CN113576403A - Quantitative evaluation method for human body bidirectional coupling information conduction path and sensing system - Google Patents
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Abstract
The invention discloses a quantitative evaluation method for a human body bidirectional coupling information conduction path, relates to a set of multi-sensor fusion system, and is particularly provided for nervous system disease patients with motor symptoms. The human body has a bidirectional coupling information conduction path which is connected with the intrinsic physiological electricity and the extrinsic behavioral expression, namely an electroencephalogram-electromyogram-action downlink control information conduction path and an action-electromyogram-electroencephalogram uplink feedback information conduction path. The invention simultaneously monitors three key node information of brain, muscle and action in the two-way information conduction path, on one hand, the invention assists doctors to carry out comprehensive and accurate quantitative evaluation on the symptoms of patients; and on the other hand, the nerve source is positioned through the connectivity analysis of the cerebral cortex-muscle, so that a personalized treatment scheme is customized for the patient.
Description
Technical Field
The invention belongs to medical instruments, and particularly relates to a multi-sensor fusion system which is particularly provided for nervous system disease patients with motor symptoms and used for quantitative evaluation of information conduction paths in human bodies in two-way coupling.
Background
The nervous system of the human body is a highly complex nonlinear coupling system. In the downlink control information path of brain-muscle-action, a brain movement area transmits a control signal to target muscle through nerves to enable the target muscle to contract and relax, and further to represent external action performance; in the up-going feedback information path of action-muscle-brain, human action brings stimulation to the sensory organs, and the sensation is fed back to the somatosensory region of the brain through nerves, which in turn provides negative feedback regulation to the brain motor region. The information path of the human body bidirectional coupling realizes the closed-loop negative feedback real-time control of the brain to the muscle. When a lesion occurs in a certain part of the nervous system, that is, information is prevented from being transmitted in the position, or information is lost in transmission, or a long delay exists, the stability of the whole nervous closed-loop control system is affected, and the disordered behavior output is caused. Thus, many neurological diseases are characterized by diversity, complexity, and difficulty in treatment, and the location of the disease-causing lesion is difficult.
Common non-invasive assessment means for the nervous system include Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Magnetoencephalography (MEG), near-infrared brain function imaging (fNIRS), and the like. For example, the invention patent of general hospital strength in eastern war zone of people liberation military in 2020: a functional imaging based epileptic activity detection method and system (CN202010439968.X) provides an epileptic activity detection method based on functional imaging. However, these conventional imaging examinations are usually complex and bulky, expensive to examine, unable to monitor for a long time, and difficult to capture the onset of certain neurological diseases.
In addition to neuroimaging methods, symptomatology is also a focus of attention of physicians in clinical diagnosis, but the chief complaints and scales of symptoms are not reliable enough in many patients, especially for patients with neurological diseases leading to cognitive impairment. Doctors often need to judge the condition of patients by recording the onset of symptoms of the patients and combining the experience of the previous cases. This subjective assessment is also directly related to the physician's medical skill and experience, and in areas of less developed medical conditions, many patients do not have access to professionally effective medical advice. In summary, there is currently no objective, effective, long-range measurable method for quantitatively evaluating the information transmission pathway in the human body.
The nervous system is used as an important carrier for information conduction in human body, and an important characteristic is embodied in rapidity and real-time property. Human emotion, sensation and motion processes are all very rapid, the occurrence time is within tens to hundreds of milliseconds, and in order to capture the rapidly changing dynamic physiological processes, the physiological electrical sensing technology has incomparable advantages compared with other neural imaging technologies due to the extremely high time resolution. The acquisition frequency of the electroencephalogram and the electromyogram sensors is usually hundreds to thousands of hertz, and the high sampling rate meets the requirement of understanding the dynamic physiological process of the rapid response of the nervous system. For example, Qinghua university Yan Yuxiang invention patent: the processing method and device for the epileptic interval electroencephalogram signals, storage inoculation and equipment (CN202010414039.3) pay attention to scalp electroencephalogram signals, and a method for extracting abnormal electroencephalogram signals is provided for predicting epileptic seizures.
