Electrical stimulation control device and electrical stimulation system

Abstract

The present application provides a method for generating stimulation parameters, an electrical stimulation control device and an electrical stimulation system. After receiving an electroencephalogram signal, the electroencephalogram signal is decomposed to obtain a first sub-signal and a second sub-signal. Then, the first sub-signal is analyzed to obtain an essential frequency sequence. And, the second sub-signal is converted into a Boolean signal. After that, the essential frequency sequence and the Boolean signal are outputted as a set of stimulation parameters to a stimulator, so that the stimulator generates a stimulation signal.

Description

Technical Field

[0001] This invention relates to the control of neurological diseases, and more particularly to a method for generating stimulation parameters, an electrical stimulation control device, and an electrical stimulation system. Background Technology

[0002] Epilepsy is the most common syndrome of chronic neurological disorders, affecting approximately 60 million people worldwide. Nearly 30% of these individuals cannot achieve effective seizure control with current antiepileptic drugs and require non-pharmacological supportive treatments. While epilepsy surgery is effective, some patients are not suitable candidates for brain resection and can only opt for neuromodulation surgery to reduce severe seizures. Both traditional epilepsy surgery and newer neuromodulation surgeries require precise analysis and interpretation of seizure-related brain waves to pinpoint the affected brain region or allow the implanted neuromodulation device to determine the seizure time.

[0003] Based on pathophysiological characteristics and brain wave signal features, epileptic seizures can be broadly divided into several phases: interictal, preictal, irregular phase, and bursting phase. The latter three phases constitute the ictal phase of the epileptic seizure. Recent studies indicate that delivering corresponding electrical stimulation signals at specific phases significantly impacts the effectiveness of neuromodulation. However, recent research also suggests that stimulation is not equally effective across different seizure phases. Prolonged electrical stimulation increases patient tolerance, thus gradually reducing its effectiveness. Furthermore, electrical stimulation is energy-intensive. Therefore, determining the appropriate electrical stimulation after detecting a seizure and identifying a specific phase remains a significant challenge for current intelligent neurostimulators. Summary of the Invention

[0004] The present invention relates to a method for generating stimulation parameters, an electrical stimulation control device, and an electrical stimulation system, which can generate corresponding stimulation parameters in response to received brainwave signals.

[0005] The method for generating stimulation parameters according to the present invention includes: acquiring brainwave signals; decomposing the brainwave signals to obtain a first sub-signal and a second sub-signal, wherein the frequency of the first sub-signal is higher than the frequency of the second sub-signal; analyzing the first sub-signal to obtain an intrinsic frequency series, the intrinsic frequency series including at least one frequency component; converting the second sub-signal into a Boolean signal; and outputting the intrinsic frequency series and the Boolean signal as a set of stimulation parameters to a stimulator, causing the stimulator to generate a stimulation signal.

[0006] In one embodiment of the present invention, the steps of decomposing the brainwave signal to obtain the first sub-signal and the second sub-signal include: using Empirical Mode Decomposition (EMD) to decompose the brainwave signal into the first sub-signal and the second sub-signal.

[0007] In one embodiment of the present invention, the step of analyzing the first sub-signal to obtain the essential frequency sequence includes: performing a spectrum analysis algorithm on the first sub-signal to obtain the essential frequency sequence, wherein the spectrum analysis algorithm is one of the Fourier transform algorithm, wavelet transform algorithm, and normalized Hilbert transform algorithm.

[0008] In one embodiment of the present invention, the step of converting the second sub-signal into a Boolean signal includes: performing a binarization operation on the second sub-signal to obtain a Boolean signal.

[0009] In one embodiment of the present invention, the above-mentioned binarization calculation includes: calculating the dominant frequency of the second sub-signal; and generating a Boolean signal based on the dominant frequency.

[0010] In one embodiment of the present invention, the method for generating stimulation parameters further includes: receiving a brainwave signal and a sequence number corresponding to the brainwave signal, and recording the sequence number in a designated sequence of a parameter table. After obtaining the essential frequency sequence and the Boolean signal, the frequencies of the essential frequency sequence and the Boolean signal are recorded as a set of stimulation parameters in the parameter table at the position corresponding to the sequence number.

[0011] In one embodiment of the present invention, after recording the essential frequency sequence and the frequency of the Boolean signal as a set of stimulation parameters in the parameter table at the position corresponding to the serial number, the method further includes: inputting a set of stimulation parameters recorded in the parameter table into the stimulator in sequence based on the specified sequence to generate a stimulation signal.

