CN112843488A - Photoelectric stimulation pulse generation method and device - Google Patents
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Abstract
The invention provides a photoelectric stimulation pulse generation method and device. The basic idea is that according to the nerve signal of the near brain end of the damaged nerve, when the nerve signal exceeds a certain amplitude threshold value and meets the refractory period condition, a photoelectric stimulation pulse is generated to stimulate the corresponding damaged nerve (target nerve) of the far brain end, so that muscle movement is induced, and the motor function remodeling of the damaged nerve is realized. By using photoelectric combined stimulation, the invention improves the stimulation resolution ratio while reducing the tissue damage, and realizes accurate muscle movement control; meanwhile, the frequency of the photoelectric stimulation pulse is controlled according to the change of the nerve signal, the strength of the nerve signal is reflected in the stimulation frequency, and the explosion rate of the action potential of the neuron of the target nerve is controlled by controlling the frequency of the photoelectric stimulation pulse, so that the muscle is controlled to realize the movement of different degrees.
Description
Technical Field
The invention relates to the field of neural signal processing analysis and neural stimulation, in particular to a photoelectric stimulation pulse generation method and device.
Background
Nerve damage can cause the loss or reduction of the nerve-descending impulse, so that the muscle innervated by the damaged nerve can not complete the original contraction function, thereby losing the motor ability. The damaged nerve is stimulated through some stimulation pulses, so that the muscle can contract to a certain degree, normal autonomous movement is simulated to achieve the purposes of increasing the activity capability of limbs and recovering the functions of the stimulated muscle or muscle group, and the motor function of the damaged nerve can be remodeled.
Early neural stimulation for motor function remodeling mostly adopts a pulse sequence preset in a program, the stimulation mode is single, and the stimulation intensity cannot be adjusted according to neural signals, so that the control precision of muscles is low, and the muscles are easy to fatigue. In general, the intensity of the stimulated nerve to generate muscle movement can be adjusted by adjusting the intensity (stimulation width and amplitude) of the stimulation pulse and the frequency of the stimulation pulse, but most of the existing stimulation pulses control the muscle movement only by adjusting the stimulation intensity while the stimulation frequency is fixed, for example, the stimulation intensity parameter is proportionally adjusted by using the amplitude envelope or amplitude-related characteristics of the nerve signal, such as average absolute value, root mean square value and the like. The literature indicates that frequency modulation shows better performance in fatigue resistance than pulse width modulated stimulation. Therefore, the invention designs a neural stimulation pulse generation algorithm according to the characteristics of the neural signals, controls the frequency of the neural stimulation pulses according to the change of the neural signals, realizes the change of the stimulation frequency, and applies stimulation with the changed frequency to the damaged nerves, thereby enabling muscles to generate contraction motion with different strengths.
It is noted that the existing neural stimulation mostly uses a single electrical stimulation or a single laser stimulation. The single electrical stimulation is easy to control and quantify, but has low spatial resolution, and easily causes stimulation artifacts to target nerve cells; although the single laser stimulation has high spatial resolution, the energy is difficult to control, the target nerve is easy to cause thermal injury, and the literature indicates that the ratio of the tissue thermal ablation threshold to the activation threshold is only 2: 1 under the single laser stimulation, but the ratio can be improved to 6: 1 under the photoelectric combined stimulation, so that the biological safety is greatly improved.
Therefore, the invention starts from the characteristics of the action potential of the neuron, designs the neural stimulation pulse generation algorithm and the device according to the threshold characteristics of the action potential in the neural signal, adjusts the frequency of the neural stimulation pulse according to the change of the neural signal, realizes the change of the stimulation frequency, applies stimulation with the frequency change to the damaged nerve, and controls the muscle to realize the movement of different degrees. Meanwhile, the combined stimulation scheme of electrical stimulation and laser stimulation is adopted, so that the spatial resolution of the electrical stimulation can be improved, the selective stimulation to nerves can be realized, the required electrical stimulation energy and laser stimulation energy can be reduced, and the electrical injury and the thermal injury to the nerves can be reduced. Therefore, the nerve stimulation device has better biocompatibility, can stimulate nerves more accurately, and realizes more fine motor function remodeling.
Disclosure of Invention
The invention aims to realize motor function remodeling of damaged nerves, and provides a photoelectric stimulation pulse generation method and a device. The basic idea is that according to the nerve signal near the brain end of the damaged nerve, when the nerve signal exceeds a certain amplitude threshold value and meets the refractory period condition, a similar nerve pulse signal is used for stimulation on the damaged nerve (target nerve) at the corresponding far brain end, so that muscle movement is induced, and motor function remodeling of the damaged nerve is realized. The invention generates photoelectric stimulation pulse according to the amplitude information of the nerve signal and the sending rate information of the action potential, uses the photoelectric stimulation pulse for remodeling the motor function of the damaged nerve, and improves the stimulation resolution ratio while reducing the tissue damage by using photoelectric combined stimulation. Meanwhile, the frequency of the photoelectric stimulation pulse is controlled according to the change of the nerve signal, and the strength of the nerve signal is reflected in the stimulation frequency. Since the central nervous system can control the force output by two methods, the number of recruited motor neurons (recruitment code) and the action potential burst rate of the recruited motor neurons (burst rate code), when the muscle contracts autonomously. The invention controls the burst rate of action potential of the neuron of the target nerve by controlling the frequency of the photoelectric stimulation pulse, thereby controlling the muscle to realize the movement of different degrees.
