Method and apparatus for implantable myocardial contractility modulation electrode-myocardial contact evaluation

Abstract

The application provides an implantable myocardial contraction regulation electrode-myocardial contact evaluation method and device, and relates to the technical field of implantable medical devices. The method comprises the following steps: collecting various electrical parameters such as contact impedance and contact voltage; calculating a quantitative index representing the comprehensive quality of contact; comparing the index with a threshold value to grade the contact state; and performing targeted closed-loop calibration according to the grade, including adjusting the electrical stimulation parameters, adjusting the algorithm parameters used to calculate the quantitative index, or reducing the stimulation to a safety value and alarming in the case of serious abnormalities. The application realizes active and accurate management of the contact state through multi-parameter fusion and hierarchical closed-loop control, improves the stimulation effectiveness and safety, and has low power consumption.

Description

Technical Field

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

[0002] Implantable myocardial contractility modulatory (CCM) is an effective treatment for patients with moderate to severe heart failure. Its core principle lies in applying electrical stimulation to myocardial tissue via implanted electrodes to improve myocardial function. The effectiveness and safety of this treatment method highly depend on a stable and good electrical contact between the stimulating electrode and the myocardial tissue. However, the contact state between the electrode and the myocardium is not constant and is affected by various factors, including individual patient physiological differences, fibrotic responses in surrounding tissues after electrode implantation, real-time changes in heart rate or body position, and minute electrode displacement.

[0003] Existing technologies have significant shortcomings in ensuring electrode-myocardial contact quality. First, existing technologies typically rely solely on monitoring a single contact impedance value to roughly determine the contact status. This method cannot fully reflect the complex characteristics of the electrode-myocardial interface, and misjudgments are highly likely when contact voltage or contact stability is abnormal while impedance remains within the normal range. Second, existing technologies lack a real-time quantitative assessment mechanism for contact quality, providing only qualitative conclusions and failing to identify slight, gradual deterioration in contact status, leading to the accumulation of potential risks. More importantly, existing closed-loop stimulation control systems rely heavily on the final effect of stimulation, such as whether a heartbeat was successfully captured, rather than the prerequisite for stimulation, i.e., physical contact quality. This "post-event compensation" logic is passive; by the time ineffective stimulation is detected, poor contact may have already occurred, failing to fundamentally and proactively guarantee effective stimulation delivery. Furthermore, when contact abnormalities are detected, existing devices typically lack automated closed-loop calibration mechanisms, requiring manual intervention from medical personnel, resulting in a significant delay in response. Some solutions employ complex algorithms or add dedicated hardware to improve detection accuracy, but this leads to problems such as high power consumption, increased cost, and larger implant size, making them unsuitable for implantable systems with stringent requirements for power consumption and size. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to provide an electrode-myocardial contact assessment method and device for implantable myocardial contraction regulation.

[0005] An electrode-myocardial contact assessment method for implantable myocardial contraction modulation provided by the present invention includes: Acquire at least two different types of electrical parameters at the interface between the electrode and myocardial tissue; Based on the at least two different types of electrical parameters, a quantitative index characterizing the overall quality of electrode-myocardial electrical contact is calculated. The quantitative indicators are compared with one or more abnormal grading thresholds to determine the level to which the current electrode-myocardial contact state belongs; Depending on the level, different closed-loop calibration operations are performed to adjust the electrical stimulation parameters and / or the algorithm parameters used for subsequent calculation of quantitative indicators.

[0006] Furthermore, the at least two different types of electrical parameters include contact impedance and contact voltage.

[0007] Furthermore, the calculation steps for the quantitative indicator include: Based on the time-varying contact voltage, calculate the contact stability parameters; and The contact impedance, contact voltage, and contact stability parameters are subjected to preset mathematical operations to calculate the quantitative index.

[0008] Furthermore, the quantitative index is calculated by weighted summation of the contact impedance, the contact voltage, and the contact stability parameter.

[0009] Furthermore, the levels include at least a minor abnormal state, a moderate abnormal state, and a severe abnormal state; The closed-loop calibration operation specifically includes the following steps: When the condition is determined to be a slight abnormality, the stimulation parameters of the electrical stimulation applied to the myocardial tissue are adjusted. When the moderate abnormal state is determined, the stimulation parameters are adjusted, and the algorithm parameters used for subsequent calculation of quantitative indicators are adjusted according to the preset adaptive adjustment strategy. When the severe abnormal state is determined, the stimulation parameters are adjusted to a preset safe value and an alarm is triggered.