At present, researchers are mostly based on separate researches on the brain and the muscle, but the researches on the combination of the researches are less. An information conduction path in a human body is a highly complex coupling system, and the fact that only electroencephalogram signals or electromyogram signals are relied on means that only an isolated link of the path is concerned is not comprehensive enough. The general Hospital, Heber Yong et al, Tianjin medical university, states in the text "early evaluation of the prognosis of patients with cerebral infarction and aphasia by transcranial magnetic stimulation exercise-evoked potential": "during transcranial magnetic stimulation treatment, pulse current generated by motor cortex can be conducted to limb muscles along motor neuron pathway, and Motor Evoked Potential (MEP) is detected at muscles, and any damage to any part of the pathway can cause abnormal motor evoked potential, including latency and peak value change. The conclusion also indicates that the functional connection of the nerve conduction path of the testee can be quantitatively evaluated through connectivity analysis in order to research the bidirectional coupling information conduction path in the human body and simultaneously monitor the electroencephalogram and the myoelectricity, which is very necessary.
The control signal and the feedback signal in the human body are transmitted in the nervous system in the form of physiological electricity, and finally, the control signal and the feedback signal are expressed as the action outside the human body. For some patients with motor attacks, in order to reconstruct and restore the motion of the patient, the motion angle and speed of the limb of the patient are accurately recorded, and a motion capture technology is also introduced. The current mainstream motion capture technology comprises three modes of optical motion capture, inertial motion capture and optical-inertial hybrid motion capture. Patent inventions of Chenjinquan and sesbania in 2018 are disclosed as follows: a multi-modal epilepsy diagnosis system and method (CN108647645A) based on video analysis focuses on the behavior of a patient, collects the video information of the patient, and is used for monitoring the epileptic seizure and diagnosing the epilepsy. However, the optical motion capture system needs to be provided with a camera in advance, is limited by collecting ambient light and the angle of the camera, and considers the wearability and the mobility of the device, and the inertial motion capture scheme is adopted in the invention.
In order to comprehensively and quantitatively know information conduction paths and nervous system diseases, a multi-modal sensor is required to be used for integrally researching information of each main node in the paths in a connection mode, and further, the connectivity of cerebral cortex and muscles is researched to realize the positioning of nerve sources. Therefore, the invention is proposed to quantitatively evaluate the physiological electro-behavioral bidirectional coupling information conduction pathway based on a multi-sensor fusion method, and is particularly provided for nervous system disease patients with motor symptoms.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a quantitative evaluation method for a bidirectional coupling information conduction path in a human body aiming at nervous system diseases with motor attack symptoms, and relates to a set of multi-sensor fusion system.
The invention is realized by the following technical scheme: a multi-mode sensor (a multi-channel electroencephalogram sensor, a multi-channel surface electromyogram sensor and a nine-axis inertial sensor) is used for simultaneously monitoring an electroencephalogram-electromyogram-action downlink control information conduction path and an action-electromyogram-electroencephalogram uplink feedback information conduction path in a human body. The electroencephalogram sensor monitors a control instruction sent by the brain and a response after receiving a feedback signal; the electromyographic sensor monitors the activated process of the muscle after receiving the control instruction; the inertial sensors monitor the final output of the motor activity after the muscle is activated.
In the sensor, the myoelectric sensor is controlled by a master control chip to control a single acquisition chip, the electroencephalogram sensor is controlled by a master control chip to control a plurality of acquisition chips, and the number of the acquisition chips is determined by the number of measured channels. The main control chip and the acquisition chip are communicated through an SPI protocol, and physiological electric data are sent to a PC end upper computer in a wireless communication mode; an accelerometer, a gyroscope and a magnetometer are integrated on the nine-axis inertial sensor chip, the inertial sensor chip is communicated with the main control chip through an SPI protocol, and inertial sensing data are sent to a PC end upper computer in a wireless communication mode. All the sensors are independently powered by lithium batteries.
In the invention, a scalp electroencephalogram sensor is placed on the scalp of a patient according to an internationally recognized 10-20 standard lead position, a surface electromyogram sensor is placed on the four limbs, the face and other positions of the patient according to the specific attack symptoms of the patient, and inertial sensors are placed on two sides of the main joints of the human body in pairs.
The method for noise reduction preprocessing of the acquired physiological electric signal comprises the following steps: baseline drift and high-frequency interference are removed through a 1-80Hz band-pass filter, external noise interference is removed through a 50Hz wave trap, and particularly, the interference of electrocardio artifacts and ocular artifacts is removed through Independent Component Analysis (ICA) on electroencephalogram signals.