[0012] The electrostimulation control device of the present invention includes: a signal acquisition circuit configured to acquire brainwave signals; a processor coupled to the signal acquisition circuit and configured to: decompose the brainwave signals to obtain a first sub-signal and a second sub-signal, wherein the frequency of the first sub-signal is higher than the frequency of the second sub-signal; analyze the first sub-signal to obtain an essential frequency sequence, the essential frequency sequence including at least one frequency component; and convert the second sub-signal into a Boolean signal; and a storage device coupled to the processor and configured to store the essential frequency sequence and the Boolean signal; wherein the processor transmits the essential frequency sequence and the Boolean signal to a stimulator, such that the stimulator generates a stimulation signal based on the essential frequency sequence and the Boolean signal.

[0013] The electrostimulation system of the present invention includes: a signal acquisition circuit configured to receive brainwave signals; a processor coupled to the signal acquisition circuit and configured to: decompose the brainwave signals to obtain a first sub-signal and a second sub-signal, wherein the frequency of the first sub-signal is higher than the frequency of the second sub-signal; analyze the first sub-signal to obtain an essential frequency sequence, the essential frequency sequence including at least one frequency component; and convert the second sub-signal into a Boolean signal; a storage device coupled to the processor and configured to store the essential frequency sequence and the Boolean signal; and a stimulator coupled to the processor and configured to: receive the essential frequency sequence and the Boolean signal, and generate a stimulation signal based on the essential frequency sequence and the Boolean signal.

[0014] Based on the above, the present invention can generate corresponding stimulation parameters for the intrinsic frequency of brainwave signals. Attached Figure Description

[0015] Figure 1 This is a block diagram of an electrical stimulation control device according to an embodiment of the present invention;

[0016] Figure 2 This is a flowchart of a method for generating a stimulus signal according to an embodiment of the present invention;

[0017] Figure 3 This is a block diagram of an electrical stimulation system according to an embodiment of the present invention.

[0018] Explanation of reference numerals in the attached figures

[0019] 100: Electrical stimulation control device

[0020] 110: Signal Acquisition Circuit

[0021] 120: Processor

[0022] 130: Storage device

[0023] 201: Disassembly Module

[0024] 203: Reconstruction Module

[0025] 205: Spectrum Analysis Module

[0026] 207: Stimulation Parameter Table

[0027] 300: Electrical Stimulation System

[0028] 310: Stimulator

[0029] X(t): Brainwave signal

[0030] C1: First sub-signal

[0031] C2: Second sub-signal

[0032] D: Boolean signal

[0033] E: Essential frequency sequence

[0034] F: Stimulus signal

[0035] S205~S225: Steps in the method of generating stimulus signals Detailed Implementation

[0036] Figure 1 This is a block diagram of an electrical stimulation control device according to an embodiment of the present invention. Please refer to... Figure 1 The electrical stimulation control device 100 includes at least a signal acquisition circuit 110, a processor 120, and a storage device 130. The processor 120 is coupled to the signal acquisition circuit 110 and the storage device 130. The electrical stimulation control device 100 can be a device with computing capabilities, such as a desktop computer, a laptop computer, or a smartphone.

[0037] The signal acquisition circuit 110 can be implemented by an integrated circuit or a microchip. Here, the brainwave signal received by the signal acquisition circuit 110 can be a signal of a specific phase, such as a signal of the bursting phase. For example, a detector (not shown) can be used to first identify the brain nerve signals of a specific phase (e.g., the bursting phase) during an epileptic seizure in the brainwave signal, and then transmit the brain nerve signals to the electrical stimulation control device 100.

[0038] Generally, the computational steps of brainwave signal processing algorithms mainly include: feature extraction and classification. After spike detection, the detection results are converted into interpretations of epileptic seizures. The acquired features are then input into a judgment model for classification. The judgment model generally needs to be trained before it can be used, and methods include artificial neural networks, support vector machines, linear classification models, fuzzy logic models, and autolearning systems.

[0039] The processor 120 may be, for example, a central processing unit (CPU), a physical processing unit (PPU), a programmable microprocessor, an embedded control chip, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), or other similar devices.

[0040] Storage device 130 may be, for example, any type of fixed or removable random access memory (RAM), read-only memory (ROM), flash memory, hard disk, or other similar device or combination thereof. Storage device 130 stores a plurality of code segments, which, after being installed, are executed by processor 120 to implement the method for generating stimulus parameters described later.

[0041] Figure 2 This is a flowchart of a method for generating stimulus parameters according to an embodiment of the present invention. See below for further details. Figure 1 and Figure 2 Let's explain. In step S205, the signal acquisition circuit 110 acquires the brainwave signal. Next, in step S210, the processor 120 decomposes the brainwave signal to obtain a first sub-signal and a second sub-signal. Here, the frequency of the first sub-signal is higher than the frequency of the second sub-signal. For example, Empirical Mode Decomposition (EMD) can be used to decompose the brainwave signal into the first and second sub-signals. The first sub-signal is, for example, the main frequency signal.

