CN113209469A - Signal extraction method under deep intracerebral stimulation DBS equipment discharge intervention state - Google Patents
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Abstract
The invention discloses a signal extraction method and a signal extraction system under the discharge intervention state of deep intracerebral stimulation DBS equipment. The method comprises the following steps: acquiring a dot matrix signal acquired by using a nerve probe and a DBS discharge signal of deep intracerebral stimulation DBS equipment in a discharge intervention state; integrating the lattice signals transmitted inside the nerve probe, and performing analog-to-digital conversion on the integrated lattice signals and DBS discharge signals to obtain high-frequency digital signals; decoding the high-frequency digital signal to obtain a neural lattice signal and a DBS intervention signal, and performing electromagnetic field calculation after restoring the DBS intervention signal; and comparing the position of the electromagnetic field calculation result with the position of the neural lattice signal, and removing noise according to the comparison result to obtain a pure neural signal. The invention can remove interference signals in the mixed signals acquired when the DBS equipment intervenes in discharging, and realizes the intensity calculation and observation of the brain nerve signals.
Description
Technical Field
The invention relates to the technical field of signal processing, in particular to a signal extraction method and a signal extraction system under the discharge intervention state of deep intracerebral stimulation DBS equipment.
Background
Deep Brain Stimulation (DBS): the electrode is mainly implanted into the brain of a patient, a pulse generator is used for stimulating certain nerve cores at the deep part of the brain of the patient, and abnormal large brain electrical circuits are corrected, so that the symptoms of the nerve aspects are relieved. Unlike some treatment methods (destruction or radiotherapy) that permanently irregulable and irreversibly damage the brain, DBS does not destroy brain structure and may allow future further treatment. The diseases treatable and interventionalised by DBS mainly include: parkinson's disease, essential tremor, dystonia disease, epilepsy, obsessive compulsive disorder, anorexia, senile dementia and the like. The stimulated brain region is generally in the middle brain and around the ventricle.
The brain neural signals acquired during DBS intervention are characterized by signal clutter and difficult discrimination, which is a confounding signal. The cortical position of the implanted DBS device electrodes, the acquired signal is more refined than EEG signals, and the noise and resolution and bandwidth are insufficient compared to signals acquired by the implanted brain-computer interface recognizing nerve fibers. In summary, DBS devices in the intervening discharge state disturb the brain's own nervous system electrical signals.
At present, in the discharging intervention process of DBS equipment, no mature method can avoid interference and extract pure electroencephalogram signals, so that the intensity of brain nerve signals is difficult to calculate and observe.
Disclosure of Invention
The invention aims to provide a signal extraction method and a signal extraction system under the discharge intervention state of deep intracerebral stimulation DBS equipment, which realize the calculation and observation of the strength of brain nerve signals in the discharge intervention process of the DBS equipment by acquiring, transmitting and processing brain self-body electric signals.
In order to solve the above technical problem, in one aspect, the present invention provides a signal extraction method in a deep intracerebral stimulation DBS device discharge intervention state, including:
acquiring a dot matrix signal acquired by using a nerve probe and a DBS discharge signal of deep intracerebral stimulation DBS equipment in a discharge intervention state;
integrating the lattice signals transmitted inside the nerve probe, and performing analog-to-digital conversion on the integrated lattice signals and DBS discharge signals to obtain high-frequency digital signals;
decoding the high-frequency digital signal to obtain a neural lattice signal and a DBS intervention signal, and performing electromagnetic field calculation after restoring the DBS intervention signal;
and comparing the position of the electromagnetic field calculation result with the position of the neural lattice signal, and removing noise according to the comparison result to obtain a pure neural signal.
The invention also provides a signal extraction system under the discharge intervention state of the deep intracerebral stimulation DBS equipment, which is used for realizing the method and comprises the following steps:
the signal collection subsystem is used for acquiring a dot matrix signal acquired by using a nerve probe and a DBS discharge signal of the deep intracerebral stimulation DBS equipment in a discharge intervention state;
the signal preprocessing subsystem is used for integrating the lattice signals transmitted inside the nerve probe and performing analog-to-digital conversion on the integrated lattice signals and DBS discharge signals to obtain high-frequency digital signals;
the analysis and calculation subsystem is used for decoding the high-frequency digital signal to obtain a neural lattice signal and a DBS intervention signal, and performing electromagnetic field calculation after the DBS intervention signal is restored;
and the interference removal subsystem is used for comparing the position of the electromagnetic field calculation result with the position of the neural lattice signal and removing noise according to the comparison result to obtain a pure neural signal.