The method for calculating the change angle of the central joint axis comprises the following steps: and integrating the angular velocity output by the gyroscope to obtain the attitude angle of the current inertial sensor by using a Kalman filtering algorithm to fuse the data of the accelerometer (three axes), the gyroscope (three axes) and the magnetometer, and correcting the accumulated drift amount of the gyroscope by using the data of the accelerometer and the magnetometer. The motion attitude is expressed by using a quaternion method, and multiple rotations in the euler angle expression method are equivalent to rotation by a certain angle theta around a certain axis k. The unit quaternion is expressed as [0015 ]]Shown, rotational attitude q of the center jointj(t) is composed of [0016]Calculation, wherein [ ] represents a quaternion multiplication, q1 E(t)、q2 EAnd (t) are the real-time postures of the two inertial sensors near the joint at any time t. And finally, converting the rotation attitude quaternion of the central joint into a joint rotation Euler angle, wherein alpha is a joint flexion and extension angle, beta is a joint contraction and extension angle, gamma is a joint rotation angle, and the conversion mode of the quaternion and the Euler angle is as shown in [0017 ]]As shown.
The method for analyzing the connectivity of the cerebral cortex-muscle comprises the following steps: the signal is transformed from the time domain to the frequency domain using a fourier transform or wavelet transform for coherence analysis. On one hand, the coherence among the electroencephalogram signals recorded by different brain area electrodes is calculated; on the other hand, the coherence between the brain electrical signals of different brain areas and the myoelectrical signals of muscles at different positions is calculated. According to prior knowledge, the invention focuses on the coherent relationship between the electroencephalogram of the primary motor cortex responsible for movement and the myoelectric signal at the most obvious disease symptom reaction. For two signals x and y, the coherence coefficient calculation is shown as [0019]
Wherein, CohxyExpressed as the correlation coefficient of the two signals at frequency f, CohxyWhen 0, x and y are not coherent, CohxyWhen 1, the signals x and y are completely coherent. Wherein, PxxAnd PyyRepresenting the respective power spectral densities, P, of signal x and signal yxyRepresenting the cross spectral density between signal x and signal y. In the invention, x and y are physiological electric signals recorded by the electroencephalogram sensor and the electromyogram sensor. The coherence value reflects the consistency of phase difference of the two signals under a given frequency, functional connection between different areas of the brain is evaluated by calculating coherence between electroencephalogram signals of different channels, functional connection and information transmission between neuromuscular are evaluated by calculating coherence degree of myoelectricity and electroencephalogram, and furthermore, a nerve source related to abnormal myoelectricity signals can be positioned through the position of an electroencephalogram electrode.
The invention has the following advantages: 1. the invention uses the multi-mode sensor to simultaneously acquire the physiological and electrical information and the motion information of the patient, and assists doctors to comprehensively and accurately quantitatively evaluate the symptoms of the patient with the nervous system diseases.
2. The invention carries out focal nerve source positioning through cerebral cortex-muscle connectivity analysis and time delay analysis, and assists doctors to customize personalized treatment schemes for patients.
3. The invention adopts low power consumption circuit design and large capacity battery, realizes long-term monitoring, is beneficial to catching the attack period of the patient, and can further track the complex evolution process of the disease by long-term monitoring.
4. The invention belongs to a non-invasive and non-toxic side effect evaluation means, the preparation before monitoring the patient is simple, the requirement on the matching capability of the patient is not high, all sensors use a wireless data transmission mode, and the sensors are discrete and wearable without influencing the normal life of the patient.
5. The myoelectricity brain electric sensor used by the invention has high time resolution up to 1000Hz, and is beneficial to capturing the dynamic physiological process of rapid change in human body.
6. The invention uses the inertial sensor to calculate the angle of the main joint and skeleton motion when the patient has attack in real time, has the advantage that an optical motion capturing system does not have, namely is not influenced by light, can be used in a dark environment, and particularly has important advantage for monitoring the attack of the patient at night.
Drawings
Fig. 1 is an abstract attached drawing of a quantitative evaluation method for a human body bidirectional coupling information conduction path provided by the invention.
Fig. 2 is a schematic diagram of an embodiment of a quantitative evaluation method for a bidirectional coupling information transmission path of a human body and a schematic diagram of typical placement positions of sensors according to the present invention.