[0010] Furthermore, the stimulation parameters include stimulation amplitude and / or stimulation pulse width.

[0011] Furthermore, the algorithm parameters include: A set of weighting coefficients used to calculate the quantification index by weighting multiple parameters; and / or The anomaly classification threshold.

[0012] Furthermore, the calculations in the quantization step are performed using 16-bit fixed-point recursive arithmetic.

[0013] According to the present invention, an implantable electrode-myocardial contact assessment device for myocardial contraction regulation includes an electrical contact detection module and a main control MCU. The electrical contact detection module is configured to collect at least two different types of electrical parameters at the interface between the electrode and myocardial tissue. The main control MCU is configured as follows: The electrical parameters are received, and a quantitative index characterizing the overall quality of electrode-myocardial electrical contact is calculated based on the at least two different types of electrical parameters. The quantitative indicators are compared with one or more anomaly grading thresholds to determine the level of the current electrode-myocardial contact state; and Based on the level, a closed-loop calibration instruction is generated to adjust the electrical stimulation parameters and / or the algorithm parameters used for subsequent calculation of quantitative indicators.

[0014] An implantable myocardial contraction modulation device according to the present invention includes the aforementioned implantable myocardial contraction modulation electrode-myocardial contact assessment device.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The detection accuracy and reliability are significantly improved. By integrating multiple parameters such as contact impedance, contact voltage and contact stability, it comprehensively reflects the true state of the electrode-myocardial interface, avoiding the one-sidedness and misjudgment risk of single impedance detection, and can accurately identify slight and instantaneous contact abnormalities.

[0016] By achieving forward-looking and intelligent closed-loop management, this application transforms passive "post-event compensation" into proactive "pre-event assessment and calibration." Based on the quantified contact quality, it classifies and precisely controls the contact, enabling real-time responses to changes in contact status. This fundamentally ensures the effectiveness of stimulation and avoids energy waste and treatment delays caused by ineffective stimulation.

[0017] Clinical safety is greatly improved. In the event of severe abnormal conditions, the system can automatically reduce the stimulation to a safe level and issue an alarm, effectively avoiding the risk of local myocardial damage or arrhythmia caused by excessive electrode contact or displacement.

[0018] With extremely low power consumption and cost, the overall algorithm adopts efficient fixed-point recursive operation with extremely low power consumption, making it perfectly compatible with battery-free wireless power supply and other implantable systems that are extremely sensitive to power consumption. Moreover, the solution completely reuses existing hardware, requiring only software upgrades and no additional hardware costs.

[0019] With broad clinical adaptability, this method can automatically adapt to the physiological differences of different patients and the long-term contact environment changes caused by tissue fibrosis after implantation, thus broadening the scope of application of the device and simplifying clinical management. 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 A schematic diagram of the system architecture of an implantable myocardial contraction modulation device provided in this application embodiment; Figure 2 A flowchart illustrating a method for quantitative assessment and closed-loop calibration of electrode-myocardial contact state provided in an embodiment of this application; Figure 3 This is a timing diagram of the signaling interaction between the implanted unit and the external monitoring unit in the embodiments of this application; Figure 4 This is a schematic diagram of the hierarchical calibration logic provided in the embodiments of 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 provides a basic implementation scheme for an electrode-myocardial contact assessment method and device for electro-implantable myocardial contraction modulation. This scheme aims to achieve accurate and dynamic assessment of the electrode-myocardial tissue contact quality through multi-dimensional signal fusion analysis, and to perform intelligent closed-loop feedback calibration based on the assessment results.

[0023] Please see Figure 1 This figure is a schematic diagram of the system architecture of an implantable myocardial contraction regulation device according to an embodiment of this application. As shown in the figure, the device mainly consists of an in vivo implantable unit 100 implanted in the patient's body and an external monitoring unit 200 held by medical personnel or the patient. The in vivo implantable unit 100 and the external monitoring unit 200 exchange data via a wireless communication link 300, for example, Bluetooth Low Energy technology can be used.

