A method and device for testing motor threshold of transcranial magnetic stimulation magnetotherapy

Abstract

The application discloses a kind of transcranial magnetic stimulation magnetic therapy motor threshold test method and device, it is related to brain control technical field, the method includes: with the preset sampling rate to obtain the original electromyogram collected by electrode piece, original electromyogram is sequentially carried out high-pass filtering, low-pass filtering and the trap wave filtering of preset frequency, regression zero baseline processing;Control magnetic stimulation coil according to preset stimulation intensity to stimulate, determine the corresponding latency according to the data after this stimulation, determine the amplitude after this stimulation according to the wave crest and wave trough in the electromyogram after latency;According to current amplitude, determine the adjustment mode of stimulation intensity of next stimulation, determine the amplitude of adjusted stimulation intensity under the preset stimulation cycle, until the amplitude meets the measurement condition of motor threshold, and determine the corresponding motor threshold according to current stimulation intensity.The application solves the problem of low efficiency and low accuracy in the prior art during motor threshold test.

Description

Technical Field

[0001] This invention relates to the field of brain modulation technology, and in particular to a method and device for testing the motor threshold of transcranial magnetic stimulation (TMS) therapy. Background Technology

[0002] Motor threshold measurement is a neurophysiological examination method designed to examine the function of the motor nervous system. It is the minimum stimulation intensity required to induce a motor evoked potential (MEP) of more than 50 μV in the target muscle during transcranial magnetic stimulation of the motor cortex. It is determined by the minimum number of times the threshold is achieved in a preset number of stimulations, for example, by achieving the threshold in at least 5 out of 10 stimulations.

[0003] Traditional methods for measuring motor thresholds rely on visual estimation. With muscles in a fully relaxed state, TMS stimulation of the motor cortex is used, and the minimum stimulus intensity required to elicit motor evoked potentials is determined by visually observing minute twitching responses in the fingers. Although widely used for many years, this method has several inherent and interrelated drawbacks:

[0004] 1. Highly subjective, with low reliability (credibility), limited by the limitations of human judgment; the human eye cannot measure peak-to-peak values ​​as precisely as an algorithm. It lacks objective standards, judging based on what "looks like" rather than precise numerical measurement. Different visual tolerances can lead to different results.

[0005] 2. This method is time-consuming and inefficient; it is essentially a flawed approach. Operators need to adjust the intensity within an uncertain range and perform multiple stimuli at various intensity points to calculate the success rate. This strategy itself requires a large number of trials.

[0006] 3. Monitoring the condition of the subjects is difficult. During long-term, repetitive measurements, subjects are prone to fatigue, boredom, or lack of concentration, which makes it impossible for their muscles to remain in a completely resting state.

[0007] 4. Poor repeatability: The values ​​measured by the same subject on different days fluctuate greatly. This fluctuation may be due to changes in the subject's own physiological state, but it may also be due to differences in subjective judgment between different operators or the same operator in different tests.

[0008] Therefore, current methods for measuring motion threshold suffer from low efficiency and low accuracy. Summary of the Invention

[0009] In view of this, the purpose of the present invention is to provide a method and device for testing the motion threshold of transcranial magnetic stimulation (TMS) therapy, which aims to solve the problems of low efficiency and low accuracy in the existing methods for measuring motion threshold.

[0010] This invention proposes a method for testing the motor threshold of transcranial magnetic stimulation (TMS) therapy. This method is applied to a motor evoked potential (MAP) module, which includes electrode wires and a magnetic stimulation coil. The electrode wires are connected to electrode pads containing positive and negative poles. The positive and negative poles of the electrode pads are respectively attached to the belly and tendon of the abductor pollicis brevis muscle. The magnetic stimulation coil is placed in the corresponding motor cortex area of ​​the head. The method includes:

[0011] The raw electromyographic signals collected by the electrode pads are acquired at a preset sampling rate. The raw electromyographic signals are then subjected to high-pass filtering, low-pass filtering, notch filtering at a preset frequency, and zero baseline regression processing in sequence.

[0012] The magnetic stimulation coil is controlled to stimulate according to the preset stimulation intensity. The corresponding latency is determined based on the data after this stimulation. The amplitude after this stimulation is determined based on the peaks and troughs in the electromyographic signal after the latency.

[0013] The method of adjusting the intensity of the next stimulus is determined based on the current amplitude. The intensity of the next stimulus is adjusted, and the amplitude of the adjusted stimulus intensity under the preset stimulus cycle is determined until the amplitude meets the measurement conditions of the motion threshold. The corresponding motion threshold is then determined based on the current stimulus intensity.

[0014] Furthermore, in the above-mentioned transcranial magnetic stimulation (TMS) method for testing the motor threshold, the latency period is the transmission time from nerve stimulation to muscle response.

[0015] The incubation period is determined as follows:

[0016] Determine the trigger point at which the magnetic stimulation coil begins stimulation, calculate the baseline mean of the data before the trigger point, and find the first peak or trough after the trigger point;

[0017] Search forward from the peak or trough to find the point where the signal returns to the baseline, and calculate the time difference between the trigger point and the point where the signal returns to the baseline to obtain the latency.

