CN113208618A

CN113208618A - Excrement and urine excretion early warning method and system based on EEG signal

Info

Publication number: CN113208618A
Application number: CN202110365832.3A
Authority: CN
Inventors: 韩越; 卢树强; 王晓岸
Original assignee: Beijing Brain Up Technology Co ltd
Current assignee: Beijing Brain Up Technology Co ltd
Priority date: 2021-04-06
Filing date: 2021-04-06
Publication date: 2021-08-06

Abstract

The invention discloses a defecation and urination early warning method and system based on an EEG signal, wherein the method comprises the following steps: the EEG signal acquisition equipment acquires an EEG signal for a user and transmits the acquired EEG signal to the data analysis system; the data analysis system processes the EEG signal to obtain a pure EEG signal, then analyzes the pure EEG signal to obtain a target characteristic value, and inputs the target characteristic value into the algorithm model for classification and identification so as to evaluate the current excretion control state of the user; and when the data analysis system detects that the user feels defecation through the control state, the data analysis system sends voice prompt information to the public address equipment to remind a worker to deal with the defecation problem of the user in advance. The invention realizes the intellectualization of predicting and monitoring the defecation event, improves the detection efficiency and reduces the labor cost.

Description

Excrement and urine excretion early warning method and system based on EEG signal

Technical Field

The invention relates to the technical field of EEG signal identification, in particular to a defecation and urination early warning method and system based on an EEG signal.

Background

Since China walks into the aging society in 1999, population aging is accelerated, and the aged population has the characteristics of large scale and rapid growth and increasingly shows the tendency of aging and incapacitation. The excretion is the basic physiological requirement of the old, but because the old usually suffers from urinary system diseases, the urination and defecation condition of the old can not be controlled by the old, and once the involuntary excretion behavior occurs, the old can be seriously troubled, the body of the old can be injured, the self-respect of the old can be injured, the cost of artificial nursing is increased, the labor cost and the time cost are higher, and therefore, a method and a system for early warning, detecting and monitoring the excretion of the old are needed.

However, no brain-computer equipment for intelligently analyzing electroencephalogram signals to predict and monitor defecation processes exists in the market and clinically, defecation events cannot be predicted in time, old people cannot be nursed in time, labor cost and time are high, and life is inconvenient.

Disclosure of Invention

The invention aims to provide a defecation and urination early warning method and system based on an EEG signal, so as to predict defecation events, give an early warning in time, reduce the cost and time of manual nursing, automatically recognize early warning, monitor the defecation motivation of an old user, improve the accompanying quality, improve the living self-respect and the living quality of the old and improve the living convenience.

In order to solve the technical problem, the invention provides a defecation and urination early warning method based on an EEG signal, which comprises the following steps:

the EEG signal acquisition equipment acquires an EEG signal for a user and transmits the acquired EEG signal to the data analysis system;

the data analysis system processes the EEG signal to obtain a pure EEG signal, then analyzes the pure EEG signal to obtain a target characteristic value, and inputs the target characteristic value into the algorithm model for classification and identification so as to evaluate the current excretion control state of the user;

and when the data analysis system detects that the user feels defecation through the control state, the data analysis system sends voice prompt information to the public address equipment to remind a worker to deal with the defecation problem of the user in advance.

Preferably, the data analysis system filters the EEG signal using band-pass and notch filtering algorithms, and then removes noise using a regression method and fourier transform to obtain a clean EEG signal.

Preferably, the time domain and frequency domain analysis is performed on the pure EEG signal, and the converted time-frequency domain EEG signal value is calculated to obtain the target characteristic value.

Preferably, an artificial intelligence algorithm is adopted to calculate a power value or an entropy value of the time-frequency domain EEG signal value as the target characteristic value.