[0024] The implantable unit 100, serving as the execution entity for the method of this application, has a compact structure and integrates multiple functional modules. Specifically, the implantable unit 100 includes a main control MCU 110, an electrical contact detection module 120, a myocardial stimulation module 130, a wireless communication module 140, and electrodes 150. The main control MCU 110 is the control core of the entire implantable unit, responsible for running the core algorithm and coordinating the work of each module. The end of the electrode 150 is designed to directly contact myocardial tissue, serving as both a sensor for collecting bioelectrical signals and an actuator for applying electrical stimulation. The electrical contact detection module 120 is connected to the electrode 150 and is used to measure the electrical characteristics of the interface between the electrode 150 and the myocardial tissue in real time, providing the measurement data to the main control MCU 110. The myocardial stimulation module 130 is also connected to the electrode 150 and, under the instructions of the main control MCU 110, is responsible for generating electrical stimulation pulses with specific parameters (such as amplitude and pulse width) and applying them to the myocardial tissue through the electrode 150. The wireless communication module 140 is responsible for establishing and maintaining the wireless communication link 300 with the external monitoring unit 200 to send device status and alarm information, and to receive commands from the outside. The external monitoring unit 200 is typically a dedicated handheld device or integrated into a monitoring system, equipped with a display interface and user interface, capable of displaying the working status of the implanted unit 100 in real time, quantified contact quality indicators, and alerting the user when an alarm is received.

[0025] It should be noted that in this embodiment, all the above modules can reuse the hardware platform of existing mature myocardial contractility regulation devices. The core innovation of this application lies in a brand-new algorithm running in the main control MCU 110, without adding any additional hardware costs.

[0026] The following will combine Figure 2 The method flow in the embodiments of this application is described. Figure 2 This is a flowchart illustrating a method for quantitative assessment and closed-loop calibration of electrode-myocardial contact status provided in an embodiment of this application. The process is executed periodically by the main control MCU 110, forming a continuously operating closed-loop monitoring and calibration system.

[0027] After the device is implanted and initialized, the main control MCU 110 loads a series of preset or offline calibrated parameters as the basis for algorithm operation. In this embodiment, these parameters can be specifically set as: standard contact resistance Z. std =800Ω, which represents the typical impedance value under ideal contact conditions; standard contact voltage U std =50mV, which represents the typical interface voltage under ideal contact conditions; weighting coefficient K Z =0.4, K U =0.35, K S=0.25, representing the relative importance of contact impedance, contact voltage, and contact stability in the comprehensive quantitative evaluation; anomaly classification threshold Q th1 =6, Q th2 =4, Q th3 =2, used to classify the quantified contact quality into different levels; and standard initial stimulation parameters, such as standard stimulation amplitude A0=3V, standard stimulation pulse width P0=20ms.

[0028] After the process begins, step S101 is executed to acquire signals. In this step, the main control MCU 110 controls the electrical contact detection module 120 to synchronously acquire at least two different types of electrical parameters at the current time t through the electrode 150. As a preferred implementation, these two electrical parameters are the contact impedance signal Z. con (t) and contact voltage signal U con (t). It is understandable that contact impedance reflects the degree of obstruction of the current path between the electrode and the tissue, while contact voltage reflects the electrochemical characteristics such as polarization at the interface. Combining both can provide a more comprehensive characterization of the contact interface state than a single parameter. The acquisition frequency can be set to 100Hz to ensure that rapid changes in the contact state caused by physiological activities such as heartbeat and respiration can be captured.

[0029] Subsequently, in step S102, the acquired raw signal is preprocessed. Since the signal directly acquired from electrode 150 may contain noise and artifacts, filtering is required to improve the accuracy of subsequent calculations. This embodiment employs a computationally efficient second-order recursive filtering algorithm suitable for operation on resource-constrained MCUs. For example, for the contact impedance signal, its filtered value Z... con,fil (t) can be calculated using the following formula:

[0030] Among them, Z con (t) is the currently acquired raw impedance value, Z con,fil (t-1) and Z con,fil (t-2) represents the filtered value at the first two time points. Correspondingly, for the contact voltage signal, its filtered value U... con,fil (t) can be calculated using a similar recursive formula, for example:

[0031] It should be noted that these filter coefficients (such as 0.5, 0.3, 0.2, etc.) can be adjusted and optimized according to the actual signal characteristics.

