodiment 1. However, the specific materials of each layer and the design of some components differ: Flexible substrate layer 111: The polyimide material used in Example 1 is replaced with medical-grade polydimethylsiloxane. Polydimethylsiloxane has a lower Young's modulus, typically in the range of 1 to 2 MPa, which makes it more flexible and has better mechanical compliance with myocardial tissue, theoretically allowing for lower interfacial stress.

[0054] Intermediate conductive layer 112: The platinum-iridium alloy thin film prepared by magnetron sputtering in Example 1 is replaced with a serpentine silver wire fabricated on a polydimethylsiloxane substrate by screen printing. The serpentine design allows the wire to unfold like a spring when the substrate is stretched, thus enabling it to withstand greater tensile deformation (e.g., up to 30% strain) without breaking, which is particularly important for the more flexible polydimethylsiloxane substrate.

[0055] Sensing layer 113: The contact pressure sensor 113a therein replaces the piezoresistive sensor that may be used in Embodiment 1 with a capacitive sensor. This sensor consists of two opposing conductive planes (which may be part of an intermediate conductive layer and an additional conductive layer) and an intermediate elastic dielectric (i.e., the polydimethylsiloxane substrate itself or an insulating protective layer). When external pressure is applied to the electrodes, the thickness of the dielectric layer changes slightly, resulting in a change in capacitance. The algorithm control unit 12 infers the magnitude of the contact pressure by measuring this change in capacitance.

[0056] The closed-loop control method flow executed by the algorithm control unit 12 (e.g.) Figure 4 (As shown) is exactly the same as in Example 1. However, in the initialization and parameter calibration stage of step S10, a completely different set of reference values ​​and initial adjustment coefficients will be applied or calibrated based on the new material and structural characteristics in this example. For example, because the polydimethylsiloxane substrate is softer, the reference value of the bonding pressure required to achieve the ideal bonding state is... It may be even lower; the resistivity and temperature coefficient of resistance of silver wires differ from those of platinum-iridium alloys, therefore the reference value for electrode contact impedance... and the temperature correction factor used for compensation All require recalibration; the operating curve of a capacitive pressure sensor differs from that of a piezoresistive sensor, therefore a specific conversion model is needed to convert the measured capacitance value into a pressure value. Only then can the values ​​be substituted into the quantization formula for the bonding state for calculation.

[0057] Working Process: Although the polydimethylsiloxane substrate, serpentine silver wires, and capacitive pressure sensor bring significantly different mechanical, electrical, and sensing response characteristics compared to Example 1, the core logic of the "sensing-quantization-adjustment-correction" four-in-one algorithm of this application remains unchanged and exhibits strong adaptability. The initial calibration step (S10) ensures that the mathematical model of the algorithm matches the new hardware physical characteristics. During system operation, regardless of the type of sensor, as long as it can provide real-time information on pressure, impedance, and temperature, the algorithm can use it as input and substitute it into the corresponding formulas (such as the fit state quantization formula, impedance compensation formula, etc.) for calculation. The closed-loop feedback correction mechanism (S90, S91) is also effective; it automatically fine-tunes based on the actual performance deviations generated under the new hardware platform. , , By using core coefficients, the system performance converges to the optimal state.

[0058] The intended effect of this embodiment is that it demonstrates that the closed-loop control method of this application can be successfully adapted to flexible electrodes using different materials (such as polydimethylsiloxane and silver) and different sensors (such as capacitive electrodes), as long as the electrode can provide the multidimensional state parameters required by the algorithm. This greatly broadens the scope of protection and application flexibility of this application, allowing developers to select the most suitable electrode material and manufacturing process according to different clinical needs (e.g., scenarios with extreme requirements for flexibility or cost sensitivity) without redesigning the core control algorithm.

[0059] Example 3 This embodiment aims to demonstrate a variant implementation strategy of the closed-loop control method of this application, with extreme low power consumption as the optimization objective. For long-term implantable devices that rely on energy harvesting technology or have extremely limited battery capacity, power consumption is a key factor determining their feasibility. This embodiment significantly reduces the computational load and average power consumption of the system during daily operation by introducing a hierarchical calculation and lookup table mechanism, while fully retaining the core adaptive and self-correcting functions.

[0060] In this embodiment, the hardware structure of the adaptive flexible electrode system, including the flexible electrode 11 and the algorithm control unit 12, can be exactly the same as in Embodiment 1. The main change occurs at the software level executed by the algorithm control unit 12.