According to the signal extraction method and system under the discharge intervention state of the deep intracerebral stimulation DBS equipment, the neural probe is used for carrying out dot matrix signal collection, the collected signals are integrated, internally transmitted, subjected to analog-to-digital conversion, decoded and subjected to signal reduction, an electromagnetic field model is combined to measure the interference change of DBS discharge intensity on the brain nervous system discharge, and finally, pure neural signals are obtained through result comparison. The invention can remove interference signals in the mixed signals acquired when the DBS equipment intervenes in discharging, and realizes the intensity calculation and observation of the brain nerve signals.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic working flow diagram of a signal extraction method in a deep intracerebral stimulation DBS device discharge intervention state according to the present invention;
fig. 2 is a schematic application flow diagram of a signal extraction method in a deep intracerebral stimulation DBS device discharge intervention state provided by the present invention;
FIG. 3 is a schematic diagram of a metrology model algorithm provided by the present invention; and
fig. 4 is a schematic block diagram of a signal extraction system in a deep intracerebral stimulation DBS device discharge intervention state provided by the present invention.
Detailed Description
The core of the invention is to provide a signal extraction method and a signal extraction system under the discharge intervention state of a deep intracerebral stimulation DBS device, so that interference signals are removed from mixed signals obtained when the DBS device intervenes in discharge, and the intensity calculation and observation of brain nerve signals are realized.
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a signal extraction method under the discharge intervention state of deep intracerebral stimulation DBS equipment. As shown in fig. 1, the method includes:
step S101: when a nerve probe is used for carrying out dot matrix signal acquisition, dot matrix signals under the discharge intervention state of deep intracerebral stimulation DBS equipment are obtained;
step S102: integrating the dot matrix signals after internal transmission, performing analog-to-digital conversion on the integrated dot matrix signals to obtain high-frequency digital signals, and transmitting the high-frequency digital signals to an analysis and calculation subsystem;
step S103: the analysis and calculation subsystem decodes the high-frequency digital signal, and performs electromagnetic field calculation after restoring the interference signal by utilizing deep intracerebral stimulation DBS;
step S104: and comparing the electromagnetic field calculation result with the position of the lattice signal, and removing noise according to the comparison result to obtain a pure neural signal.
According to the invention, the neural probe is used for carrying out dot matrix signal collection, the dot matrix signals are integrated, internally transmitted, subjected to analog-to-digital conversion, decoded and subjected to signal reduction, interference change of DBS discharge intensity on cerebral nervous system discharge is measured by combining an electromagnetic field model, and finally, pure neural signals are obtained through result comparison.
To further illustrate the method provided by the present invention, the following detailed description is made with reference to fig. 2. When in use, the neural probe is used for collecting dot matrix signals. In particular, the nerve probe uses a point-shaped coating at the tip and the cortical area and a lead wire inside to complete the electric signal collection. Preferably, the inner wires are photo-etched wires. Using a featured chip to integrate signals; the electrodes in the cortical region are arranged transversely and longitudinally, and n is m. Preferably, where n and m are 3 x 25, additions may be made as appropriate. After the neural probe is used for carrying out dot matrix signal collection, the collected dot matrix signals are integrated and transmitted internally. The integration of the lattice signals is generally completed by using a chip, and n × m array data acquired by each probe can be integrated into integrated high-frequency analog signal data. The integration can be done with resonators with resonator frequencies on the order of Mhz, much higher than the bioelectric signal frequencies, and therefore can be done using high frequency carriers. The transmission of the lattice signal within the nerve probe preferably relies on a photo-etched wire with appropriate transmissibility and impedance to distinguish between interfering signals and changes in micro-potential. The wave frequency of the interference signal is far lower than that of a normal signal and is 1-25 hz, and the wave frequency of the normal signal is about 75hz, so that the filtering processing can be directly carried out in an internal circuit of the nerve probe.
And integrating the dot matrix signals after internal transmission, performing analog-to-digital conversion on the integrated dot matrix signals to obtain high-frequency digital signals, and transmitting the high-frequency digital signals to the analysis and calculation subsystem. The analog-to-digital conversion process can be completed by a front end chip of the deep intracerebral stimulation DBS device, the front end chip is located in a circuit box of the deep intracerebral stimulation DBS device, power is supplied by an overall power supply, the circuit box is divided into different areas according to the number of the nerve probes, and each nerve probe generates a group of signals. The process of analog-to-digital conversion is directly controlled by the resonator frequency, and the integrated high-frequency analog signals are standardized and aligned to send the end of the deep intracerebral stimulation DBS device for docking. Because the integrated high-frequency analog signal is not greatly different from the digital signal, the analog-to-digital conversion step also comprises time window translation and normalization of the signal, and data loss is avoided. The converted high-frequency digital signal can be transmitted by using a high-speed wireless Bluetooth protocol so as to be received by an analysis computing system.