[0032] Next, the process executes step S103, which is the core step. This step aims to integrate multiple dimensions of electrical information into a single, quantifiable index Q(t) that directly reflects the overall quality of the current electrode-myocardial electrical contact. This calculation process consists of two steps: First, an innovative contact stability parameter S is calculated. con (t). This parameter characterizes the fluctuations in contact status over a short period of time, and is particularly important for identifying transient poor contact caused by changes in body position or minute electrode slippage. Its calculation formula is:

[0033] The physical meaning of this formula is that the smaller the change in the filtered contact voltage between the two consecutive moments, the better S... con The closer the value of (t) is to 1, the more stable the contact; conversely, the greater the voltage fluctuation, the less stable the contact. con The smaller the value of (t), the less unstable the contact. The U in the denominator... std Used for normalization.

[0034] Then, the filtered contact impedance Z con,fil (t), contact voltage U con,fil (t) and contact stability parameter S con We perform weighted fusion on (t) to calculate the final quantitative index Q(t). The weighting formula is as follows:

[0035] In this formula, the first term represents the degree of deviation between the current impedance and the standard impedance; the smaller the deviation, the greater the contribution of this term. The second term represents the ratio of the current contact voltage to the standard voltage; the larger the ratio (within a reasonable range), the greater the contribution. The third term directly uses the contact stability parameter. By weighted summing these three terms, Q(t) can comprehensively and holistically reflect the contact quality.

[0036] After obtaining the quantitative index Q(t), a classification judgment is performed in step S104. The main control MCU 110 compares the calculated Q(t) with the preset anomaly classification threshold Q. th1 =6, Q th2 =4, Q th3 =2 for comparison. If Q(t) ≥ Q th1 (For example, if Q(t) ≥ 6), it is judged as "good state", indicating that the current electrode contact quality is ideal, and no intervention is required. The process directly returns to the signal acquisition step S101 to continue the next round of monitoring. If Q th2 ≤ Q(t) th1 (For example, if 4 ≤ Q(t) < 6), it is determined to be a "minor abnormal state", and the system will trigger the minor abnormality calibration step S105. If Q th3 ​≤ Q(t) th2 (For example, if 2 ≤ Q(t) < 4), then it is determined to be a "moderate abnormal state," and the system will trigger the moderate abnormality calibration step S106. If Q(t) th3 (For example, if Q(t) < 2), it is determined to be a "serious abnormal state", and the system will trigger the serious abnormality handling and alarm step S107.

[0037] After completing the corresponding calibration steps (S105 or S106), the process returns to the signal acquisition step S101, forming a closed loop. For the severe anomaly handling step S107, in addition to performing safety operations, it may be necessary to wait for external intervention, so the process may be paused or enter a special monitoring mode.

[0038] Please see Figure 3 The diagram illustrates the signaling interaction between the implanted unit 100 and the external monitoring unit 200. During normal operation, the implanted unit 100 periodically (e.g., every minute or hour) sends "status information" containing the current quantized value Q(t) and device status to the external monitoring unit 200 via the wireless communication module 140, enabling routine, non-invasive follow-up by healthcare personnel. However, if a serious abnormality is detected in step S107, the implanted unit 100 immediately sends a high-priority "high-level alarm" signal to the external monitoring unit 200, which then alerts the user with sound, vibration, or a prominent visual cue, ensuring timely attention to the emergency. Furthermore, the external monitoring unit 200 can also proactively send "parameter query / setting instructions" to the implanted unit 100; for example, a doctor can adjust thresholds or weighting coefficients based on the patient's condition.

[0039] This embodiment constructs a complete prospective assessment and closed-loop calibration system through the above structure and process. It can monitor the electrode-myocardial contact status in real time and quantitatively, and adopt different response strategies according to the severity of the problem, thereby improving safety while ensuring treatment effectiveness. Experimental data show that using this method, the contact status identification accuracy can be improved to over 99.5%, and the abnormal calibration response time is less than 5 milliseconds.

[0040] Example 2 This embodiment focuses on how the method proposed in this application achieves ultra-low power operation through optimized computation to meet the stringent power consumption requirements of implantable devices powered wirelessly or with long-life batteries. The core of this method lies in the fact that all computational steps are performed using 16-bit fixed-point recursive operations.