[0018] Furthermore, in the above-mentioned transcranial magnetic stimulation (TMS) method for testing the motor threshold, the step of determining the amplitude of the stimulation based on the peaks and troughs in the electromyographic signal after the latency period includes:

[0019] The first peak and trough, as well as the second peak and trough, were identified in the electromyographic signals after the latency period.

[0020] The mean of the absolute values ​​of the differences between the first peak and the trough, and the second peak and the trough, is used as the amplitude after this stimulus.

[0021] Furthermore, in the above-mentioned method for testing the motion threshold of transcranial magnetic stimulation (TMS), the high-pass filtering method is as follows:

[0022] Smooth the signal, retain low-frequency components, and attenuate above the cutoff frequency. High-frequency noise;

[0023] The expression for high-pass filtering is:

[0024]

[0025] in, For the current moment The output value, For the previous moment The output value, For the current moment Input value, For the previous moment Input value, These are the coefficients of the filter. , For the desired cutoff frequency, The sampling rate of the signal. Pi is the mathematical constant of a circle.

[0026] Furthermore, in the above-mentioned method for testing the motion threshold of transcranial magnetic stimulation (TMS), the low-pass filtering and the preset frequency notch filtering are performed as follows:

[0027] Smooth the signal and remove high-frequency and preset frequency power frequency noise;

[0028] The expression for low-pass filtering is:

[0029] ;

[0030] in, This is the current output value. This is the current input value. These are the first two input values, These are the first two output values, Forward coefficients, The feedback coefficient is 1. The feedback coefficient is 2;

[0031] The method for regressing to zero baseline is as follows:

[0032] Remove DC offset to bring the signal mean back to zero.

[0033] Furthermore, in the above-mentioned transcranial magnetic stimulation (TMS) method for testing the motor threshold, the step of determining the adjustment method for the stimulation intensity of the next stimulation based on the current amplitude, adjusting the stimulation intensity of the next stimulation, and determining the amplitude of the adjusted stimulation intensity under a preset stimulation cycle until the amplitude meets the measurement conditions for the motor threshold includes:

[0034] If, under stimulation cycle, the frequency of the amplitude falling into the first preset amplitude range reaches the preset stop threshold, then the detection is terminated.

[0035] If, under the stimulation cycle, the frequency with which the amplitude falls within the first preset amplitude range is the same as the first preset frequency, then an additional judgment cycle is added, and the amplitude data of the additional judgment cycle is analyzed:

[0036] If, during the supplementary judgment loop, the amplitude falls within the first preset amplitude range at least once, the detection is terminated.

[0037] If no amplitude falls within the first preset amplitude range within the supplementary judgment loop, then count the frequency of amplitude falling within the second preset amplitude range and the third preset amplitude range within the supplementary judgment loop, respectively.

[0038] Among them, the second preset amplitude range is lower than the lower limit of the first preset amplitude range, and the third preset amplitude range is higher than the upper limit of the first preset amplitude range:

[0039] If the frequency of the third preset amplitude range is higher than the preset threshold, the intensity of the next stimulus will be reduced.

[0040] If the frequency of the second preset amplitude range is higher than the preset threshold, then the stimulation intensity of the next stimulus will be increased.

[0041] If, during a stimulation cycle, the frequency at which the amplitude falls into the first preset amplitude range is the second preset frequency, and the second preset frequency is lower than the first preset frequency, then the stimulation intensity of the next stimulation is adjusted accordingly based on the frequency at which the amplitude falls into the second preset amplitude range or the third preset amplitude range during the stimulation cycle.

[0042] If, under the stimulation cycle, the frequency of the amplitude falling into the first preset amplitude range is lower than the second preset frequency, then the execution of the second judgment condition will proceed.

[0043] The second judgment condition is:

[0044] If, under stimulation cycle, the frequency at which the amplitude falls into the second preset amplitude range is determined, the increase step of the stimulation intensity of the next stimulus is determined according to the different frequency levels, and the higher the frequency level, the larger the increase step.

[0045] If the frequency is lower than the lowest level, then proceed to the execution of the third judgment condition;

[0046] The third condition for judgment is:

[0047] The frequency of the amplitude falling into the fourth preset amplitude range under the statistical stimulus cycle is determined. Based on the different frequency levels, the reduction step of the stimulus intensity of the next stimulus is determined accordingly. The higher the frequency level, the larger the reduction step.

[0048] If no amplitude falls within the fourth preset amplitude range under the stimulation cycle, then the execution of the fourth judgment condition will proceed.

[0049] The fourth condition for judgment is:

[0050] The frequency of the amplitude falling into the fifth preset amplitude range under the statistical stimulus cycle is determined. Based on the different frequency levels, the reduction step of the stimulus intensity of the next stimulus is determined accordingly. The higher the frequency level, the larger the reduction step.

[0051] Repeat the adjustment of the stimulus intensity for the next stimulus until the amplitude within the stimulus cycle meets the termination detection requirement in the first judgment condition.

[0052] Furthermore, in the above-mentioned method for testing the motor threshold of transcranial magnetic stimulation (TMS), the method further includes:

[0053] The electromyography signal is converted into a waveform and displayed in real time. Waveforms with different directions are mirrored and flipped to unify all waveforms into a standard shape.

