Real-time closed-loop brainstem stimulation system and method for alleviating hypertension

Abstract

Provided is a real-time closed-loop brainstem stimulation system for alleviating hypertension, the system comprising: a nucleus tractus solitarius (NTS) stimulation unit attached to a subject and stimulating the subject's NTS with a preset parameter; an NTS activity measurement unit for measuring NTS activity; and a closed-loop control unit for receiving feedback on the NTS activity measured according to the stimulation by the NTS stimulation unit and controlling the parameter of the NTS.

Description

Real-time closed-loop brainstem stimulation system and method for improving hypertension

[0001] The present invention relates to a real-time closed-loop brainstem stimulation system and method for improving hypertension.

[0002] Controlling blood pressure (BP) is crucial for ensuring proper systemic blood circulation, which is a fundamental requirement for the proper functioning of body tissues and organs and, ultimately, for maintaining life. Although BP naturally fluctuates significantly, consistently rising BP levels are considered dangerous and are therefore classified as a chronic disease known as hypertension.

[0003] Hypertension is considered a major health condition due to its widespread prevalence and correlation with serious health outcomes. While medical treatments for hypertension are widely accepted, new therapies must be devised for resistant hypertension that does not respond adequately to existing medications; however, prolonged unmanaged hypertension increases the risk of cardiovascular complications and organ damage.

[0004] Therefore, individuals with resistant hypertension face a particularly serious risk of life-threatening disease, and due to this persistent risk, alternative BP management methods and systems must be developed to overcome current restrictive limitations.

[0005] BP regulation is intricately linked to the nervous system, which continuously monitors and adjusts fluctuating BP levels. In hypertension, elevated BP is often accompanied by sympathetic nervous system imbalance, characterized by heightened sympathetic activity and decreased parasympathetic activity, and is associated with cardiovascular mechanisms. Autonomic nervous system imbalance in uncontrollable high BP suggests the potential to use device-based neurostimulation modalities to treat resistant hypertension.

[0006] Therefore, neuromodulation modalities targeting the vagus nerve and carotid sinus nerve are being explored as a promising solution for resistant hypertension, and previous studies have shown that neuromodulation is an effective medical modality for alleviating autonomic nervous system imbalances (Non-patent Literature 1, 2, 3).

[0007] Therefore, despite these possibilities, neuromodulation requires further development due to its currently limited clinical efficacy, but existing clinical neurostimulation therapies have used open-loop (OL) stimulation without feedback using fixed, pre-set parameters.

[0008] However, OL stimulation can impair the effects of neuromodulation because it cannot process changes in the individual patient's physiological characteristics (Non-patent literature 4, 5).

[0009] In other words, prioritizing a fundamental understanding of physiological mechanisms is essential for continuously tracking the patient's changing physiological state to prevent a decline in therapeutic efficacy, but there are limitations to the currently available OL methods. Therefore, to improve this, it is necessary to develop a real-time closed-loop (CL) stimulation system that is effective for natural BP regulation in a healthy cardiovascular system.

[0010] [Prior Art Literature]

[0011] [Non-patent literature]

[0012] (비특허문헌 1)1. Bisognano JD, Bakris G, Nadim MK, Sanchez L, Kroon AA, Schafer J, et al. Baroreflex activation therapy lowers blood pressure in patients with resistant hypertension: results from the double-blind, randomized, placebo-controlled rheos pivotal trial. Journal of the American College of Cardiology 2011;58(7):765-73.

[0013] (비특허문헌 2)2. Fisher H, Stowell J, Garcia R, Sclocco R, Goldstein J, Napadow V, et al. Acute effects of respiratory-gated auricular vagal afferent nerve stimulation (RAVANS) in the modulation of blood pressure in hypertensive patients. 2018 Computing in Cardiology Conference (CinC). 45. IEEE; 2018:1-4.

[0014] (비특허문헌 3)3. Antonino D, Teixeira AL, Maia-Lopes PM, Souza MC, Sabino-Carvalho JL, Murray AR, et al. Non-invasive vagus nerve stimulation acutely improves spontaneous cardiac baroreflex sensitivity in healthy young men: A randomized placebo-controlled trial. Brain stimulation 2017;10(5):875-81.

[0015] (Non-patent Document 4)4. Price JB, Rusheen AE, Barath AS, Cabrera JMR, Shin H, Chang SY, et al. Clinical applications of neurochemical and electrophysiological measurements for closed-loop neurostimulation. Neurosurgical focus 2020;49(1):E6.

[0016] (Non-patent Document 5) 5. Kobayashi RO, Gogeascoechea A, Tomy LJ, Van Asseldonk E, Sartori M. Neural data-driven model of spinal excitability changes induced by transcutaneous electrical stimulation in spinal cord injury subjects. 2022 International Conference on Rehabilitation Robotics (ICORR). IEEE; 2022:1-6.

[0017] Therefore, the problem that the present invention aims to solve is to provide a real-time closed-loop (CL) stimulation system and method effective for BP regulation.