[0061] The algorithm flow has been adjusted as follows: the original unified calculation process has been divided into two levels with different frequencies and different computational complexities: Real-time monitoring level (high frequency, low power consumption): This level operates at the highest frequency (e.g., every 7 milliseconds, the same as in Example 1), with the core objective of achieving rapid response to rapid changes such as myocardial beats. However, to minimize power consumption, this level no longer performs complex floating-point multiplication and exponentiation operations to solve the aforementioned series of formulas in real time. Instead, this level performs fast table lookup operations. Specifically, during initialization in step S10, the algorithm control unit 12 generates or loads a two-dimensional or multi-dimensional lookup table in its memory. The "index" of this lookup table is a properly quantized and encoded real-time state parameter, while the "value" is a pre-calculated optimal stimulus parameter. For example, a lookup table can be constructed using quantized fit state coefficients. Quantized and compensated output impedance This is a two-dimensional lookup table with two dimensions. Each cell in the table stores a corresponding set of stimulus parameters {A}. stim , τ stim , f stim In the real-time monitoring loop, after step S20 collects the state parameters, steps S30 and S40 may only perform simplified calculations to obtain quantified values. and As indexes, in step S50, the algorithm control unit 12 directly uses these two indexes to perform a single memory access in this lookup table to instantly obtain the corresponding stimulus parameters without any complex calculations. The power consumption of this process is comparable to that of a simple memory read, far lower than performing multiple floating-point operations.

[0062] Correction computing level (low frequency, high power consumption): Tasks at this level are executed at a very low frequency, such as once every 2 minutes, or are triggered under specific conditions (e.g., when the algorithm control unit 12 detects a continuous period of time). When the average value remains below a preset threshold, such as 0.7, it indicates that the system performance may be drifting. This level will fully execute the complete set of complex calculation processes described in Example 1, including: accurately using the fit state quantification formula, electrode impedance adaptive compensation formula, and stimulation parameter adaptive adjustment formula to calculate the "theoretically" most accurate stimulation parameters based on the current real-time parameters; and executing closed-loop feedback correction steps (S90 and S91), that is, calculating and updating the core adjustment coefficient based on the performance deviation over a period of time. , , The key step is that after the calibration calculation is completed, it does not directly use the calculated stimulus parameters for a single stimulus, but instead uses the calculation results to "refresh" and "update" the aforementioned lookup table. In other words, it recalculates the stimulus parameter values ​​corresponding to some or all entries in the lookup table based on the updated core modulation coefficients, and writes the new values ​​back to the lookup table.

[0063] Operating Process: For the vast majority of the time (e.g., over 99.9%), the system operates in a very low-power "real-time monitoring level," responding to every heartbeat through rapid table lookups, achieving an efficient "cruise mode." This allows the system's average operating power consumption to be kept to an extremely low level. Only when the system's internal closed-loop correction logic determines that performance drift may occur (e.g., electrode aging) will it initiate a high-power "correction calculation level" for a deep "maintenance and calibration." This involves recalculating and updating the lookup table to realign the algorithm model with the changed hardware state. This strategy can be understood as a dual-mode operating mechanism combining "daily cruising" and "periodic calibration," ensuring both economic efficiency in daily operation and long-term accuracy through periodic self-calibration.

[0064] The expected effect of this embodiment is that, compared to Embodiment 1, the average operating power consumption of the system can be further reduced by an order of magnitude, for example, to below 1.5 microamps. This significant power saving greatly extends the battery life of the implanted device and even makes battery-free implantable systems using micro-energy harvesting technologies (such as harvesting energy from heartbeat or body temperature) possible, which is of great significance for improving patients' quality of life and reducing long-term medical costs. At the same time, because the complete closed-loop feedback correction mechanism is retained, the long-term control accuracy and stability of this scheme are not compromised by the introduction of a lookup table.

[0065] Example 4 This embodiment aims to elaborate on a hierarchical safety early warning and emergency response mechanism integrated into the algorithm control unit 12. For Class III medical devices implanted in the human body, safety is the primary consideration, surpassing all performance indicators. This embodiment demonstrates the in-depth design of this application in ensuring patient safety to cope with various foreseeable abnormal situations.

[0066] The hardware structure is the same as in Embodiment 1 or 2. In the algorithm flow, step S70 (security check) and its subsequent processing, which were mentioned in a general sense in Embodiment 1, are refined in this embodiment into a logically rigorous, progressively advancing three-level response system. This system is implemented by a dedicated security monitoring module in the algorithm control unit 12.