[0042] Next, in step S215, processor 120 analyzes the first sub-signal to obtain an intrinsic frequency series. The intrinsic frequency series includes at least one frequency component. Then, in step S220, processor 120 converts the second sub-signal into a Boolean signal. Here, binarization is performed on the second sub-signal to obtain a Boolean signal, which is then used as a switching signal.

[0043] In step S225, the processor 120 outputs the essential frequency sequence and Boolean signal as a set of stimulation parameters to the stimulator, causing the stimulator to generate a stimulation signal. For example, after obtaining the essential frequency sequence and Boolean signal, the processor 120 records the frequencies of the essential frequency sequence and Boolean signal as a set of stimulation parameters in the parameter table of the storage device 130. Then, the stimulation parameters are sequentially output from the parameter table to the stimulator.

[0044] Let's take another example to illustrate the electrical stimulation system. Figure 3 This is a block diagram of an electrical stimulation system according to an embodiment of the present invention. Please refer to... Figure 3 The electrical stimulation system 300 includes an electrical stimulation control device 100 and a stimulator 310. In this embodiment, the electrical stimulation control device 100 includes a disassembly module 201, a reconstruction module 203, and a spectrum analysis module 205. The processor 120 executes the disassembly module 201, reconstruction module 203, and spectrum analysis module 205 to obtain stimulation parameters from the brainwave signal X(t). Here, the disassembly module 201 and spectrum analysis module 205 can, through calculation, generate corresponding electrical stimulation parameters for the essential frequency of the brainwave signal X(t). The reconstruction module 203 can access the corresponding stimulation activation and deactivation for specific stage states. That is, the reconstruction module 203 serves as the activation device for stimulation control.

[0045] The signal acquisition circuit 110 receives the brainwave signal X(t) and the corresponding sequence number "NO.1". The signal acquisition circuit 110 transmits the brainwave signal X(t) to the disassembly module 201 and records the sequence number "NO.1" in the specified sequence of the stimulation parameter table 207.

[0046] After receiving the brainwave signal X(t), the decomposition module 201 performs non-steady-state decomposition on the brainwave signal X(t) to obtain a first sub-signal C1 and a second sub-signal C2. The first sub-signal C1 is transmitted to the spectrum analysis module 205, and the second sub-signal C2 is transmitted to the reconstruction module 203. The spectrum analysis module 205 performs a spectrum analysis algorithm on the first sub-signal C1 to obtain the essential frequency sequence E. The spectrum analysis algorithm is one of the Fourier transform algorithm, wavelet transform algorithm, and normalized Hilbert transform algorithm. The essential frequency sequence E includes at least one frequency component. In this embodiment, the essential frequency sequence E includes two frequency components, namely 421Hz and 180Hz. Then, the two frequency components included in the essential frequency sequence E are output to the position corresponding to the sequence number "NO.1" in the stimulation parameter table 207.

[0047] The reconstruction module 203 performs a binarization operation on the second sub-signal C2 to obtain the Boolean signal D. For example, the reconstruction module 203 calculates the dominant frequency of the second sub-signal C2 and then generates the Boolean signal D based on the dominant frequency. This is merely an example and is not a limitation; any binarization operation that can convert the second sub-signal C2 into the Boolean signal D can be used. Here, the Boolean signal D is used as a switch signal. Assuming the dominant frequency of the second sub-signal C2 is 8Hz, a Boolean signal D with 8 cycles per second is generated, with each cycle including two Boolean values ​​(true and false). Here, the reconstruction module 203 acts as a stimulus control initiation device, generating the Boolean signal D as a switch signal. Then, the frequency of the Boolean signal D (as the ON / OFF frequency, 8Hz) is output to the position corresponding to the number "NO.1" in the stimulus parameter table 207.

[0048] In addition, the signal acquisition circuit 110 can continue to receive another brainwave signal and its corresponding number "NO.2", and perform the same processing on the brainwave signal "NO.2" as on the brainwave signal X(t) with the number "NO.1" mentioned above, and output the stimulation parameters (ON / OFF frequency and frequency components) corresponding to the number "NO.2" to the position corresponding to the number "NO.2" in the stimulation parameter table 207. Similarly, multiple sets of stimulation parameters can be recorded in the stimulation parameter table 207 according to a specified sequence.

[0049] Subsequently, the processor 120 outputs a set of stimulation parameters corresponding to the sequence numbers recorded in the specified sequence to the stimulator 310 in sequence, so that the stimulator 310 generates a stimulation signal F based on the stimulation parameters. That is, first, the stimulation parameters corresponding to the sequence number "NO.1" are output to the stimulator 310 to generate a stimulation signal F, then the stimulation parameters corresponding to the sequence number "NO.2" are output to the stimulator 310 to generate another stimulation signal, and so on, until the stimulation parameters corresponding to the last sequence number in the specified sequence of the stimulation parameter table 207 are output to the stimulator 310 to generate a stimulation signal.

[0050] In summary, the present invention can generate stimulation parameters corresponding to brainwave signals, which helps to generate more accurate stimulation signals and thereby reduce uncertainty.

Claims

1. An electrical stimulation system, characterized in that, include: The signal acquisition circuit is configured to acquire brainwave signals; A processor, coupled to the signal acquisition circuit, and configured to: decompose the brainwave signal into a first sub-signal and a second sub-signal using empirical mode decomposition, wherein the frequency of the first sub-signal is higher than the frequency of the second sub-signal; analyze the first sub-signal to obtain an essential frequency sequence, the essential frequency sequence including at least one frequency component; and generate a Boolean signal based on the dominant frequency of the second sub-signal. A storage device, coupled to the processor, and configured to store the intrinsic frequency sequence and the Boolean signal; as well as A stimulator, coupled to the processor, and configured to: receive the essential frequency sequence and the Boolean signal, and generate a stimulation signal based on the essential frequency sequence and the Boolean signal.

2. The electrical stimulation system of claim 1, wherein the processor is configured to: Perform a spectrum analysis algorithm on the first sub-signal to obtain the essential frequency sequence. The spectrum analysis algorithm mentioned therein is one of the Fourier transform algorithm, wavelet transform algorithm, and normalized Hilbert transform algorithm.

3. The electrical stimulation system of claim 1, wherein the processor is configured to: The Boolean signal is obtained by performing a binarization operation on the second sub-signal.

4. The electrical stimulation system of claim 3, wherein performing the binarization calculation comprises: Calculate the dominant frequency of the second sub-signal.

5. The electrical stimulation system of claim 1, wherein the signal acquisition circuit is configured to: Receive the brainwave signal and the sequence number corresponding to the brainwave signal, and record the sequence number in a specified sequence in the parameter table; in, The processor is configured to: After obtaining the essential frequency sequence and the Boolean signal, the frequencies of the essential frequency sequence and the Boolean signal are recorded as a set of stimulus parameters in the parameter table at the position corresponding to the sequence number.

6. The electrical stimulation system of claim 5, wherein the processor is configured to: Based on the specified sequence, a set of stimulation parameters recorded in the parameter table are sequentially input into the stimulator to generate the stimulation signal.

7. An electrical stimulation control device, characterized in that, include: The signal acquisition circuit is configured to acquire brainwave signals; A processor, coupled to the signal acquisition circuit, and configured to: decompose the brainwave signal into a first sub-signal and a second sub-signal using empirical mode decomposition, wherein the frequency of the first sub-signal is higher than the frequency of the second sub-signal; analyze the first sub-signal to obtain an essential frequency sequence, the essential frequency sequence including at least one frequency component; and generate a Boolean signal based on the dominant frequency of the second sub-signal. as well as A storage device, coupled to the processor, and configured to store the intrinsic frequency sequence and the Boolean signal; The processor transmits the essential frequency sequence and the Boolean signal to the stimulator, so that the stimulator generates a stimulation signal based on the essential frequency sequence and the Boolean signal.

8. The electrical stimulation control device according to claim 7, wherein the processor is configured to: The disassembly module is executed to disassemble the brainwave signal using the empirical mode decomposition.

9. The electrical stimulation control device according to claim 7, wherein the processor is configured to: The spectrum analysis module is executed to perform a spectrum analysis algorithm on the first sub-signal to obtain the essential frequency sequence. The spectrum analysis algorithm mentioned therein is one of the Fourier transform algorithm, wavelet transform algorithm, and normalized Hilbert transform algorithm.

10. The electrical stimulation control device according to claim 7, wherein the processor is configured to: The reconstruction module is executed to perform binarization calculations on the second sub-signal to obtain the Boolean signal.

11. The electrical stimulation control device according to claim 10, wherein the binarization calculation includes: Calculate the dominant frequency of the second sub-signal.

12. The electrical stimulation control device according to claim 7, wherein the signal acquisition circuit is configured to: The system receives the sequence number corresponding to the brainwave signal and records the sequence number into a designated sequence in a parameter table, wherein the parameter table is stored in the storage device. in, The processor is configured to: After obtaining the essential frequency sequence and the Boolean signal, the frequencies of the essential frequency sequence and the Boolean signal are recorded as a set of stimulus parameters in the parameter table at the position corresponding to the sequence number.

13. The electrical stimulation control device of claim 12, wherein the processor is configured to: Based on the specified sequence, a set of stimulation parameters recorded in the parameter table are sequentially input into the stimulator to generate the stimulation signal.

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