The analysis and calculation subsystem decodes the high-frequency digital signals, and performs electromagnetic field calculation after the deep intracerebral stimulation DBS intervention signals are used for restoration. The high-frequency digital signals comprise neural lattice digital signals and DBS intervention digital signals, and the decryption process comprises the following steps:
1. decoding comprises the step of respectively decoding the neural lattice digital signal and the DBS intervention digital signal which are contained in the high-frequency digital signal, wherein the high-frequency digital signal is decoded into a reverse process of the encoding step, and the decoding result is the neural lattice signal with interference; and the decoding of the DBS intervention digital signal is direct parameter decoding and is determined by parameters in a preset model of the deep intracerebral stimulation DBS device. In this embodiment, only the time parameter, intensity parameter, and frequency parameter information of the deep intracerebral stimulation DBS device intervention may be analyzed.
And 2, the DBS intervention signal reduction means that the DBS parameters are reduced to real DBS stimulation signals.
3. The electromagnetic field calculation is preferably performed in the cloud server, and the calculation simulates the electric field and the electric field variation, the magnetic field and the magnetic field variation, and the electric field and the variation thereof caused by the magnetic field variation generated in the brain by the DBS signal by using the metric model of the principle as shown in fig. 3, so as to generate the relationship between the mutual influence and induction of the electric field and the magnetic field. The decoding process is essentially an iterative process, in which smaller-scale magnetic field changes are induced by electric field changes, and then the electric field changes continue to be induced. In the conventional analysis, the change is generally considered unstable and is difficult to calculate, and the method adopts an iterative recursive mode, nests a multi-layer metric model on the basis of the metric model, preferably takes 1% intensity critical as a characteristic, ignores the change of the excessively weak potential, and accordingly approximates the electric field induced by the DBS.
And finally, comparing the electric field calculation result obtained in the step with the position of the lattice signal by the interference removal system, simulating the influence on the lattice signal, and further removing noise contained in the neural lattice signal to obtain a pure neural signal.
The invention also provides a signal extraction system under the discharge intervention state of the deep intracerebral stimulation DBS equipment. As shown in fig. 4, the system includes:
a signal collection subsystem 100 for collecting the lattice signals using a neural probe;
the signal preprocessing subsystem 200 is used for integrating the dot matrix signals after internal transmission, performing analog-to-digital conversion on the integrated dot matrix signals to obtain high-frequency digital signals, and transmitting the high-frequency digital signals to the analysis and calculation subsystem;
the analysis and calculation subsystem 300 is used for decoding the high-frequency digital signals, and performing electromagnetic field calculation after the deep intracerebral stimulation DBS intervention signals are restored;
and the interference removal subsystem 400 is used for comparing the electromagnetic field calculation result with the position of the lattice signal and removing noise according to the comparison result to obtain a pure neural signal.
Therefore, the system collects lattice signals by using the nerve probe, integrates the collected signals, performs internal transmission, analog-to-digital conversion, decoding and signal reduction, measures the interference change of DBS discharge intensity on the brain nervous system discharge by combining an electromagnetic field model, and finally obtains pure nerve signals by result comparison. The invention can remove interference signals in the mixed signals acquired when the DBS equipment intervenes in discharging, and realizes the intensity calculation and observation of the brain nerve signals.
For the introduction of the signal extraction system under the discharge intervention state of the deep intracerebral stimulation DBS device provided by the present invention, please refer to the foregoing embodiment of the signal extraction method under the discharge intervention state of the deep intracerebral stimulation DBS device, and the embodiments of the present invention are not described herein again.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The signal extraction method and system in the deep intracerebral stimulation DBS device discharge intervention state provided by the present invention are introduced in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (10)
1. A signal extraction method under the discharge intervention state of deep intracerebral stimulation (DBS) equipment is characterized by comprising the following steps:
acquiring a dot matrix signal acquired by using a nerve probe and a DBS discharge signal of deep intracerebral stimulation DBS equipment in a discharge intervention state;
integrating the lattice signals transmitted inside the nerve probe, and performing analog-to-digital conversion on the integrated lattice signals and the DBS discharge signals to obtain high-frequency digital signals;
decoding the high-frequency digital signal to obtain a neural lattice signal and a DBS intervention signal, and performing electromagnetic field calculation after restoring the DBS intervention signal;
and comparing the position of the electromagnetic field calculation result with the position of the neural lattice signal, and removing noise according to the comparison result to obtain a pure neural signal.
2. The method of claim 1, wherein the electrical signal collection is accomplished by using a spot-like coating on the tip and cortical region of the nerve probe and a wire inside the probe, wherein the electrodes in the cortical region are arranged in a transverse and longitudinal direction, n is m, and n and m are integers.