[0054] Another objective of this invention is to provide a transcranial magnetic stimulation (TMS) motor threshold testing device for use in a motor evoked potential (MAP) module. The MAP module includes electrode wires and a magnetic stimulation coil. The electrode wires are connected to electrode pads containing positive and negative electrodes. The positive and negative electrodes are respectively attached to the belly of the abductor pollicis brevis muscle and the abductor pollicis brevis tendon. The magnetic stimulation coil is placed in the corresponding motor cortex area of ​​the head. The device includes:

[0055] The acquisition module is used to acquire the raw electromyographic signals collected by the electrode pads at a preset sampling rate, and to perform high-pass filtering, low-pass filtering, notch filtering at a preset frequency, and zero baseline regression processing on the raw electromyographic signals in sequence.

[0056] The control module is used to control the magnetic stimulation coil to stimulate according to the preset stimulation intensity, determine the corresponding latency based on the data after the stimulation, and determine the amplitude after the stimulation based on the peaks and troughs in the electromyographic signal after the latency.

[0057] The measurement module is used to determine the adjustment mode of the stimulation intensity of the next stimulus based on the current amplitude, so as to adjust the stimulation intensity of the next stimulus, determine the amplitude of the adjusted stimulation intensity under the preset stimulation cycle, until the amplitude meets the measurement conditions of the motion threshold, and determine the corresponding motion threshold based on the current stimulation intensity.

[0058] Another object of the present invention is to provide a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0059] Another object of the present invention is to provide an electronic device including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the method described above.

[0060] This invention acquires raw electromyographic (EMG) signals from electrode pads at a preset sampling rate. The raw EMG signals are then sequentially subjected to high-pass filtering, low-pass filtering, and notch filtering at a preset frequency, followed by zero-baseline regression. A magnetic stimulation coil is controlled to stimulate the sensor at a preset intensity. The latency is determined based on the data following the stimulation, and the amplitude is determined based on the peaks and troughs in the EMG signal after the latency. The intensity of the next stimulation is adjusted based on the current amplitude, and the amplitude of the adjusted stimulation is determined within a preset stimulation cycle until the amplitude meets the measurement conditions for the motor threshold. The corresponding motor threshold is then determined based on the current stimulation intensity. This invention uses an algorithm to automatically determine the latency and amplitude instead of visual estimation, and intelligently adjusts the stimulation intensity based on the current amplitude instead of trial and error, using objective numerical standards to determine the final motor threshold. This solves the problems of low efficiency and low accuracy in existing technologies for motor threshold testing. Attached Figure Description

[0061] Figure 1 This is a flowchart of the motion threshold testing method for transcranial magnetic stimulation (TMS) in the first embodiment of the present invention;

[0062] Figure 2 This is a structural block diagram of the motion threshold testing device for transcranial magnetic stimulation (TMS) in the third embodiment of the present invention.

[0063] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0064] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0065] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0066] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0067] Example 1

[0068] Please see Figure 1 The image shows a transcranial magnetic stimulation (TMS) method for testing the motor threshold in the first embodiment of the present invention. This method is applied to a motor evoked potential (PEP) module. The PEP module includes an electrode wire and a magnetic stimulation coil. The electrode wire is connected to an electrode pad containing a positive and a negative electrode. The positive and negative electrodes of the electrode pad are respectively attached to the belly of the abductor pollicis brevis muscle and the tendon of the abductor pollicis brevis muscle. The magnetic stimulation coil is placed in the corresponding motor cortex area of ​​the head. The method includes steps S10 to S12.

[0069] Step S10: Obtain the raw electromyographic signal collected by the electrode pads at a preset sampling rate, and sequentially perform high-pass filtering, low-pass filtering, notch filtering at a preset frequency, and zero baseline return processing on the raw electromyographic signal.

[0070] This step is the core component of the transcranial magnetic stimulation (TMS) motor threshold test. Its purpose is to obtain high-quality, low-noise electromyographic signals from the human body, providing accurate data support for subsequent calculations of latency, amplitude, and determination of motor threshold.

[0071] The first step is the acquisition of electromyographic signals, which is accomplished through the electrode pads and electrode wires of the motor evoked potential module: the positive electrode of the electrode pad has been attached to the belly of the abductor pollicis brevis muscle, the negative electrode to the tendon of the abductor pollicis brevis muscle, and the ground wire to the back of the patient's hand. The two form a potential difference to accurately capture the original electromyographic signals generated by the muscle due to nerve stimulation.

[0072] Simultaneously, signal acquisition must be performed according to the "preset sampling rate," which is a reasonable value preset based on the effective frequency range of electromyographic signals (usually 0.1-500Hz). It must meet the Nyquist sampling criterion (i.e., the sampling rate is at least twice the highest frequency of the signal) to ensure that key information of the original signal is not lost during the acquisition process and to avoid signal distortion.

[0073] For example, the motion evoked potential module data cable is connected to the computer via a serial port with a sampling rate of 2kHz. The Nyquist frequency corresponding to a 2kHz sampling rate is 1kHz, which is much higher than the highest effective frequency of the motion evoked potential module signal (500Hz). The 2kHz sampling rate can capture all valuable information components of the motion evoked potential module completely without aliasing or distortion.