[0041] ​​In implantable medical devices, power consumption is one of the key design constraints. Traditional complex algorithms based on floating-point operations consume significant computing resources and electrical energy, making them unsuitable for resource-constrained microcontrollers like the MCU 110. The method in this embodiment fully considers this factor from the initial algorithm design stage.

[0042] To achieve ultra-low power consumption, this embodiment deeply optimizes the algorithm implementation. On one hand, the floating-point numbers and floating-point operations involved in Embodiment 1 are equivalently converted into fixed-point operations and efficient bitwise operations. For example, in signal preprocessing step S102, the filtering formula Z... con,fil (t) = 0.5 Z con Multiplication in (t) + ... 0.5, at the hardware level, can be implemented as an efficient right shift of an integer by one bit, rather than performing floating-point multiplication. For other coefficients that are not powers of 2, such as... 0.4 can be approximated as (x 4) / 10. Here... 4 can be achieved through two left shifts, while division / 10 can be implemented using a lookup table or a more complex fixed-point division algorithm, with overall overhead far less than directly calling the hardware floating-point arithmetic unit. In 16-bit fixed-point representation, a variable can be defined, for example, with the high 8 bits representing the integer part and the low 8 bits representing the fractional part. All addition, subtraction, multiplication, and division operations are performed in this fixed-point format, completely avoiding dependence on floating-point arithmetic hardware.

[0043] On the other hand, the algorithm itself has a "recursive" characteristic. Whether it's the signal filtering formula or the contact stability calculation, the calculation at the current moment only depends on the current acquired value and the calculated results from the previous one or two moments. This means that the main control MCU 110 does not need to allocate a large buffer in memory to store long-term historical data, thus significantly saving memory resources and corresponding power consumption.

[0044] Meanwhile, the operating mode of the main control MCU 110 has also been optimized. The MCU does not run at high speed continuously, but instead employs an "on-demand wake-up" strategy. Most of the time, the main control MCU 110 is in deep sleep or low-power mode. It is only woken up by a timer or external interrupt during specific time windows of each cardiac cycle (e.g., the absolute refractory period of the ventricle, when myocardial electrical activity is most stable and suitable for measurement). After waking up, the MCU quickly executes a complete "acquisition-preprocessing-quantization-judgment-calibration" process. Because all calculations are efficient fixed-point operations, the entire process takes a very short time, typically within a few milliseconds (e.g., a complete calculation takes less than 3 milliseconds). After the task is completed, the main control MCU 110 immediately returns to low-power sleep mode, waiting for the next cycle.

[0045] By combining fixed-point arithmetic, recursive algorithms, and on-demand wake-up strategies, this embodiment successfully controls the average power consumption of the entire algorithm to an extremely low level. Experimental tests show that its average power consumption can be as low as below 2.5μA, which is more than 60% lower than the traditional floating-point arithmetic scheme (power consumption is usually above 7μA). This significant low-power characteristic makes the method proposed in this application well-suited for next-generation implantable systems that employ wireless energy harvesting and have no built-in battery, or for extending the lifespan of existing battery-equipped systems by several years, thus possessing significant clinical application value and commercial prospects.

[0046] Example 3 This embodiment will elaborate on one of the core innovations of this application, namely, the intelligent hierarchical calibration logic. This logic embodies the idea of ​​adopting different levels and strategies to address problems based on their severity, thereby achieving an optimal balance between treatment effectiveness and patient safety. Please refer to... Figure 4 The diagram clearly illustrates this hierarchical calibration logic in the form of a functional block diagram.

[0047] like Figure 4 As shown, the core of this logic is a decision module, whose input is the quantized value Q(t) of the contact state calculated in real time. The decision module compares Q(t) with multiple preset thresholds (Q... th1 Q th2 Q th3 The values ​​are compared, and different calibration strategies are output based on the interval in which Q(t) is located.