[0018] To solve the above problem, the present invention provides a real-time closed-loop brainstem stimulation system for improving hypertension, comprising: an NTS stimulation unit attached to a subject to stimulate the subject's NTS (Nucleus tractus solitarius) with preset parameters; an NTS activity measurement unit for measuring said NTS activity; and a closed-loop control unit that receives feedback on the NTS activity measured according to stimulation by said NTS stimulation unit and controls said NTS parameters.

[0019] In one embodiment of the present invention, the NTS stimulating unit electrically stimulates the NTS, and the parameter includes frequency or voltage magnitude or both.

[0020] In one embodiment of the present invention, a real-time closed-loop brainstem stimulation system for improving hypertension of the subject further includes a blood pressure measuring unit for measuring the subject's BP (blood pressure).

[0021] In one embodiment of the present invention, the closed-loop control unit outputs parameters of the NTS using the measured blood pressure and the measured NTS activity as input values.

[0022] In one embodiment of the present invention, the NTS stimulation unit is a linear quadratic Gaussian (LQG) controller.

[0023] In one embodiment of the present invention, the LQG regulator is composed of a linear quadratic integral regulator (LQI) and a Kalman filter.

[0024] In one embodiment of the present invention, the linear quadratic integral regulator (LQI) minimizes the error to reach a target value r using a quadratic cost function of the following equation.

[0025]

[0026] (Here , ui is an initial input to induce a stimulus effect, and

[0027] is the discrete-time equation for the NTS activation rate and the error term for the set point r of the NTS activation rate yt, where Q and R are parameters determining the point at which NTS activity converges to the set point and the magnitude of the stimulus parameter, respectively.

[0028] In one embodiment of the present invention, the closed-loop control unit optimizes the parameters to minimize Q and R.

[0029] In one embodiment of the present invention, the Kalman filter corrects the error between the model and the in vivo experimental conditions using the following formula.

[0030]

[0031] The present invention also provides a real-time closed-loop brainstem stimulation method for improving hypertension, characterized by comprising: a step of electrically stimulating the NTS (Nucleus tractus solitarius) of a subject; a step of measuring the NTS activity; and a step of controlling parameters of the electrical stimulation step after receiving feedback on the measured NTS activity value.

[0032] In one embodiment of the present invention, the NTS activity is associated with the blood pressure of the subject.

[0033] In one embodiment of the present invention, the parameter is frequency or voltage magnitude or both.

[0034] The present invention also provides a hypertension treatment device comprising the stimulation system described above.

[0035] In one embodiment of the present invention, the hypertension treatment device monitors the effect of the hypertension treatment drug by the NTS activity.

[0036] The treatment system according to the present invention can ultimately provide neuromodulatory therapy for resistant hypertension by applying CL stimulation accessible through NTS, and furthermore, provide a new means for a CL stimulation mechanism for BP control, thereby providing a new treatment method for resistant hypertension.

[0037] FIG. 1 is a block diagram of a real-time closed-loop brainstem stimulation system for improving hypertension according to one embodiment of the present invention.

[0038] Figures 1b and 1c are schematic diagrams illustrating the core concepts of the study, including closed-loop stimulation, based on the temporal correlation between NTS activity and BP response.

[0039] Figure 2a is a schematic diagram of a data-based model system for a neuromodulation system.

[0040] Figure 2b is a block diagram of a model-based closed-loop stimulator.

[0041] Figure 3 shows the forward prediction accuracy results for two samples of input-based NTS activity using the O model.

[0042] Figure 4a is a representative result of the normalized activity rate (FR) of NTS for four selected channels (constant parameters of 20 Hz and 200 μA) for OL.

[0043] Figure 4b shows the cumulative NTS activity results for the OL and CL protocols, represented by the curve (normalized FR × time) area.

[0044] Figure 4c shows the performance results of the CL brainstem modulation system in terms of alignment with the NTS FR target (good alignment, Case 1; bad alignment, Case 2, red curve, NTS FR for the CL protocol; blue curve, target level; green curve, frequency input parameters, voltage magnitude, maximum limit, frequency 60 Hz, and voltage magnitude 300 μA).

[0045] Figure 4d is a heatmap of aligned neuron spike signals across all subjects (n = 6) according to the OL and CL protocols during the pre-stimulation period, during stimulation, and post-stimulation period.

[0046] Figure 4e is a representative plot of FR measured in real time (4 channels), which is a plot expressed as a linear combination of information extracted from independent component analysis (ICA) after classifying neuron spikes in NTS (16 channels) excluding noise measured in OL and CL stimulation protocols.

[0047] Figure 4f shows the linear combination results of the linearity of FR measured in real-time (4 channels) and the independent components (IC) of neuron spikes classified in NTS.

[0048] Figure 5a is a representative result of the blood pressure (BP) response to OL (constant parameters of 20 Hz and 200 μA, black curve, average BP response, gray shaded area).

[0049] Figure 5b shows the maximum change in BP for the OL and CL protocols during stimulation.