Preferably, the brain area for controlling urination and excretion is a paracortical leaflet, and the EEG signal acquisition equipment acquires EEG signals through Cz, C1 and C2 electrodes; the brain area for controlling excrement excretion is the forehead lobe, and EEG signal acquisition equipment acquires EEG signals through AF3, AF4 and AFz electrodes.

Preferably, the value range of the target characteristic value is [0,100], and different intervals for distinguishing whether the target characteristic value is convenient or not are included.

The invention also provides a defecation and urination early warning system based on the EEG signal, which is used for realizing the method and comprises the following steps:

the EEG signal acquisition equipment is used for acquiring an EEG signal for a user and transmitting the acquired EEG signal to the data analysis system;

the data analysis system is used for processing the EEG signals to obtain pure EEG signals, analyzing the pure EEG signals to obtain target characteristic values, and inputting the target characteristic values into the algorithm model for classification and identification so as to evaluate the current excretion control state of the user; and when the defecation feeling of the user is detected through the control state, sending voice prompt information to the public address equipment to remind a worker to deal with the defecation problem of the user in advance.

According to the defecation and urination early warning method and system based on the EEG signals, the collected EEG signals are processed to obtain pure EEG signals, then the pure EEG signals are analyzed to obtain target characteristic values, finally the characteristic values are extracted and then are included into the algorithm model for classification and recognition, the current control state of the user for defecation is evaluated and fed back, so that the technical effect of intelligently predicting and monitoring the defecation process is achieved, manual participation is not needed, a large amount of time is not needed, the detection efficiency is improved, the labor cost is reduced, defecation events are predicted, early warning is timely performed, the cost and time for manual nursing are reduced, the defecation motivation of old users is automatically recognized and early warned, the quality of accompanying nursing is improved, the living self-respect and the quality of the old users are improved, and the life convenience is improved.

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 flowchart illustrating an implementation of a defecation and urination warning method based on an EEG signal according to the present invention;

FIG. 2 is a flow chart of the portable BCI device operation;

FIG. 3 is a flow chart of an EEG data acquisition process;

fig. 4 is a schematic structural diagram of a defecation and urination warning system based on an EEG signal provided by the present invention.

Detailed Description

The core of the invention is to provide a defecation and urination early warning method and system based on an EEG signal, so as to predict defecation events, perform early warning in time, reduce the cost and time of manual nursing, automatically recognize early warning, monitor the defecation motivation of an old user, improve the accompanying quality, improve the living self-respect and the living quality of the old, and improve the living convenience.

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 defecation and urination early warning method based on an EEG signal, which comprises the following steps:

s11: the EEG signal acquisition equipment acquires an EEG signal for a user and transmits the acquired EEG signal to the data analysis system;

wherein, the brain area for controlling the urination is a paracortical lobule, and EEG signal acquisition equipment acquires EEG signals through Cz, C1 and C2 electrodes; the brain area for controlling excrement excretion is the forehead lobe, and EEG signal acquisition equipment acquires EEG signals through AF3, AF4 and AFz electrodes.

S12: the data analysis system processes the EEG signal to obtain a pure EEG signal, then analyzes the pure EEG signal to obtain a target characteristic value, and inputs the target characteristic value into the algorithm model for classification and identification so as to evaluate the current excretion control state of the user;

the data analysis system filters the EEG signals by adopting a band-pass and notch filtering algorithm, and then removes noise by adopting a regression method and Fourier transform to obtain pure EEG signals. And analyzing the time domain and the frequency domain of the pure EEG signal, and calculating the converted time-frequency domain EEG signal value to obtain a target characteristic value. And calculating a power value or an entropy value of the time-frequency domain EEG signal value by adopting an artificial intelligence algorithm to serve as a target characteristic value. The value range of the target characteristic value is [0,100], and different sections which are convenient to distinguish are included.

S13: and when the data analysis system detects that the user feels defecation through the control state, the data analysis system sends voice prompt information to the public address equipment to remind a worker to deal with the defecation problem of the user in advance.