[0048] Scenario A: Minor anomaly calibration (corresponding to) Figure 2 Step S105 and Figure 4 Output A in When the decision module determines that Qth2 ≤ Q(t)<Qth1 (for example, at a certain time t, the calculated Q(t) =7.0, which is greater than or equal to the threshold value 4 but less than the threshold value 6), the system determines it as a "slight abnormal state". This situation usually corresponds to some instantaneous, non-fundamental contact fluctuations, such as tiny gap changes between the electrode 150 and the myocardial tissue caused by the patient taking a deep breath or a slight posture change. At this time, the basic contact condition is good, and the problem is not serious. Correspondingly, the calibration strategy adopted by the system is "adjust stimulation parameters only". This is a compensatory strategy, which aims to overcome minor poor contact by temporarily increasing the stimulation energy without changing the basic working mode of the system, so as to ensure the effectiveness of the current myocardial stimulation. Specifically, the main control MCU 110 will moderately increase the amplitude A(t) and / or pulse width P(t) of the electrical stimulation output by the next myocardial stimulation module 130 according to the degree of abnormality. For example, the adjustment of the stimulation amplitude can follow the following formula:

[0049] where A0 is the standard stimulation amplitude, and α is a small gain coefficient (for example, 0.5). For Q(t)=7.0, the new stimulation amplitude will be about 6.25% higher than the standard value. This fine adjustment ensures that the stimulation energy can be effectively transmitted even if there is a tiny gap, and at the same time, since the increase is not large, no safety risk will be brought. In this scenario, the algorithm parameters used to calculate Q(t) (such as the weight coefficient K Z , K U , K S ) remain unchanged.

[0050] Scenario B: Moderate abnormality calibration (corresponding to Figure 2 step S106 in and Figure 4 output B in) When the decision module determines that Qth3 ≤ Q(t)<Qth2 (for example, the calculated Q(t) = 5.2, which is between 2 and 4), the system determines it as a "moderate abnormal state". This state may represent a more persistent, structural change in the contact environment, for example, a thin layer of fibrous tissue capsule begins to form around the electrode after implantation, resulting in drift of the baseline impedance and voltage characteristics of the electrode-myocardium interface. At this time, if the stimulation parameters are simply compensated as in the case of slight abnormality, the effect may be poor and only treat the symptoms rather than the root cause. To this end, the system adopts a "composite" calibration strategy, that is, the combination of "adjusting algorithm parameters" and "adjusting stimulation parameters". First, adjust the stimulation parameters. The adjustment range at this time will be larger than that in the case of slight abnormality, so as to overcome the more significant signal transmission obstacle. For example, a formula similar to that in scenario A can be used, but a larger gain coefficient β (for example, 1.2) is adopted. Assume the abnormality quantification value E con,abn (t) = ((Qstd - Q(t)) / Q std ) 10 = ((8 - 5.2) / 8) 10 =3.5, then the new stimulation amplitude and pulse width can be calculated as:

[0051]

[0052] More critically, the system will perform adaptive adjustment to modify the algorithm parameters used for subsequent calculation of Q(t). For example, the main control MCU 110 will dynamically adjust the weight coefficient according to a preset adaptive strategy. If the system determines that impedance change is the main factor, it may increase K Z the weight of, for example: K Z (t) = K Z (t-1) 1.2 = 0.4 1.2 = 0.48, and adjust other weights correspondingly to keep the sum unchanged or adjust proportionally. This adjustment of algorithm parameters is equivalent to enabling the algorithm to "learn" and "adapt" to the new contact environment baseline, so that it can work more sensitively and accurately on the new baseline in subsequent monitoring, which reflects the deep intelligence of the solution of the present application.

[0053] Scenario C: Severe Abnormality Handling (corresponding to Figure 2 step S107 in and Figure 4 output C in) When the decision module determines that Q(t)<Qth3 (for example, the calculated Q(t) = 1.8, which is much lower than the threshold 2), the system determines it as a "severe abnormal state". This situation most likely means that a major physical failure has occurred, for example, the electrode 150 has completely fallen off the myocardial tissue, or the electrode is completely wrapped by thick fibrous tissue, resulting in the failure of effective current transmission. In this case, continuing to increase the stimulation intensity is not only ineffective, but also potentially dangerous, which may cause current to concentrate at a certain point, resulting in tissue damage or triggering malignant arrhythmia. Therefore, the system adopts a "degradation and alarm" strategy that puts safety first. The main control MCU 110 will immediately perform the following operations: First, stop all compensatory behaviors of increasing stimulation parameters, and instead forcibly adjust the stimulation parameters to a preset, absolutely safe safety value, for example, reduce the stimulation amplitude to 50% of the standard value (A(t) = 0.5 A0) or lower, even completely turn off the stimulation output; second, through the wireless communication module 140, immediately send a highest priority "high-level alarm" signal to the in-vitro monitoring unit 200 (refer to Figure 3The system will display an error code indicating a serious contact malfunction. Upon receiving this signal, the external monitoring unit 200 will alert the patient and doctor in the strongest possible way (such as a continuous beeping and flashing red light), indicating that immediate manual examination and intervention are required.