[0067] The specific settings for the three-level response system are as follows: Level 1 Warning (Information Prompt and Recording): Triggering Condition: This level is triggered when any monitored status parameter deviates from its optimal operating range but has not yet reached a clearly defined danger boundary. For example, electrode operating temperature. Between 39°C and 40°C (above normal body temperature but below the generally accepted threshold for tissue damage), or with pressure application. Slightly above or below the normal range. Response: To ensure treatment continuity, the system does not immediately change the current stimulation strategy, but the algorithm control unit 12 records an event log in its internal non-volatile memory, detailing the event type, time of occurrence, and the values ​​of various parameters at that time. Simultaneously, it can wirelessly send a low-priority status code to the external control module 20. This allows doctors to review these "sub-health" state events at the next follow-up visit, providing richer information for clinical decision-making.

[0068] Level 2 Warning (Proactive Intervention and High-Priority Alert): Triggering Condition: This level is triggered when any status parameter explicitly exceeds a preset safety threshold for the first time. For example, operating temperature. The temperature first reaches or exceeds 40°C; or the pressure is applied. A voltage exceeding 0.25 Newtons may cause compressive damage to myocardial tissue; or contact resistance A sudden increase in Ω (e.g., >1500Ω) may indicate the formation of air bubbles or localized detachment between the electrode and tissue. Response: The system immediately implements pre-set active interventions to mitigate the risk. This intervention is rapid, automatic, and reversible. For example, once an excessive temperature is detected, the algorithm control unit 12 immediately bypasses the normal adjustment formula and forcibly increases the stimulation amplitude. And / or the pulse width is reduced by 50% to rapidly reduce heat generation. Simultaneously, the system immediately sends a high-priority alarm signal to the external control module 20 via wireless communication to alert medical staff or the patient. At this time, the system does not stop working but instead switches to continuously monitoring the parameter that triggered the alarm at a higher frequency. If the parameter returns to a safe range within a preset time (e.g., 10 seconds), the system automatically deactivates the intervention and returns to normal adaptive adjustment mode.

[0069] Level 3 Protection (Emergency Shutdown and Highest Alarm): Triggering Conditions: This level serves as the final safety barrier for patient protection and is triggered in the most severe circumstances. Triggering conditions include: failure of proactive intervention following a Level 2 warning, i.e., the excessive parameter fails to return to normal within 10 seconds after intervention; or, the system detects an event indicating a catastrophic hardware failure, such as contact impedance. A sharp drop to extremely low values ​​(e.g., <50Ω) strongly suggests a short circuit between the electrode leads; or, the amount of tensile deformation measured by a strain sensor... Exceeding the material's elastic limit (e.g., >35%) indicates that the electrode is about to break or has already broken physically. Response: In this situation, the system's primary task is to ensure patient safety under any fault conditions. The algorithm control unit 12 immediately executes an emergency shutdown procedure, completely cutting off the power to the intermediate frequency electrical stimulation module 13 or setting its output to a high-impedance state, stopping all electrical stimulation output. Simultaneously, it sends a highest-level emergency shutdown alarm to the external control module 20, which may be accompanied by a special code to indicate the type of serious fault that has occurred in the external device. At this point, the implant 10 enters a safe standby mode that maintains only minimal communication and monitoring functions. The device can only be reactivated after an external professional sends an encrypted reset command using a dedicated external device and after a series of security checks.

[0070] Example of working process: Suppose that a patient suddenly develops a high fever, causing a rise in body temperature, which in turn causes the tissue temperature around the flexible electrode 11 to slowly increase. When the algorithm control unit 12 monitors the electrode temperature... When the temperature reaches 39.5°C, the system triggers a Level 1 warning, recording an entry in the log, but stimulation continues as normal. If the patient's body temperature continues to rise, causing the electrode temperature to reach 40.1°C, a Level 2 warning is triggered. The algorithm control unit 12 immediately halve the stimulation energy (e.g., amplitude) and sends a vibration alarm to the external alert device worn by the patient. Due to the reduced stimulation energy and heat generation, the electrode temperature may stabilize. However, if external factors (such as increased inflammation) cause the temperature to continue to spike to 41°C and show no downward trend within 10 seconds, a Level 3 protection mechanism will be activated. The algorithm control unit 12 will decisively cut off all stimulation output and send an emergency shutdown alarm to the hospital's central monitoring system, thereby completely eliminating any possibility of thermal damage to the myocardial tissue.