[0050] Figure 5c shows the average BP change for the OL and CL protocols during the pre-stimulation, stimulation, and post-stimulation periods.

[0051] Figure 5d shows the cumulative BP response (normalized BP response × time) for the OL and CL protocols, expressed as the area under the curve (AUC).

[0052] Figure 5e shows the recovery time of the OL and CL protocols calculated as the time to reach 70% of the AUC.

[0053] Figure 6 is a step diagram of a real-time closed-loop brainstem stimulation method for improving hypertension.

[0054] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0055] Before describing the present invention in detail, terms and words used in this specification should not be interpreted as being unconditionally limited to their ordinary or dictionary meanings, and the inventor of the present invention may appropriately define and use the concepts of various terms to best describe their invention.

[0056] Furthermore, it should be understood that these terms or words should be interpreted in a meaning and concept consistent with the technical spirit of the present invention.

[0057] In other words, the terms used in this specification are used merely to describe preferred embodiments of the invention and are not intended to specifically limit the content of the invention.

[0058] It should be noted that these terms are defined in consideration of the various possibilities of the present invention.

[0059] Additionally, in this specification, singular expressions may include plural expressions unless the context clearly indicates a different meaning.

[0060] In addition, you should be aware that even if it is expressed in the plural, it may contain a singular meaning.

[0061] Throughout this specification, where it is stated that a component "includes" another component, unless specifically stated otherwise, this may mean that it does not exclude any other component but may include any other component.

[0062] Furthermore, in cases where it is stated that a component "exists inside or is installed in connection with" another component, this component may be installed in direct connection with or in contact with the other component.

[0063] In addition, they may be installed spaced apart at a certain distance, and in the case where they are installed spaced apart at a certain distance, there may be a third component or means for fixing or connecting the component to another component.

[0064] Meanwhile, it should be noted that the description of the third component or means mentioned above may be omitted.

[0065] On the other hand, if it is stated that one component is "directly connected" or "directly connected" to another component, it should be understood that there is no third component or means.

[0066] Likewise, other expressions describing the relationship between each component, such as “between” and “right between”, or “adjacent to” and “directly adjacent to”, should be interpreted as having the same intent.

[0067] In addition, terms such as “one side,” “other side,” “one side,” “other side,” “first,” “second,” etc., in this specification are used to ensure that one component can be clearly distinguished from another component.

[0068] However, it should be noted that the meaning of the component is not used restrictively by such terminology.

[0069] In addition, positional terms such as "top," "bottom," "left," and "right" used in this specification should be understood as indicating the relative position of the corresponding component in the drawing.

[0070] Furthermore, unless an absolute location is specified regarding their positions, terms related to these locations should not be understood as referring to absolute locations.

[0071] Furthermore, in the specification of the present invention, terms such as “…part,” “…unit,” “module,” and “device,” if used, refer to a unit capable of handling one or more functions or operations.

[0072] You should be aware that this can be implemented in hardware, software, or a combination of hardware and software.

[0073] In the drawings attached to this specification, the size, location, connection relationships, etc., of each component constituting the present invention may be described in a partially exaggerated, reduced, or omitted manner for the convenience of explanation or to sufficiently clearly convey the concept of the present invention, and therefore, the proportions or scale may not be strictly accurate.

[0074] In addition, in describing the present invention below, detailed descriptions of components that are deemed to unnecessarily obscure the essence of the invention, such as known technologies including prior art, may be omitted.

[0075] In order to solve the aforementioned problem, the present invention focused on the fact that inducing neural excitation in the nucleus tractus solitarius (hereinafter NTS) of the brainstem can have a significant effect on the regulation of BP response.

[0076] This phenomenon is attributed to the neuroanatomical characteristics of the NTS as a central nervous hub that integrates the cardiovascular system and other visceral sensory afferents. The present invention has developed a sophisticated CL system that enhances temporal BP reduction by utilizing the neurophysiological functions obtained from the NTS, which plays a central role in the cardiovascular mechanism.

[0077] In this invention, a CL brainstem neuromodulation system was developed to enhance the antihypertensive effect, and it was discovered that the response can be amplified by regulating NTS activity considering the intuitive association with the BP response. The antihypertensive effect regarding temporal correlation was verified by applying direct NTS stimulation.

[0078] FIG. 1 is a block diagram of a real-time closed-loop brainstem stimulation system for improving hypertension according to one embodiment of the present invention.

[0079] Referring to FIG. 1, the real-time closed-loop brainstem stimulation system according to the present invention comprises, for this purpose, an NTS stimulation unit (100) attached to a subject to stimulate the subject's NTS (Nucleus tractus solitarius) with preset parameters; an NTS activity measurement unit (200) for measuring the NTS activity; and a closed-loop control unit (300) that receives feedback on the NTS activity measured according to stimulation by the NTS stimulation unit and controls the parameters of the NTS.