[0054] Through this sophisticated three-level calibration logic, the proposed solution can not only detect abnormalities but also determine their severity, thereby enabling the most reasonable and safest response and achieving a good balance between treatment effectiveness and patient safety. Clinical data show that this mechanism can reduce the incidence of arrhythmias caused by poor contact to below 0.05%.

[0055] Example 4 This embodiment aims to illustrate the advantages of the method proposed in this application in engineering implementation, namely, how to seamlessly integrate it into existing or standard myocardial contraction regulation devices through pure software upgrades without increasing any hardware costs.

[0056] See again Figure 1 The system architecture diagram is shown below. A typical hardware platform for an implantable myocardial contraction modulation unit 100 usually includes all the physical components required to implement the method described in this application. Specifically: Main control MCU 110: Typically, a low-power microcontroller with certain computing power is selected, such as the STM32L4 series based on the ARM Cortex-M4 core. This type of MCU is fully capable of performing the 16-bit fixed-point arithmetic described in Embodiment 2. Electrical contact detection module 120: Existing myocardial contraction modulation devices integrate analog front-end circuits capable of measuring impedance and voltage, including precision excitation sources and analog-to-digital converters, to monitor basic lead impedance. The method of this application can directly reuse this module to obtain the raw data of contact impedance and contact voltage. Myocardial stimulation module 130: This is the core functional module of the myocardial contraction modulation device, containing a digital-to-analog converter and a high-voltage drive circuit for generating precise and controllable stimulation pulses. The calibration logic of this application is achieved by outputting different digital setpoints (control amplitude and pulse width) to this module. Wireless communication module 140: Existing implantable devices generally come standard with low-power wireless communication chips, such as Bluetooth Low Energy chips, to achieve postoperative programming and data transmission. The alarm and status reporting functions of this application can be directly implemented using this module.

[0057] The implementation process of this application is essentially a firmware development and upgrade process. The algorithm described in this application, which includes a series of steps such as acquisition, preprocessing, quantization, judgment, and calibration, is written into a high-efficiency software module and programmed into the flash memory inside the main control MCU 110 as part of the firmware. For equipment manufacturers, this means that they do not need to make any changes to the already finalized hardware design and production line.

[0058] During device operation, the operating system inside the main control MCU 110 (which may be a lightweight real-time operating system or a simple task scheduler) manages and schedules multiple concurrent tasks to achieve coordinated operation of various functions. A typical work cycle may be as follows: 1. A high-priority task triggered by a timer (which can be considered the software-driven part of the electrical contact detection module 120) is awakened. This task configures and starts the analog-to-digital converter, samples the voltage and current on the electrode 150, calculates the original contact impedance and contact voltage values, and stores these original data in a shared memory area. 2. The scheduler then calls the core algorithm task of this application. This task reads the original data from the shared memory and strictly follows the... Figure 2 The execution flow is as follows: a signal preprocessing subroutine is called, followed by a subroutine to calculate the quantization value Q(t), and finally a grading and calibration logic subroutine. 3. The output of the algorithm task is a set of updated stimulation parameters (new amplitude A(t) and pulse width P(t)) and possible algorithm parameters (new weighting coefficients). These new parameters are written to another shared memory area specifically for stimulation control. 4. When the stimulation moment of the next cardiac cycle arrives, a stimulation-driven task synchronized with the ECG (which can be considered the software-driven part of the myocardial stimulation module 130) is activated. This task reads the latest stimulation parameters from the shared memory and sets up the digital-to-analog converter and drive circuit accordingly to generate and output precise electrical pulses. 5. Simultaneously, a lower-priority communication task runs in the background. It periodically reads the latest quantization value Q(t) and device status from the shared memory and packages them for transmission to the external monitoring unit 200 via the wireless communication module 140. When a serious anomaly occurs, the core algorithm task sets an emergency alarm flag; upon detecting this flag, the communication task immediately constructs and sends a high-level alarm.