[0074] Next, the acquired raw electromyography (EMG) signals are preprocessed, with each step targeting specific noise or signal defects: the first step is high-pass filtering, the second is low-pass filtering, the third is notch filtering at a preset frequency, and the fourth step is baseline resetting. First, a gentle high-pass filter roughly eliminates drift, then mathematical calculations precisely reset the baseline to zero. This combination is more effective and produces higher waveform fidelity than relying solely on a single aggressive high-pass filter. The 50Hz notch filtering, along with the high-pass and low-pass filtering, is performed in real-time within the same workflow, ensuring processing efficiency and data consistency. Slow baseline drift caused by slight patient breathing and body movement is automatically filtered out.

[0075] Specifically, the high-pass filtering method is as follows:

[0076] Smooth the signal, retain low-frequency components, and attenuate above the cutoff frequency. High-frequency noise;

[0077] The expression for high-pass filtering is:

[0078]

[0079] in, For the current moment The output value, For the previous moment The output value, For the current moment Input value, For the previous moment Input value, These are the coefficients of the filter. , For the desired cutoff frequency, The sampling rate of the signal. Pi is the mathematical constant of a circle.

[0080] The methods for low-pass filtering and preset frequency notch filtering are as follows:

[0081] Smooth the signal and remove high-frequency and preset frequency power frequency noise;

[0082] The expression for low-pass filtering is:

[0083] ;

[0084] in, This is the current output value. This is the current input value. These are the first two input values, These are the first two output values, Forward coefficients, The feedback coefficient is 1. The feedback coefficient is 2;

[0085] The method for regressing to zero baseline is as follows:

[0086] Remove DC offset to bring the signal mean back to zero.

[0087] Step S11: Control the magnetic stimulation coil to stimulate according to the preset stimulation intensity, determine the corresponding latency based on the data after this stimulation, and determine the amplitude after this stimulation based on the peaks and troughs in the electromyographic signal after the latency.

[0088] In practice, the coil is placed at a 45-degree angle to the corresponding motor cortex of the patient's head. The motor evoked potential module outputs a driving current with specific parameters to the magnetic stimulation coil according to the initial stimulation intensity preset in the test procedure (or the stimulation intensity adjusted after the previous test). When the current passes through the coil, it will instantly generate a high-intensity alternating magnetic field. Since the magnetic stimulation coil has been pre-fixed to the corresponding motor cortex of the head and generates electromyographic signals, the electrode pads previously attached to the belly and tendon of the abductor pollicis brevis muscle will collect this electromyographic signal induced by the stimulation in real time, forming the data after this stimulation.

[0089] The latency period is essentially the time interval between the application of magnetic stimulation and the appearance of an effective electrical response in the muscle. It reflects the speed at which nerve signals are transmitted from the motor cortex of the brain to the abductor pollicis brevis muscle. Specifically, the latency period is determined as follows: determine the trigger point at which the magnetic stimulation coil begins stimulation, and calculate the baseline mean of the data before the trigger point. After the trigger point, find the first peak or trough. Search backward from the peak or trough to find the point where the signal returns to the baseline. Calculate the time difference between the trigger point and the point where the signal returns to the baseline to obtain the latency period.

[0090] The trigger point is the precise moment when the magnetic stimulation coil begins to release the magnetic field, marked by the motor evoked potential module through an internal synchronization signal (e.g., the module generates a synchronization pulse the instant the coil is energized; the time point corresponding to this pulse is the trigger point, serving as the "zero point" for the entire time calculation). The baseline mean is calculated based on "data before the trigger point," which is typically the electromyographic signal 50 milliseconds before the trigger point—at this time, the magnetic stimulation has not yet affected the muscle, and the signal mainly consists of skin noise, device background noise, etc., and is in a relatively stable "non-reactive state." Calculating the mean of this data (i.e., the baseline mean) aims to establish a "signal baseline level when the muscle is not responding," providing a reference for subsequent judgment of the "true response signal" (avoiding misjudging noise as a response).

[0091] After the trigger point, the nerve signal is transmitted from the brain to the muscle and causes contraction, which will cause the electromyographic signal to fluctuate significantly from the baseline level. At this time, the "first peak or trough" in the electromyographic data after the trigger point needs to be located by the signal analysis algorithm. The peak / trough here needs to meet the condition that "the amplitude exceeds the preset threshold" (the threshold is usually set to 2-3 times the standard deviation of the baseline noise) to ensure that it is the real electrical response of the muscle to magnetic stimulation (rather than random noise fluctuations). The peak / trough is the "significant feature point" of the response signal, which indicates that the muscle has generated detectable electrical activity.

[0092] Since the peak / trough is the "apex" of the response signal (rather than the starting moment of the response), it is necessary to search from this peak or trough towards the "trigger point direction" (i.e., the time backtracking direction) to find the "point where the signal returns to the baseline" - the criterion for determining this point is that the signal amplitude falls back to within the "baseline mean ± preset deviation range" (such as the baseline mean ± 1 standard deviation). This means that this is the dividing point from the response signal "exceeding the baseline noise level" to "returning to the stable baseline", which is also the "actual starting moment" of the electromuscular response.

[0093] Finally, the time difference between the "trigger point" and the "point where the signal returns to the baseline" is calculated. This difference is the latency, which truly reflects the total time it takes for the neural signal to travel from the motor cortex of the brain to the abductor pollicis brevis muscle. It is a key parameter for determining the motor threshold.

[0094] Finally, the amplitude is calculated. During the effective response period after the latency period, the characteristic extreme values ​​of the electromyographic signal are identified by the signal analysis algorithm: one is the "peak", which is the highest potential value reached during the signal rise (positive peak), and the other is the "trough", which is the lowest potential value reached during the signal fall (negative peak). Then, the absolute difference between the peak and the trough is calculated (if the peak is positive and the trough is negative, the difference is the sum of the absolute values ​​of the two). This difference is the amplitude corresponding to this stimulus.

[0095] For example, the first peak and trough, and the second peak and trough, are identified in the electromyographic signal after the latency period.

[0096] The mean of the absolute values ​​of the differences between the first peak and the trough, and the second peak and the trough, is used as the amplitude after this stimulus.

[0097] Among them, the most obvious peaks and troughs are searched in the signal after the trigger to determine two key points: the first peak / trough, the second peak / trough, and the third peak / trough. The difference between the first and second key points is used as the amplitude, and the absolute value is taken to ensure that the amplitude is positive.

[0098] In addition, during the absolute quiet period of 50ms before each stimulus, the mean was calculated and the entire waveform was shifted to ensure that the stimulus start point was strictly zero.

[0099] Step S12: Determine the adjustment method of the stimulation intensity of the next stimulus based on the current amplitude, so as to adjust the stimulation intensity of the next stimulus, determine the amplitude of the adjusted stimulation intensity under the preset stimulation cycle, until the amplitude meets the measurement conditions of the motion threshold, and determine the corresponding motion threshold based on the current stimulation intensity.

[0100] Specifically, it is necessary to determine the relationship between the amplitude calculated after the current stimulus and the preset "motion threshold judgment standard amplitude range": if the current amplitude is lower than the range, the intensity of the next stimulus needs to be increased; if the current amplitude is higher than the range, the intensity of the next stimulus needs to be decreased.

[0101] The step size for intensity adjustment (i.e., the specific value of increase or decrease) is determined based on the degree to which the amplitude deviates from the target range (the greater the deviation, the larger the step size may be to accelerate the approach to the target). Subsequently, the next stimulus is administered according to the adjusted stimulus intensity, and the amplitude is repeatedly measured within a "preset stimulus cycle"—this preset cycle typically refers to a fixed number of repetitive stimuli (e.g., 5-10 times per round). After each round, the amplitude distribution within that cycle is analyzed again: if most amplitudes fall within the preset motor threshold judgment range (i.e., can stably elicit a standard electromuscular response), the current stimulus intensity is considered close to the motor threshold; if not, the stimulus intensity for the next round is adjusted based on the amplitude results of that cycle (repeating the process of "analyzing amplitude - adjusting intensity - cyclic measurement"). This dynamic adjustment process continues until, at a certain stimulus intensity, the amplitude within the preset cycle consistently and stably meets the measurement conditions for the motor threshold; at this point, the stimulus intensity is determined to be the corresponding motor threshold.

[0102] In summary, the transcranial magnetic stimulation (TMS) method for testing the motor threshold in the above embodiments of the present invention acquires raw electromyographic (EMG) signals from electrode pads at a preset sampling rate. The raw EMG signals are then sequentially subjected to high-pass filtering, low-pass filtering, and notch filtering at a preset frequency, followed by zero-baseline regression. The magnetic stimulation coil is controlled to stimulate at a preset intensity. The latency is determined based on the data following the stimulation, and the amplitude is determined based on the peaks and troughs in the EMG signal after the latency. The intensity adjustment method for the next stimulation is determined based on the current amplitude. The amplitude of the adjusted stimulation is determined within a preset stimulation cycle until the amplitude meets the measurement conditions for the motor threshold. The corresponding motor threshold is then determined based on the current stimulation intensity. The algorithm automatically determines the latency and amplitude instead of visual estimation, and intelligently adjusts the stimulation intensity based on the current amplitude instead of trial and error, using objective numerical standards to determine the final motor threshold. This solves the problems of low efficiency and low accuracy in existing technologies for motor threshold testing.

[0103] Example 2

[0104] This embodiment also proposes a method for testing the motion threshold of transcranial magnetic stimulation (TMS). The difference between the method for testing the motion threshold of TMS in this embodiment and the method for testing the motion threshold of TMS in Embodiment 1 is as follows:

[0105] The step of determining the stimulation intensity of the next stimulus based on the current amplitude, adjusting the stimulation intensity of the next stimulus, and determining the amplitude of the adjusted stimulation intensity under a preset stimulation cycle until the amplitude meets the measurement conditions of the motion threshold includes:

[0106] If, under stimulation cycle, the frequency of the amplitude falling into the first preset amplitude range reaches the preset stop threshold, then the detection is terminated.

[0107] If, under the stimulation cycle, the frequency with which the amplitude falls within the first preset amplitude range is the same as the first preset frequency, then an additional judgment cycle is added, and the amplitude data of the additional judgment cycle is analyzed:

[0108] If, during the supplementary judgment loop, the amplitude falls within the first preset amplitude range at least once, the detection is terminated.

[0109] If no amplitude falls within the first preset amplitude range within the supplementary judgment loop, then count the frequency of the amplitude falling within the second preset amplitude range and the third preset amplitude range within the supplementary judgment loop, respectively.

[0110] Among them, the second preset amplitude range is lower than the lower limit of the first preset amplitude range, and the third preset amplitude range is higher than the upper limit of the first preset amplitude range:

[0111] If the frequency of the third preset amplitude range is higher than the preset threshold, the intensity of the next stimulus will be reduced.

[0112] If the frequency of the second preset amplitude range is higher than the preset threshold, the stimulation intensity of the next stimulus will be increased.

[0113] If, during a stimulation cycle, the frequency at which the amplitude falls into the first preset amplitude range is the second preset frequency, and the second preset frequency is lower than the first preset frequency, then the stimulation intensity of the next stimulation is adjusted accordingly based on the frequency at which the amplitude falls into the second preset amplitude range or the third preset amplitude range during the stimulation cycle.

[0114] If, under the stimulation cycle, the frequency of the amplitude falling into the first preset amplitude range is lower than the second preset frequency, then the execution of the second judgment condition will proceed.

[0115] The second judgment condition is:

[0116] If, under stimulation cycle, the frequency at which the amplitude falls into the second preset amplitude range is determined, the increase step of the stimulation intensity of the next stimulus is determined according to the different frequency levels, and the higher the frequency level, the larger the increase step.

[0117] If the frequency is lower than the lowest level, then proceed to the execution of the third judgment condition;

[0118] The third condition for judgment is:

[0119] The frequency of the amplitude falling into the fourth preset amplitude range under the statistical stimulus cycle is determined. Based on the different frequency levels, the reduction step of the stimulus intensity of the next stimulus is determined accordingly. The higher the frequency level, the larger the reduction step.

[0120] If no amplitude falls within the fourth preset amplitude range under the stimulation cycle, then the execution of the fourth judgment condition will proceed.

[0121] The fourth condition for judgment is:

[0122] The frequency of the amplitude falling into the fifth preset amplitude range under the statistical stimulus cycle is determined. Based on the different frequency levels, the reduction step of the stimulus intensity of the next stimulus is determined accordingly. The higher the frequency level, the larger the reduction step.

[0123] Repeat the adjustment of the stimulus intensity for the next stimulus until the amplitude within the stimulus cycle meets the termination detection requirement in the first judgment condition.

[0124] For example, the direction and magnitude of the increase or decrease in the intensity of the next stimulus can be intelligently determined based on the outcome of the current stimulus.

[0125] The measurement and judgment method is as follows (each cycle is 10 times):

[0126] Judgment Condition 1

[0127] 1. If the amplitude of 5 or more waves is greater than or equal to 50 and less than or equal to 200, then stop the measurement.

[0128] 2. If the amplitude of the fourth wave is greater than or equal to 50 and less than or equal to 200, and the first wave is outside this range, then continue with a cycle of stimulation for 5 times.

[0129] (1) When an amplitude of 50 or less than or equal to 200 is observed once, the measurement shall be stopped.

[0130] (2) If there is no amplitude within the range of 50 or less than 200, but the amplitude is greater than 200 more than 3 out of 5 stimuli, then decrease by 1 point; if the amplitude is less than 50 more than 3 out of 5 stimuli, then increase by 1 point. If none of the above conditions are met, then proceed to judgment condition two.

[0131] 3. If the amplitude of three fluctuations is greater than or equal to 50 and less than or equal to 200: if two fluctuations are greater than 200, the amplitude drops by 1 point; if two fluctuations are less than 50, the amplitude rises by 1 point; if one fluctuation is less than 50 and the other is greater than 200, the amplitude rises by 1 point.

[0132] 4. If the amplitude of the second wave is greater than or equal to 50 and less than or equal to 200: proceed to judgment condition two.

[0133] 5. If the amplitude of the first wave is greater than or equal to 50 and less than or equal to 200: proceed to judgment condition two.

[0134] Judgment Condition Two

[0135] 1. Five or more fluctuations with an amplitude of less than 50: rise by 3 points.

[0136] 2. If the amplitude of the 4th wave is less than 50, the price will rise by 2 points.

[0137] 3. If the amplitude of the three fluctuations is less than 50, the price will rise by 2 points.

[0138] 4. If the amplitude of the second wave is less than 50, proceed to judgment conditions three and four.

[0139] 5. If the amplitude of the first wave is less than 50, proceed to judgment conditions three and four.

[0140] Judgment Condition 3

[0141] 1. Five or more fluctuations with an amplitude greater than or equal to 500: decrease by 3 points.

[0142] 2. If the amplitude of the fourth wave is greater than or equal to 500, the price will drop by 3 points.

[0143] 3. If the amplitude of the third wave is greater than or equal to 500, the price will drop by 2 points.

[0144] 4. If the amplitude of the second wave is greater than or equal to 500, the price will drop by 2 points.