FIG. 3 is a schematic diagram of a hardware architecture of a multi-channel myoelectric and electroencephalogram sensor in the embodiment of the invention.
Fig. 4 is a schematic diagram of a hardware architecture of a nine-axis inertial sensor according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of a critical ADC chip ADS1298 peripheral circuit used in a multi-channel physiological electrical acquisition scheme according to an embodiment of the present invention.
FIG. 6 illustrates a standard 10-20 electrode placement as defined by the International electroencephalogram society in an embodiment of the present invention.
Fig. 7 is a preprocessing flow after the original electroencephalogram signal and the electromyogram signal are acquired in the embodiment of the present invention.
FIG. 8 is a calculation process of an inertial sensor estimating an attitude angle and a calculation process of a pair of inertial sensors synchronously acquiring and resolving an angle of a joint axis in the vicinity of the joint according to an embodiment of the present invention.
Fig. 9 shows the steps of implementing and using a quantitative evaluation method and a sensing system for a human body bidirectional coupling information conduction path in the embodiment of the present invention.
Description of reference numerals 1: a multi-channel electroencephalogram sensor; 2: a multi-channel myoelectric sensor; 3: a nine-axis inertial sensor;
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
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 belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein the term "and/or" includes any and all combinations of one or more of the associated listed items.
FIG. 2 is a schematic diagram of a system for quantitatively evaluating a bidirectional coupling information transmission path in a human body. The sensors used include electroencephalogram sensors, electromyogram sensors, and nine-axis inertial sensors. Considering portability and wearability, all sensors are all supplied power by independent lithium batteries, and all data are transmitted through WIFI wireless.
The subject first needs to clean the hair and skin prior to physiological electrical collection. The electrodes and scalp are usually injected with a conductive paste to reduce contact resistance and are secured by a resilient cap. The four eight-channel surface electromyographic sensors are respectively placed on four limbs, each electromyographic sensor comprises an acquisition box and eight electrode wires led out of the acquisition box, the acquisition box can be fixed on the four limbs of a patient through a binding band or a double-sided adhesive tape, and the electrode wires have certain length and can be used for a doctor to preferentially select the placement position of the electrodes according to symptoms of the patient. For patients with unclear disease conditions, a sensor recommended in the embodiment of the present invention is typically placed as follows: the EEG electrodes are placed according to the standard 10-20 lead placement method specified by the International electroencephalogram (EEG) society, as shown in figure 6. The distance from the midpoint of the frontal pole to the nasal root and the distance from the occipital point to the occipital tuberosity each account for 10% of the total length of the line, and the remaining points are separated by 20% of the total length of the line, as shown in the following figure. Odd numbers indicate the left side of the brain, even numbers indicate the right side of the brain, and the left and right sides each take 8 electrodes, plus 21 electrodes in total, the frontal midpoint (Fz), the central point (Cz), the apex (Pz), and the two ear electrodes, in the anterior-posterior position. The four 8-channel surface electromyography sensors are respectively placed on four limbs, the upper limb mainly focuses on the positions of the deltoid, biceps brachii, triceps brachii, brachioradialis and ulnar muscle, and the lower limb mainly focuses on the positions of the quadriceps femoris, biceps femoris and gastrocnemius muscle. After the original physiological electric signal is acquired, firstly, the signal is preprocessed, the preprocessing flow is shown as an attached figure 7, the physiological electric signal is often interfered by the environment in the acquisition process, firstly, the physiological electric signal passes through a band-pass filter and a 50Hz wave trap, and particularly, the electroencephalogram signal is subjected to Independent Component Analysis (ICA) to remove artifacts such as electrocardio, blink and the like.
The overall architecture of the electroencephalogram and electromyogram sensor hardware is shown in fig. 3, wherein the model of the main control chip is STM32F103, and the model of the ADC chip is ADS 1298. The ADS1298 chip is a multi-channel synchronous sampling 24-bit analog-to-digital conversion chip produced by TI company and is provided with a built-in Programmable Gain Amplifier (PGA), and at most 8-channel physiological electrical signals can be simultaneously acquired by one ADS1298 chip. In the embodiment of the invention, each electromyographic sensor is controlled by one ADS1298 controlled by one main control chip STM32F103, and each electromyographic sensor can simultaneously acquire 8-channel electromyographic signals at most; the electroencephalogram sensor is characterized in that a main control chip STM32F103 controls four ADS1298 chips, and 32 channels of electroencephalogram signals can be acquired at most simultaneously. The communication between the ADS1298 and the STM32 microcontroller adopts an SPI protocol, data are sent to a PC upper computer through an ESP8266 WIFI wireless communication module, and a schematic diagram of a peripheral circuit of a main chip ADS1298 is shown in figure 5.