Action potentials in neural signals are a triggering, explosive "all or nothing" event, i.e., when the stimulation signal acting on a neuron exceeds a neuron activation threshold, the neuron generates an action potential. The action potential has a definite activation threshold, once the action potential occurs, the amplitude and the duration of the action potential are not influenced by the strength and the duration of the stimulation, the action potential with larger amplitude cannot be generated by larger stimulation strength, and the action potential duration cannot be prolonged by longer stimulation duration. When an action potential is not completed, a stimulus is applied to the neuron again, and the neuron does not respond, which is called a refractory period. The invention designs a photoelectric stimulation pulse generation algorithm based on the characteristic of the neural signal.
The basic idea of the traditional electrical stimulation pulse generation algorithm is to calculate noise level estimation of a neural signal, a common noise level estimation method comprises standard deviation, root mean square, median absolute value and the like of the signal, then generally 3-5 times of the noise level estimation is taken as an amplitude threshold, then a sampling data point is compared with the amplitude threshold, and when the sampling data is larger than the amplitude threshold, an electrical stimulation pulse is generated. It will be appreciated that the amplitude threshold is used to identify whether the neural signal provided by the proximal cranial nerve has an action potential, and the neuron activation threshold is the threshold of the input signal that causes the neuron to generate an action potential. The core idea of the conventional electrical stimulation pulse generation algorithm is to detect an action potential in a neural signal through an amplitude threshold, and when the action potential is detected, an electrical stimulation pulse is generated. The traditional electrical stimulation pulse generation algorithm only considers the amplitude characteristic of a nerve signal, stimulation pulses are easily triggered by the fluctuation of the nerve signal or noise signals, and for dense nerve signals, dense stimulation pulses can be generated to stimulate nerves, so that muscles are easy to fatigue.
The traditional light stimulation pulse is generated by program presetting, stimulation parameters are determined by experience, information of nerve signals is not utilized, and therefore only fixed light stimulation can be realized.
The photoelectric stimulation pulse generation algorithm is designed based on the threshold characteristic and the refractory period characteristic of the neuron, and the basic idea of the photoelectric stimulation pulse generation algorithm is to generate photoelectric stimulation pulses for sampling points of preprocessed neural signals which exceed a specific amplitude threshold value outside the refractory period. For this reason, a refractory period condition and an amplitude threshold condition need to be satisfied.
The expression for the refractory period condition of the photostimulation pulse generation algorithm is as follows:
CNT＞TR (1)
in which CNT is the sample time count, TRThe refractory period is indicated. The expression of the formula means that when the sampling counting time is less than the refractory period, the former action potential of the nerve signal is not sent completely, and at the moment, no photoelectric stimulation pulse is generated; and when the sampling counting time is greater than the refractory period, judging whether the sampling signal meets the amplitude threshold condition.
The expression for the amplitude threshold condition of the photo-stimulation pulse generation algorithm is as follows:
where x (i) is the ith sampling signal, Thr is the amplitude threshold (generally 3-5 times the standard deviation estimate), and σnA is a constant for the estimated noise standard deviation. The meaning of the amplitude threshold condition expression is that if the sampled nerve signal x (n) meets the threshold requirement (equation (2)) at the ith moment and meets the constraint condition (equation (3)) of the first derivative, it indicates that an action potential exists at the moment, and therefore, a photoelectric stimulation pulse is output to stimulate the corresponding nerve. The expression (3) means that the amplitude threshold Thr is lower when the noise level of the neural signal is lower, and exceeds the thresholdThe stronger the signal rising trend of the amplitude threshold value is, the more likely the signal is to be an action potential, so the threshold value of the first derivative at the moment should be higher; as the noise level of the neural signal increases, the amplitude threshold Thr increases, and the rising trend is not too strong for action potentials exceeding the amplitude threshold, and therefore, the threshold of the first derivative should be lower at this time. Therefore, the first derivative threshold should be inversely proportional to the noise level estimate (i.e., the first derivative threshold should be inversely proportional to the noise level estimate
a is a constant). By introducing a first-order derivative (formula (3)), the defect that the traditional electric stimulation pulse generation algorithm only considers the action potential amplitude to cause false triggering and missed triggering is overcome to a certain extent, and a finer photoelectric stimulation pulse can be generated to obtain more accurate motion response.
As can be seen from the above-mentioned algorithm for generating the photo-stimulation pulses, the parameters to be determined by the algorithm include an amplitude threshold and a refractory period. The refractory period is determined by the characteristics of neurons, and is generally 2ms to 20 ms. The selection of the amplitude threshold requires two points of attention: firstly, the algorithm is required to be ensured not to generate wrong stimulation signals due to neural signal background noise; second, since the amplitude of the neural signal increases as the force of the movement increases, the amplitude threshold needs to be selected according to the amplitude of the neural signal. In the invention, the frequency of the photoelectric stimulation pulse is controlled according to the change of the nerve signal, so that the characteristics of the action potential explosion rate under different force degrees can be reflected.