Therefore, in the method, the collected EEG signals are processed to obtain pure EEG signals, the pure EEG signals are analyzed to obtain target characteristic values, the characteristic values are extracted and then are brought into an algorithm model for classification and recognition, the current control state of excretion of a user is evaluated and fed back, the technical effects of intelligently predicting and monitoring the defecation process are achieved, manual participation is not needed, a large amount of time is not consumed, the detection efficiency is improved, the labor cost is reduced, defecation events are predicted, timely early warning is achieved, the manual nursing cost and time are reduced, automatic recognition early warning is achieved, the defecation motivation of the old user is monitored, the accompanying quality is improved, the living self-respect and the living quality of the old are improved, and the living convenience is improved. The specific implementation flow diagram of the method refers to fig. 1.

Wherein, the control brain area of urine excretion is the paracortex lobule, and the control brain area of excrement excretion is the prefrontal lobe, through the collection, processing analysis and the discernment to these two regional brain signals in brain area, can monitor, early warning old person's state of wanting to relieve oneself. Fig. 2 is a flow chart of the operation of a portable BCI apparatus, the EEG apparatus used in this embodiment is preferably a portable device with 5 high-sampling-rate electrodes, the electrode points are set by the international electroencephalogram 10-20 system, and the electrode distribution is AF3, AF4, AFz, C1, C2, Cz, O1, O2, where AFz is a ground electrode and O1, O2 are reference electrodes.

Preferably, the EEG device of the present embodiment is designed to be a headband type in appearance, which is convenient for elderly users to wear for a long time. In order to improve the wearing comfort, softer conductive rubber is adopted as an electrode material, so that the pressure feeling of the electrode on the skin is reduced; the comfort level of the user during wearing is enhanced; on the selection of hair band material, chooseed a more frivolous ventilative, the cloth that has better elasticity endurance for use, the travelling comfort that life and the user of increase headgear worn is fit for the user and wears for a long time, receives the influence in weather season less.

The EEG signal acquisition equipment is used for transmitting EEG electric signals to a data analysis system after the EEG electric signals are acquired by a user, the data analysis system comprises a data processing module, an algorithm recognition and classification module and a feedback module, the data processing module is used for processing and analyzing original EEG data so as to evaluate the current control state of the user on defecation, and the feedback system is used for sending a prompt for processing the defecation problem of the user in advance when detecting that the user feels defecation.

After the EEG signal is acquired, the acquired EEG electrical signal needs to be amplified and subjected to digital-to-analog conversion, and the EEG electrical signal is converted into a digital signal and then transmitted to a data analysis system.

The data analysis system filters original data by adopting a band-pass and notch filtering algorithm, filters high-frequency and low-frequency artifacts and power frequency interference in the original data, and removes noises such as electrooculogram and myoelectricity by adopting a regression method, Fourier transform and the like to obtain a pure electroencephalogram signal.

The data analysis system performs time and frequency domain analysis on the pure electroencephalogram signals, and the frequency domain analysis method can adopt common methods such as Fourier transform, wavelet transform and the like.

And the data analysis system calculates the converted time-frequency domain electroencephalogram signal value to obtain a target characteristic value. Specifically, an artificial intelligence algorithm is adopted to calculate the power value or entropy value of the EEG signal as the characteristic value of model identification. Fig. 3 is a flow chart of an EEG data acquisition process.

The brain area for controlling the urination and the excretion is the paracortical lobule, and the electroencephalogram characteristic value is mainly calculated according to the signal values at the Cz, C1 and C2 electrodes; the control brain area for defecation is the prefrontal lobe, and the electroencephalogram characteristic value is mainly calculated according to the signal values at the AF3, AF4 and AFz electrodes.