In order to accurately capture and restore the symptoms of the patient during movement, the inertial sensors are used for capturing and recording the limb movements of the patient, 16 nine-axis inertial sensors are fixed at the positions shown in the attached figure 2 through the binding bands, and the angles of 12 human body large joints of a wrist joint, an elbow joint, a shoulder joint, a hip joint, a knee joint and an ankle joint are respectively detected. After data synchronously acquired by an accelerometer, a gyroscope and a magnetometer are obtained, a Kalman filtering technology is used for fusing data of the nine-axis inertial sensor, so that data deviation caused in the acquisition process of the sensor is reduced, and an attitude angle is estimated through integration and compensation relations. In order to realize the three-dimensional animation simulation of human motion, a local attitude angle calculated by inertial sensor data is converted into a rotation angle of a central joint shaft, a pair of nine-shaft inertial sensors near one joint synchronously acquire the motion states of limbs at two sides of the joint, and the relative position change of the two sensors, namely the angle of joint motion, can be solved through the inherent kinematic constraint of human bones. Taking the elbow joint as an example, the joint has only two degrees of freedom of flexion and extension and rotation, and the rotation does not affect the axial direction of the joint axis, so the joint can be regarded as a rigid hinge connection structure. Taking the hip joint as an example, besides flexion and extension and rotation, a more folding degree of freedom is provided, so that the hip joint can be regarded as a spherical hinge connection structure of a rigid body, and the specific calculation process is shown in fig. 7. Due to the uncertainty of the mounting position, the position of the joint axis in the local coordinate system of the inertial sensor needs to be calibrated before use.
The nine-axis inertial sensor hardware architecture is shown in fig. 4, wherein the model of the main control chip is STM32F103, the model of the nine-axis inertial sensor chip is MPU-9250, and the MPU-9250 chip integrates an accelerometer, a gyroscope and a magnetometer at the same time. Inertial sensor data passes through SPI protocol and STM32 microcontroller communication, later sends sensor data to PC host computer through ESP8266 WIFI wireless communication module.
Through the multi-sensing system, a doctor can perform long-range, quantitative and accurate evaluation on the symptoms of a patient, and perform coherence analysis on sensor data recorded by three nodes, namely the brain, the muscle and the action, so that on one hand, the coherence relation between electroencephalogram signals of different brain areas of the patient and myoelectricity at the muscles of attack muscles can be evaluated, and on the other hand, the difference between the electroencephalogram signals, the myoelectricity signals and behaviourology of the patient and normal people under the same task execution state can also be evaluated. Through the comparison of the attack state and the rest state, the patient is compared with a healthy control group, the brain area position which is possibly activated during the attack is found, the focus position is predicted, and reference is provided for individual differentiation customized treatment schemes.
The specific use steps of the embodiment of the invention are shown in the attached figure 9:
step 1: cleaning the skin and hair of the subject.
Step 2: the electroencephalogram sensor, the myoelectricity sensor and the inertial sensor are fixedly arranged according to the actual condition of a patient.
And step 3: and opening the PC end upper computer.
And 4, step 4: and turning on a power switch of the sensor, automatically addressing by the WIFI module according to a preset IP, and sending sensor data.
And 5: when a patient attacks, a guardian sends out a trigger signal, the attack time is marked on sensor data, and the sensor data are stored locally.
Step 6: preprocessing, spectrum analysis and coherence analysis are carried out on the electroencephalogram signals and the electromyogram signals.
And 7: preprocessing, spectrum analysis and coherence analysis are carried out on the electroencephalogram signals and the electromyogram signals.
And 8: and fusing the data of the nine-axis inertial sensor by using a Kalman filtering technology to estimate the attitude angle of the single IMU.
And step 9: the joint movement angle is calculated through the data synchronously acquired by a pair of IMUs near the joint.