[0059] Through this hardware-software co-design, the method of this application, acting as an "intelligent brain," is seamlessly integrated into the existing hardware "body," enabling it to possess proactive perception and adaptive capabilities. This purely software-based implementation demonstrates the strong engineering practicality, economy, and scalability of the technical solution presented in this application. Manufacturers can easily add a high-value-added core function to existing product lines or provide a powerful technological selling point for new products, thereby helping to lower the barriers to technological innovation and the costs of market promotion.

[0060] 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.

[0061] 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 method for assessing electrode-myocardial contact in implantable myocardial contraction modulation, characterized in that, include: Acquire at least two different types of electrical parameters at the interface between the electrode and myocardial tissue; Based on the at least two different types of electrical parameters, a quantitative index characterizing the overall quality of electrode-myocardial electrical contact is calculated. The quantitative indicators are compared with one or more abnormal grading thresholds to determine the level to which the current electrode-myocardial contact state belongs; Depending on the level, different closed-loop calibration operations are performed to adjust the electrical stimulation parameters and / or the algorithm parameters used for subsequent calculation of quantitative indicators.

2. The method for assessing implantable myocardial contraction modulation electrode-myocardial contact according to claim 1, characterized in that, The at least two different types of electrical parameters include contact impedance and contact voltage.

3. The method for assessing electrode-myocardial contact in implantable myocardial contraction modulation according to claim 2, characterized in that, The calculation steps for the quantitative indicator include: Based on the time-varying contact voltage, calculate the contact stability parameters; and The contact impedance, contact voltage, and contact stability parameters are subjected to preset mathematical operations to calculate the quantitative index.

4. The method for assessing electrode-myocardial contact in implantable myocardial contraction modulation according to claim 3, characterized in that, The quantitative index is calculated by weighted summation of the contact impedance, the contact voltage, and the contact stability parameter.

5. The method for assessing electrode-myocardial contact in implantable myocardial contraction modulation according to claim 1, characterized in that, The levels include at least minor abnormality, moderate abnormality, and severe abnormality. The closed-loop calibration operation specifically includes the following steps: When the condition is determined to be a slight abnormality, the stimulation parameters of the electrical stimulation applied to the myocardial tissue are adjusted. When the moderate abnormal state is determined, the stimulation parameters are adjusted, and the algorithm parameters used for subsequent calculation of quantitative indicators are adjusted according to the preset adaptive adjustment strategy. When the severe abnormal state is determined, the stimulation parameters are adjusted to a preset safe value and an alarm is triggered.

6. The method for assessing electrode-myocardial contact in implantable myocardial contraction modulation according to claim 5, characterized in that, The stimulation parameters include stimulation amplitude and / or stimulation pulse width.

7. The method for assessing electrode-myocardial contact in implantable myocardial contraction modulation according to claim 5, characterized in that, The algorithm parameters include: A set of weighting coefficients used to calculate the quantification index by weighting multiple parameters; and / or The anomaly classification threshold.

8. The method for assessing electrode-myocardial contact in implantable myocardial contraction modulation according to claim 3, characterized in that, The calculations in the quantization step are performed using 16-bit fixed-point recursive arithmetic.

9. An implantable electrode-myocardial contact assessment device for myocardial contraction modulation, characterized in that, Electrical contact detection module, main control MCU; The electrical contact detection module is configured to collect at least two different types of electrical parameters at the interface between the electrode and myocardial tissue. The main control MCU is configured as follows: The electrical parameters are received, and a quantitative index characterizing the overall quality of electrode-myocardial electrical contact is calculated based on the at least two different types of electrical parameters. The quantitative indicators are compared with one or more abnormal grading thresholds to determine the level to which the current electrode-myocardial contact state belongs; as well as Based on the level, a closed-loop calibration instruction is generated to adjust the electrical stimulation parameters and / or the algorithm parameters used for subsequent calculation of quantitative indicators.

10. An implantable myocardial contraction modulation device, characterized in that, Includes the implantable myocardial contraction modulation electrode-myocardial contact assessment device as described in claim 9.

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