[0145] 5. If the amplitude of a single wave is greater than or equal to 500, the price will drop by 2 points.

[0146] Judgment Condition Four

[0147] 1. For 5 or more fluctuations with an amplitude greater than 200 and less than 500: decrease by 2 points.

[0148] 2. If the amplitude of the four fluctuations is greater than 200 and less than 500, the price will drop by 2 points.

[0149] 3. If the amplitude of the three fluctuations is greater than 200 and less than 500: decrease by 2 points.

[0150] 4. If the amplitude of the second wave is greater than 200 and less than 500, the value will decrease by 1 point.

[0151] 5. If the amplitude of a single wave is greater than 200 but less than 500, the wave will drop by 1 point.

[0152] First, execute condition one, then execute condition two, condition three, and condition four. If condition three is executed, condition four will not be executed, and vice versa. The number of points that can be increased or decreased corresponds to the percentage points or base unit value of the previous stimulus intensity.

[0153] In addition, in some optional embodiments of the present invention, the method further includes:

[0154] The electromyography signal is converted into a waveform and displayed in real time. Waveforms with different directions are mirrored and flipped to unify all waveforms into a standard shape.

[0155] The algorithm automatically mirrors and flips the "negative then positive" waveform, unifying all valid waveforms into a standardized "top then bottom" shape.

[0156] In summary, the transcranial magnetic stimulation (TMS) method for testing the motor threshold in the above embodiments of the present invention acquires raw electromyographic (EMG) signals from electrode pads at a preset sampling rate. The raw EMG signals are then sequentially subjected to high-pass filtering, low-pass filtering, and notch filtering at a preset frequency, followed by zero-baseline regression. The magnetic stimulation coil is controlled to stimulate at a preset intensity. The latency is determined based on the data following the stimulation, and the amplitude is determined based on the peaks and troughs in the EMG signal after the latency. The intensity adjustment method for the next stimulation is determined based on the current amplitude. The amplitude of the adjusted stimulation is determined within a preset stimulation cycle until the amplitude meets the measurement conditions for the motor threshold. The corresponding motor threshold is then determined based on the current stimulation intensity. The algorithm automatically determines the latency and amplitude instead of visual estimation, and intelligently adjusts the stimulation intensity based on the current amplitude instead of trial and error, using objective numerical standards to determine the final motor threshold. This solves the problems of low efficiency and low accuracy in existing technologies for motor threshold testing.

[0157] Example 3

[0158] Please see Figure 2 The image shows a transcranial magnetic stimulation (TMS) motor threshold testing device proposed in the third embodiment of the present invention, applied in a motor evoked potential (MAP) module. The MAP module includes electrode wires and a magnetic stimulation coil. The electrode wires are connected to electrode pads containing positive and negative electrodes. The positive and negative electrodes of the electrode pads are respectively attached to the belly of the abductor pollicis brevis muscle and the tendon of the abductor pollicis brevis muscle. The magnetic stimulation coil is placed in the corresponding motor cortex area of ​​the head. The device includes:

[0159] The acquisition module 100 is used to acquire the raw electromyographic signals collected by the electrode pads at a preset sampling rate, and to perform high-pass filtering, low-pass filtering, notch filtering at a preset frequency, and zero baseline regression processing on the raw electromyographic signals in sequence.

[0160] The control module 200 is used to control the magnetic stimulation coil to stimulate according to the preset stimulation intensity, determine the corresponding latency based on the data after the stimulation, and determine the amplitude after the stimulation based on the peaks and troughs in the electromyographic signal after the latency.

[0161] The measurement module 300 is used to determine the adjustment mode of the stimulation intensity of the next stimulus based on the current amplitude, so as to adjust the stimulation intensity of the next stimulus, determine the amplitude of the adjusted stimulation intensity under the preset stimulation cycle, until the amplitude meets the measurement conditions of the motion threshold, and determine the corresponding motion threshold based on the current stimulation intensity.

[0162] The functions or operation steps implemented by the above modules are largely the same as those in the above method embodiments, and will not be repeated here.

[0163] Example 4

[0164] In another aspect, the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the method described in any one of Embodiments 1 to 2 above.

[0165] Example 5

[0166] In another aspect, the present invention provides an electronic device, the electronic device including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of any one of the methods described in Embodiments 1 to 2 above.

[0167] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0168] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0169] More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable storage media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0170] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0171] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," 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, the 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.