Conventional amplitude thresholding methods include the median absolute value thresholding method and the root mean square thresholding method.
The median absolute value threshold method uses a fixed threshold approach, in which the signal noise level is approximated by the following equation:
wherein, x (i), i ═ 1, 2.., n is the ith sampling point in the sampled neural signal, and n is the sliding window length. Calculation of amplitude thresholdCan be based on an approximate estimate sigma of the signal noise levelnThe algorithm is obtained by multiplying a certain threshold gain proportionality coefficient, and the absolute value median of the whole section of input signals needs to be calculated, so that the algorithm is generally only used for off-line analysis and cannot be applied to on-line and low-power-consumption embedded systems and the like.
The rms threshold method uses a dynamic threshold method, which calculates the rms of the sampling points in a sliding window of finite length as the noise level estimate of the signal, as follows:
wherein, x (i), i ═ 1, 2.., n is the ith sampling point in the sampled neural signal, and n is the sliding window length. Estimation x from signal noise levelRMSAnd multiplying by a certain threshold gain proportion coefficient to obtain the amplitude threshold corresponding to the current sampling point.
However, when the noise level of the signal is estimated by the above method, the signal itself contains not only the noise signal but also the action potential signal, which results in a high noise estimation of the signal. Especially, in the case of a high neuron firing frequency, the estimation error is larger. Thus, the present invention uses a closed-loop feedback adaptive dynamic threshold method to estimate the amplitude threshold, Thr.
The closed-loop feedback adaptive dynamic threshold method estimates the standard deviation level of noise in neural signals through the statistical properties of normal distributions. The basic idea is to indirectly obtain the noise level of the signal by calculating the standard deviation estimation of the sampled neural signal in a finite length sliding window, and then dynamically adjust the amplitude threshold value in real time according to different noise levels. The principle of the method is as follows: because the probability density function of gaussian noise follows normal distribution, the background noise in the neural signal can be treated as gaussian white noise under normal conditions, and the amplitude of the gaussian white noise is smaller than one standard deviation (sigma) of the gaussian white noise as known from the normal distribution probability density functionn) The probability of (c) is 31.76%. Thus, 31.76% may be set as the targetTaking absolute value of data point x (k) sampled at time k, sending the absolute value to comparator, if absolute value of x (k) is less than standard deviation estimation sigma at last timen(k-1), the comparator outputs 1, otherwise 0 is output, namely the output of the comparator can be regarded as a 0-1 sequence, the probability D '(k) that the current sampling data falls within one time of standard deviation can be obtained by calculating the ratio of 1 in the 0-1 sequence in a finite length sliding window, D (k) and D' (k) are subjected to subtraction, and an estimated error value E (k) and a new signal standard deviation estimation sigma can be obtained according to the following formulan(k) And a new amplitude threshold Thr:
wherein K is the kth sampling moment, G is the integrator gain, T is the signal sampling period, KthThe gain is a threshold gain proportionality coefficient, and generally takes 3-5 times. The closed-loop feedback self-adaptive dynamic threshold method only needs one addition, one subtraction and three multiplications for each operation, greatly reduces the operation amount and is beneficial to online realization.
As can be seen from the photoelectric stimulation pulse generation algorithm, within a period of time (action potential refractory period), the photoelectric stimulation pulse is generated only once for the sampling signal meeting the amplitude threshold condition, namely when one action potential is not completed, the nerve is not stimulated, and the defects that the traditional electric stimulation pulse generation algorithm is easy to trigger the stimulation pulse for the fluctuation of the nerve signal and the error trigger of the noise signal are overcome, so that the stimulation frequency for the nerve is reduced, and the method has obvious advantages in the aspect of nerve fatigue resistance.
If the voltage excitation mode is adopted, the injected charge is difficult to control due to the change of the impedance of the nerve tissue. Based on the current excitation mode, the injection amount of the charges can be controlled, and the stimulation mode of balancing the positive charges and the negative charges is facilitated, so that the damage to tissues is reduced. Preferably, therefore, the electrical stimulation pulses used in the present invention are biphasic charge-balanced asymmetric current pulses, which are divided into two phases: the stimulation stage and the recovery stage, the stimulation stage is used for exciting the tissue to be excited by negative pulses so as to generate action potential; the main function of the recovery phase is to cancel the accumulated charges with a positive pulse to prevent tissue damage.
Preferably, the optical stimulation pulses used in the present invention are 808nm infrared light pulses. In the present invention, the optical stimulation pulse can be regarded as a PWM wave with a duty ratio of 100%, the optical stimulation is started at the same time of the electrical stimulation output, and the optical stimulation is ended at the same time of the electrical stimulation.
Preferably, the amplitude of the optical stimulation pulse is 90% (i.e., 90% of the optical stimulation threshold) of the minimum stimulation intensity that the nerve can be activated to produce an action potential when the optical stimulation is used alone; the electrical stimulation amplitude is related to the diameter of the target nerve, with a large diameter nerve requiring a small electrical stimulation threshold and a small diameter nerve requiring a large electrical stimulation threshold. By using photoelectric combined stimulation, the electrical stimulation activation threshold of the target nerve is reduced by using subthreshold light stimulation (90% of the optical stimulation threshold when the target nerve is singly stimulated), and then the nerve is activated by using subthreshold electrical stimulation (smaller than the electrical stimulation threshold when the target nerve is singly stimulated), so that the energy required by single electrical stimulation or optical stimulation is reduced, the electrical injury and the thermal injury to the nerve are relieved, and the stimulation safety is better.