3. The method of claim 1, wherein the integration of the lattice signal is performed by integrating the n x m array data collected by each probe into an integrated high frequency analog signal, wherein the integration is performed primarily using resonators with frequencies on the order of Mhz.
4. The method of claim 1, wherein the analog-to-digital conversion is performed by a front-end chip, the front-end chip is located in a circuit box of the deep intracerebral stimulation DBS device, is powered by an integral power supply, is divided into different regions according to the number of the nerve probes, and generates a set of signals for each nerve probe, wherein the analog-to-digital conversion process is directly controlled by the resonator frequency, normalizes and aligns the integrated high-frequency analog signals, and transmits the end signals for docking.
5. The method of claim 1, wherein prior to the step of analog-to-digital converting the integrated lattice signal, the method further comprises:
and carrying out time window translation and normalization on the integrated dot matrix signals to avoid data loss.
6. The method of claim 1, wherein the high frequency digital signals comprise neural lattice digital signals and DBS intervening digital signals, and wherein the step of decoding the high frequency digital signals comprises:
and respectively decoding the neural lattice digital signal and the DBS intervention digital signal to obtain the neural lattice signal and the DBS intervention signal.
7. The method of claim 6, wherein the step of decoding the high frequency digital signal is a reverse process of the encoding step, the decoding resulting in a neural lattice signal with interference;
the decoding result of the DBS intervention digital signal is direct parameter decoding and is determined by parameters in a preset model of deep intracerebral stimulation DBS equipment;
the reduction of the DBS intervention signal means that the DBS parameters are reduced to real DBS stimulation signals.
8. The method of claim 1, wherein the electromagnetic field calculation simulates the electric field and electric field variation, magnetic field and magnetic field variation generated in the brain by the DBS intervention signal, and the electric field and its variation induced by the magnetic field variation, mainly using a metric model to form the relationship of electric and magnetic field interaction and induction.
9. The method of claim 8, wherein the electromagnetic field is calculated in an iterative recursive manner, and on the basis of the metrology model, a plurality of layers of metrology models are nested, characterized by a 1% intensity threshold, and the electric field induced by the DBS intervention signal is approximated by ignoring changes in the too weak potential.
10. A signal extraction system in a deep intracerebral stimulation DBS device discharge intervention state, for implementing the method of any of claims 1 to 9, comprising:
the signal collection subsystem is used for acquiring a dot matrix signal acquired by using a nerve probe and a DBS discharge signal of the deep intracerebral stimulation DBS equipment in a discharge intervention state;
the signal preprocessing subsystem is used for integrating the lattice signals transmitted inside the nerve probe and performing analog-to-digital conversion on the integrated lattice signals and the DBS discharge signals to obtain high-frequency digital signals;
the analysis and calculation subsystem is used for decoding the high-frequency digital signal to obtain a neural lattice signal and a DBS intervention signal, and performing electromagnetic field calculation after the DBS intervention signal is restored;
and the interference removal subsystem is used for comparing the position of the electromagnetic field calculation result with the position of the neural lattice signal and removing noise according to the comparison result to obtain a pure neural signal.
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| US20070067003A1 (en) * | 2005-09-14 | 2007-03-22 | University Of Florida Research Foundation, Inc. | Closed-loop micro-control system for predicting and preventing epilectic seizures |
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| WO2016196790A1 (en) * | 2015-06-02 | 2016-12-08 | Battelle Memorial Institute | Closed loop deep brain stimulation systems and methods |
| US20170224990A1 (en) * | 2012-11-26 | 2017-08-10 | Isy Goldwasser | Apparatuses and methods for neuromodulation |
| US20180185649A1 (en) * | 2017-01-05 | 2018-07-05 | Regents Of The University Of Minnesota | System and method for feedback-driven neuromodulation |
| CN108784693A (en) * | 2018-06-15 | 2018-11-13 | 北京理工大学 | P300 single-trial extraction technologies based on independent component analysis and Kalman smoothing |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20070067003A1 (en) * | 2005-09-14 | 2007-03-22 | University Of Florida Research Foundation, Inc. | Closed-loop micro-control system for predicting and preventing epilectic seizures |
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| US20170224990A1 (en) * | 2012-11-26 | 2017-08-10 | Isy Goldwasser | Apparatuses and methods for neuromodulation |
| WO2016196790A1 (en) * | 2015-06-02 | 2016-12-08 | Battelle Memorial Institute | Closed loop deep brain stimulation systems and methods |
| US20180185649A1 (en) * | 2017-01-05 | 2018-07-05 | Regents Of The University Of Minnesota | System and method for feedback-driven neuromodulation |
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