[0080] In particular, the NTS activity and electrical stimulation parameters (either one or both of frequency and voltage magnitude) of the present invention are configured as a single CL, and the stimulation parameters are controlled according to the activity value to induce the effect of improving hypertension.

[0081] The present invention will be explained in more detail through the following preferred embodiments.

[0082] Examples

[0083] Materials and Methods

[0084] In an embodiment of the present invention, a linear quadratic Gaussian (LQG) modulator was used as the NTS stimulation unit. This is based on a mechanism that considers the relationship between NTS activity and BP response during NTS stimulation, and the system according to the present invention automatically optimized stimulation parameters in real time by monitoring NTS electrophysiological signals (Fig. 1b).

[0085]

[0086] IO (input-output) model

[0087] The present invention used a linear state-space model (LSSM) obtained from a data-based system identification method to explain uncertain stimulus-based NTS dynamics.

[0088] x t+1 = Ax t + Bu t + W t (1)

[0089] y t = Cx t + Du t + v t (2)

[0090]

[0091] Here, xt is the hidden neural state, ut is the stimulation parameter (frequency and voltage magnitude), yt is the NTS firing rate observed in the spike, and wt and vt are the system disturbance and measurement noise, respectively.

[0092]

[0093] LQG controller

[0094] The LQG regulator used in in vivo protocols consists of a linear quadratic integral regulator (LQI) and a Kalman filter. To regulate NTS activity to enhance antihypertensive effects, the inhibitory nature of stimulus-induced activation must be considered. An LQI regulator that minimizes the error in reaching the setpoint r can compensate for depressant effects. The quadratic cost function of the LQI algorithm is expressed as follows.

[0095]

[0096] Here , ui is the initial input to induce the stimulus effect, and z t is a hidden attribute x t and error e t The new state of the system including ufreq and uamp represent the stimulation frequency and stimulation amplitude, respectively.

[0097] , is the discrete-time equation for the NTS activation rate and the error term for the set point r of the NTS activation rate yt.

[0098] Ts is the unit time (1 second), t is an arbitrary time, and k is the time for each step; the error is the sum of operations from 0 to t of (unit time) x (difference in NTS activation rate relative to the set point for each time).

[0099] In addition, Q and R of the cost function are parameters that determine the point at which NTS activity converges to the set point and the magnitude of the stimulus parameter, respectively.

[0100] From the perspective of control theory, optimally setting the parameters can minimize both factors. An important consideration of the present invention is that a control system is required to continuously activate the NTS signal.

[0101] According to results from modeling studies indicating that neural stimulation parameters must be continuously increased to overcome the depressive characteristics of NTS, Q and R settings for a system where stimulation parameters (frequency, voltage magnitude) can be continuously increased during the CL protocol deviate from conventional control perspectives. Therefore, considering the limitations of stimulation system input and maintaining NTS activation, Q and R values ​​were empirically selected where stimulation parameters are expected to increase steadily during the protocol's stimulation time. Optimal input, u t is expressed as follows,

[0102] u t = -Kx t + u i

[0103] Here, K=[Kk Ki], the feedback gain K is the sum of Kk (i.e., the solution of the linear quadratic controller) and Ki (i.e., the solution of the integral term) derived as solutions to the Riccati equation when matrices A and B have full rank (i.e., a controllable system).

[0104] The Kalman filter used to correct the error between the O model and in vivo experimental conditions is expressed as follows.

[0105]

[0106] Here, the Kalman gain matrix L can be derived as a solution to the algebraic Riccati equation when matrices A and C have full rank (i.e., the observable system).

[0107] The invention experimentally determined the Kalman gain L by considering inter-subject variability and in vivo conditions.

[0108] A, B, and C are matrices of the estimated linear state-space model, ut is the input value at t, x^t |t is the state estimate at t based on the information at t, x^t +1 |t is the state estimate for the state at t+1 based on the information at t, and x^t+1 |t+1 is the final state estimate for t+1 reflecting the information at t+1. y t+1 is the output value (fire rate of NTS) measured at t+1.

[0109] animal

[0110] In the embodiments of the present invention, the study was conducted on male Sprague-Dowley rats (age: 8–10 weeks, body weight: 270–320 g) with the approval of the National Institute of Health’s ethical guidelines and the Animal Protection and Use Committee of Pohang University of Science and Technology.

[0111] Surgical procedure

[0112] All rats were anesthetized by inhaling isoflurane (5% O2 flow rate 0.4–0.6 l / min) followed by intraperitoneal injection of urethane (1.4 g / kg and 0.2 g / ml, Sigma-Aldrich). A cannula was inserted into the trachea to prevent respiratory problems caused by saliva. The anesthetic state was maintained for 4–6 hours until the designed experimental protocol was completed. A cannula was inserted into the surgically exposed femoral artery for direct BP measurement (SP-10; Natsume Seisakusho Co., Ltd.). The surgical procedure to expose the brainstem of the rats followed a conventional protocol.

[0113] The rat was fixed to a stereotactic frame for craniotomy near the bregma to insert anchor screws, and positioned to expose the brainstem through a neck incision including the dorsal medulla and inferior rhombohedral fossa for electrode insertion.

[0114]

[0115] Experimental Protocol

[0116] To demonstrate that NTS activation enhances temporal antihypertensive effects, both OL and CL stimulation protocols were performed in a normal mouse model (Fig. 1b, c). In an experiment according to one embodiment of the present invention, a commercial stimulator (IZ-32, 32 channels; Tucker-Davis Technologies-TDT) and a custom bipolar electrode (diameter 150 μm, enamel encapsulated stainless steel; Goodfellow) were inserted at a target location to stimulate a single neuron in the brainstem.

[0117] Three types of stimulation protocols were designed: 1) system identification, 2) OL, and 3) CL protocols.

[0118] Each test consisted of 180 seconds of stimulation, and 10 cycles of 300 seconds of rest were administered to separate rats (n = 6) using the OL and CL protocols.

[0119] The OL protocol provided stimulation with fixed parameters (20 Hz, 200 μA, 100 μs), while the CL protocol had initial parameters (11 Hz, 112 μA, 100 μs) that were adjusted in real time according to the NTS activity rate.

[0120] Both protocols used three 180-second stimulation tests and a 600-second rest period on the same rats (n = 6), and the effects were compared using a 40-minute rest period until the application of the different protocols. During the experiment, the stimulation settings of the two protocols did not affect the respiration of the rats.

[0121]

[0122] BP and NTS Signal Acquisition and Preprocessing

[0123] Arterial BP in rats was measured using Lab-Scribe V3 software by transmitting signals from a femoral artery insertion pressure transducer (BP-102, iWorx) to acquisition hardware (IX-RA-834, iWorx). BP data acquired at 100 samples / s were converted to .mat" format and then processed and analyzed in MathWorks MATLAB R2022b. Mean arterial pressure was derived by applying low-pass (<0.4 Hz) and high-pass (>0.001 Hz) filtering to a 1-second signal window to match the CL stimulation interval.

[0124] The anatomical position for electrode insertion was set with the reference point of the stereotactic coordinates as the obex, representing the distal end of the tibial plane, and the NTS was positioned at depths of 0.5 mm rostral, 0.6 mm lateral, and 0.3 mm to 0.8 mm ventral relative to the reference point. The position of the measurement electrode was determined by observing synchronized neural signals during a short stimulation test that induces a hypertensive effect.

[0125] NTS neural activity was acquired at a sampling rate of 24 kHz using a multichannel probe (A1x16-Poly2s-5mm-50 s-177-A16; NeuroNexus Technologies) and a Tetrode model (Q1x1-tet-10mm-121-HQ4; NeuroNexus Technologies). The experiment was performed in a Faraday cage to block external electrical noise, and the acquired signals were transmitted to a computer via the optical fiber of a digital processor (RZ5; TDT) installed inside the cage.

[0126] Data were converted to the .mat" format using the TDT MATLAB software development kit, and stimulation artifacts were removed with a 3ms adjustment. For spike detection, the signal was bandpass filtered from 300 to 5000 Hz. Spike detection was performed in real-time on 16-channel electrodes in an RPvdEx environment (TDT) using the 4-channel NTS activity used in the CL system.

[0127] Single neuron activities were classified using the open-source Klusta package to extract neuronal activities from NTS while mitigating noise. Stimulation artifacts were first rejected using the same post-processing methods as in the real-time process. Neuronal activations from NTS were analyzed by merging data from OL and CL protocols for clustering and manually excluding noisy and unclear neurons.

[0128]

[0129] Experimental results

[0130] Dynamic characteristics of the IO model

[0131] Dynamic modeling of NTS as a physiological processor for BP control was performed using machine learning. This dynamic model formed the basis of a process model for the real-time CL brainstem neuromodulation system, which relies on the temporal correlation between NTS activity and BP response via sensory afferent stimulation. NTS activity was observed in rats (n = 6) with stochastic input parameters, and the activity rate was calculated from processed NTS data excluding artifacts. The input dataset included binary noise pattern parameters, and the model was refined using machine learning on the IO dataset (60 trials), and its dynamics were evaluated through eigenvalues ​​and quadruple cross-validation.

[0132] For effective model-based CL neuromodulation, the NTS model must accurately capture the dynamics induced by stimulation. To evaluate the dynamic fidelity of the IO model according to the present invention, the prediction accuracy was compared with the actual stimulus-based dynamics. This evaluation was based on the average dynamics of the test set obtained by iteratively averaging the protocol results to reduce the influence of external disturbances and focus on stimulus-based dynamics.

[0133] The evaluation compared the forward prediction output estimating NTS activity from the stochastic input of the IO model with the mean results of the test set considered as actual facts using correlation coefficients. The mean prediction accuracy of the fitted IO model exceeded 95% (mean ± standard deviation (SD), 97 ± 0.85%), as shown in Figure 3.