Preferably, the device for operating the above-mentioned algorithm for generating the photo-stimulation pulses mainly comprises two modules: the neural stimulation device comprises a neural signal sampling module and a neural stimulation module. The nerve signal sampling module samples the nerve signals from the brain-proximal end of the damaged nerve mainly through the detection electrode, and then sends the nerve signals into the microprocessor to run a photoelectric stimulation pulse generation algorithm after the nerve signals are subjected to amplification, filtering, analog-to-digital conversion and the like. The photo-stimulation pulse generation algorithm is implemented by a program running, for example, on a microprocessor. The nerve stimulation module is controlled by the sampled nerve signals to generate photoelectric stimulation pulses to stimulate the far brain end of the corresponding damaged nerve, and the nerve at the far brain end enables the corresponding muscle to act. For ease of expression, the proximal cranial nerve of the neural signal being sampled is also referred to as the sampled nerve; the distal brain nerve to which the photoelectric stimulation pulse is applied is also referred to as the stimulated nerve. The device mainly comprises the following parts:
(1) the pre-amplification module is used for amplifying the sampling neural signals;
(2) the filtering module comprises a low-pass filter, a high-pass filter and a 50Hz wave trap and is used for filtering low-frequency interference such as polarization voltage and the like, high-frequency interference such as myoelectricity and/or inherent noise of an electronic device and 50Hz power frequency noise;
(3) an analog-to-digital converter (AD) for converting the neural signal subjected to amplification and filtering pretreatment into a digital signal;
(4) a Microprocessor (MCU) for controlling neural signal sampling and running a photoelectric stimulation pulse generation algorithm;
(5) the digital-to-analog converter (DA) is controlled by the microprocessor to generate a photoelectric stimulation pulse control signal;
(6) the voltage-current conversion circuit is used for converting a photoelectric stimulation pulse control signal generated by a digital-to-analog converter (DA) into a current signal for generating an electric stimulation constant current pulse and controlling a laser element to output a light stimulation pulse; optionally, the optical-to-electrical stimulation pulse control signal of the digital-to-analog converter (DA) directly drives the laser device to output the optical stimulation pulse.
(7) A laser output element for outputting optical stimulation pulses;
(8) the detection electrode is used for detecting a neural signal of the damaged nerve at the near-brain end;
(9) a stimulation electrode for delivering electrical stimulation pulses to a target nerve;
(10) a stimulating optode for delivering optical stimulation pulses to the target nerve.
Preferably, the pre-amplification module of the device is a differential amplifier, and common-mode interference in signals is suppressed through differential input;
preferably, the low-pass filter and the high-pass filter in the filtering module of the device are second-order active filters;
preferably, the analog-to-digital converter (AD) of the apparatus is a high-speed synchronous sampling ADC to realize high-speed sampling of the neural signal;
preferably, the Microprocessor (MCU) of the above device should support floating point arithmetic and have a large running memory to run the photo-electro stimulation pulse generation algorithm;
preferably, the digital-to-analog converter (DA) of the above device should be a high-speed DAC with at least two-channel output, and support independent programming of each output channel to regulate and control the electrical stimulation output pulse and the optical stimulation output pulse respectively;
preferably, the voltage-current conversion circuit of the device is designed based on an active operational amplifier, and can convert voltage input into current output;
preferably, the laser output element of the device is a current-mode laser, i.e. a laser with light output power regulated by current, so as to be compatible with the voltage-current output circuit of the device and conveniently control the photostimulation output pulse;
preferably, the detection electrode and the stimulation electrode of the device can be biocompatible electrodes such as a skin-clamping electrode or a needle electrode, and the like, so as to be attached to a nerve to acquire an effective nerve signal or perform electrical stimulation;
preferably, the stimulation optode of the above device may be a hydrogel optode having excellent light guiding properties or a small-diameter optical fiber to efficiently deliver light stimulation pulses to the target nerve.
Compared with the prior art, the invention has the following innovation points:
(1) the invention provides a photoelectric stimulation pulse generation method and device. The method takes the threshold characteristic and the refractory period characteristic of the neuron into consideration, controls the frequency of the photoelectric stimulation pulse according to the change of the neural signal, and reflects the strength of the neural signal in the stimulation frequency. By controlling the frequency of the photoelectric stimulation pulse, the burst rate of action potential of the neuron of the target nerve can be controlled, and further the response intensity of the muscle is controlled, so that the muscle can realize different degrees of movement.
(2) The constraint condition of the first derivative is introduced on the basis of the traditional electrical stimulation pulse generation algorithm, the first derivative of the neural signal reflects the change trend of the neural signal, when the signal noise level is low, the amplitude threshold value is low, the stronger the rising trend of the signal exceeding the amplitude threshold value is, the more possible the signal is the action potential, and therefore the threshold value of the first derivative is high; as the noise level increases, the amplitude threshold increases, and the rising trend is not too strong for action potentials that exceed the amplitude threshold, and therefore the threshold for the first derivative at this time is lower. By introducing the first derivative, the defect that the traditional electric stimulation pulse generation algorithm only considers the action potential amplitude to cause false triggering and missed triggering is overcome to a certain extent.
(3) The method can dynamically adjust the amplitude threshold according to the change of the neural signal background noise, and overcomes the defect of large error of the traditional threshold estimation method to a certain extent, so that a photoelectric stimulation pulse generation algorithm based on the amplitude threshold can generate more accurate stimulation pulses according to the neural signal.
(4) The nerve stimulation pulse adopts the photoelectric combined stimulation pulse, so that the spatial resolution of electrical stimulation can be improved, the selective stimulation to nerves can be realized, the required electrical stimulation energy and laser stimulation energy can be reduced, and the electrical injury and thermal injury to the nerves can be reduced. Therefore, the nerve stimulation device has better biocompatibility, can stimulate nerves more accurately, and realizes more fine motor function remodeling.
Drawings
Fig. 1 is a schematic diagram of an application of the inventive photo-stimulation pulse generation algorithm.
Fig. 2 is a photo-stimulation pulse generation apparatus according to an embodiment of the present invention.
Fig. 3 is an internal block diagram of the photo-stimulation pulse generation apparatus according to the embodiment of the present invention.
FIG. 4 is a waveform diagram of a photo-stimulation pulse according to an embodiment of the present invention.
FIG. 5 is a block diagram of an amplitude threshold estimation by the closed-loop feedback adaptive dynamic threshold method of the present invention.
Fig. 6 is a flowchart of an implementation of the closed-loop feedback adaptive dynamic threshold method for estimating an amplitude threshold in a microprocessor according to an embodiment of the present invention.
Fig. 7 is a flow chart of a photo-stimulation pulse generation algorithm according to an embodiment of the present invention.
Fig. 8 shows an application example of the photo-stimulation pulse generation algorithm and device of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and examples.
Fig. 1 is a schematic diagram of an application of the inventive photo-stimulation pulse generation algorithm.
Referring to fig. 1, the present invention samples a neural signal near a brain end of an injured nerve, performs a filtering preprocessing on the neural signal with a sliding window, for example, band-pass filtering the neural signal with an IIR digital band-pass filter (infinite impulse response filter), the passband of which is 10Hz to 3kHz, estimates an amplitude threshold value in the sliding window by using a closed loop feedback adaptive dynamic threshold method, and generates a photoelectric stimulation pulse signal to stimulate the injured nerve (target nerve) at a corresponding far brain end when the sampled neural signal exceeds the amplitude threshold value and meets a refractory period condition, so as to induce muscle movement and achieve motor function remodeling of the injured nerve. On one hand, the photoelectric combined stimulation is used, so that the stimulation resolution is improved while the tissue damage is reduced; on the other hand, the frequency of the photoelectric stimulation pulse is controlled according to the change of the nerve signal, the intensity of the nerve signal is reflected in the stimulation frequency, so that the burst rate change of the action potential of the neuron of the target nerve is controlled through the change of the frequency of the photoelectric stimulation pulse, and the muscle is controlled to generate different degrees of movement response.
Fig. 2 and 3 are block diagrams of a photo-stimulation pulse generation device and its internal block diagram according to an embodiment of the present invention.
Referring to fig. 2, the optoelectronic stimulation pulse generating device integrates the various modules into a protective case based on, for example, an integrated chip design. Leading out the input ends (ports 1 and 2) of detection electrodes of a neural signal sampling module and a neural stimulation module and the output ends (ports 3-6) of a voltage-current conversion circuit, wherein the input ends (ports 1 and 2) of the detection electrodes are externally connected with the detection electrodes 1 and 2 and are used for detecting neural signals; one part (port 3 and port 4) of the output end of the voltage-current conversion circuit is connected with the stimulating electrode 1 and the stimulating electrode 2 and is used for outputting an electrical stimulation pulse; the other part (port 5 and port 6) is connected with a laser output element, and the output end of the laser output element is connected with a stimulation optode so as to output optical stimulation pulses.
Referring to fig. 3, the photoelectric stimulation pulse generation apparatus has a working process that a nerve signal is sampled from a brain-proximal end of a damaged nerve through a detection electrode, the nerve signal is amplified, filtered, subjected to analog-to-digital conversion and the like, and then sent to a microprocessor, the microprocessor performs digital filtering on the sampled nerve signal to perform interference suppression, and operates a photoelectric stimulation pulse generation algorithm, and a digital-to-analog converter outputs a voltage of a corresponding magnitude according to an algorithm result. Because the electrical stimulation pulse is a constant current pulse, the output voltage needs to be converted into current through the voltage-current conversion circuit and then output. The photostimulation output is provided by the laser output element. The laser output element adopts a current control type laser, and the laser output power can be adjusted according to the input current, so that the laser output element is compatible with the device disclosed by the invention, and the modulation of laser pulses can be better realized.
FIG. 4 is a waveform diagram of a photo-stimulation pulse according to an embodiment of the present invention.
Referring to fig. 4, in the present embodiment, the optical stimulation pulses are 808nm infrared light pulses, and the single pulse is a PWM wave with 100% duty cycle, for example, the forward pulse width is 500us, and the total length of the wave is 500 us; the electrical stimulation pulses are biphasic charge-balanced asymmetric current pulses, for example, the ratio of the amplitude of the stimulation phase to the amplitude of the recovery phase of a single pulse is 4: 1, the ratio of the duration is 1: 4, the pulse width of the stimulation phase is 100us, the pulse width of the recovery phase is 400us, and the total length of the waveform is 500 us. The photo-stimulation pulses are simultaneously started and stopped. In the single stimulation process, the light stimulation intensity is unchanged, and the nerve tissue is always irradiated to reduce the electrical stimulation threshold; the electrical stimulation firstly stimulates nerve tissues through negative-going pulses to induce action potentials, and then counteracts accumulated charges through positive-going pulses to prevent tissue damage.
Fig. 5 is a block diagram of an amplitude threshold value estimated by the closed-loop feedback adaptive dynamic threshold value method of the present invention, and fig. 6 is a flowchart of an implementation of the amplitude threshold value estimated by the closed-loop feedback adaptive dynamic threshold value method in a Microprocessor (MCU) according to an embodiment of the present invention.
Referring to fig. 5, the basic principle of the closed-loop feedback adaptive dynamic threshold method for estimating the amplitude threshold is to make the amplitude of white gaussian noise less than one standard deviation (σ) of the white gaussian noisen) The probability of (k) is set as a target value D (k), a finite length sliding window is set, the absolute value of the neural signal x (k) sampled at the k-th moment is taken and sent to a comparator, and if the absolute value of x (k) is smaller than the standard deviation estimation sigma at the last momentn(K-1), the comparator outputs 1, otherwise 0 is output, i.e. the output of the comparator can be regarded as a 0-1 sequence, the 0-1 sequence is passed through a decoder (essentially a bit counter), the ratio D ' (K) of 1 in the 0-1 sequence is calculated, D ' (K) represents the probability that the current sampling data falls within one time of standard deviation, D (K) and D ' (K) are differenced to obtain E (K), E (K) is passed through an integrator to obtain a new standard deviation estimate, and the standard deviation estimate is multiplied by a threshold gain proportionality coefficient KthThe amplitude threshold estimate Thr at that sampling instant is obtained.
Referring to fig. 6, the flow of implementing the closed-loop feedback adaptive dynamic threshold method to estimate the amplitude threshold in the MCU is to set the length of the sliding window to L (in this embodiment, L is 128, i.e., the length of the comparator output buffer is 128), and p (k) is a bit counter (bitcounter), which holds the number of 1 in the sliding window at the kth time. Every time a new datum is sampled, the sliding window is moved by one bit, the form of a queue is similar, the oldest datum (the first datum) is deleted, the new datum is added, then P (k) in the sliding window is recalculated, D' (k) ═ P (k)/L is calculated, and finally standard deviation estimation and updating of the amplitude threshold value Thr are carried out. Through the process flow of fig. 6, the calculations of the above equations (6), (7), and (8) are completed, and the sampled neural signal x is filled into the sliding window as the latest data (e.g., the lth position of the sliding window) at the update comparator output buffer step.
Fig. 7 is a flow chart of a photo-stimulation pulse generation algorithm according to an embodiment of the present invention.
In this embodiment, the method of closed-loop feedback adaptive dynamic threshold is first used to estimate the thresholdSetting a refractory period T by an amplitude threshold value in a pre-sliding time windowR(depending on the response characteristics of the target neuron). Subsequently, the photo-stimulation pulses are generated in accordance with a photo-stimulation pulse generation algorithm. Referring to FIG. 7, out _ flag indicates an output flag, which is initially 0, out _ len indicates the current output pulse position, which is initially 0, neg _ width indicates the electrical stimulation negative pulse width, pulse _ len indicates the total length of the stimulation pulse, CNT is time count, and CNT > T at initializationR. The photo-stimulation pulse generation algorithm may be implemented based on a timer interrupt service routine of the MCU, setting the timer interrupt period to 100us, i.e., sampling the neural signal using a 10kHz sampling rate.
Referring to FIG. 7, in response to a timer interrupt occurring, an interrupt service routine is entered through an interrupt service routine entry. In the interrupt service program, after AD conversion is performed on sampled neural signal data (to obtain sampled data x (i)), an output flag out _ flag is firstly judged, if the output flag out _ flag is in an output state (out _ flag is 1), an optical electrostimulation pulse is output, otherwise, a count value CNT is judged to see whether the count value CNT meets a refractory period condition (see formula (1)) or not, and if CNT is more than TRIt is further determined whether the sampled neural signal values satisfy an amplitude threshold condition (see also equations (2) and (3)). When the refractory period condition and the amplitude threshold condition are simultaneously met, the system sets an output flag to be 1(out _ flag is equal to 1), simultaneously clears a count value (CNT is equal to 0), enters an optical electrical stimulation pulse output state, starts optical stimulation waveform output and negative output of an electrical stimulation pulse, and increases the output pulse position progressively (out _ len + +). And after outputting the negative-going waveform of the electrical stimulation pulse, outputting the positive-going waveform of the electrical stimulation pulse. The respective lengths of the negative and positive waveforms of the electrical stimulation pulse are controlled by neg _ width and pulse _ len. When the forward waveform output of the electrical stimulation pulse is finished, the optical stimulation output and the electrical stimulation output are simultaneously closed, an output flag is set to be 0(out _ flag is 0), and the output pulse position is reset (out _ len is 0). If CNT < TROr the sampled neural signal value does not meet the amplitude threshold condition, no photoelectric stimulation pulse is generated. The photoelectric stimulation pulse is output at most once in a refractory period. Therefore, when the neuron is in a resting state, the neural signal is relatively stableThe detected action potential sending frequency is low, and the stimulation pulse frequency generated by the algorithm is low; when the neuron is in a motion state, the detected action potential emission frequency is high, and thus, the generated stimulation pulse frequency is high. By controlling the frequency of the photoelectric stimulation pulses, the burst rate of action potential of neurons of the target nerve can be controlled, and further the response intensity of muscles can be controlled. Since the interrupt period is 100us, the system can output effective stimulation pulse width of integral multiple of 100 us.
The burst rate means that when the muscle contracts autonomously, the central nervous system can control the force output by two methods, the number of recruited motor neurons (recruitment code) and the burst rate of action potentials of the recruited motor neurons (burst rate code). The stimulation frequency of the photoelectric stimulation pulse is dynamically adjusted according to the sending rate of action potential in the nerve signal of the brain-proximal end of the damaged nerve, and under the stimulation of different frequencies, the response effect of the target nerve is different. When the detected action potential in the nerve signal is high in sending rate, the stimulation frequency of the generated photoelectric stimulation pulse is high, and the stimulation frequency of the photoelectric stimulation pulse is high at the moment, so that the action potential outbreak rate of the neuron of the target nerve is high, and the muscle movement strength is high. Thus by controlling the frequency of the electro-optical stimulation pulses the strength of the muscle response can be controlled.
Fig. 8 is an application example of the photo-stimulation pulse generation algorithm of the present invention.
Referring to fig. 8, fig. 8 is an example of applying the inventive photostimulation pulse generation algorithm to a neural signal acquired over a segment of a nerve. In this example, the amplitude threshold is first estimated using a closed-loop feedback adaptive dynamic threshold method with the threshold gain scaling factor set to 4 times (i.e., K)th4), a refractory period T is setRThen, the above-described photo-stimulation pulse generation algorithm is applied to generate the photo-stimulation pulses for 5 ms. It can be seen that, for the time when the sampled neural signal exceeds the amplitude threshold and meets the first derivative condition and the refractory period condition, the photoelectric stimulation pulse can be generated; for the time when the sampled neural signal exceeds the amplitude threshold but does not satisfy the first derivative condition or the refractory period conditionNo photo-electric stimulation pulses are generated. The optical stimulation pulse waveform and the electrical stimulation pulse waveform are waveforms shown in fig. 4. For the sampling time which meets the amplitude threshold condition for a plurality of times due to nerve signal fluctuation or noise disturbance in a short time (refractory period), only one photoelectric stimulation pulse is generated under the photoelectric stimulation pulse generation algorithm of the invention, the effectiveness of the generated photoelectric stimulation pulse is ensured, and simultaneously the stimulation to the nerve is reduced, thereby reducing the electrical injury and the thermal injury to the nerve and having better biocompatibility.
Claims (10)
1. A method of optoelectronic stimulation pulse generation, comprising:
acquiring a plurality of sampling data of a neural signal of a first sampling nerve;
if a plurality of sampling data of the nerve signal of the first sampled nerve satisfy the refractory period condition and a first sampling data (x (i)) and a second sampling data (x (i-1)) of the plurality of sampling data satisfy the amplitude threshold condition, generating a light stimulation pulse and an electrical stimulation pulse for simultaneously stimulating the first stimulated nerve, wherein the amplitude of the light stimulation pulse is smaller than the light stimulation threshold of the first stimulated nerve, and the amplitude of the electrical stimulation pulse is smaller than the electrical stimulation threshold of the first stimulated nerve.
2. The method of optoelectronic stimulation pulse generation as in claim 1, wherein the refractory period condition is expressed by:
CNT＞TR
wherein CNT is the value of a timer started after the last simultaneous generation of the optical stimulation pulse and the electrical stimulation pulse for the first stimulated nerve, and TRIs a designated refractory period.
3. The method of optoelectronic stimulation pulse generation according to claim 2, wherein the amplitude threshold condition is expressed by:
wherein x (i) is a first sample data of the plurality of sample data, x (i-1) is a second sample data of the plurality of sample data, the first sample data x (i) is greater than an amplitude threshold Thr, the second sample data x (i-1) is less than the amplitude threshold Thr, and a first derivative of the first sample data x (i) and the second sample data x (i-1) is greater than a first derivative threshold
Wherein the first sample data and the second sample data are respectively ith sample data and (i-1) th sample data which are adjacently sampled, i is a positive integer, Thr is an amplitude threshold, and σ isnFor noise standard deviation estimation, a is a constant.