The data analysis system also needs to extract characteristic values and incorporate the characteristic values into an algorithm model for classification and identification so as to evaluate the current control state of the user on excretion. The range of the eigenvalues can be set to [0,100], where [0,25) is an idle interval, [25,75) is an interval with more obvious idle, and [75,100] is an interval in which the idle state or the idle state is difficult to control. In the step, an algorithm model is adopted to identify and classify the EEG signal characteristic values, and the algorithm model is preferably an algorithm model such as a vector machine, a KNN, a naive Bayes classification, a least square method, an artificial neural network and the like.

And when the feedback module detects that the user feels defecation, a prompt for processing the defecation problem of the user in advance is sent. In this embodiment, it is preferable to send the voice prompt message to the public address device in a wireless connection manner, so as to efficiently remind the user or a caregiver of the user to deal with the defecation problem of the user in advance. Preferably, when the characteristic value is detected to be in the [25,75) interval, the voice warns the defecation information of the user; when the characteristic value is detected to be in the [75,100] interval, the user is prompted in a mode of combining an alarm sound and voice. The voice early warning system of the embodiment can be connected with any audio amplifier with complete functions in a Bluetooth mode.

Referring to fig. 4, fig. 4 is a schematic structural diagram of a defecation and urination warning system based on EEG signals, which is provided by the present invention and is used for implementing the defecation and urination warning method based on EEG signals, and the system includes:

an EEG signal acquisition device 101 for acquiring an EEG signal for a user and transmitting the acquired EEG signal to a data analysis system;

the data analysis system 102 is used for processing the EEG signal to obtain a pure EEG signal, analyzing the pure EEG signal to obtain a target characteristic value, and inputting the target characteristic value into the algorithm model for classification and identification so as to evaluate the current excretion control state of the user; and when the defecation feeling of the user is detected through the control state, sending voice prompt information to the public address equipment to remind a worker to deal with the defecation problem of the user in advance.

It is thus clear that, in this system, through handling the EEG signal that gathers, obtain pure EEG signal, carry out the analysis again in order to obtain the target characteristic value, take into the algorithm model after extracting the characteristic value at last and carry out classification and identification, the evaluation user is current to excrete control state and make the feedback, so reach the technological effect of intelligent prediction and monitoring defecation process, no longer need artifical the participation, also need not consume a large amount of time, detection efficiency is improved, the cost of labor has been reduced, realize predicting the defecation incident, in time the early warning, reduce artifical nursing cost and time, and automatic identification early warning, monitor old user's defecation motivation, promote the quality of accompanying and attending to, promote old person's life self-esteem and quality of life, improve the life convenience.

For the introduction of the urination and defecation early warning system based on the EEG signal provided by the present invention, please refer to the aforementioned embodiment of the urination and defecation early warning method based on the EEG signal, which is 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. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.

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 method and system for early warning of defecation and urination based on the EEG signal provided by the invention are described 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

1. A defecation and urination early warning method based on an EEG signal is characterized by comprising the following steps:

2. The method of claim 1, wherein the data analysis system filters the EEG signal using band pass and notch filtering algorithms, and then removes noise using a regression method, fourier transform, resulting in a clean EEG signal.

3. The method of claim 1, wherein the time and frequency domain analysis is performed on the clean EEG signal and the transformed time-frequency domain EEG signal values are calculated to obtain the target feature values.

4. A method as claimed in claim 3, wherein an artificial intelligence algorithm is used to calculate the power or entropy values of the time-frequency domain EEG signal values as the target feature values.

5. The method of claim 1, wherein the brain area controlling urinary excretion is a paracortical leaflet, and the EEG signal acquisition device acquires EEG signals via Cz, C1, C2 electrodes; the brain area for controlling excrement excretion is the forehead lobe, and EEG signal acquisition equipment acquires EEG signals through AF3, AF4 and AFz electrodes.

6. The method of claim 1, wherein the target characteristic value ranges from [0,100], and includes different intervals for distinguishing between the presence and absence of inconvenience.

7. An early warning system for defecation and urination based on EEG signals, for implementing the method of any one of claims 1 to 6, comprising: