Multi-disease compatible closed-loop regulation system for real-time adjustment of electrical stimulation scheme based on neural markers

Abstract

The present application relates to a kind of multi-disease compatibility closed-loop control system based on neural marker real-time adjustment electric stimulation scheme, wherein the system includes: training module, for obtaining the individualized intervention threshold of each user;And intervention module, connected with the training module, for obtaining each individualized intervention threshold, it is carried out real-time online closed-loop intervention processing, the intervention module specifically includes paradigm presentation unit, electroencephalogram data acquisition unit, electroencephalogram real-time processing unit and electric stimulator control unit.This multi-disease compatibility closed-loop control system based on neural marker real-time adjustment electric stimulation scheme of the present application can be in the intervention process, for the signal needing to continuously monitor, carry out online data processing, and real-time adjustment including time, parameter etc. in need of stimulation scheme, to ensure optimal effect, it is expected to improve the diagnosis and treatment efficiency of clinical neurology, mental illness.

Description

Technical Field

[0001] This invention relates to the field of neuromodulation technology, specifically to a multi-disease compatible closed-loop modulation system based on real-time adjustment of electrical stimulation protocols using neural markers. Background Technology

[0002] Neuromodulation refers to the use of various methods to adjust the activity of the nervous system in order to improve a patient's symptoms or quality of life. This includes brain stimulation techniques (such as deep brain stimulation and transcranial magnetic stimulation), neurofeedback (such as electroencephalography feedback), and pharmacological treatments. Neuromodulation can be used to treat a variety of neurological and psychiatric disorders, including Parkinson's disease, depression, and epilepsy.

[0003] Closed-loop neuromodulation is a special form of neuromodulation that involves monitoring a patient's physiological or neural signals and then adjusting treatment parameters in real time based on these signals. This real-time feedback system allows for personalized treatment, adjusted according to the patient's current state. Typically, achieving closed-loop neuromodulation requires the following steps:

[0004] 1) Signal acquisition: Collecting data related to the physiological or neural signals that need to be regulated, such as electroencephalograms (EEGs), magnetoencephalograms (MEGs), and biofeedback signals. This is usually acquired using existing specialized equipment for recording neural and physiological signals.

[0005] 2) Signal Processing: The collected signals are processed and analyzed to extract useful information. Different diseases have different regulatory targets and monitoring characteristics. Numerous studies have explored the neurological markers of different neurological and mental diseases (e.g., depression, de Aguiar Neto et al., 2019; obsessive-compulsive disorder, Takagi et al., 2017; autism, Frye et al., 2019, etc.), thus providing a theoretical basis for closed-loop regulation.

[0006] 3) Feedback System: Closed-loop control also requires a real-time feedback system to adjust treatment parameters in real time based on signal analysis results. Currently, some patents have been used to design relevant feedback systems for specific scenarios and diseases (e.g., Parkinson's disease, CN202110551731.5; stroke, CN201710610541.X, etc.). However, there is still no feedback system compatible with multiple diseases.

[0007] 4) Intervention Stimulation: Based on the output of the feedback system, corresponding intervention stimulation is implemented. This is usually done through existing specialized stimulation equipment such as electrical, magnetic, sound, and light stimulation devices.

[0008] During closed-loop regulation and intervention, it is necessary to continuously monitor signals, perform online data processing, and adjust the stimulus program, including time and parameters, in real time as needed to ensure the best results.

[0009] Existing closed-loop modulation intervention technologies all have technical shortcomings that urgently need optimization in the four aspects mentioned above, especially the lack of multi-disease compatible technical solutions in real-time signal processing and feedback system logic architecture. Current basic research has provided some understanding of neural biomarkers and potential intervention targets for many diseases. There is significant commonality in the algorithms for feature extraction of EEG biomarkers, and the electrical stimulation parameter space can be shared. Therefore, by constructing a multi-disease compatible technical solution, the common aspects across diseases in electrical stimulation-based closed-loop interventions can be extracted. Developing a multi-disease compatible closed-loop modulation system based on real-time adjustment of electrical stimulation protocols using neural biomarkers can promote more efficient, personalized, precise, and dynamic closed-loop neuromodulation research, and is expected to improve the efficiency of clinical diagnosis and treatment of neurological and psychiatric diseases. Summary of the Invention

[0010] The purpose of this invention is to overcome the shortcomings of the prior art and provide a multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation schemes using neural markers.

[0011] To achieve the above objectives, the multi-disease compatible closed-loop modulation system of the present invention, based on real-time adjustment of electrical stimulation protocols using neural markers, is as follows:

[0012] This multi-disease compatible closed-loop modulation system based on real-time adjustment of electrical stimulation protocols using neural markers is characterized by the following:

[0013] The training module is used to obtain the individualized intervention threshold for each user; and

[0014] The intervention module, connected to the training module, is used to perform real-time online closed-loop intervention processing on each individualized intervention threshold obtained.

[0015] Preferably, the training module specifically performs the following processing:

[0016] The cognitive behavioral paradigm that can induce specific neural markers is presented by the paradigm presentation unit. After the presentation is completed, the algorithm is called to perform offline analysis of the EEG data during the task and extract the target neural markers according to the established algorithm logic, so as to calculate the intervention threshold.

[0017] Preferably, the intervention module specifically includes:

[0018] The paradigm presentation unit is used to present cognitive behavioral paradigms that can induce specific neural markers based on the characteristics of the target disease, and to output event labels to specific EEG channels through data communication protocols, and to present the paradigm process online by adjusting the input of intervention stimulation commands from the received real-time EEG processing unit.

[0019] Preferably, the paradigm presentation unit presents the paradigm of evoked neural markers on a trial-by-trial basis. At the end of the trial, it sends event tags to the external EEG amplifier via a network communication protocol. During the trial interval, it continuously reads the intervention stimulation instructions issued by the real-time EEG processing unit through the network communication interface. Depending on whether stimulation is provided, different visual cues are presented on the display.

[0020] Preferably, the intervention module specifically includes:

[0021] The EEG data acquisition unit is connected to the paradigm presentation unit and interfaces with an external EEG amplifier. It is used to capture specific event tags from the real-time data stream of the EEG amplifier through a data communication protocol, thereby intercepting target data packets online.

[0022] Especially, the specific event label mentioned above is:

[0023] A real-time EEG data packet of size (number of EEG leads + 1) × number of data points is obtained from the real-time data stream of the EEG amplifier. The corresponding event tag is parsed from the last lead, and the maximum value in the current data packet is found. If there is a valid event tag, the data corresponding to the time period of the corresponding task obtained from the paradigm presentation unit is extracted from the data packet.

[0024] Preferably, the real-time EEG processing unit is connected to the paradigm presentation unit and the EEG data acquisition unit, and is used to extract target neural markers according to predetermined algorithm logic, make corresponding logical judgments by comparing with the intervention threshold obtained by the training module, and output intervention stimulation commands to the electrostimulator control unit and the paradigm presentation unit.

[0025] Preferably, the real-time EEG processing unit performs the following processing: it analyzes the single-trial data based on the offline algorithm for extracting neural markers, and compares it with the intervention threshold obtained by the training module. It then performs logical processing based on whether the target neural marker is positively or negatively correlated with the symptoms, and generates corresponding stimulation schemes and related parameters.

[0026] Preferably, the logical processing is as follows:

[0027] If the correlation is positive, no stimulation is performed if the value of the neural marker calculated in a single trial does not exceed the threshold. If the value of the neural marker calculated in a single trial exceeds the threshold, the stimulation frequency band is the frequency band where the neural marker is located, and the stimulation phase is out of phase.

[0028] If the correlation is negative, no stimulation is performed when the value of the neural marker calculated in a single trial exceeds the threshold. When the value of the neural marker calculated in a single trial is lower than the threshold, the stimulation frequency band is the frequency band where the neural marker is located, and the stimulation phase is in phase. If the stimulation target is different from the neural marker acquisition site, the stimulation frequency band is a low-frequency modulation band, and the stimulation intensity is preset according to the intervention needs and individual acceptability.

[0029] Preferably, the electrostimulator control unit is connected to the real-time EEG processing unit and interfaces with an external electrostimulator. When receiving an intervention stimulation command from the real-time EEG processing unit via a data communication protocol, the control unit transmits information on whether to initiate stimulation and the relevant parameters of the stimulation protocol to the electrostimulator, thereby initiating stimulation.

[0030] The multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation schemes using neural markers, as described in this invention, can perform online data processing on signals that require continuous monitoring during the intervention process, and adjust the stimulation scheme, including time and parameters, in real time as needed to ensure optimal results. This provides a personalized, precise, and dynamic intervention method, which is expected to improve the efficiency of clinical diagnosis and treatment of neurological and psychiatric diseases. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the overall structure of the multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation schemes using neural markers, as per the present invention.

[0032] Figure 2 This is a schematic diagram of the intervention module of the multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation protocols using neural markers, as described in this invention.

[0033] Figure 3 This is a schematic diagram illustrating the output logic of event tags and EEG real-time processing unit stimulation state commands in the paradigm presentation unit of this invention.

[0034] Figure 4 This is a schematic diagram of online screenshotting of the target data packet in practical application of the multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation schemes using neural markers according to the present invention. Detailed Implementation

[0035] To more clearly describe the technical content of the present invention, the following description is provided in conjunction with specific embodiments.

[0036] Before describing the embodiments of the present invention in detail, it should be noted that, in the following, the terms “comprising,” “including,” or any other variations are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0037] This technical solution is based on the user's existing clear target neural markers, neural marker induction paradigms, and offline algorithms for neural marker extraction, and performs closed-loop control of electrical stimulation.

[0038] Please see Figure 1 As shown, this multi-disease compatible closed-loop modulation system based on real-time adjustment of electrical stimulation protocols using neural markers includes:

[0039] The training module is used to obtain the individualized intervention threshold for each user; and

[0040] The intervention module, connected to the training module, is used to perform real-time online closed-loop intervention processing on each individualized intervention threshold obtained.

[0041] In a preferred embodiment of the present invention, the training module specifically performs the following processing:

[0042] The cognitive behavioral paradigm that can induce specific neural markers is presented by the paradigm presentation unit. After the presentation is completed, the algorithm is called to perform offline analysis of the EEG data during the task and extract the target neural markers according to the established algorithm logic, so as to calculate the intervention threshold.

[0043] It should be noted that the offline processing algorithm, threshold calculation logic, and stimulation-inducing paradigm mentioned above are all peripheral aspects of the closed-loop control system of this technical solution. In other words, they are prerequisites for entering this system for control and management. They are prior information that users need to prepare before calling the closed-loop control system. They are not the core points of this technical solution. The core of this technical solution is to be compatible with various application scenarios, that is, to be able to generate personalized electrical stimulation programs through this closed-loop control system in different application scenarios.

[0044] In a preferred embodiment of the present invention, the intervention module specifically includes:

[0045] The paradigm presentation unit is used to present cognitive behavioral paradigms that can induce specific neural markers based on the characteristics of the target disease, and to output event labels to specific EEG channels through data communication protocols, and to present the paradigm process online by adjusting the input of intervention stimulation commands from the received real-time EEG processing unit.

[0046] In practical applications, the paradigm presentation unit can present cognitive behavioral paradigms (including but not limited to cue reaction paradigms) that can induce specific neural markers based on the characteristics of the target disease, and is compatible with visual, auditory and other paradigm modalities. In addition, it outputs event tags to specific EEG channels through data communication protocols, and adjusts the presentation of paradigm processes online according to the intervention stimulus commands output by the received EEG processing real-time processing unit.

[0047] The process control mentioned above refers to, for example, Figure 3 As shown, the paradigm presentation unit presents the paradigm for eliciting neural markers on a trial-by-trial basis. At the end of each trial, it sends event tags (such as codes for the number of trials, '1', '2', etc., which can be compatible with different coding logics, such as '100', '200', etc., depending on the paradigm design requirements) to an external EEG amplifier via a network communication protocol. During the trial intervals, it continuously reads the intervention stimulation commands issued by the real-time EEG processing unit through the network communication port. Depending on whether stimulation is received, the paradigm presentation unit presents different visual cues on the display.

[0048] In a preferred embodiment of the present invention, the paradigm presentation unit presents the paradigm of induced neural markers in units of trials. At the end of the trial, the unit sends event tags to the external EEG amplifier via a network communication protocol. During the trial interval, the unit continuously reads the intervention stimulation instructions issued by the real-time EEG processing unit through the network communication interface. Depending on whether stimulation is performed, different visual cues are presented on the display.

[0049] In a preferred embodiment of the present invention, the intervention module specifically includes:

[0050] The EEG data acquisition unit is connected to the paradigm presentation unit and interfaces with an external EEG amplifier. It is used to capture specific event tags (generally the event tag with the largest value in the event tag lead in the current data stream, i.e., the most recent trial) from the real-time data stream of the EEG amplifier through a data communication protocol, thereby intercepting target data packets online.

[0051] In a preferred embodiment of the present invention, the specific event tag is specifically:

[0052] A real-time EEG data packet of size (number of EEG leads + 1) × number of data points is obtained from the real-time data stream of the EEG amplifier. The corresponding event tag is parsed from the last lead, and the maximum value in the current data packet is found. If there is a valid event tag, the data corresponding to the time period of the corresponding task obtained from the paradigm presentation unit is extracted from the data packet.

[0053] Please see Figure 4As shown, in practical applications, the EEG data acquisition unit interfaces with an external EEG amplifier and captures specific event tags from the real-time data stream of the EEG amplifier via a data communication protocol, thereby intercepting target data packets online. The EEG data acquisition unit obtains real-time EEG data packets of size (number of EEG leads + 1) × number of data points from the real-time data stream of the EEG amplifier via the data communication protocol. It parses event tags from the last lead, finds the maximum value in the current data packet, and if a valid event tag is found, extracts data from the data packet corresponding to the time period of the task in the paradigm.

[0054] In a preferred embodiment of the present invention, the real-time EEG processing unit is connected to the paradigm presentation unit and the EEG data acquisition unit, and is used to extract target neural markers according to a predetermined algorithm logic, make corresponding logical judgments by comparing the intervention threshold obtained by the training module, and output intervention stimulation commands to the electrostimulator control unit and the paradigm presentation unit.

[0055] In a preferred embodiment of the present invention, the real-time EEG processing unit specifically performs the following processing: it analyzes the single-trial data according to the offline algorithm for extracting neural markers, and compares it with the intervention threshold obtained by the training module, and performs logical processing according to whether the target neural marker is positively or negatively correlated with the symptoms, and generates the corresponding stimulation scheme and related parameters.

[0056] In a preferred embodiment of the present invention, the logic processing specifically includes:

[0057] If the correlation is positive, no stimulation is performed if the value of the neural marker calculated in a single trial does not exceed the threshold. If the value of the neural marker calculated in a single trial exceeds the threshold, the stimulation frequency band is the frequency band where the neural marker is located, and the stimulation phase is out of phase.

[0058] If the correlation is negative, no stimulation is performed when the value of the neural marker calculated in a single trial exceeds the threshold. When the value of the neural marker calculated in a single trial is lower than the threshold, the stimulation frequency band is the frequency band where the neural marker is located, and the stimulation phase is in phase. If the stimulation target is different from the neural marker acquisition site, the stimulation frequency band is a low-frequency modulation band, and the stimulation intensity is preset according to the intervention needs and individual acceptability.

[0059] In practical applications, it is understandable that the processing logic mentioned above applies to multiple disease application environments.

[0060] In practical applications, the real-time EEG processing unit extracts target neural markers according to a predetermined algorithm. By comparing this with the intervention threshold obtained from the training module, it performs logical judgment and outputs intervention stimulation commands to the electrostimulator control unit and the paradigm presentation unit. The algorithm logic analyzes single-trial data based on an offline neural marker extraction algorithm. When comparing with the intervention threshold obtained from the training module, stimulation protocols and related parameters are generated according to whether the target neural marker is positively or negatively correlated with the symptoms. If positively correlated, no stimulation is performed if the neural marker value calculated in a single trial does not exceed the threshold; if the neural marker value exceeds the threshold, the stimulation frequency band is the same as the neural marker's frequency band, and the stimulation phase is out of phase. If negatively correlated, no stimulation is performed if the neural marker value exceeds the threshold; if the neural marker value is below the threshold, the stimulation frequency band is the same as the neural marker's frequency band, and the stimulation phase is in phase. If the stimulation target point differs from the neural marker acquisition site, the stimulation frequency band is a low-frequency modulation band. The stimulation intensity is preset based on intervention needs and individual acceptability, and the total current does not exceed the safe range of 2mA.

[0061] In a preferred embodiment of the present invention, the electrostimulator control unit is connected to the real-time EEG processing unit and interfaces with an external electrostimulator. When receiving an intervention stimulation command from the real-time EEG processing unit via a data communication protocol, the control unit transmits information on whether to initiate stimulation and the relevant parameters of the stimulation protocol to the electrostimulator, thereby initiating stimulation.

[0062] In one specific embodiment of the present invention, the training module presents cognitive behavioral paradigms that can induce specific neural markers through a paradigm presentation unit. After presentation, an algorithm is invoked to perform offline analysis of the EEG data during the task, extracting the target neural markers according to the predetermined algorithm logic, and calculating the intervention threshold. Taking emotional problems as an example, if the neural response under neutral conditions is x, and the neural response under the current emotional condition is y, the intervention threshold can be set as: mean(x) + 3 × std(y - x). The algorithm for neural markers and the setting criteria for the intervention threshold can be adjusted according to the specific needs of the user.

[0063] The intervention module includes: a paradigm presentation unit, an EEG data acquisition unit, an EEG real-time processing unit, and an electrical stimulator control unit. Figure 2 (As shown). The paradigm presentation unit is mainly responsible for presenting the neural marker evoked paradigm, transmitting event tags to the EEG data acquisition unit, and controlling the presentation progress of the evoked paradigm based on the stimulus instructions returned by the real-time EEG processing unit. For example... Figure 3As shown, in this invention, event tags are adjusted according to the paradigm progress. The EEG data acquisition unit obtains a real-time EEG data packet of size (number of EEG leads + 1) × number of data points from the real-time data stream of the EEG amplifier via a data communication protocol. Event tags are parsed from the last lead to find the maximum value in the current data packet. If a valid event tag is found, data corresponding to the time period of the task in the paradigm is extracted from the data packet. After receiving a valid data segment, the EEG real-time processing unit extracts the target neural markers according to a predetermined algorithm, compares them with the intervention threshold obtained from the training module, performs logical judgment, and outputs an intervention stimulation command to the electrostimulator control unit and the paradigm presentation unit. When there is no intervention stimulation command, a specific identifier is output to the paradigm presentation unit to prompt continued paradigm progress. When the EEG data acquisition unit captures the paradigm progress end event tag output by the paradigm presentation unit, all units finish their work, completing one closed-loop control intervention.

[0064] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0065] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution device.

[0066] In the description of this specification, references to terms such as "an embodiment," "some embodiments," "example," "specific example," or "embodiment," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0067] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

[0068] The multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation schemes using neural markers, as described in this invention, can perform online data processing on signals that require continuous monitoring during the intervention process, and adjust the stimulation scheme, including time and parameters, in real time as needed to ensure optimal results. This provides a personalized, precise, and dynamic intervention method, which is expected to improve the efficiency of clinical diagnosis and treatment of neurological and psychiatric diseases.

[0069] In this specification, the invention has been described with reference to specific embodiments thereof. However, it will be apparent that various modifications and variations can be made without departing from the spirit and scope of the invention. Therefore, the specification and drawings should be considered illustrative rather than restrictive.

Claims

1. A multi-disease compatible closed-loop control system for real-time adjustment of electrical stimulation protocols based on neural markers, characterized in that, The system includes: The training module is used to obtain the individualized intervention threshold for each user; and The intervention module, connected to the training module, is used to perform real-time online closed-loop intervention processing on each individualized intervention threshold obtained. The intervention module specifically includes: The paradigm presentation unit is used to present cognitive behavioral paradigms that can induce specific neural markers based on the characteristics of the target disease, and to output event labels to specific EEG channels through data communication protocols, and to present the paradigm process online by adjusting the intervention stimulus commands output by the received EEG real-time processing unit. The EEG data acquisition unit is connected to the paradigm presentation unit and interfaces with an external EEG amplifier. It is used to capture specific event tags from the real-time data stream of the EEG amplifier through a data communication protocol, thereby intercepting target data packets online. The real-time EEG processing unit is connected to the paradigm presentation unit and the EEG data acquisition unit. It is used to analyze the single-trial data according to the offline algorithm for extracting neural markers. When comparing the data with the intervention threshold obtained by the training module, it performs logical processing according to whether the target neural marker is positively or negatively correlated with the symptoms, and generates the corresponding stimulation plan and related parameters to the electrostimulator control unit and the paradigm presentation unit. The specific logical processing is as follows: If the correlation is positive, no stimulation is performed if the value of the neural marker calculated in a single trial does not exceed the threshold. If the value of the neural marker calculated in a single trial exceeds the threshold, the stimulation frequency band is the frequency band where the neural marker is located, and the stimulation phase is out of phase. If the correlation is negative, no stimulation is performed when the value of the neural marker calculated in a single trial exceeds the threshold. When the value of the neural marker calculated in a single trial is lower than the threshold, the stimulation frequency band is the frequency band where the neural marker is located, and the stimulation phase is in phase. If the stimulation target is different from the neural marker acquisition site, the stimulation frequency band is a low-frequency modulation band, and the stimulation intensity is preset according to the intervention needs and individual acceptability.

2. The multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation protocols using neural markers according to claim 1, characterized in that, The training module specifically performs the following processing: The cognitive behavioral paradigm that can induce specific neural markers is presented by the paradigm presentation unit. After the presentation is completed, the algorithm is called to perform offline analysis of the EEG data during the task and extract the target neural markers according to the established algorithm logic, so as to calculate the intervention threshold.

3. The multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation protocols using neural markers according to claim 1, characterized in that, The paradigm presentation unit presents the paradigm of evoked neural markers in trial units. At the end of the trial, it sends event tags to the external EEG amplifier via a network communication protocol. During the trial interval, it continuously reads the intervention stimulation instructions issued by the real-time EEG processing unit through the network communication interface and presents different visual cues on the display depending on whether stimulation is provided.

4. The multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation protocols using neural markers according to claim 1, characterized in that, The specific event tags mentioned are: A real-time EEG data packet of size (number of EEG leads + 1) × number of data points is obtained from the real-time data stream of the EEG amplifier. The corresponding event tag is parsed from the last lead, and the maximum value in the current data packet is found. If there is a valid event tag, the data corresponding to the time period of the corresponding task obtained from the paradigm presentation unit is extracted from the data packet.

5. The multi-disease compatible closed-loop control system based on real-time adjustment of electrical stimulation protocols using neural markers according to claim 1, characterized in that, The electrostimulator control unit is connected to the real-time EEG processing unit and interfaces with an external electrostimulator. When it receives an intervention stimulation command from the real-time EEG processing unit, it transmits the information on whether to start stimulation and the relevant parameters of the stimulation plan to the electrostimulator via a data communication protocol, thereby initiating stimulation.

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