Step 10: and performing coupling analysis on a brain Region of interest (Region interest), a target muscle and a target joint motion.
The structure shown in fig. 1 is described in detail below with reference to the first to third embodiments:
the first embodiment is as follows: quantitative evaluation method of bidirectional coupling information conduction path in human body for epileptic patient
Epilepsy is one of the most common diseases of the nervous system, and the pathogenesis of epilepsy is sudden abnormal discharge of cerebral neurons, resulting in transient cerebral dysfunction. The epileptic seizures have different behaviors and can be expressed as comprehensive tonic-clonic seizures, absence seizures, tonic seizures, myoclonic seizures, spasm and the like.
The key to the diagnosis and treatment of epilepsy is the accurate positioning of the brain focus, and the current method for positioning epilepsy mainly depends on symptomatology, for example, when the symptoms of deviation of the head and the eye occur during the epileptic attack, the focus is likely to be positioned on the opposite side of the deviation; the patient usually has a rubble pill-like attack and a money-like action, usually a temporal lobe attack. However, the symptom expression depends on the observation of doctors, is greatly influenced by the subjectivity of doctors, and an effective quantitative evaluation means is not available at present.
The specific implementation example simultaneously uses an electroencephalogram sensor, a myoelectricity sensor and a nine-axis inertial sensor to respectively monitor three important links of a brain, muscles and behaviors in a two-way coupling information conduction path in a human body. In particular, for patients with different seizure symptoms, the position of the myoelectric electrode and the position of the nine-axis inertial sensor should be selected according to the actual occurrence of the patient, for example, for a patient who is not laughing voluntarily at the time of an epileptic seizure, a doctor may focus on facial muscles and the myoelectric electrode should be placed on the face of the patient. For example, for a patient with the epileptic seizure behavior being myoclonus of the four limbs, the myoelectric electrodes should be placed at the positions of triceps, biceps femoris, quadriceps, etc.; the inertial sensors are placed on two sides of the elbow joint, the wrist joint, the knee joint and the ankle joint, and angle changes of the joints are calculated in real time. The doctor can accurately and quantitatively evaluate the symptoms of the patient through the invention, can calculate the coherence between the electromyographic signals of the attack area and different brain areas of the brain, and can predict the possible lesion positions in the brain by comparing the difference between the patient and a healthy control group and the difference between the attack period and the intermission period.
Example two: quantitative evaluation method for bidirectional coupling information conduction path in human body for Parkinson patient
Parkinson is a common degenerative disease of the nervous system, and is common among the elderly. The first act is often tremor or awkward movement of one limb, and thus involves the opposite limb. Clinically, the symptoms are static tremor, bradykinesia, muscular rigidity and gait disorder. Most patients take tremor as the first action, mostly starting from the distal end of the upper limb on one side, and appearing or evident when the patient is static, and relieving or stopping the tremor when the patient moves randomly, and static tremor of hands is aggravated when the patient walks.
The specific embodiment simultaneously uses an electroencephalogram sensor, a myoelectricity sensor and a nine-axis inertial sensor. A doctor can preferably select the positions where the myoelectric electrode and the inertial sensor are placed according to the actual condition of a patient, for example, a hand tremor patient can focus on the forearm muscle, brachioradialis muscle and extensor carpi ulnaris muscle which control the wrist and fingers; a pair of inertial sensors may be placed at the lower arm and palm to accurately resolve the frequency of the patient's hand tremors in real time. For a patient with gait disorder, the patient can focus on the calf gastrocnemius muscle controlling the ankle, and the pair of inertial sensors can be placed at the calf and the instep to calculate the change of the ankle joint angle of the patient in real time. On one hand, the inertial sensor can accurately record the limb actions of the patient, and is beneficial to helping doctors grade the illness state of the patient; on the other hand, the whole coupling analysis of the electroencephalogram, the myoelectricity and the behaviors of the patient is also beneficial to the positioning of a nerve source, and an individualized treatment scheme is provided for the selection of the stimulation target points of the noninvasive nerve regulation and control methods such as transcranial magnetic stimulation and the like.