[0071] The intended effect of this embodiment is that, by establishing such a clear, reliable, and progressively layered safety protection system, the technical solution of this application can achieve the best balance between ensuring absolute patient safety (through emergency shutdown) and maintaining treatment continuity (through proactive intervention). It incorporates a variety of potential physical and electrical risks into its monitoring scope, greatly improving the safety of the product and the reliability of its clinical application, and meeting the most stringent safety requirements for implantable medical devices.

[0072] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0073] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A flexible electrode for an implantable myocardial contraction modulation device, characterized in that, include: The sensing and monitoring layer integrates a contact pressure sensor, an electrode impedance sensor, and a temperature sensor. The algorithm control unit is configured as follows: State parameters are obtained through the sensing and monitoring layer; Based on the state parameters, the parameters of the electrical stimulation signal applied to the flexible electrode are calculated and adjusted using a preset algorithm formula; Based on the adjustment deviation between the preset target physiological parameters and the physiological parameter evaluation values ​​obtained from the state parameters, one or more core adjustment coefficients that serve as weighting factors in the algorithm formula are dynamically adjusted. The methods for calculating and adjusting the parameters of the electrical stimulation signal applied to the flexible electrode using a preset algorithm formula include: Based on the bonding pressure, contact resistance, and operating temperature in the aforementioned state parameters, a bonding state coefficient is calculated to quantify the bonding state. as well as Based on the adhesion state coefficient, at least one of the amplitude, pulse width, and frequency of the electrical stimulation signal is adjusted.

2. The flexible electrode of the implantable myocardial contraction modulation device according to claim 1, characterized in that, The calculation result is obtained by using a preset algorithm formula, and the corresponding electrical stimulation signal parameter is found in a preset lookup table based on the calculation result. The lookup table is updated based on the dynamically adjusted core adjustment coefficient.

3. The flexible electrode of the implantable myocardial contraction modulation device according to claim 1, characterized in that, The algorithm control unit is also configured as follows: When the state parameter exceeds the preset safety threshold, the application of the electrical stimulation signal is stopped.

4. The flexible electrode of the implantable myocardial contraction modulation device according to claim 1, characterized in that, The preset algorithm formula includes: in, Let be the fitting state coefficient at time t. For the pressure to fit at time t, To match the pressure reference value, Let t be the electrode contact impedance deviation. This is the reference value for electrode contact impedance. Let be the electrode temperature deviation at time t. This is the reference value for the electrode operating temperature. Let be the amount of electrode tensile deformation at time t. This is the reference value for tensile deformation.

5. The flexible electrode of the implantable myocardial contraction modulation device according to claim 1, characterized in that, The flexible electrode further includes: The flexible substrate layer forms the flexible support substrate for the entire electrode; An intermediate conductive layer is connected to the flexible substrate layer, and the sensor of the sensing and monitoring layer is embedded between the flexible substrate layer and the intermediate conductive layer, or is located on the same plane as the intermediate conductive layer.

6. The flexible electrode of the implantable myocardial contraction modulation device according to claim 5, characterized in that, The intermediate conductive layer is an interdigitated electrode array structure, which includes multiple pairs of staggered electrode contacts and wires connecting these contacts.

7. The flexible electrode of the implantable myocardial contraction modulation device according to claim 6, characterized in that, The flexible electrode further includes: An insulating protective layer covers the intermediate conductive layer and the sensing and monitoring layer; The interface layer uses a flexible printed circuit to bring out the wires of the intermediate conductive layer and the signal leads of each sensor in the sensing and monitoring layer, and bring them together to a miniature connector.

8. The flexible electrode of the implantable myocardial contraction modulation device according to claim 4, characterized in that, The algorithm control unit is also configured to calculate the impedance compensation amount based on the acquired contact impedance and operating temperature using an adaptive electrode impedance compensation formula. According to the impedance compensation amount Adjust output impedance .

9. The flexible electrode of the implantable myocardial contraction modulation device according to claim 8, characterized in that, The algorithm control unit is also configured to, based on the bonding state coefficient at time t... and output impedance The electrical stimulation signal parameters applied to the intermediate conductive layer are dynamically calculated and adjusted.

10. The flexible electrode of the implantable myocardial contraction modulation device according to claim 4, characterized in that, The algorithm control unit is also configured to execute a correction cycle at a low frequency, the correction cycle being: Assess performance deviations over a period of time, including deviations in fit adjustment, impedance compensation, or stimulation parameter adjustment. Correct and adjust the fit adjustment coefficient, impedance compensation coefficient, and stimulation amplitude adjustment coefficient through closed-loop feedback.

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