4. The optoelectronic stimulation pulse generation method as recited in claim 3, wherein the amplitude threshold Thr is estimated using a closed-loop feedback adaptive dynamic threshold method:
the closed-loop feedback adaptive dynamic threshold method comprises the following steps: setting 31.76% as a target value D (k), taking the absolute value of the nerve signal data point x (k) of the first sampling nerve sampling at the k time, sending the absolute value to a comparator, and if the absolute value of x (k) is less than the noise standard deviation estimation sigma at the last timen(k-1), the comparator outputs 1, otherwise 0, the ratio of '1' in the '0-1' sequence output by the comparator in the finite length sliding window is calculated to obtain the probability D '(k) that the sampling data at the k-th moment falls within one time of noise standard deviation estimation, D (k) and D' (k) are subjected to subtraction, and an estimation error value E (k) and an updated noise standard deviation estimation sigma can be obtained according to the following formulan(k) And the updated amplitude threshold Thr:
wherein K is the kth sampling moment, G is the integrator gain, T is the signal sampling period, KthIs a threshold gain scaling factor.
5. A photoelectric stimulation pulse generation device comprises a neural signal sampling module and a neural stimulation module; the nerve signal sampling module samples a nerve signal from a first sampling nerve through the detection electrode, and the sampled nerve signal is amplified, filtered and subjected to analog-to-digital conversion to obtain sampling data; the neural signal sampling module also provides the sampled data to the neural stimulation module; the nerve stimulation module generates photoelectric stimulation pulses according to the sampling data provided by the nerve signal sampling module to control photoelectric stimulation applied to the first stimulated nerve.
6. The optoelectronic stimulation pulse generating device according to claim 5, the neural signal sampling module comprises a detection electrode, a pre-amplification module, a filtering module and an analog-to-digital converter (AD); the nerve stimulation module comprises a Microprocessor (MCU), a digital-to-analog converter (DA), a voltage-current conversion circuit, a laser output element, a stimulation electrode and a stimulation photoelectrode.
7. The optoelectronic stimulation pulse generating device as claimed in claim 6, wherein the pre-amplifying module is a differential amplifier for suppressing common-mode interference in the sampled neural signal through differential input and amplifying the sampled neural signal;
the filtering module comprises a second-order active low-pass filter, a second-order active high-pass filter and a 50Hz power frequency trap and is used for filtering high-frequency interference, low-frequency interference and 50Hz power frequency interference in the neural signals, wherein the high-frequency interference comprises intrinsic noise of a muscle and/or an electronic device, and the low-frequency interference comprises polarization voltage;
the analog-to-digital converter (AD) is a high-speed synchronous sampling ADC (analog-to-digital converter) so as to realize high-speed sampling of the neural signals and convert the neural signals into digital signals;
the Microprocessor (MCU) runs a program to perform the method of optoelectronic stimulation pulse generation according to one of claims 1-4;
the digital-to-analog converter (DA) comprises at least two output channels, and each output channel respectively regulates and controls an electrical stimulation output pulse and an optical stimulation output pulse;
the voltage-current conversion circuit converts a voltage input provided by the digital-to-analog converter (DA) into a current output;
the laser output element controls the light stimulation output pulse according to the output of the voltage-current conversion circuit;
the detection electrode and the stimulation electrode are biocompatible electrodes;
the laser is hydrogel optode or small-caliber optical fiber.
8. The optoelectronic stimulation pulse generating apparatus according to claim 7, wherein all modules are disposed in a protection box, and the input ends of the neural signal sampling module and the detection electrode of the neural stimulation module and the output end of the voltage-current conversion circuit are led out, and the input ends of the detection electrode are externally connected with a detection electrode 1 and a detection electrode 2 for collecting neural signals; the output port 3 and the port 4 of the voltage-current conversion circuit are connected with the stimulating electrode 1 and the stimulating electrode 2 and used for outputting an electrical stimulation pulse; the output port 5 and the port 6 of the voltage-current conversion circuit are connected with a laser output element, and the output end of the laser output element is connected with a stimulation photoelectrode so as to output photostimulation pulses.
9. The optoelectronic stimulation pulse generating device according to one of claims 5-8, wherein:
the light stimulation pulse is a PWM wave with 100% duty cycle, and the amplitude of the light stimulation pulse is 90% of the minimum stimulation intensity capable of activating the first stimulation nerve to generate action potential;
the electrical stimulation pulse is a biphasic charge-balanced asymmetric current pulse, which is divided into two phases: the stimulation stage and the recovery stage, the stimulation stage is used for exciting the first stimulation nerve to be excited by negative pulses so as to generate action potentials; the main function of the recovery stage is to counteract the accumulated charges by positive pulses, so as to prevent the first stimulated nerve from being damaged; the amplitude of the electrical stimulation pulse is inversely related to the diameter of the first stimulated nerve.
10. The optoelectronic stimulation pulse generating device as claimed in claim 9, wherein the outputs of the optical stimulation pulse and the electrical stimulation pulse are started simultaneously and stopped simultaneously; in the single stimulation process, the light stimulation intensity is unchanged, and the first stimulation nerve is always irradiated to reduce the electrical stimulation threshold; the electrical stimulation firstly stimulates the first stimulated nerve through negative-going pulse to induce action potential, and then counteracts accumulated charges through positive-going pulse to prevent the first stimulated nerve from being damaged.
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