Example three: quantitative evaluation method of bidirectional coupling information conduction path in human body for stroke patient
Stroke is a disease in which blood cannot flow into the brain due to rupture or blockage of blood vessels in the brain, thereby causing damage to brain tissue. The behavioral manifestations are dizziness, numbness of one side or hands and feet, involuntary twitching of one side of the body, sudden fall or faint for unknown reasons. The root of these behaviors is the impairment of the motor nervous system, which results in the failure of good coordination between the downlink control signals and the uplink feedback signals in the bidirectional information transmission pathway.
At present, the evaluation of the behavior of stroke patients mostly depends on the subjective experience of doctors, the efficiency is low, the substantive reference is lacked, and the quantitative evaluation means is lacked. Therefore, the method provided by the invention can be used for stroke patients, and the specific implementation example simultaneously uses the electroencephalogram sensor, the myoelectricity sensor and the nine-axis inertial sensor to integrally analyze the bidirectional information conduction path. For example, for a patient with unilateral numbness of hands and feet, the difference between physiological electrical information and ethology of the normal side and the abnormal side can be analyzed with emphasis; for the patient in the rehabilitation period, the development of the patient's condition is quantitatively evaluated by calculating the time-lapse of the uplink and downlink channel information conduction. Through electroencephalogram-electromyogram-behavioural coupling analysis, the contribution degree of cerebral cortex participating in movement control to muscle control in the movement process can be explored, the influence of external different symptomatology expressions on a two-way coupling information conduction channel in the human body can be deeply known, and a doctor is further guided to position a pathogenic focus, so that accurate treatment is realized.
The invention is not the best known technology. The above embodiments are merely illustrative of the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (9)
1. A quantitative evaluation method of a human body bidirectional coupling information conduction path is characterized in that a multi-mode sensor system is used for simultaneously monitoring a human body electroencephalogram-electromyogram-action downlink control information conduction path and an action-electromyogram-electroencephalogram uplink feedback information conduction path, wherein the multi-mode sensor comprises but is not limited to an electroencephalogram sensor, an electromyogram sensor and a motion sensor; the main links of the human body information conduction path comprise brain, muscle and action.
2. The method of claim 1, wherein the disease is selected from the group consisting of epilepsy, Parkinson's disease, and stroke.
3. The quantitative evaluation method of the two-way coupling information transmission path of human body according to claim 1, wherein the three main links of brain, muscle and action are studied as a whole without being limited to the individual links in the path.
4. The quantitative assessment method of human body bidirectional coupling information transmission pathway as claimed in claim 1, wherein the functional connection and information transmission between neuromuscular is assessed by analyzing the coupling strength of brain, muscle and action, and the localization of nerve source is further realized, the method includes but is not limited to coherence analysis.
5. The quantitative evaluation method of the human body bidirectional coupling information conduction path as claimed in claim 1, characterized by comprising the steps of:
(1) simultaneously acquiring by using an electroencephalogram sensor, an electromyogram sensor and a motion sensor;
(2) carrying out noise reduction pretreatment and spectrum analysis on the electroencephalogram signals and the electromyogram signals;
(3) fusing nine-axis inertial sensor data, and estimating the attitude angle of a single IMU; the moving angle of a central joint axis is calculated through data synchronously acquired by a pair of IMUs near the joint;
(4) and performing overall coupling analysis on the brain Region of interest (Region of interest), the target muscle and the target joint motion.
6. The electroencephalogram and electromyogram sensors can select proper channel numbers according to actual needs, including any channel number with the channel number being 0; the motion sensors include, but are not limited to, three-axis inertial sensors, six-axis inertial sensors, nine-axis inertial sensors, capacitive sensors, piezoelectric sensors, strain sensors, optical cameras.
7. The multi-sensor fusion system of claim 6, wherein the physician can select the number and placement positions of the electroencephalogram sensor, the electromyogram sensor and the motion sensor flexibly according to the actual condition of the patient.
8. The set of multi-sensor fusion system of claim 6, wherein all sensors are powered by independent lithium batteries, all sensors include a main control chip and an acquisition chip, a communication protocol between the acquisition chip and the main control chip includes but is not limited to an SPI communication protocol, and a wireless communication mode between the sensors and a PC upper computer includes but is not limited to WIFI communication.
9. The set of multi-sensor fusion systems of claim 6, wherein human skeletal constraints are introduced, and the angle of central joint axis change is resolved from a pair of inertial sensor data in the vicinity of the joint using methods including, but not limited to, kalman filtering.
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