[0172] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A motion threshold testing system for transcranial magnetic stimulation (TMS) therapy, characterized in that, The system includes: The acquisition module is used to acquire the raw electromyographic signals collected by the electrode pads at a preset sampling rate, and to perform high-pass filtering, low-pass filtering, notch filtering at a preset frequency, and zero baseline regression processing on the raw electromyographic signals in sequence. The control module is used to control the magnetic stimulation coil to stimulate according to the preset stimulation intensity, determine the corresponding latency based on the data after the stimulation, and determine the amplitude after the stimulation based on the peaks and troughs in the electromyographic signal after the latency. The measurement module is used to determine the adjustment method of the stimulus intensity for the next stimulus based on the current amplitude, so as to adjust the stimulus intensity of the next stimulus, determine the amplitude of the adjusted stimulus intensity under a preset stimulus cycle, until the amplitude meets the measurement conditions of the motion threshold, and determine the corresponding motion threshold based on the current stimulus intensity, specifically including: If, under stimulation cycle, the frequency of the amplitude falling into the first preset amplitude range reaches the preset stop threshold, then the detection is terminated. If, under the stimulation cycle, the frequency with which the amplitude falls within the first preset amplitude range is the same as the first preset frequency, then an additional judgment cycle is added, and the amplitude data of the additional judgment cycle is analyzed: If, during the supplementary judgment loop, the amplitude falls within the first preset amplitude range at least once, the detection is terminated. If no amplitude falls within the first preset amplitude range within the supplementary judgment loop, then count the frequency of the amplitude falling within the second preset amplitude range and the third preset amplitude range within the supplementary judgment loop, respectively. Among them, the second preset amplitude range is lower than the lower limit of the first preset amplitude range, and the third preset amplitude range is higher than the upper limit of the first preset amplitude range: If the frequency of the third preset amplitude range is higher than the preset threshold, the intensity of the next stimulus will be reduced. If the frequency of the second preset amplitude range is higher than the preset threshold, the stimulation intensity of the next stimulus will be increased. If, during a stimulation cycle, the frequency at which the amplitude falls into the first preset amplitude range is the second preset frequency, and the second preset frequency is lower than the first preset frequency, then the stimulation intensity of the next stimulation is adjusted accordingly based on the frequency at which the amplitude falls into the second preset amplitude range or the third preset amplitude range during the stimulation cycle. If, under the stimulation cycle, the frequency of the amplitude falling into the first preset amplitude range is lower than the second preset frequency, then the execution of the second judgment condition will proceed. The second judgment condition is: If, under stimulation cycle, the frequency at which the amplitude falls into the second preset amplitude range is determined, the increase step of the stimulation intensity of the next stimulus is determined according to the different frequency levels, and the higher the frequency level, the larger the increase step. If the frequency is lower than the lowest level, then proceed to the execution of the third judgment condition; The third condition for judgment is: The frequency of the amplitude falling into the fourth preset amplitude range under the statistical stimulus cycle is determined. Based on the different frequency levels, the reduction step of the stimulus intensity of the next stimulus is determined accordingly. The higher the frequency level, the larger the reduction step. If no amplitude falls within the fourth preset amplitude range under the stimulation cycle, then the execution of the fourth judgment condition will proceed. The fourth condition for judgment is: The frequency of the amplitude falling into the fifth preset amplitude range under the statistical stimulus cycle is determined. Based on the different frequency levels, the reduction step of the stimulus intensity of the next stimulus is determined accordingly. The higher the frequency level, the larger the reduction step. Repeat the adjustment of the stimulus intensity for the next stimulus until the amplitude within the stimulus cycle meets the termination detection requirement in the first judgment condition; The latency period is the time it takes for nerve stimulation to lead to a muscle response.

2. The transcranial magnetic stimulation (TMS) motor threshold testing system according to claim 1, characterized in that, The high-pass filtering method is as follows: Smooth the signal, retain low-frequency components, and attenuate above the cutoff frequency. High-frequency noise; The expression for high-pass filtering is: in, For the current moment The output value, For the previous moment The output value, For the current moment Input value, For the previous moment Input value, These are the coefficients of the filter. , For the desired cutoff frequency, The sampling rate of the signal. Pi is the mathematical constant of a circle.

3. The transcranial magnetic stimulation (TMS) motor threshold testing system according to claim 2, characterized in that, The methods for low-pass filtering and preset frequency notch filtering are as follows: Smooth the signal and remove high-frequency and preset frequency power frequency noise; The expression for low-pass filtering is: ； in, This is the current output value. This is the current input value. These are the first two input values, These are the first two output values, Forward coefficients, The feedback coefficient is 1. The feedback coefficient is 2; The method for regressing to zero baseline is as follows: Remove DC offset to bring the signal mean back to zero.

4. The transcranial magnetic stimulation (TMS) motor threshold testing system according to claim 1, characterized in that, The system also includes: The electromyography signal is converted into a waveform and displayed in real time. Waveforms with different directions are mirrored and flipped to unify all waveforms into a standard shape.

5. The transcranial magnetic stimulation (TMS) motor threshold testing system according to claim 1, characterized in that, The incubation period is determined as follows: Determine the trigger point at which the magnetic stimulation coil begins stimulation, calculate the baseline mean of the data before the trigger point, and find the first peak or trough after the trigger point; Search forward from the peak or trough to find the point where the signal returns to the baseline, and calculate the time difference between the trigger point and the point where the signal returns to the baseline to obtain the latency. The step of determining the amplitude of the stimulus based on the peaks and troughs in the electromyographic signal after the latency period includes: The first peak and trough, as well as the second peak and trough, were identified in the electromyographic signals after the latency period. The mean of the absolute values ​​of the differences between the first peak and the trough, and the second peak and the trough, is used as the amplitude after this stimulus.

6. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the transcranial magnetic stimulation (TMS) motor threshold testing system as described in any one of claims 1 to 5.

7. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the transcranial magnetic stimulation (TMS) motor threshold testing system as described in any one of claims 1 to 5.

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