[0134] Referring to Figure 3, it can be seen that the IO model-based estimate shows 97% accuracy for the Ground truth input-driven dynamic, which is both a measurement and a true value. The Data augmented IO model-based estimate, which added noise to prevent overfitting that lowers the model's generalization performance and reliability, showed 89% accuracy relative to the true value. In other words, the developed IO model was able to effectively predict NTS activities.

[0135] Therefore, the model adequately captured stimulus-based NTS dynamics. To alleviate overfitting and improve CL system functionality considering NTS depression in OL stimuli [25, 30, 33, 35], artificial Gaussian noise was added to the training set for data augmentation.

[0136] The prediction accuracy of the empirically selected IO model (Gaussian noise with σ = 10) was tested in vivo, including conditions where external noise was unknown. The mean prediction accuracy of the data-augmented IO model was valid at 89% (mean ± SD, 89 ± 6.4%). The selected IO model was used as a system model in the CL neuromodulation system for in vivo experiments.

[0137] The dynamic characteristics of the NTS model were evaluated for stability using the eigenvalues ​​of the state transition matrix, which contains all eigenvalues ​​within the unit circle.

[0138] The eigenvalues ​​along the positive real axis exhibited an exponential damping response, while the eigenvalues ​​along the imaginary axis exhibited oscillatory dynamics. The IO model was designated as a system model and exhibited both oscillatory and exponentially damped dynamic characteristics. These dynamic properties of the IO model explained the stimulus-based dynamics of NTS and were consistent with the functions required for accurate brain network prediction and control as proposed in

[0031] .

[0139]

[0140] NTS spike activity for OL and CL protocols with direct NTS stimulation

[0141] To investigate the potential of the proposed CL neurostimulation system based on NTS activity as a BP-related neurological biomarker, a comprehensive analysis of BP and NTS responses during acute stimulation was performed.

[0142] First, NTS activity corresponding to the four channels activated by stimulation was analyzed and selected from 16 measurement channels on the microelectrode. Subsequently, the response of NTS activity to OL and CL stimulation was compared. The average NTS activity, expressed as a normalized activity rate per protocol, was calculated to minimize neurological variation per test (Fig. 4a).

[0143] Referring to FIG. 4a, the closed-loop brainstem stimulation system (CL) according to the present invention was able to elicit higher NTS activity compared to the conventional stimulation system (OL).

[0144] Next, cumulative NTS activity was analyzed by comparing the temporal integration exceeding the offset value of NTS activity at stimulation. Thus, the temporal response of the normalized NTS activity rates of the two protocols was evaluated.

[0145] As a result of the evaluation, the cumulative NTS activity of the CL protocol was 2.3 times greater than that of the OL protocol (mean ± standard error of the mean - SEM: OL, 15.03 ± 2.65 mmHg; CL, 34.37 ± 7.55 mmHg; OL vs. CL, p = 0.021) (Fig. 4b).

[0146] Referring to Fig. 4b, which is identical to the interpretation of Fig. 4a, the closed-loop stimulation system was able to elicit greater activity from NTS.

[0147] The CL protocol with optimized stimulation parameters improved the temporal response in NTS activity. The performance of CL neuromodulation was demonstrated in two cases classified as "good" and "poor" based on the degree of achievement of the target NTS activity level (Fig. 4c).

[0148] CL neuromodulation significantly enhanced NTS neuroactivity, but could not accurately control firing rate to achieve the desired activity level.

[0149] The CL system according to the present invention focused on the neurodynamics of four specific NTS channels rather than 16 available channels, assuming that the selected channel adequately represents the overall neuronal activity.

[0150] The hypothesis was verified by comparing the NTS spike activity of 16 channels processed using a spike alignment algorithm with the NTS spike activity of 4 selected channels.

[0151] The heatmap in Fig. 4d shows the normalized single neuron spike activity of NTS containing 16 channels. To evaluate whether the neural activity of the selected 4 channels captured information on the classified NTS spike activity from the 16-channel data, a linear combination of the independent spike activities of the 16 channels was represented using independent component analysis and is shown in Fig. 4e.

[0152] Referring to FIG. 4e, the four channels used in the present invention contain all the information of neurons measured from 16 channels, which means that the entire data can be sufficiently simulated with a small amount of data. This demonstrates that when implanting the stimulation system into an implantable device, it has a significant advantage in that it consumes less resources, such as computational load.

[0153] The linear combination of NTS spike activity of 4 channels using the extracted independent component (IC) showed a strong correlation with the total activity of 16 channels (R2 = 0.852 and R2 = 0.736) (Fig. 4f).

[0154] Therefore, the NTS activity of the four selected channels adequately explains the complexity of the 16 channels, indicating that the CL system according to the present invention surpasses the conventional OL system in NTS activation.

[0155]

[0156] Antihypertensive effects of OL and CL protocols under direct NTS stimulation

[0157] The average BP over time per stimulation test and protocol was investigated to compare BP changes similar to NTS activity (Fig. 5a). The minimum BP change (δ BP) between the OL protocol and the CL protocol, which quantitatively confirmed the decrease in δ BP, did not differ statistically between the protocols (mean ± SEM: OL, -16.76 ± 3.40 mmHg; CL, -20.03 ± 3.98 mmHg; OL vs. CL, p=0.43) (Fig. 5b).

[0158] Referring to Figure 5b, there was no significant difference in the maximum change in blood pressure.

[0159]

[0160] However, the average δ BP per cycle considering the temporal response (before stimulation, at stimulation, after stimulation, 180 seconds) significantly decreased at stimulation of the CL protocol compared to the changes before and after stimulation, whereas the average BP of the OL protocol did not decrease significantly compared to the changes before and after stimulation (Q2 [Q1~Q3]mmHg,

[0161] CL, 0.36 [-1.39~0.94] at pre-stimulation, -4.123 [-11.11~0.34] at stimulation, -1.13 [-3.44~-0.37] at post-stimulation, CL, -7.80 [-16.66~-4.73] at pre-stimulation, -0.01 [1.53~3.39] at post-stimulation, OL, p=0.13 at pre-stimulation after stimulation, p=0.36; CL, p=0.0095 at pre-stimulation versus 0.0095 at 0.0095 at pre-stimulation after stimulation, p=0.81 at post-stimulation after stimulation, p=0.0027) (Fig. 5c).

[0162] Referring to Figure 5c, the change in blood pressure during the stimulation period compared to before and after stimulation was significant in the CL protocol.

[0163] These results showed that while the reduction in BP was not statistically different between protocols, the temporal antihypertensive effect increased.

[0164] Further analysis of the cumulative response difference of BP change was performed using normalized average BP over time (Fig. 5a). Through the analysis of the cumulative BP response, it was possible to simultaneously consider the quantitative decrease and the temporal response by integrating BP over time until it recovered to the baseline level upon stimulation.

[0165] The cumulative BP response of the CL protocol was 1.8 times greater than that of the OL protocol (mean ± SEM; OL, 37.65 ± 13.17 mmHg; CL, 67.56 ± 12.49 mmHg; OL vs. CL, p = 0.0046) (Fig. 5d).

[0166] Referring to Fig. 5d, the cumulative BP response was significantly higher with the CL protocol. Since the purpose of the system proposed in the present invention is to treat hypertension and continuously and more significantly lower blood pressure, the core blood pressure lowering effect can be enhanced through the introduction of the CL protocol.

[0167] To ignore individual recovery differences, the recovery time of the antihypertensive effect reaching 70% of the cumulative BP response was delayed by 45 seconds for the CL protocol compared to the OL protocol (mean ± SEM; OL, 75.17 ± 24.25 s; CL, 120.33 ± 14.36 s; OL vs. CL, p = 0.012) (Fig. 5e).

[0168] Referring to Figure 5e, the time required for blood pressure recovery was significantly longer with the CL protocol, which supports the hypothesis that the CL protocol can extend the blood pressure lowering effect.

[0169] These results demonstrated that the CL protocol according to the present invention improved the antihypertensive effect by approximately 1.6 times compared to the conventional OL protocol.

[0170]

[0171] Correlation between antihypertensive effect and NTS activity

[0172] In this experiment, to confirm the relationship between NTS activity and BP response during CL stimulation, a linear comparison was attempted to express the BP response using the same method used to compare the relationship between real-time measured NTS activity and the IC of classified neuronal spike activity.

[0173] In particular, the antihypertensive effect was adequately explained by a linear combination of the ICs of classified neuron spikes measured in 16 channels (OL, R2 = 0.818, CL, R2 = 0.822).

[0174] As described above, the present invention provides a novel closed-loop-based system for monitoring and treating resistant hypertension that cannot be effectively managed by existing pharmacological treatments. To this end, the present invention provides a novel stimulation system comprising an NTS stimulating unit for stimulating NTS.

[0175] Furthermore, existing neurostimulation techniques for hypertension management are based on OL stimulation using fixed parameters without feedback to adapt to various physiological conditions. This OL stimulation approach had clinical limitations in explaining between-subject and within-subject variability in physiological status.

[0176] However, the present invention discovered that NTS activity can be used as a biomarker for highly variable BP, particularly OL stimulation, and furthermore, can act as a therapeutic agent for resistant hypertension by stimulating it.

[0177] Furthermore, the antihypertensive effect of the CL stimulation method according to the present invention can serve as a means to evaluate the clinical effect of hypertension management using nerve stimulation.

[0178] The concept of cumulative BP, which quantifies exposure to high BP status, has recently been known as a risk assessment factor for hypertension. The reduction in cumulative BP observed with CL stimulation in the system according to the present invention suggests the possibility of maintaining a longer normal blood pressure state in hypertension management using real-time CL stimulation.

[0179] Therefore, the system according to the present invention can be utilized not only as a therapeutic device but also as an integrated therapeutic device used in conjunction with drugs, etc., rather than replacing existing treatments.

[0180] The BP response appeared as a linear combination of purified NTS activity, confirming the temporal correlation between the two signals for the OL and CL protocols. The consistency of this relationship and the nonlinear model describing the relationship between BP response and NTS activity suggest the potential of a CL neuromodulatory system that can directly utilize the BP signal as a physiological biomarker without the use of NTS activity.

[0181] In the proposed CL system, the target signal for control was the direct activation rate in four selected channels among the signals measured in the NTS. This configuration was made to accommodate limited resources, such as real-time online signal processing using available hardware, but the NTS activity captured in the four channels encompassed complex information on refined single-neuron activity within the NTS classified by spike classification (Fig. 4e).

[0182] That is, despite using a smaller number of channels, the 4-channel NTS activity containing refined single-neuron activity from 16 available channels did not cause technical problems such as information loss.

[0183] Figure 6 is a step diagram of a stimulation method using the system described above.

[0184] Referring to FIG. 6, a stimulation method according to one embodiment of the present invention comprises: a step of electrically stimulating the NTS (Nucleus tractus solitarius) of a subject; a step of measuring the NTS activity; and a step of controlling the parameters of the electrical stimulation step after receiving feedback on the measured NTS activity value, wherein the parameters of the electrical stimulation are amplitude or voltage magnitude, as described above.

[0185] The treatment system and method according to the present invention described above can ultimately provide neuromodulatory therapy for resistant hypertension by applying CL stimulation accessible through NTS, and furthermore, provide a new means for a CL stimulation mechanism for BP control, thereby providing a new treatment method for resistant hypertension.

Claims

1. As a real-time closed-loop brainstem stimulation system for the improvement of hypertension, An NTS stimulator attached to a subject to stimulate the subject's NTS (Nucleus tractus solitarius) with preset parameters; An NTS activity measuring unit for measuring the above NTS activity; and A real-time closed-loop brainstem stimulation system for improving hypertension, comprising a closed-loop control unit that controls parameters of the NTS by receiving feedback on NTS activity measured according to stimulation by the NTS stimulation unit.

2. In Paragraph 1, A real-time closed-loop brainstem stimulation system for improving hypertension, characterized in that the above NTS stimulation unit electrically stimulates the NTS, and the parameters include frequency or voltage magnitude or both.

3. In claim 1, the real-time closed-loop brainstem stimulation system for improving hypertension of the subject comprises: A real-time closed-loop brainstem stimulation system for improving hypertension, characterized by further including a blood pressure measuring unit for measuring the BP (blood pressure) of the subject.

4. In Paragraph 3, A real-time closed-loop brainstem stimulation system for improving hypertension, characterized in that the closed-loop control unit outputs parameters of the NTS using the measured blood pressure and the measured NTS activity as input values.

5. In Paragraph 1, A real-time closed-loop brainstem stimulation system for improving hypertension, characterized in that the above-mentioned NTS stimulation unit is a linear quadratic Gaussian (LQG) modulator.

6. In Paragraph 5, A real-time closed-loop brainstem stimulation system for improving hypertension, characterized in that the above LQG regulator is composed of a linear quadratic integral regulator (LQI) and a Kalman filter.

7. In Paragraph 6, A real-time closed-loop brainstem stimulation system for improving hypertension, wherein the above-described linear quadratic integral regulator (LQI) is characterized by minimizing the error to reach a target value r using a quadratic cost function of the following equation. (Here , ui is an initial input to induce a stimulus effect, and is the discrete-time equation for the NTS activation rate and the error term for the set point r of the NTS activation rate yt, where Q and R are parameters determining the point at which NTS activity converges to the set point and the magnitude of the stimulus parameter, respectively.

8. In Paragraph 7, A real-time closed-loop brainstem stimulation system for improving hypertension, characterized in that the closed-loop control unit optimizes the parameters to minimize Q and R.

9. In Paragraph 6, A real-time closed-loop brainstem stimulation system for improving hypertension, characterized by the above Kalman filter correcting the error between the model and in vivo experimental conditions using the following formula.

10. A real-time closed-loop brainstem stimulation method for improving hypertension using a system according to Paragraph 1, wherein A step of electrically stimulating the subject's NTS (Nucleus tractus solitarius); Step of measuring the above NTS activity; and A real-time closed-loop brainstem stimulation method for improving hypertension, characterized by including a step of controlling parameters of the electrically stimulating step after receiving feedback on the measured NTS activity value.

11. In Paragraph 10, A real-time closed-loop brainstem stimulation method for improving hypertension, characterized in that the above NTS activity is associated with the blood pressure of the subject.

12. In Paragraph 10, A real-time closed-loop brainstem stimulation method for improving hypertension, characterized in that the above parameters are frequency or voltage magnitude or both.

13. A hypertension treatment device comprising a stimulation system according to any one of claims 1 to 9.

14. In Paragraph 13, The above hypertension treatment device is characterized by monitoring the effect of a hypertension treatment drug through the above NTS activity.

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